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Zhou YF, Chen S, Chen JX, Chen S, Wang G, Pan XF, Wu S, Pan A. Cost-Effectiveness of a Workplace-Based Hypertension Management Program in Real-World Practice in the Kailuan Study. J Am Heart Assoc 2024; 13:e031578. [PMID: 38563379 DOI: 10.1161/jaha.123.031578] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Accepted: 03/01/2024] [Indexed: 04/04/2024]
Abstract
BACKGROUND In 2009, a workplace-based hypertension management program was launched among men with hypertension in the Kailuan study. This program involved monitoring blood pressure semimonthly, providing free antihypertensive medications, and offering personalized health consultations. However, the cost-effectiveness of this program remains unclear. METHODS AND RESULTS This analysis included 12 240 participants, with 6120 in each of the management and control groups. Using a microsimulation model derived from 10-year follow-up data, we estimated costs, quality-adjusted life years (QALYs), life-years, and incremental cost-effectiveness ratios (ICERs) for workplace-based management compared with routine care in both the study period and over a lifetime. Analyses are conducted from the societal perspective. Over the 10-year follow-up, patients in the management group experienced an average gain of 0.06 QALYs with associated incremental costs of $633.17 (4366.85 RMB). Projecting over a lifetime, the management group was estimated to increase by 0.88 QALYs or 0.92 life-years compared with the control group, with an incremental cost of $1638.64 (11 301.37 RMB). This results in an incremental cost-effectiveness ratio of $1855.47 per QALY gained and $1780.27 per life-year gained, respectively, when comparing workplace-based management with routine care. In probabilistic sensitivity analyses, with a threshold willingness-to-pay of $30 765 per QALY (3 times 2019 gross domestic product per capita), the management group showed a 100% likelihood of being cost-effective in 10 000 samples. CONCLUSIONS Workplace-based management, compared with routine care for Chinese men with hypertension, could be cost-effective both during the study period and over a lifetime, and might be considered in working populations in China and elsewhere.
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Affiliation(s)
- Yan-Feng Zhou
- Department of Social Medicine, School of Public Health Guangxi Medical University Nanning China
| | - Shuohua Chen
- Department of Cardiology, Kailuan General Hospital North China University of Science and Technology Tangshan China
| | - Jun-Xiang Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College Huazhong University of Science and Technology Wuhan China
| | - Simiao Chen
- Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China
- Heidelberg Institute of Global Health, Faculty of Medicine and University Hospital Heidelberg University Heidelberg Germany
| | - Guodong Wang
- Department of Cardiology, Kailuan General Hospital North China University of Science and Technology Tangshan China
| | - Xiong-Fei Pan
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, West China Second University Hospital, Sichuan University Shuangliu Institute of Women's and Children's Health, Shuangliu Maternal and Child Health Hospital Chengdu China
| | - Shouling Wu
- Department of Cardiology, Kailuan General Hospital North China University of Science and Technology Tangshan China
| | - An Pan
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College Huazhong University of Science and Technology Wuhan China
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He X, Xue Q, Li D, Zhang S, Wu N, Li S, Yang Y, Dong Y, Li F, Li P, Wen Y, Pan XF. Association between Biomarkers of Phthalate Exposure and Serum Folate Concentrations in Children: A Population-Based Cross-Sectional Study of the NHANES from 2011 to 2016. J Nutr 2024:S0022-3166(24)00157-3. [PMID: 38484977 DOI: 10.1016/j.tjnut.2024.03.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 02/28/2024] [Accepted: 03/08/2024] [Indexed: 04/05/2024] Open
Abstract
BACKGROUND Although adverse health effects of phthalates have been reported, very few studies have assessed the associations between biomarkers of phthalate exposure and serum folate concentrations in children. OBJECTIVES We aimed to examine the association between urinary phthalate metabolites, as biomarkers of exposure to phthalates, and total serum folate concentrations in children using national data from the United States. METHODS We conducted cross-sectional analyses of 2100 individuals aged 6-18 y enrolled in the National Health and Nutrition Examination Survey, 2011-2016. Multivariable linear regression was applied to examine the relationship between natural logarithm (ln)-transformed urinary phthalate metabolites and serum folate concentrations. The quantile-based g-computation was used to assess the association of urinary phthalate metabolite mixture with serum folate levels. Subgroup analyses were conducted by sex, age, and race/ethnicity, and the interactions were assessed by adding interaction terms of these stratifying variables and phthalates and modeling through the Wald test. RESULTS In multiple linear regression models, for participants in the highest tertile of MEHHP, MEOHP, DEHP, MCPP, and MCOP, total serum folate concentrations were 1.566 [β: -1.566; 95% confidence interval: -2.935, -0.196], 1.423 (-1.423; -2.689, -0.157), 1.309 (-1.309; -2.573, -0.044), 1.530 (-1.530; -2.918, -0.142), and 1.381 (-1.381; -2.641, -0.122) ng/mL lower than those in the lowest tertile. The inverse associations were consistent in different subgroups by sex, age, and race/ethnicity (P for interaction ≥0.083 for all). In addition, the phthalate mixture showed a strong inverse correlation with serum folate; a quartile increase in the phthalate mixture on the ln scale was associated with 0.888 (-0.888; -1.677, -0.099) ng/mL decrease in the serum folate. CONCLUSIONS Higher concentrations of urinary phthalate metabolites were associated with lower serum folate concentrations in children. Although our findings should be validated through additional population and mechanistic studies, they support a potential adverse effect of phthalate exposure on folate metabolism in children.
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Affiliation(s)
- Xingchen He
- Section of Epidemiology and Population Health & Department of Gynecology and Obstetrics, Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children & National Medical Products Administration Key Laboratory for Technical Research on Drug Products In Vitro and In Vivo Correlation, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Qingping Xue
- Department of Epidemiology and Biostatistics, School of Public Health, Chengdu Medical College, Chengdu, Sichuan, China
| | - Di Li
- Data Science Program, New York University Shanghai, Pudong, Shanghai, China
| | - Shanshan Zhang
- Section of Epidemiology and Population Health & Department of Gynecology and Obstetrics, Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children & National Medical Products Administration Key Laboratory for Technical Research on Drug Products In Vitro and In Vivo Correlation, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China; Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Nianwei Wu
- Section of Epidemiology and Population Health & Department of Gynecology and Obstetrics, Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children & National Medical Products Administration Key Laboratory for Technical Research on Drug Products In Vitro and In Vivo Correlation, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China; West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Shuo Li
- Section of Epidemiology and Population Health & Department of Gynecology and Obstetrics, Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children & National Medical Products Administration Key Laboratory for Technical Research on Drug Products In Vitro and In Vivo Correlation, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yunhaonan Yang
- Section of Epidemiology and Population Health & Department of Gynecology and Obstetrics, Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children & National Medical Products Administration Key Laboratory for Technical Research on Drug Products In Vitro and In Vivo Correlation, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yidan Dong
- Section of Epidemiology and Population Health & Department of Gynecology and Obstetrics, Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children & National Medical Products Administration Key Laboratory for Technical Research on Drug Products In Vitro and In Vivo Correlation, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Fan Li
- Section of Epidemiology and Population Health & Department of Gynecology and Obstetrics, Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children & National Medical Products Administration Key Laboratory for Technical Research on Drug Products In Vitro and In Vivo Correlation, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Ping Li
- Department of Pediatrics, Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Ying Wen
- Department of Communicable Disease Control and Prevention, Shenzhen Center for Disease Control and Prevention, Shenzhen, Guangdong, China
| | - Xiong-Fei Pan
- Section of Epidemiology and Population Health & Department of Gynecology and Obstetrics, Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children & National Medical Products Administration Key Laboratory for Technical Research on Drug Products In Vitro and In Vivo Correlation, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China; West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China; Shuangliu Institute of Women's and Children's Health, Shuangliu Maternal and Child Health Hospital, Chengdu, Sichuan, China.
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Liu D, Li N, Zhou Y, Wang M, Song P, Yuan C, Shi Q, Chen H, Zhou K, Wang H, Li T, Pan XF, Tian H, Li S. Sex-specific associations between skeletal muscle mass and incident diabetes: A population-based cohort study. Diabetes Obes Metab 2024; 26:820-828. [PMID: 37997500 DOI: 10.1111/dom.15373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 10/31/2023] [Accepted: 11/04/2023] [Indexed: 11/25/2023]
Abstract
AIMS To investigate the sex-specific associations between predicted skeletal muscle mass index (pSMI) and incident type 2 diabetes in a retrospective longitudinal cohort of Chinese men and women. MATERIALS AND METHODS We enrolled Chinese adults without diabetes at baseline from WATCH (West chinA adulT health CoHort), a large health check-up-based database. We calculated pSMI to estimate skeletal muscular mass, and measured blood glucose variables and assessed self-reported history to identify new-onset diabetes. The nonlinear association between pSMI and incident type 2 diabetes was modelled using the penalized spline method. The piecewise association was estimated using segmented linear splines in weighted Cox proportional hazards regression models. RESULTS Of 47 885 adults (53.2% women) with a median age of 40 years, 1836 developed type 2 diabetes after a 5-year median follow-up. In women, higher pSMI was associated with a lower risk of incident type 2 diabetes (Pnonlinearity = 0.09, hazard ratio [HR] per standard deviation increment in pSMI: 0.79 [95% confidence interval {CI} 0.68, 0.91]). A nonlinear association of pSMI with incident type 2 diabetes was detected in men (Pnonlinearity < 0.001). In men with pSMI lower than 8.1, higher pSMI was associated with a lower risk of incident type 2 diabetes (HR 0.58 [95% CI 0.40, 0.84]), whereas pSMI was not significantly associated with incident diabetes in men with pSMI equal to or greater than 8.1 (HR 1.08 [95% CI 0.93, 1.25]). CONCLUSIONS In females, a larger muscular mass is associated with a lower risk of type 2 diabetes. For males, this association is significant only among those with diminished muscle mass.
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Affiliation(s)
- Dan Liu
- Department of Endocrinology and Metabolism, West China Hospital, Sichuan University, Chengdu, China
| | - Nan Li
- Department of Informatics, West China Hospital, Sichuan University, Chengdu, China
| | - Yiling Zhou
- Department of Endocrinology and Metabolism, West China Hospital, Sichuan University, Chengdu, China
| | - Miye Wang
- Department of Informatics, West China Hospital, Sichuan University, Chengdu, China
| | - Peige Song
- School of Public Health, Zhejiang University, Hangzhou, China
| | - Changzheng Yuan
- School of Public Health, Zhejiang University, Hangzhou, China
| | - Qingyang Shi
- Department of Endocrinology and Metabolism, West China Hospital, Sichuan University, Chengdu, China
| | - Hui Chen
- School of Public Health, Zhejiang University, Hangzhou, China
| | - Kaixin Zhou
- College of Life Sciences, University of the Chinese Academy of Sciences, Beijing, China
- College of Public Health, Guangzhou Medical University, Guangzhou, China
| | - Huan Wang
- Division of Population Health and Genomics, School of Medicine, University of Dundee, Dundee, UK
| | - Tao Li
- Department of Anesthesiology, Laboratory of Mitochondria and Metabolism, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
| | - Xiong-Fei Pan
- Section of Epidemiology and Population Health, Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children, West China Second University Hospital, Sichuan University, Chengdu, China
| | - Haoming Tian
- Department of Endocrinology and Metabolism, West China Hospital, Sichuan University, Chengdu, China
| | - Sheyu Li
- Department of Endocrinology and Metabolism, West China Hospital, Sichuan University, Chengdu, China
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Wu P, Wu L, Wang Y, Ye Y, Yang X, Yuan J, Xu J, Wang YX, Song X, Yan S, Lv C, Liu G, Pan A, Pan XF. Maternal overweight and obesity modify the association of serum fibroblast growth factor 21 levels with gestational diabetes mellitus: A nested case-control study. Diabetes Metab Res Rev 2024; 40:e3717. [PMID: 37649397 DOI: 10.1002/dmrr.3717] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 07/28/2023] [Accepted: 08/07/2023] [Indexed: 09/01/2023]
Abstract
AIMS To examine the prospective association between fibroblast growth factor 21 (FGF21) and risk of gestational diabetes mellitus (GDM) and the modifying effect of overweight/obesity for this association. METHODS Serum FGF21 levels were measured at 6-15 weeks of gestation among 332 GDM cases and 664 matched controls. Conditional logistic regression was used to evaluate its association with GDM risk. Interaction analyses on multiplicative and additive scales were conducted to investigate the modifying effect of overweight/obesity. RESULTS Elevated FGF21 levels were associated with a higher risk of GDM in multivariable models, but the positive association was attenuated after further adjustment for pre-pregnancy body mass index (BMI). A significant multiplicative interaction was noted between FGF21 (both continuous and dichotomous) and pre-pregnancy BMI (p for interaction = 0.049 and 0.03), and the association was only significant in participants with pre-pregnancy BMI ≥24 kg/m2 . When participants were grouped based on pre-pregnancy BMI (≥24 and <24 kg/m2 ) and FGF21 levels (≥median and CONCLUSIONS Elevated serum FGF21 levels in early pregnancy were associated with a higher risk of GDM, particularly among those with overweight/obesity.
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Affiliation(s)
- Ping Wu
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Linjing Wu
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yi Wang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yi Ye
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xue Yang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Jiaying Yuan
- Department of Science and Education, Shuangliu Maternal and Child Health Hospital, Chengdu, China
| | - Jianguo Xu
- Department of Clinical Laboratories, Shuangliu Maternal and Child Health Hospital, Chengdu, China
| | - Yi-Xin Wang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xingyue Song
- Department of Emergency, Hainan Clinical Research Center for Acute and Critical Diseases, The Second Affiliated Hospital of Hainan Medical University, Haikou, China
| | - Shijiao Yan
- School of Public Health, Hainan Medical University, Haikou, China
- Research Unit of Island Emergency Medicine, Chinese Academy of Medical Sciences, Hainan Medical University, Haikou, China
| | - Chuanzhu Lv
- School of Public Health, Hainan Medical University, Haikou, China
- Emergency Medicine Center, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China
- Key Laboratory of Emergency and Trauma of Ministry of Education, Hainan Medical University, Haikou, China
| | - Gang Liu
- Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - An Pan
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiong-Fei Pan
- Section of Epidemiology and Population Health & Department of Gynecology and Obstetrics, Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children & National Medical Products Administration Key Laboratory for Technical Research on Drug Products In Vitro and In Vivo Correlation, West China Second University Hospital, Sichuan University, Chengdu, China
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China
- Shuangliu Institute of Women's and Children's Health, Shuangliu Maternal and Child Health Hospital, Chengdu, China
- Center for Epidemiology and Population Health, Integrated Traditional Chinese and Western Medicine Institute & Chengdu Integrated Traditional Chinese and Western Medicine Hospital, Chengdu University of Traditional Chinese Medicine, Chengdu, China
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Sun Y, Wang YX, Liu C, Mustieles V, Pan XF, Zhang Y, Messerlian C. Exposure to Trihalomethanes and Bone Mineral Density in US Adolescents: A Cross-Sectional Study (NHANES). Environ Sci Technol 2023; 57:21616-21626. [PMID: 38091484 DOI: 10.1021/acs.est.3c07214] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/27/2023]
Abstract
Animal and human studies have suggested that trihalomethane (THM) has toxicity to bone. In this study, we included adolescents from the National Health and Nutrition Examination Survey who had quantified blood and tap water THM concentrations [chloroform (TCM), bromodichloromethane (BDCM), dibromochloromethane (DBCM), and bromoform (TBM)] and lumbar spine or total body less head (TBLH) bone mineral density (BMD). A 2.7-fold increase in concentrations of blood TCM, DBCM, chlorinated THMs (the sum of TCM, BDCM, and DBCM), and total THMs (the sum of 4 THMs) was associated with lower lumbar spine BMD z-scores by -0.06 [95% confidence interval (CI): -0.12, -0.01], -0.06 (95% CI: -0.11, -0.003), -0.08 (95% CI: -0.14, -0.02), and -0.07 (95% CI: -0.13, -0.003), respectively, in adjusted models. Similarly, a 2.7-fold increase in blood BDCM, DBCM, and chlorinated THM concentrations was associated with lower TBLH BMD z-scores by -0.10 (95% CI: -0.17, -0.02), -0.10 (95% CI: -0.17, -0.03), and -0.11 (95% CI: -0.20, -0.01), respectively. Low-to-moderate predictive power was attained when tap water THM concentrations were used to predict blood THM measurements. Notably, the inverse associations for blood THMs persisted exclusively between water concentrations of DBCM and Br-THMs and the TBLH BMD z-scores. Our findings suggest that exposure to THMs may adversely affect the adolescent BMD.
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Affiliation(s)
- Yang Sun
- Department of Otolaryngology-Head and Neck Surgery & Center of Sleep Medicine, Shanghai Jiao Tong University School of Medicine Affiliated Sixth People's Hospital, Shanghai 200233, China
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 02115, United States
| | - Yi-Xin Wang
- Department of Environmental Health, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Chong Liu
- Department of Environmental Health, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Vicente Mustieles
- Center for Biomedical Research (CIBM), University of Granada, Granada 18016,Spain
- Instituto de Investigación Biosanitaria Ibs GRANADA, Granada 18012,Spain
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid 28029, Spain
| | - Xiong-Fei Pan
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, West China Second University Hospital, Shuangliu Institute of Women's and Children's Health, Shuangliu Maternal and Child Health Hospital, Chengdu 610041, China
| | - Yu Zhang
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 02115, United States
| | - Carmen Messerlian
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 02115, United States
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 02115, United States
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Wu L, Ouyang J, Lai Y, Wu P, Wang Y, Ye Y, Wang J, Hu M, Zhang J, Xu J, Yang X, Yuan J, Zhao B, Song X, Yan S, Lv C, Liu G, Pan A, Pan XF. Combined healthy lifestyle in early pregnancy and risk of gestational diabetes mellitus: A prospective cohort study. BJOG 2023; 130:1611-1619. [PMID: 37212437 DOI: 10.1111/1471-0528.17548] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Revised: 04/25/2023] [Accepted: 05/04/2023] [Indexed: 05/23/2023]
Abstract
OBJECTIVE To examine the association of a combined healthy lifestyle in early pregnancy with gestational diabetes mellitus (GDM) risk. DESIGN, SETTING AND POPULATION A Chinese prospective cohort study with 6980 pregnant women. METHODS Individual modifiable lifestyle factors were assessed in early pregnancy and a combined lifestyle score was derived from the sum of the lifestyle factors, with a higher score indicating a healthier lifestyle. The association of a combined healthy lifestyle with GDM risk was examined. MAIN OUTCOME MEASURES Gestational diabetes mellitus was diagnosed in middle pregnancy according to the International Association of Diabetes and Pregnancy Study Group criteria or diagnoses in medical records. RESULTS Overall, 501 (7.2%) pregnant women were diagnosed with GDM. Being physically active (total energy expenditure in upper three quintiles, i.e. ≥100.1 metabolic equivalent of task [MET]-hours/week; odds ratio [OR] 0.76, 95% confidence interval [CI] 0.63-0.92), healthy diet (total intake of vegetables and fruits ≥5 times/day; OR 0.74, 95% CI 0.59-0.94), sufficient sleep (night-time sleep duration ≥7 hours/night; OR 0.66, 95% CI 0.48-0.90) and healthy weight (early-pregnancy BMI <24.0 kg/m2 ; OR 0.57, 95% CI 0.46-0.71) were associated with lower GDM risk. The GDM risk decreased linearly across the combined lifestyle score (Ptrend <0.001): women with 2, 3 and 4 lifestyle factors compared with those with 0-1 factor had 38% (OR 0.62, 95% CI 0.46-0.84), 57% (OR 0.43, 95% CI 0.31-0.58) and 66% (OR 0.34, 95% CI 0.22-0.52) lower risks of GDM, respectively. CONCLUSION A healthy lifestyle in early pregnancy was associated with a substantially lower GDM risk.
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Affiliation(s)
- Linjing Wu
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jing Ouyang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yuwei Lai
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ping Wu
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yi Wang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yixiang Ye
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jingyi Wang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Mengyan Hu
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jijuan Zhang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jiajing Xu
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xue Yang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Section of Epidemiology and Population Health & Department of Gynecology and Obstetrics, Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children & National Medical Products Administration Key Laboratory for Technical Research on Drug Products In Vitro and In Vivo Correlation, West China Second University Hospital, Sichuan University, Chengdu, China
| | - Jiaying Yuan
- Department of Science and Education, Shuangliu Maternal and Child Health Hospital, Chengdu, China
| | - Bin Zhao
- Antenatal Care Clinics, Shuangliu Maternal and Child Health Hospital, Chengdu, China
| | - Xingyue Song
- Department of Emergency, Hainan Clinical Research Centre for Acute and Critical Diseases, The Second Affiliated Hospital of Hainan Medical University, Haikou, China
| | - Shijiao Yan
- School of Public Health, Hainan Medical University, Haikou, Hainan, China
- Research Unit of Island Emergency Medicine, Chinese Academy of Medical Sciences, Hainan Medical University, Haikou, China
| | - Chuanzhu Lv
- Emergency Medicine Centre, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China
- Key Laboratory of Emergency and Trauma of Ministry of Education, Hainan Medical University, Haikou, China
| | - Gang Liu
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Department of Nutrition & Food Hygiene, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - An Pan
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiong-Fei Pan
- Section of Epidemiology and Population Health & Department of Gynecology and Obstetrics, Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children & National Medical Products Administration Key Laboratory for Technical Research on Drug Products In Vitro and In Vivo Correlation, West China Second University Hospital, Sichuan University, Chengdu, China
- Shuangliu Institute of Women's and Children's Health, Shuangliu Maternal and Child Health Hospital, Chengdu, China
- Centre for Epidemiology and Population Health, Integrated Traditional Chinese and Western Medicine Institute & Chengdu Integrated Traditional Chinese and Western Medicine Hospital, Chengdu University of Traditional Chinese Medicine, Chengdu, China
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Ye YX, Wang Y, Wu P, Yang X, Wu L, Lai Y, Ouyang J, Li Y, Li P, Hu Y, Wang YX, Song X, Yan S, Lv C, Liu G, Pan A, Pan XF. Blood Cell Parameters From Early to Middle Pregnancy and Risk of Gestational Diabetes Mellitus. J Clin Endocrinol Metab 2023; 108:e1702-e1711. [PMID: 37279929 DOI: 10.1210/clinem/dgad336] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 05/22/2023] [Accepted: 06/02/2023] [Indexed: 06/08/2023]
Abstract
CONTEXT Chronic low-grade inflammation may play a crucial role in the pathogenesis of gestational diabetes mellitus (GDM). However, prospective studies on the relations of inflammatory blood cell parameters during pregnancy with GDM are lacking. OBJECTIVE To prospectively investigate the associations of inflammatory blood cell parameters in both early and middle pregnancy, and their change patterns from early to middle pregnancy, with GDM risk. METHODS We used data from the Tongji-Shuangliu Birth Cohort. Inflammatory blood cell parameters (white blood cells [WBC], neutrophils, lymphocytes, monocytes, neutrophil to lymphocyte ratio [NLR], and platelets) were assayed before 15 weeks and between 16 and 28 weeks of gestational age. Logistic regression was used to evaluate the associations between inflammatory blood cell parameters and GDM. RESULTS Of the 6354 pregnant women, 445 were diagnosed with GDM. After adjustment for potential confounders, WBC, neutrophils, lymphocytes, monocytes, and NLR in early pregnancy were positively associated with GDM risk (odds ratios [95% CI] for extreme-quartile comparison were 2.38 [1.76-3.20], 2.47 [1.82-3.36], 1.40 [1.06-1.85], 1.69 [1.27-2.24], and 1.51 [1.12-2.02], respectively, all P for trend ≤ .010). Similarly, higher levels of WBC, neutrophils, monocytes, and NLR in middle pregnancy were associated with increased risk of GDM (all P for trend ≤ .014). Stable high levels (≥ median in both early and middle pregnancy) of WBC, neutrophils, monocytes, and NLR were positively associated with GDM risk (all P ≤ .001). CONCLUSION Increased WBC, neutrophils, monocytes, and NLR in both early and middle pregnancy and their stable high levels from early to middle pregnancy were associated with higher GDM risk, highlighting that they might be clinically relevant for identifying individuals at high risk for GDM.
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Affiliation(s)
- Yi-Xiang Ye
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Yi Wang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Ping Wu
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Xue Yang
- Section of Epidemiology and Population Health, Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children, West China Second University Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Linjing Wu
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Yuwei Lai
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Jing Ouyang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Yanqin Li
- Department of Obstetrics, Shuangliu Maternal and Child Health Hospital, Chengdu, Sichuan 610200, China
| | - Peishan Li
- Department of Obstetrics, Shuangliu Maternal and Child Health Hospital, Chengdu, Sichuan 610200, China
| | - Yayi Hu
- Department of Obstetrics and Gynecology, Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children, West China Second University Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Yi-Xin Wang
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA 02138, USA
| | - Xingyue Song
- Department of Emergency, Hainan Clinical Research Center for Acute and Critical Diseases, The Second Affiliated Hospital of Hainan Medical University, Haikou, Hainan 570311, China
| | - Shijiao Yan
- School of Public Health, Hainan Medical University, Haikou, Hainan 571199, China
- Research Unit of Island Emergency Medicine, Chinese Academy of Medical Sciences, Hainan Medical University, Haikou, Hainan 571199, China
| | - Chuanzhu Lv
- Research Unit of Island Emergency Medicine, Chinese Academy of Medical Sciences, Hainan Medical University, Haikou, Hainan 571199, China
- Emergency Medicine Center, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan 610072, China
- Key Laboratory of Emergency and Trauma of Ministry of Education, Hainan Medical University, Haikou, Hainan 571199, China
| | - Gang Liu
- Department of Nutrition & Food Hygiene, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - An Pan
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Xiong-Fei Pan
- Section of Epidemiology and Population Health & Department of Gynecology and Obstetrics, Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children & National Medical Products Administration Key Laboratory for Technical Research on Drug Products In Vitro and In Vivo Correlation, West China Second University Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- Shuangliu Institute of Women's and Children's Health, Shuangliu Maternal and Child Health Hospital, Chengdu, Sichuan 610200, China
- Center for Epidemiology and Population Health, Integrated Traditional Chinese and Western Medicine Institute & Chengdu Integrated Traditional Chinese and Western Medicine Hospital, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 611137, China
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Wang L, Pan XF, Munro HM, Shrubsole MJ, Yu D. Consumption of ultra-processed foods and all-cause and cause-specific mortality in the Southern Community Cohort Study. Clin Nutr 2023; 42:1866-1874. [PMID: 37625316 PMCID: PMC10528155 DOI: 10.1016/j.clnu.2023.08.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2023] [Revised: 07/25/2023] [Accepted: 08/14/2023] [Indexed: 08/27/2023]
Abstract
BACKGROUND & AIMS Higher intake of ultra-processed foods (UPF) has been linked with higher risks of cancer, cardiovascular disease, and diabetes, as well as all-cause mortality. However, studies on UPF and cause-specific mortality remain limited, especially among disadvantaged populations. We aimed to examine associations of UPF intake with all-cause and cause-specific mortality among low-income Americans. METHODS In the Southern Community Cohort Study (SCCS), a prospective cohort of mostly low-income Black and White Americans, we included 77,060 participants who completed a food frequency questionnaire (FFQ) at baseline (2002-2009) and had at least 1 year follow-up. All 89 items in the FFQ were categorized using the Nova classification. UPF intake was calculated as % of daily foods intake by weight (grams). Cox regression was used to estimate HR (95% CI) for the association of UPF intake (quartile or per 10% increase) with total and cause-specific mortality (cancer, coronary heart disease [CHD], stroke, and diabetes) after adjusting for sociodemographics, lifestyles, and disease history. RESULTS Of 77,060 participants, 46,175 (59.9%) were women, 49,857 were Black (64.7%), and mean age was 52.4 (SD: 8.8) years at baseline. The mean intake of UPF was 41.0% (SD: 15.7%). UPF intake was inversely associated with Healthy Eating Index and intakes of fiber, minerals, and vitamins but positively associated with intakes of sugars and fats (all PFDR<0.0001). During an average follow-up of 12.2 years, we documented 17,895 total deaths, including 4267 from cancer, 2208 from CHD, 867 from stroke, and 997 from diabetes. In the fully adjusted model, higher UPF intake was not associated with all-cause, cancer, CHD, or stroke mortality but showed a significant association with increased diabetes mortality (HR [95% CI] = 1.32 [1.07, 1.62] for the highest versus lowest quartiles [>51.1% vs. <29.3%] and 1.09 [1.04, 1.15] per 10% increase). The adverse UPF-diabetes mortality association was noted regardless of sex, race, income, neighborhood deprivation, lifestyles, and cardiometabolic disease history, while particularly evident in participants with no more than high school education or a history of hypercholesterolemia (HR [95% CI] per 10% increase = 1.12 [1.05, 1.18] and 1.14 [1.07, 1.22], respectively; both Pinteraction<0.05). CONCLUSIONS Among predominantly low-income Black and White American adults, UPF intake was associated with increased diabetes mortality, especially for individuals with limited education or hypercholesterolemia. Our findings suggest the potential impact of increasing access and intake of un/minimally processed food to replace UPF on reducing diabetes-related mortality among populations facing socioeconomic and health disparities.
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Affiliation(s)
- Lei Wang
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37203, USA
| | - Xiong-Fei Pan
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37203, USA
| | - Heather M Munro
- International Epidemiology Field Station, Vanderbilt University Medical Center, Nashville, TN 37203, USA
| | - Martha J Shrubsole
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37203, USA; International Epidemiology Field Station, Vanderbilt University Medical Center, Nashville, TN 37203, USA
| | - Danxia Yu
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37203, USA.
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Ma M, Pan XF, Pan A, Jiang L. Effects of Sample Dilution on Nuclear Magnetic Resonance-Derived Metabolic Profiles of Human Urine. Anal Chem 2023; 95:13769-13778. [PMID: 37681715 DOI: 10.1021/acs.analchem.3c00029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/09/2023]
Abstract
Traditionally, a relatively big urine volume (e.g., 500 μL) is used in nuclear magnetic resonance (NMR)-based human metabolomics, which is not feasible for studies with limited/precious samples. Although urine may be diluted before conventional high-throughput metabolomics analysis, the comprehensive effect of urine dilution on metabolic profiles is unknown. Here, for the first time, we systematically investigated the effect of urine dilution on 1H NMR metabolic profiles, by evaluating signal detectability, integration, signal-to-noise ratio (SNR), chemical shift (δ) and its variation, and signal overlapping of 47 metabolites in 10 volunteers. We observed significant linear changes along with increased dilution, including decreased integration and SNR, altered δ, decreased intersample variation of δ, and increased separation between overlapped signals, e.g., lactate and threonine, β-d-glucose and an unassigned signal, and histidine and 3-methylhistidine. We further tested the 40% dilution level (i.e., employing 300 μL urine) in an epidemiological study containing 1018 pregnant women from the Tongji-Shuangliu Birth Cohort, showing acceptable detectability and chemical shift variability for most of the 47 metabolites profiled. It indicated that mild (e.g., 40%) dilution of human urine can largely preserve the high-abundance metabolites profiled, reduce intersample chemical shift variations, and increase separations of overlapped signals, which is an improvement of routine sample preparation methods in NMR-based metabolomics and is applicable for studies with limited urine volumes, including large-scale epidemiological studies.
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Affiliation(s)
- Mengnan Ma
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan 430030, China
| | - Xiong-Fei Pan
- Section of Epidemiology and Population Health, Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children, West China Second University Hospital & West China Biomedical Big Data Center, West China Hospital, Sichuan University; Shuangliu Institute of Women's and Children's Health, Shuangliu Maternal and Child Health Hospital, Chengdu, Sichuan 610041, China
| | - An Pan
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan 430030, China
| | - Limiao Jiang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan 430030, China
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Sun F, Pan XF, Hu Y, Xie J, Cui W, Ye YX, Wang Y, Yang X, Wu P, Yuan J, Yang Y, Pan A, Chen D. Metal Exposure during Early Pregnancy and Risk of Gestational Diabetes Mellitus: Mixture Effect and Mediation by Phospholipid Fatty Acids. Environ Sci Technol 2023; 57:13778-13792. [PMID: 37656932 DOI: 10.1021/acs.est.3c04065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/03/2023]
Abstract
Despite existing studies exploring the association between metal exposure and gestational diabetes mellitus (GDM), most of them have focused on a single metal or a small mixture of metals. Our prospective work investigated the joint and independent effects of early gestational exposure to 17 essential and nonessential metals on the GDM risk and potential mediation by plasma phospholipid fatty acids (PLFAs) based on a nested case-control study established with 335 GDM cases and 670 randomly matched healthy controls. The Bayesian kernel machine regression (BKMR) and quantile g-computation analyses demonstrated a joint effect from metal co-exposure on GDM risk. BKMR with hierarchical variable selection indicated that the group of essential metals was more strongly associated with GDM than the group of nonessential metals with group posterior inclusion probabilities (PIPs) of 0.979 and 0.672, respectively. Cu (0.988) and Ga (0.570) had the largest conditional PIPs within each group. We also observed significant mediation effects of selected unsaturated PLFAs on Cu-GDM and Ga-GDM associations. KEGG enrichment analysis further revealed significant enrichment in the biosynthesis of unsaturated PLFAs. C18:1 n-7 exhibited the largest proportion of mediation in both associations (23.8 and 22.9%). Collectively, our work demonstrated the joint effect of early gestational metal exposure on GDM risk and identified Cu and Ga as the key species to the joint effect. The findings lay a solid ground for further validation through multicenter investigations and mechanism exploration via laboratory studies.
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Affiliation(s)
- Fengjiang Sun
- School of Environment, Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou 510632, Guangdong, China
| | - Xiong-Fei Pan
- Section of Epidemiology and Population Health & Department of Gynecology and Obstetrics, Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children, and National Medical Product Administration Key Laboratory for Technical Research on Drug Products in Vitro and in Vivo Correlation, West China Second University Hospital, Sichuan University and Shuangliu Institute of Women's and Children's Health, Shuangliu Maternal and Child Health Hospital, Chengdu 610041, Sichuan, China
| | - Yongxia Hu
- School of Environment, Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou 510632, Guangdong, China
| | - Jinxin Xie
- School of Environment, Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou 510632, Guangdong, China
| | - Wenxuan Cui
- School of Environment, Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou 510632, Guangdong, China
| | - Yi-Xiang Ye
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, China
| | - Yi Wang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, China
| | - Xue Yang
- Section of Epidemiology and Population Health & Department of Gynecology and Obstetrics, Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children, and National Medical Product Administration Key Laboratory for Technical Research on Drug Products in Vitro and in Vivo Correlation, West China Second University Hospital, Sichuan University and Shuangliu Institute of Women's and Children's Health, Shuangliu Maternal and Child Health Hospital, Chengdu 610041, Sichuan, China
| | - Ping Wu
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, China
| | - Jiaying Yuan
- Department of Science and Education, Shuangliu Maternal and Child Health Hospital, Chengdu 610200, Sichuan, China
| | - Yan Yang
- School of Chemical Engineering and Light Industry, Guangdong University of Technology, Guangzhou 510006, Guangdong, China
- Synergy Innovation Institute of GDUT, Shantou 515041, Guangdong, China
| | - An Pan
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, China
| | - Da Chen
- School of Environment, Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou 510632, Guangdong, China
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Huang W, Pan XF, Tang S, Sun F, Wu P, Yuan J, Sun W, Pan A, Chen D. Target Exposome for Characterizing Early Gestational Exposure to Contaminants of Emerging Concern and Association with Gestational Diabetes Mellitus. Environ Sci Technol 2023; 57:13408-13418. [PMID: 37651547 DOI: 10.1021/acs.est.3c04492] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/02/2023]
Abstract
Characterization of gestational exposure to complex contaminants of emerging concern (CECs) is critical to the identification of environmental risk factors for pregnancy complications. However, determination of various CECs with diverse physicochemical properties in biological fluids is technically challenging. In the present study, we developed a target exposome protocol, consisting of simple liquid-liquid extraction-based sample preparation and sensitive liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis, to determine 325 CECs covering 11 subclasses, including poly- and perfluoroalkyl substances, organophosphate esters, ultraviolet (UV) stabilizers, synthetic antioxidants, phthalate esters, and several others. The protocol exhibits exceptional advantages over traditional approaches in the coverage of chemicals, sample volume demand, and time and financial cost. The protocol was applied in a prospective nested gestational diabetes mellitus (GDM) study including 120 cases and 240 matched healthy controls. Thirty-three CECs were detected in >70% of the samples, with a combined concentration of 17.0-484.7 ng/mL. Bayesian kernel machine regression analysis showed that exposure to the CEC mixture was significantly associated with a higher GDM risk. For example, when increasing all CECs in the mixture from 50th percentile to 75th percentile, the estimated probit of GDM incidence had an increase of 92% (95% CI: 56%, 127%). Meanwhile, perfluorohexanesulfonic acid, 1,3-diphenylguanidine, and dibutyl fumarate were identified as the key CECs driving the joint effect. This work demonstrates great potential of our target exposome protocol for environmental risk factor identification in large-scale epidemiology or biomonitoring studies.
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Affiliation(s)
- Wei Huang
- School of Environment, Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou 510632, Guangdong, China
| | - Xiong-Fei Pan
- Section of Epidemiology and Population Health & Department of Gynecology and Obstetrics, Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children & National Medical Products Administration Key Laboratory for Technical Research on Drug Products In Vitro and In Vivo Correlation, West China Second University Hospital, Sichuan University; Shuangliu Institute of Women's and Children's Health, Shuangliu Maternal and Child Health Hospital, Chengdu, Sichuan 610041, China
| | - Shuqin Tang
- School of Environment, Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou 510632, Guangdong, China
| | - Fengjiang Sun
- School of Environment, Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou 510632, Guangdong, China
| | - Ping Wu
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Jiaying Yuan
- Department of Science and Education, Shuangliu Maternal and Child Health Hospital, Chengdu, Sichuan 610200, China
| | - Wenwen Sun
- Shanghai AB Sciex Analytical Instrument Trading Co., Ltd, Shanghai 200335, China
| | - An Pan
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Da Chen
- School of Environment, Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou 510632, Guangdong, China
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Ni W, Xue Q, Zhang S, Yang X, Wu S, He X, Xiao Y, Chang W, Wen Y, Huang Y, Wang YX, Chen D, Yang CX, Pan XF. High quality diet attenuated the positive association between polychlorinated biphenyls and premature mortality among middle-aged and older adults. Environ Res 2023; 231:116031. [PMID: 37156355 DOI: 10.1016/j.envres.2023.116031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Revised: 04/30/2023] [Accepted: 05/01/2023] [Indexed: 05/10/2023]
Abstract
OBJECTIVE Polychlorinated biphenyls (PCBs) have been reported to be a risk factor for premature death, while a high diet quality is thought to lower mortality risk. We aimed to examine whether PCBs were associated with higher all-cause and cause-specific mortality risk and whether such associations could be modified by the diet quality among US middle-aged and older adults. METHODS Included were 1259 participants aged 40 years or older from the 1999-2004 National Health and Nutrition Examination surveys. Exposure to PCBs was assessed in non-fasting serum samples, and mortality status was ascertained through December 31, 2019 using the public-use, linked mortality files. Diet quality was assessed using the Healthy Eating Index-2015 based on 24-h dietary recalls. Cox proportional hazard regression was applied to assess the associations of different PCB congener groups with mortality and the modifying effect by the diet quality. RESULTS During a median follow-up of 17.75 years, 419 deaths occurred, including 131 from cardiovascular disease (CVD) and 102 from cancer. Serum concentrations of dioxin-like PCBs and non-dioxin-like PCBs were significantly associated with all-cause mortality, with hazard ratios (HRs) of 1.84 (95% confidence interval [CI], 1.10, 2.99) and 1.82 (1.09, 3.03) for extreme-tertile comparisons. A significant interaction was noted between dioxin-like PCBs and diet quality (P for interaction: 0.012), with a substantially more pronounced association among participants with a low diet quality (HR, 3.47; 95% CI: 1.29, 9.32), compared to those with a high diet quality (HR, 0.98; 95% CI: 0.40, 2.43). A similar weaker association was observed for total PCBs in participants with a high diet quality (P for interaction: 0.032). However, effect modifications by diet quality were not noted for the associations between different PCB groups and CVD mortality. CONCLUSIONS While our findings need to be validated in other populations and mechanistic studies, they may suggest that a high quality diet could potentially attenuate the harmful effects of chronic PCB exposure.
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Affiliation(s)
- Weigui Ni
- Section of Epidemiology and Population Health, Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children & National Medical Products Administration Key Laboratory for Technical Research on Drug Products in Vitro and in Vivo Correlation, West China Second University Hospital, Sichuan University; Shuangliu Institute of Women's and Children's Health, Shuangliu Maternal and Child Health Hospital, Chengdu, Sichuan, China; Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Qingping Xue
- Department of Epidemiology and Biostatistics, School of Public Health, Chengdu Medical College, Chengdu, Sichuan, China
| | - Shanshan Zhang
- Section of Epidemiology and Population Health, Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children & National Medical Products Administration Key Laboratory for Technical Research on Drug Products in Vitro and in Vivo Correlation, West China Second University Hospital, Sichuan University; Shuangliu Institute of Women's and Children's Health, Shuangliu Maternal and Child Health Hospital, Chengdu, Sichuan, China; Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xue Yang
- Section of Epidemiology and Population Health, Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children & National Medical Products Administration Key Laboratory for Technical Research on Drug Products in Vitro and in Vivo Correlation, West China Second University Hospital, Sichuan University; Shuangliu Institute of Women's and Children's Health, Shuangliu Maternal and Child Health Hospital, Chengdu, Sichuan, China; Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Shiyi Wu
- Section of Epidemiology and Population Health, Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children & National Medical Products Administration Key Laboratory for Technical Research on Drug Products in Vitro and in Vivo Correlation, West China Second University Hospital, Sichuan University; Shuangliu Institute of Women's and Children's Health, Shuangliu Maternal and Child Health Hospital, Chengdu, Sichuan, China; Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xingcheng He
- Section of Epidemiology and Population Health, Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children & National Medical Products Administration Key Laboratory for Technical Research on Drug Products in Vitro and in Vivo Correlation, West China Second University Hospital, Sichuan University; Shuangliu Institute of Women's and Children's Health, Shuangliu Maternal and Child Health Hospital, Chengdu, Sichuan, China
| | - Yan Xiao
- Section of Epidemiology and Population Health, Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children & National Medical Products Administration Key Laboratory for Technical Research on Drug Products in Vitro and in Vivo Correlation, West China Second University Hospital, Sichuan University; Shuangliu Institute of Women's and Children's Health, Shuangliu Maternal and Child Health Hospital, Chengdu, Sichuan, China; Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Wenling Chang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Ying Wen
- Shenzhen Center for Disease Control and Prevention, Shenzhen, Guangdong, China
| | - Yichao Huang
- Department of Toxicology, School of Public Health, Anhui Medical University, Hefei, China
| | - Yi-Xin Wang
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Da Chen
- School of Environment and Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou, Guangdong, China
| | - Chun-Xia Yang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
| | - Xiong-Fei Pan
- Section of Epidemiology and Population Health, Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children & National Medical Products Administration Key Laboratory for Technical Research on Drug Products in Vitro and in Vivo Correlation, West China Second University Hospital, Sichuan University; Shuangliu Institute of Women's and Children's Health, Shuangliu Maternal and Child Health Hospital, Chengdu, Sichuan, China.
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Wu P, Wang Y, Ye Y, Yang X, Huang Y, Ye Y, Lai Y, Ouyang J, Wu L, Xu J, Yuan J, Hu Y, Wang YX, Liu G, Chen D, Pan A, Pan XF. Liver biomarkers, lipid metabolites, and risk of gestational diabetes mellitus in a prospective study among Chinese pregnant women. BMC Med 2023; 21:150. [PMID: 37069659 PMCID: PMC10111672 DOI: 10.1186/s12916-023-02818-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Accepted: 03/06/2023] [Indexed: 04/19/2023] Open
Abstract
BACKGROUND Liver plays an important role in maintaining glucose homeostasis. We aimed to examine the associations of liver enzymes and hepatic steatosis index (HSI, a reliable biomarker for non-alcoholic fatty liver disease) in early pregnancy with subsequent GDM risk, as well as the potential mediation effects of lipid metabolites on the association between HSI and GDM. METHODS In a birth cohort, liver enzymes were measured in early pregnancy (6-15 gestational weeks, mean 10) among 6,860 Chinese women. Multivariable logistic regression was performed to examine the association between liver biomarkers and risk of GDM. Pearson partial correlation and least absolute shrinkage and selection operator (LASSO) regression were conducted to identify lipid metabolites that were significantly associated with HSI in a subset of 948 women. Mediation analyses were performed to estimate the mediating roles of lipid metabolites on the association of HSI with GDM. RESULTS Liver enzymes and HSI were associated with higher risks of GDM after adjustment for potential confounders, with ORs ranging from 1.42 to 2.24 for extreme-quartile comparisons (false discovery rate-adjusted P-trend ≤0.005). On the natural log scale, each SD increment of alanine aminotransferase, aspartate aminotransferase, gamma-glutamyl transferase, alkaline phosphatase, and HSI was associated with a 1.15-fold (95% CI: 1.05, 1.26), 1.10-fold (1.01, 1.20), 1.21-fold (1.10, 1.32), 1.15-fold (1.04, 1.27), and 1.33-fold (1.18, 1.51) increased risk of GDM, respectively. Pearson partial correlation and LASSO regression identified 15 specific lipid metabolites in relation to HSI. Up to 52.6% of the association between HSI and GDM risk was attributed to the indirect effect of the HSI-related lipid score composed of lipid metabolites predominantly from phospholipids (e.g., lysophosphatidylcholine and ceramides) and triacylglycerol. CONCLUSIONS Elevated liver enzymes and HSI in early pregnancy, even within a normal range, were associated with higher risks of GDM among Chinese pregnant women. The association of HSI with GDM was largely mediated by altered lipid metabolism.
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Affiliation(s)
- Ping Wu
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
| | - Yi Wang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
| | - Yi Ye
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
| | - Xue Yang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Yichao Huang
- Department of Toxicology, School of Public Health, Anhui Medical University, Hefei, 230032, Anhui, China
| | - Yixiang Ye
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
| | - Yuwei Lai
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
| | - Jing Ouyang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
| | - Linjing Wu
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
| | - Jianguo Xu
- Department of Clinical Laboratories, Shuangliu Maternal and Child Health Hospital, Chengdu, 610200, Sichuan, China
| | - Jiaying Yuan
- Department of Science and Education, Shuangliu Maternal and Child Health Hospital, Chengdu, 610200, Sichuan, China
| | - Yayi Hu
- Department of Obstetrics and Gynecology & Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children, West China Second University Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Yi-Xin Wang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
| | - Gang Liu
- Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
| | - Da Chen
- School of Environment, Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou, 511436, Guangdong, China
| | - An Pan
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China.
| | - Xiong-Fei Pan
- Section of Epidemiology and Population Health & Department of Obstetrics and Gynecology, Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children & National Medical Products Administration Key Laboratory for Technical Research on Drug Products In Vitro and In Vivo Correlation, West China Second University Hospital, Sichuan University, Sichuan, Chengdu, 610041, China.
- Shuangliu Institute of Women's and Children's Health, Shuangliu Maternal and Child Health Hospital, Chengdu, 610041, Sichuan, China.
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Ouyang J, Lai Y, Wu L, Wang Y, Wu P, Ye YX, Yang X, Gao Y, Yuan J, Song X, Yan S, Lv C, Wang YX, Liu G, Hu Y, Pan A, Pan XF. Association between prepregnancy weight change and risk of gestational diabetes mellitus in Chinese pregnant women. Am J Clin Nutr 2023:S0002-9165(23)46845-1. [PMID: 37062367 DOI: 10.1016/j.ajcnut.2023.04.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Revised: 03/28/2023] [Accepted: 04/13/2023] [Indexed: 04/18/2023] Open
Abstract
BACKGROUND Evidence regarding prepregnancy weight change and gestational diabetes mellitus (GDM) is lacking among East Asian women. OBJECTIVE Our study aimed to investigate the association between weight change from age 18 years to pregnancy and GDM in Chinese pregnant women. METHODS Our analyses included 6972 pregnant women from the Tongji-Shuangliu Birth Cohort. Body weights were recalled for age 18 years and the time point immediately before pregnancy, while height was measured during early pregnancy. Prepregnancy weight change was calculated as the difference between weight immediately before pregnancy and weight at age 18 years. GDM outcomes were ascertained by 75-g oral glucose tolerance test. Multivariable logistic regression models were used to estimate the association between prepregnancy weight change and risk of GDM. RESULTS 501 (7.2%) developed GDM in the cohort. After multivariable adjustments, prepregnancy weight change was linearly associated with a higher risk of incident GDM (P < 0.001). Compared with participants with stable weight (weight change within 5.0 kg) before pregnancy, multivariable-adjusted odds ratios and 95% confidence intervals were 1.55 (1.22, 1.98) and 2.24 (1.78, 2.83) for participants with moderate (weight gain of 5-9.9 kg) and high (weight gain ≥ 10 kg) weight gain, respectively. In addition, overweight/obesity immediately before pregnancy mediated 17.6% and 31.7% of the associations of moderate and high weight gain with GDM risk, while weekly weight gain during pregnancy mediated 21.1% and 22.7% of the associations. CONCLUSIONS Weight gain from age 18 years to pregnancy was significantly associated with a higher risk of GDM. Maintaining weight stability, especially prevention of excessive weight gain from early adulthood to pregnancy could be a potential strategy to reduce GDM risk.
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Affiliation(s)
- Jing Ouyang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Yuwei Lai
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Linjing Wu
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Yi Wang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Ping Wu
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Yi-Xiang Ye
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Xue Yang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, China; Section of Epidemiology and Population Health & Department of Obstetrics and Gynecology, Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children & National Medical Products Administration Key Laboratory for Technical Research on Drug Products In Vitro and In Vivo Correlation, West China Second University Hospital, Sichuan University, Chengdu 610041, China
| | - Yanyu Gao
- Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Jiaying Yuan
- Department of Science and Education, Shuangliu Maternal and Child Health Hospital, Chengdu 610200, China
| | - Xingyue Song
- Department of Emergency, Hainan Clinical Research Center for Acute and Critical Diseases, The Second Affiliated Hospital of Hainan Medical University, Haikou 571199, China
| | - Shijiao Yan
- School of Public Health, Hainan Medical University, Haikou 571199, China; Research Unit of Island Emergency Medicine, Chinese Academy of Medical Sciences, Hainan Medical University, Haikou 571199, China
| | - Chuanzhu Lv
- Research Unit of Island Emergency Medicine, Chinese Academy of Medical Sciences, Hainan Medical University, Haikou 571199, China; Emergency Medicine Center, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 610072, China; Key Laboratory of Emergency and Trauma of Ministry of Education, Hainan Medical University, Haikou 571199, China
| | - Yi-Xin Wang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Gang Liu
- Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Yayi Hu
- Department of Obstetrics and Gynecology, Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children, West China Second University Hospital, Sichuan University, Chengdu 610041, China
| | - An Pan
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.
| | - Xiong-Fei Pan
- Section of Epidemiology and Population Health & Department of Obstetrics and Gynecology, Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children & National Medical Products Administration Key Laboratory for Technical Research on Drug Products In Vitro and In Vivo Correlation, West China Second University Hospital, Sichuan University, Chengdu 610041, China; Shuangliu Institute of Women's and Children's Health, Shuangliu Maternal and Child Health Hospital, Chengdu 610200, China; Center for Epidemiology and Population Health, Integrated Traditional Chinese and Western Medicine Institute & Chengdu Integrated Traditional Chinese and Western Medicine Hospital, Chengdu University of Traditional Chinese Medicine, Chengdu 610041, China.
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15
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Liao XF, Liao BJ, Tan WH, Wang L, Wang DD, Tang EF, Li FG, Pan XF, Ji LH, She Q. [Genetic diagnosis of microcephaly]. Zhonghua Fu Chan Ke Za Zhi 2023; 58:178-184. [PMID: 36935194 DOI: 10.3760/cma.j.cn112141-20221102-00675] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 03/21/2023]
Abstract
Objective: To explore the diagnostic value of chromosome karyotype analysis, chromosomal microarray analysis (CMA) and whole exome sequencing (WES) in microcephaly. Methods: A total of 9 cases of microcephaly fetuses diagnosed by prenatal ultrasound or children with microcephaly diagnosed after birth were selected from the Sixth Affiliated Hospital of Guangzhou Medical University from January 2014 to August 2022.Karyotype analysis and/or CMA were used to detect. The cases with negative karyotype analysis and CMA results were further sequenced by trio-based WES (Trio-WES). Then the coding genes contained in the pathogenic copy number variation (CNV) fragments were analyzed by gene ontology (GO) enrichment. The genes related to the development of the central nervous system contained in the pathogenic CNV and the pathogenic genes found by Trio-WES were combined for gene interaction network analysis. Results: In this study, 9 cases of microcephaly were recruited, with the time of diagnosis ranged from 23 weeks of gestation to 7 years after birth, and the head circumference of fetus or children ranged from 18.3 to 42.5 cm (-7SD to -2SD). Karyotype analysis was detected in all 9 cases and no abnormality result was found. Eight cases were detected by CMA, and one abnormal was found. Five cases were detected by Trio-WES, and two cases were detected with likely pathogenic genes. The GO enrichment analysis of the coding gene in the 4p16.3 microdeletion (pathogenic CNV) region showed that: in biological process, it was mainly concentrated in phototransduction, visible light; in terms of molecular function, it was mainly concentrated in fibroblast growth factor binding; in terms of cell components, it was mainly concentrated in rough endoplasmic reticulum. Gene interaction network analysis suggested that CDC42 gene could interact with CTBP1, HTT and ASPM gene. Conclusions: CMA could be used as a first-line detection technique for microcephaly. When the results of chromosome karyotype analysis and/or CMA are negative, Trio-WES could improve the detection rate of pathogenicity of microcephaly.
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Affiliation(s)
- X F Liao
- Prenatal Diagnostic Center, Qingyuan People's Hospital, the Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan 511518, China
| | - B J Liao
- Stem Cell and Regenerative Medicine Laboratory, Qingyuan People's Hospital, the Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan 511518, China
| | - W H Tan
- Prenatal Diagnostic Center, Qingyuan People's Hospital, the Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan 511518, China
| | - L Wang
- Prenatal Diagnostic Center, Qingyuan People's Hospital, the Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan 511518, China
| | - D D Wang
- Prenatal Diagnostic Center, Qingyuan People's Hospital, the Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan 511518, China
| | - E F Tang
- Prenatal Diagnostic Center, Qingyuan People's Hospital, the Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan 511518, China
| | - F G Li
- Prenatal Diagnostic Center, Qingyuan People's Hospital, the Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan 511518, China
| | - X F Pan
- Prenatal Diagnostic Center, Qingyuan People's Hospital, the Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan 511518, China
| | - L H Ji
- Prenatal Diagnostic Center, Qingyuan People's Hospital, the Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan 511518, China
| | - Q She
- Prenatal Diagnostic Center, Qingyuan People's Hospital, the Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan 511518, China
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16
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Liu D, Gao X, Pan XF, Zhou T, Zhu C, Li F, Fan JG, Targher G, Zhao J. The hepato-ovarian axis: genetic evidence for a causal association between non-alcoholic fatty liver disease and polycystic ovary syndrome. BMC Med 2023; 21:62. [PMID: 36800955 PMCID: PMC9940436 DOI: 10.1186/s12916-023-02775-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/08/2022] [Accepted: 02/09/2023] [Indexed: 02/21/2023] Open
Abstract
BACKGROUND Recent studies found associations between non-alcoholic fatty liver disease (NAFLD) and polycystic ovary syndrome (PCOS), but the causal nature of this association is still uncertain. METHODS We performed a bidirectional two-sample Mendelian randomization (MR) analysis to test for the causal association between NAFLD and PCOS using data from a large-scale biopsy-confirmed NAFLD genome-wide association study (GWAS) (1483 cases and 17,781 controls) and PCOS GWAS (10,074 cases and 103,164 controls) in European ancestries. Data from glycemic-related traits GWAS (in up to 200,622 individuals) and sex hormones GWAS (in 189,473 women) in the UK Biobank (UKB) were used in the MR mediation analysis to assess potential mediating roles of these molecules in the causal pathway between NAFLD and PCOS. Replication analysis was conducted using two independent datasets from NAFLD and PCOS GWASs in the UKB and a meta-analysis of data from FinnGen and the Estonian Biobank, respectively. A linkage disequilibrium score regression was conducted to assess genetic correlations between NAFLD, PCOS, glycemic-related traits, and sex hormones using full summary statistics. RESULTS Individuals with higher genetic liability to NAFLD were more likely to develop PCOS (OR per one-unit log odds increase in NAFLD: 1.10, 95% CI: 1.02-1.18; P = 0.013). Indirect causal effects of NAFLD on PCOS via fasting insulin only (OR: 1.02, 95% CI: 1.01-1.03; P = 0.004) and further a suggestive indirect causal effect via fasting insulin in concert with androgen levels were revealed in MR mediation analyses. However, the conditional F statistics of NAFLD and fasting insulin were less than 10, suggesting likely weak instrument bias in the MVMR and MR mediation analyses. CONCLUSIONS Our study suggests that genetically predicted NAFLD was associated with a higher risk of developing PCOS but less evidence for vice versa. Fasting insulin and sex hormones might mediate the link between NAFLD and PCOS.
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Affiliation(s)
- Dong Liu
- Ministry of Education and Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, No.1665, Kongjiang Road, Yangpu District, Shanghai, 200092, China
| | - Xue Gao
- Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Xiong-Fei Pan
- Ministry of Education Key Laboratory of Birth Defects and Related Diseases in Women and Children, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China.,Shuangliu Institute of Women's and Children's Health, Shuangliu Maternal and Child Health Hospital, Chengdu, Sichuan, China
| | - Tao Zhou
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
| | - Cairong Zhu
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Fei Li
- Ministry of Education and Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, No.1665, Kongjiang Road, Yangpu District, Shanghai, 200092, China.,Department of Developmental and Behavioral Pediatric & Child Primary Care, Brain and Behavioral Research Unit of Shanghai Institute for Pediatric Research, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,Department of Maternal and Child Health, School of Public Health, Shanghai Jiao Tong University, Shanghai, China
| | - Jian-Gao Fan
- Department of Gastroenterology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,Shanghai Key Lab of Pediatric Gastroenterology and Nutrition, Shanghai, China
| | - Giovanni Targher
- Section of Endocrinology, Diabetes and Metabolism, Department of Medicine, University of Verona, Verona, Italy
| | - Jian Zhao
- Ministry of Education and Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, No.1665, Kongjiang Road, Yangpu District, Shanghai, 200092, China. .,Department of Maternal and Child Health, School of Public Health, Shanghai Jiao Tong University, Shanghai, China. .,MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
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17
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Abstract
PURPOSE OF REVIEW Epidemiological and mechanistic studies have reported relationships between blood lipids, mostly measured by traditional method in clinical settings, and gestational diabetes mellitus (GDM). Recent advances of high-throughput lipidomics techniques have made available more comprehensive lipid profiling in biological samples. This review aims to summarize evidence from prospective studies in assessing relations between blood lipids and GDM, and discuss potential underlying mechanisms. RECENT FINDINGS Mass spectrometry and nuclear magnetic resonance spectroscopy-based analytical platforms are extensively used in lipidomics research. Epidemiological studies have identified multiple novel lipidomic biomarkers that are associated with risk of GDM, such as certain types of fatty acids, glycerolipids, glycerophospholipids, sphingolipids, cholesterol, and lipoproteins. However, the findings are inconclusive mainly due to the heterogeneities in study populations, sample sizes, and analytical platforms. Mechanistic evidence indicates that abnormal lipid metabolism may be involved in the pathogenesis of GDM by impairing pancreatic β-cells and inducing insulin resistance through several etiologic pathways, such as inflammation and oxidative stress. SUMMARY Lipidomics is a powerful tool to study pathogenesis and biomarkers for GDM. Lipidomic biomarkers and pathways could help to identify women at high risk for GDM and could be potential targets for early prevention and intervention of GDM.
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Affiliation(s)
- Yi Wang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Xiong-Fei Pan
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, West China Second University Hospital, Sichuan University
- Shuangliu Institute of Women's and Children's Health, Shuangliu Maternal and Child Health Hospital, Chengdu, China
| | - An Pan
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan
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18
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Ong KL, Marklund M, Huang L, Rye KA, Hui N, Pan XF, Rebholz CM, Kim H, Steffen LM, van Westing AC, Geleijnse JM, Hoogeveen EK, Chen YY, Chien KL, Fretts AM, Lemaitre RN, Imamura F, Forouhi NG, Wareham NJ, Birukov A, Jäger S, Kuxhaus O, Schulze MB, de Mello VD, Tuomilehto J, Uusitupa M, Lindström J, Tintle N, Harris WS, Yamasaki K, Hirakawa Y, Ninomiya T, Tanaka T, Ferrucci L, Bandinelli S, Virtanen JK, Voutilainen A, Jayasena T, Thalamuthu A, Poljak A, Bustamante S, Sachdev PS, Senn MK, Rich SS, Tsai MY, Wood AC, Laakso M, Lankinen M, Yang X, Sun L, Li H, Lin X, Nowak C, Ärnlöv J, Risérus U, Lind L, Le Goff M, Samieri C, Helmer C, Qian F, Micha R, Tin A, Köttgen A, de Boer IH, Siscovick DS, Mozaffarian D, Wu JH. Association of omega 3 polyunsaturated fatty acids with incident chronic kidney disease: pooled analysis of 19 cohorts. BMJ 2023; 380:e072909. [PMID: 36653033 PMCID: PMC9846698 DOI: 10.1136/bmj-2022-072909] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 12/12/2022] [Indexed: 01/20/2023]
Abstract
OBJECTIVE To assess the prospective associations of circulating levels of omega 3 polyunsaturated fatty acid (n-3 PUFA) biomarkers (including plant derived α linolenic acid and seafood derived eicosapentaenoic acid, docosapentaenoic acid, and docosahexaenoic acid) with incident chronic kidney disease (CKD). DESIGN Pooled analysis. DATA SOURCES A consortium of 19 studies from 12 countries identified up to May 2020. STUDY SELECTION Prospective studies with measured n-3 PUFA biomarker data and incident CKD based on estimated glomerular filtration rate. DATA EXTRACTION AND SYNTHESIS Each participating cohort conducted de novo analysis with prespecified and consistent exposures, outcomes, covariates, and models. The results were pooled across cohorts using inverse variance weighted meta-analysis. MAIN OUTCOME MEASURES Primary outcome of incident CKD was defined as new onset estimated glomerular filtration rate <60 mL/min/1.73 m2. In a sensitivity analysis, incident CKD was defined as new onset estimated glomerular filtration rate <60 mL/min/1.73 m2 and <75% of baseline rate. RESULTS 25 570 participants were included in the primary outcome analysis and 4944 (19.3%) developed incident CKD during follow-up (weighted median 11.3 years). In multivariable adjusted models, higher levels of total seafood n-3 PUFAs were associated with a lower incident CKD risk (relative risk per interquintile range 0.92, 95% confidence interval 0.86 to 0.98; P=0.009, I2=9.9%). In categorical analyses, participants with total seafood n-3 PUFA level in the highest fifth had 13% lower risk of incident CKD compared with those in the lowest fifth (0.87, 0.80 to 0.96; P=0.005, I2=0.0%). Plant derived α linolenic acid levels were not associated with incident CKD (1.00, 0.94 to 1.06; P=0.94, I2=5.8%). Similar results were obtained in the sensitivity analysis. The association appeared consistent across subgroups by age (≥60 v <60 years), estimated glomerular filtration rate (60-89 v ≥90 mL/min/1.73 m2), hypertension, diabetes, and coronary heart disease at baseline. CONCLUSIONS Higher seafood derived n-3 PUFA levels were associated with lower risk of incident CKD, although this association was not found for plant derived n-3 PUFAs. These results support a favourable role for seafood derived n-3 PUFAs in preventing CKD.
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Affiliation(s)
- Kwok Leung Ong
- Lipid Research Group, School of Biomedical Sciences, University of New South Wales, Sydney, NSW, Australia
| | - Matti Marklund
- The George Institute for Global Health, Faculty of Medicine and Health, University of New South Wales, Sydney, NSW, Australia
- The Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of Public Health and Caring Sciences, Clinical Nutrition and Metabolism, Uppsala University, Uppsala, Sweden
| | - Liping Huang
- The George Institute for Global Health, Faculty of Medicine and Health, University of New South Wales, Sydney, NSW, Australia
| | - Kerry-Anne Rye
- Lipid Research Group, School of Biomedical Sciences, University of New South Wales, Sydney, NSW, Australia
| | - Nicholas Hui
- Lipid Research Group, School of Biomedical Sciences, University of New South Wales, Sydney, NSW, Australia
| | - Xiong-Fei Pan
- The George Institute for Global Health, Faculty of Medicine and Health, University of New South Wales, Sydney, NSW, Australia
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China
- Shuangliu Institute of Women's and Children's Health, Shuangliu Maternal and Child Health Hospital, Chengdu, Sichuan, China
| | - Casey M Rebholz
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Hyunju Kim
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Lyn M Steffen
- University of Minnesota School of Public Health, Minneapolis, MN, USA
| | - Anniek C van Westing
- Division of Human Nutrition and Health, Wageningen University, Wageningen, The Netherlands
| | - Johanna M Geleijnse
- Division of Human Nutrition and Health, Wageningen University, Wageningen, The Netherlands
| | - Ellen K Hoogeveen
- Department of Nephrology, Jeroen Bosch Hospital, Den Bosch, The Netherlands
- Institute of Epidemiology and Preventive Medicine College of Public Health, National Taiwan University, Taipei, Taiwan
- Department of Medical Research, Taichung Veterans General Hospital, Taichung, Taiwan
- Heart Rhythm Center, Division of Cardiology, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan
| | | | - Kuo-Liong Chien
- Institute of Epidemiology and Preventive Medicine College of Public Health, National Taiwan University, Taipei, Taiwan
| | - Amanda M Fretts
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | | | - Fumiaki Imamura
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Nita G Forouhi
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Nicholas J Wareham
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Anna Birukov
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Susanne Jäger
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Olga Kuxhaus
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Matthias B Schulze
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
- Institute of Nutritional Science, University of Potsdam, Potsdam, Germany
| | - Vanessa Derenji de Mello
- Institute of Public Health and Clinical Nutrition, School of Medicine, University of Eastern Finland, Kuopio, Finland
| | - Jaakko Tuomilehto
- Population Health Unit, Finnish Institute for Health and Welfare, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Saudi Diabetes Research Group, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Matti Uusitupa
- Institute of Public Health and Clinical Nutrition, School of Medicine, University of Eastern Finland, Kuopio, Finland
| | - Jaana Lindström
- Population Health Unit, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Nathan Tintle
- The Fatty Acid Research Institute, Sioux Falls, SD, USA
- Department of Population Health Nursing Science, College of Nursing, University of Illinois-Chicago, Chicago, IL, USA
| | - William S Harris
- The Fatty Acid Research Institute, Sioux Falls, SD, USA
- Department of Internal Medicine, Sanford School of Medicine, University of South Dakota, Sioux Falls, SD, USA
- Department of Epidemiology and Public Health, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Keisuke Yamasaki
- Department of Epidemiology and Public Health, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Yoichiro Hirakawa
- Department of Medicine and Clinical Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Toshiharu Ninomiya
- Department of Epidemiology and Public Health, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Toshiko Tanaka
- Translational Gerontology Branch, National Institute on Aging, National Institute of Health, Baltimore, MD, USA
| | - Luigi Ferrucci
- Translational Gerontology Branch, National Institute on Aging, National Institute of Health, Baltimore, MD, USA
| | | | - Jyrki K Virtanen
- Institute of Public Health and Clinical Nutrition, School of Medicine, University of Eastern Finland, Kuopio, Finland
| | - Ari Voutilainen
- Institute of Public Health and Clinical Nutrition, School of Medicine, University of Eastern Finland, Kuopio, Finland
| | - Tharusha Jayasena
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
| | - Anbupalam Thalamuthu
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
| | - Anne Poljak
- Mark Wainwright Analytical Centre, University of New South Wales, Sydney, NSW, Australia
| | - Sonia Bustamante
- Mark Wainwright Analytical Centre, University of New South Wales, Sydney, NSW, Australia
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
| | | | - Mackenzie K Senn
- USDA/ARS Children's Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
| | - Stephen S Rich
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Michael Y Tsai
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
| | - Alexis C Wood
- USDA/ARS Children's Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
| | - Markku Laakso
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
- Department of Medicine, Kuopio University Hospital, Kuopio, Finland
| | - Maria Lankinen
- Institute of Public Health and Clinical Nutrition, School of Medicine, University of Eastern Finland, Kuopio, Finland
| | - Xiaowei Yang
- Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Liang Sun
- Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Huaixing Li
- Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Xu Lin
- Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
- Key Laboratory of Systems Health Science of Zhejiang Province, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Hangzhou, China
| | - Christoph Nowak
- Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Sweden
| | - Johan Ärnlöv
- Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Sweden
| | - Ulf Risérus
- Department of Public Health and Caring Sciences, Clinical Nutrition and Metabolism, Uppsala University, Uppsala, Sweden
| | - Lars Lind
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Mélanie Le Goff
- Bordeaux Population Health Research Centre, INSERM, UMR 1219, University of Bordeaux, Bordeaux, France
| | - Cécilia Samieri
- Bordeaux Population Health Research Centre, INSERM, UMR 1219, University of Bordeaux, Bordeaux, France
| | - Catherine Helmer
- Bordeaux Population Health Research Centre, INSERM, UMR 1219, University of Bordeaux, Bordeaux, France
| | - Frank Qian
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Harvard Medical School, Boston, MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Renata Micha
- Department of Food Science and Nutrition, University of Thessaly, Karditsa, Greece
- The Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA
| | - Adrienne Tin
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Anna Köttgen
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Institute of Genetic Epidemiology, Department of Data Driven Medicine, Faculty of Medicine and Medical Centre, University of Freiburg, Freiburg, Germany
| | - Ian H de Boer
- Division of Nephrology, Department of Medicine, University of Washington, Seattle, WA, USA
- Kidney Research Institute, University of Washington, Seattle, WA, USA
- Puget Sound VA Healthcare System, Seattle, WA, USA
| | | | - Dariush Mozaffarian
- The Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA
| | - Jason Hy Wu
- The George Institute for Global Health, Faculty of Medicine and Health, University of New South Wales, Sydney, NSW, Australia
- School of Population Health, University of New South Wales, Sydney, NSW, Australia
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19
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Zhang YB, Pan XF, Lu Q, Wang YX, Geng TT, Zhou YF, Liao LM, Tu ZZ, Chen JX, Xia PF, Wang Y, Wan ZZ, Guo KQ, Yang K, Yang HD, Chen SH, Wang GD, Han X, Wang YX, Yu D, He MA, Zhang XM, Liu LG, Wu T, Wu SL, Liu G, Pan A. Association of Combined Healthy Lifestyles With Cardiovascular Disease and Mortality of Patients With Diabetes: An International Multicohort Study. Mayo Clin Proc 2023; 98:60-74. [PMID: 36603958 PMCID: PMC9830550 DOI: 10.1016/j.mayocp.2022.08.012] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2022] [Revised: 07/29/2022] [Accepted: 08/12/2022] [Indexed: 01/04/2023]
Abstract
OBJECTIVE To prospectively examine the associations of combined lifestyle factors with incident cardiovascular disease (CVD) and mortality in patients with diabetes. PATIENTS AND METHODS Patients with prevalent diabetes were included from 5 prospective, population-based cohorts in China (Dongfeng-Tongji cohort and Kailuan study), the United Kingdom (UK Biobank study), and the United States (National Health and Nutrition Examination Survey and National Institutes of Health-AARP Diet and Health Study). Healthy lifestyle scores were constructed according to non-current smoking, low to moderate alcohol drinking, regular physical activity, healthy diet, and optimal body weight; the healthy level of each lifestyle factor was assigned 1 point, or 0 for otherwise, and the range of the score was 0 to 5. Cox proportional hazards models were used to estimate hazard ratios for incident CVD, CVD mortality, and all-cause mortality adjusting for sociodemographic, medical, and diabetes-related factors, and outcomes were obtained by linkage to medical records and death registries. Data were collected from October 18, 1988, to September 30, 2020. RESULTS A total of 6945 incident CVD cases were documented in 41,350 participants without CVD at baseline from the 2 Chinese cohorts and the UK Biobank during 389,330 person-years of follow-up, and 40,353 deaths were documented in 101,219 participants from all 5 cohorts during 1,238,391 person-years of follow-up. Adjusted hazard ratios (95% CIs) comparing patients with 4 or 5 vs 0 or 1 healthy lifestyle factors were 0.67 (0.60 to 0.74) for incident CVD, 0.58 (0.50 to 0.68) for CVD mortality, and 0.60 (0.53 to 0.68) for all-cause mortality. Findings remained consistent across different cohorts, subgroups, and sensitivity analyses. CONCLUSION The international analyses document that adherence to multicomponent healthy lifestyles is associated with lower risk of CVD and premature death of patients with diabetes.
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Affiliation(s)
- Yan-Bo Zhang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiong-Fei Pan
- Key Laboratory of Birth Defects and Related Diseases of Women and Children, Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, China; Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University Medical Center, Nashville, TN
| | - Qi Lu
- Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yan-Xiu Wang
- Department of Cardiology, Kailuan Hospital, North China University of Science and Technology, Tangshan, China
| | - Ting-Ting Geng
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yan-Feng Zhou
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Linda M Liao
- Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD
| | - Zhou-Zheng Tu
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jun-Xiang Chen
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Peng-Fei Xia
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yi Wang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhen-Zhen Wan
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Kun-Quan Guo
- Affiliated Dongfeng Hospital, Hubei University of Medicine, Shiyan, China
| | - Kun Yang
- Affiliated Dongfeng Hospital, Hubei University of Medicine, Shiyan, China
| | - Han-Dong Yang
- Affiliated Dongfeng Hospital, Hubei University of Medicine, Shiyan, China
| | - Shuo-Hua Chen
- Department of Cardiology, Kailuan Hospital, North China University of Science and Technology, Tangshan, China
| | - Guo-Dong Wang
- Department of Cardiology, Kailuan Hospital, North China University of Science and Technology, Tangshan, China
| | - Xu Han
- Department of Cardiology, Kailuan Hospital, North China University of Science and Technology, Tangshan, China
| | - Yi-Xin Wang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Danxia Yu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University Medical Center, Nashville, TN
| | - Mei-An He
- Department of Occupational and Environmental Health, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiao-Min Zhang
- Department of Occupational and Environmental Health, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Lie-Gang Liu
- Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Tangchun Wu
- Department of Occupational and Environmental Health, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shou-Ling Wu
- Department of Cardiology, Kailuan Hospital, North China University of Science and Technology, Tangshan, China.
| | - Gang Liu
- Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| | - An Pan
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
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20
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Zhang S, Li J, Huang Y, Yu J, Pan XF. Editorial: New mechanisms and drugs for the treatment of cardiovascular disease with diabetes. Front Cardiovasc Med 2023; 10:1144858. [PMID: 36891244 PMCID: PMC9986534 DOI: 10.3389/fcvm.2023.1144858] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2023] [Accepted: 01/26/2023] [Indexed: 02/22/2023] Open
Affiliation(s)
- Shanshan Zhang
- Section of Epidemiology and Population Health, Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children, National Medical Products Administration Key Laboratory for Technical Research on Drug Products In Vitro and In Vivo Correlation, West China Second University Hospital, Chengdu, Sichuan, China.,Shuangliu Institute of Women's and Children's Health, Shuangliu Maternal and Child Health Hospital, Chengdu, Sichuan, China.,Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Jingwei Li
- Department of Cardiology, Xinqiao Hospital, Army Military Medical University, Chongqing, China
| | - Yuli Huang
- Department of Cardiology, Shunde Hospital, Southern Medical University, Foshan, China
| | - Jie Yu
- The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
| | - Xiong-Fei Pan
- Section of Epidemiology and Population Health, Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children, National Medical Products Administration Key Laboratory for Technical Research on Drug Products In Vitro and In Vivo Correlation, West China Second University Hospital, Chengdu, Sichuan, China.,Shuangliu Institute of Women's and Children's Health, Shuangliu Maternal and Child Health Hospital, Chengdu, Sichuan, China
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21
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Liu C, Chen YJ, Sun B, Chen HG, Mustieles V, Messerlian C, Sun Y, Meng TQ, Lu WQ, Pan XF, Xiong CL, Hou J, Wang YX. Blood trihalomethane concentrations in relation to sperm mitochondrial DNA copy number and telomere length among 958 healthy men. Environ Res 2023; 216:114737. [PMID: 36372149 DOI: 10.1016/j.envres.2022.114737] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 10/19/2022] [Accepted: 11/03/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND In animal and human studies, exposure to trihalomethanes (THMs) has been associated with reduced semen quality. However, the underlying mechanisms remain poorly understood. OBJECTIVE To investigate the associations of blood THM concentrations with sperm mitochondrial DNA copy number (mtDNAcn) and telomere length (TL) among healthy men. METHODS We recruited 958 men who volunteered as potential sperm donors. A single blood sample was collected from each participant at recruitment and measured for chloroform (TCM), bromodichloromethane (BDCM), dibromochloromethane (DBCM), and bromoform (TBM) concentrations. Within a 90-day follow-up, the last semen sample provided by each participant was quantified for sperm mtDNAcn and TL. We used multivariable linear regression models to assess the associations between blood THM concentrations and sperm mtDNAcn and TL. We also performed stratified analyses according to the time intervals between baseline blood THM determinations and semen collection (i.e., 0-9, 10-14, 15-69, or >69 days) to explore potential windows of susceptibility. RESULTS After adjusting for potential confounders, we found inverse associations between quartiles (or categories) of blood TBM, brominated THM (Br-THM, the sum of BDCM, DBCM, and TBM), and total THM (TTHM, the sum of all four THMs) concentrations and sperm mtDNAcn (all P for trend≤0.03). Besides, we found inverse associations between quartiles of blood TCM, Br-THM, chlorinated THM (Cl-THM, the sum of TCM, BDCM, and DBCM), and TTHM concentrations and sperm TL (all P for trend<0.10). Stratified analyses showed stronger associations between Br-THM concentrations and sperm mtDNAcn determined 15-69 days since baseline exposure determinations, and between blood TCM and TTHM concentrations and sperm TL determined >69 days since baseline exposure determinations. CONCLUSION Exposure to THMs may be associated with sperm mitochondrial and telomeric dysfunction.
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Affiliation(s)
- Chong Liu
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, And State Key Laboratory of Environmental Health (incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, PR China; Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, PR China
| | - Ying-Jun Chen
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, PR China
| | - Bin Sun
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, And State Key Laboratory of Environmental Health (incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, PR China
| | - Heng-Gui Chen
- Clinical Research and Translation Center, The First Affiliated Hospital, Fujian Medical University, Fuzhou, PR China
| | - Vicente Mustieles
- University of Granada, Center for Biomedical Research (CIBM); Consortium for Biomedical Research in Epidemiology & Public Health (CIBERESP), Madrid, Spain
| | - Carmen Messerlian
- Department of Epidemiology and Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Yang Sun
- Department of Epidemiology and Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Tian-Qing Meng
- Hubei Province Human Sperm Bank, Center of Reproductive Medicine, Wuhan Tongji Reproductive Medicine Hospital, Wuhan, PR China
| | - Wen-Qing Lu
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, And State Key Laboratory of Environmental Health (incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, PR China; Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, PR China
| | - Xiong-Fei Pan
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, PR China
| | - Chen-Liang Xiong
- Hubei Province Human Sperm Bank, Center of Reproductive Medicine, Wuhan Tongji Reproductive Medicine Hospital, Wuhan, PR China.
| | - Jian Hou
- Department of Epidemiology and Biostatistics, School of Public Health, Zhengzhou University, Zhengzhou, PR China.
| | - Yi-Xin Wang
- Department of Epidemiology and Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
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22
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Zhang YB, Pan XF, Lu Q, Wang YX, Geng TT, Zhou YF, Liao LM, Tu ZZ, Chen JX, Xia PF, Wang Y, Wan ZZ, Guo KQ, Yang K, Yang HD, Chen SH, Wang GD, Han X, Wang YX, Yu D, He MA, Zhang XM, Liu LG, Wu T, Wu SL, Liu G, Pan A. Correction to: Associations of combined healthy lifestyles with cancer morbidity and mortality among individuals with diabetes: results from five cohort studies in the USA, the UK and China. Diabetologia 2022; 65:2174. [PMID: 36197538 DOI: 10.1007/s00125-022-05802-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Affiliation(s)
- Yan-Bo Zhang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiong-Fei Pan
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, China
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Centre, Vanderbilt University Medical Centre, Nashville, TN, USA
| | - Qi Lu
- Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yan-Xiu Wang
- Department of Cardiology, Kailuan Hospital, North China University of Science and Technology, Tangshan, China
| | - Ting-Ting Geng
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yan-Feng Zhou
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Linda M Liao
- Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Zhou-Zheng Tu
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jun-Xiang Chen
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Peng-Fei Xia
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yi Wang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhen-Zhen Wan
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Kun-Quan Guo
- Affiliated Dongfeng Hospital, Hubei University of Medicine, Shiyan, China
| | - Kun Yang
- Affiliated Dongfeng Hospital, Hubei University of Medicine, Shiyan, China
| | - Han-Dong Yang
- Affiliated Dongfeng Hospital, Hubei University of Medicine, Shiyan, China
| | - Shuo-Hua Chen
- Department of Cardiology, Kailuan Hospital, North China University of Science and Technology, Tangshan, China
| | - Guo-Dong Wang
- Department of Cardiology, Kailuan Hospital, North China University of Science and Technology, Tangshan, China
| | - Xu Han
- Department of Cardiology, Kailuan Hospital, North China University of Science and Technology, Tangshan, China
| | - Yi-Xin Wang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Danxia Yu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Centre, Vanderbilt University Medical Centre, Nashville, TN, USA
| | - Mei-An He
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiao-Min Zhang
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Lie-Gang Liu
- Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Tangchun Wu
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shou-Ling Wu
- Department of Cardiology, Kailuan Hospital, North China University of Science and Technology, Tangshan, China.
| | - Gang Liu
- Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| | - An Pan
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
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23
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Zhang YB, Pan XF, Lu Q, Wang YX, Geng TT, Zhou YF, Liao LM, Tu ZZ, Chen JX, Xia PF, Wang Y, Wan ZZ, Guo KQ, Yang K, Yang HD, Chen SH, Wang GD, Han X, Wang YX, Yu D, He MA, Zhang XM, Liu LG, Wu T, Wu SL, Liu G, Pan A. Associations of combined healthy lifestyles with cancer morbidity and mortality among individuals with diabetes: results from five cohort studies in the USA, the UK and China. Diabetologia 2022; 65:2044-2055. [PMID: 36102938 PMCID: PMC9633429 DOI: 10.1007/s00125-022-05754-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Accepted: 05/30/2022] [Indexed: 01/11/2023]
Abstract
AIMS/HYPOTHESIS Cancer has contributed to an increasing proportion of diabetes-related deaths, while lifestyle management is the cornerstone of both diabetes care and cancer prevention. We aimed to evaluate the associations of combined healthy lifestyles with total and site-specific cancer risks among individuals with diabetes. METHODS We included 92,239 individuals with diabetes but without cancer at baseline from five population-based cohorts in the USA (National Health and Nutrition Examination Survey and National Institutes of Health [NIH]-AARP Diet and Health Study), the UK (UK Biobank study) and China (Dongfeng-Tongji cohort and Kailuan study). Healthy lifestyle scores (range 0-5) were constructed based on current nonsmoking, low-to-moderate alcohol drinking, adequate physical activity, healthy diet and optimal bodyweight. Cox regressions were used to calculate HRs for cancer morbidity and mortality, adjusting for sociodemographic, medical and diabetes-related factors. RESULTS During 376,354 person-years of follow-up from UK Biobank and the two Chinese cohorts, 3229 incident cancer cases were documented, and 6682 cancer deaths were documented during 1,089,987 person-years of follow-up in the five cohorts. The pooled multivariable-adjusted HRs (95% CIs) comparing participants with 4-5 vs 0-1 healthy lifestyle factors were 0.73 (0.61, 0.88) for incident cancer and 0.55 (0.46, 0.67) for cancer mortality, and ranged between 0.41 and 0.63 for oesophagus, lung, liver, colorectum, breast and kidney cancers. Findings remained consistent across different cohorts and subgroups. CONCLUSIONS/INTERPRETATION This international cohort study found that adherence to combined healthy lifestyles was associated with lower risks of total cancer morbidity and mortality as well as several subtypes (oesophagus, lung, liver, colorectum, breast and kidney cancers) among individuals with diabetes.
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Affiliation(s)
- Yan-Bo Zhang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiong-Fei Pan
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, China
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Centre, Vanderbilt University Medical Centre, Nashville, TN, USA
| | - Qi Lu
- Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yan-Xiu Wang
- Department of Cardiology, Kailuan Hospital, North China University of Science and Technology, Tangshan, China
| | - Ting-Ting Geng
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yan-Feng Zhou
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Linda M Liao
- Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Zhou-Zheng Tu
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jun-Xiang Chen
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Peng-Fei Xia
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yi Wang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhen-Zhen Wan
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Kun-Quan Guo
- Affiliated Dongfeng Hospital, Hubei University of Medicine, Shiyan, China
| | - Kun Yang
- Affiliated Dongfeng Hospital, Hubei University of Medicine, Shiyan, China
| | - Han-Dong Yang
- Affiliated Dongfeng Hospital, Hubei University of Medicine, Shiyan, China
| | - Shuo-Hua Chen
- Department of Cardiology, Kailuan Hospital, North China University of Science and Technology, Tangshan, China
| | - Guo-Dong Wang
- Department of Cardiology, Kailuan Hospital, North China University of Science and Technology, Tangshan, China
| | - Xu Han
- Department of Cardiology, Kailuan Hospital, North China University of Science and Technology, Tangshan, China
| | - Yi-Xin Wang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Danxia Yu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Centre, Vanderbilt University Medical Centre, Nashville, TN, USA
| | - Mei-An He
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiao-Min Zhang
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Lie-Gang Liu
- Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Tangchun Wu
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shou-Ling Wu
- Department of Cardiology, Kailuan Hospital, North China University of Science and Technology, Tangshan, China.
| | - Gang Liu
- Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| | - An Pan
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
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Liu XD, Meng XJ, Zhang XM, Li J, Pan XF. [A non-targeted metabolomics study on serum of occupational people exposed with nanometer titanium dioxide particles (TiO(2)-NPs)]. Zhonghua Lao Dong Wei Sheng Zhi Ye Bing Za Zhi 2022; 40:813-820. [PMID: 36510714 DOI: 10.3760/cma.j.cn121094-20210318-00158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Objective: To study the changes of serum metabolic profile of occupational people exposed with nanometer titanium dioxide particles (TiO(2)-NPs), and to explore the biomarkers and injury mechanism of TiO(2)-NPs health effects. Methods: From June 2020 to June 2021, a TiO(2)-NPs production enterprise was selected as the research site by a typical sampling method, 64 people in the TiO(2)-NPs exposure group were selected from the enterprise, and 62 people of the logistics administrative staff in the same enterprise were selected as the control group, and blood samples were collected using non-anticoagulant blood collection tubes. After the samples were methanol-precipitated, the untargeted metabolomic data was collected by ultra-high performance liquid chromatography time-of-flight mass spectrometry, and biomarkers were screened and metabolic pathway analysis was performed. Results: 46 different metabolites were screened out by P<0.05 and variable importance projection index (VIP) value >1, mainly including glycerides, sphingomyelin, glycerophospholipid, fatty acyl, etc.; By ROC analysis to determine 3-hydroxy-4, 5-dimethyl-2 (5H) - furanone, 4-aminobiphenyl, heptanoylcarnitine, Hexadecanedioic acid mono-L-carnitine ester, Ibutilide, LysoPA (18∶1 (9Z) /0∶0), LysoPC (18∶0), PC (16∶0/16∶0), PC (16∶0/20: 4 (5Z, 8Z, 11Z, 14Z) ), PC (P-18∶1 (9Z) /P-18∶1 (9Z) ) 10 candidate biomarkers; involving changes in 4 metabolic pathways, namely glycerophospholipid metabolism, sphingolipid metabolism, phenylalanine, tyrosine and tryptophan acid biosynthesis, linoleic acid metabolism. Conclusion: Occupational exposure to TiO(2)-NPs has a significant impact on serum metabolic profiles.
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Affiliation(s)
- X D Liu
- Central Laboratory, The Beijing Prevention and Treatment Hospital of Occupational Disease for Chemical Industry, Beijing 100093, China
| | - X J Meng
- Central Laboratory, The Beijing Prevention and Treatment Hospital of Occupational Disease for Chemical Industry, Beijing 100093, China
| | - X M Zhang
- Central Laboratory, The Beijing Prevention and Treatment Hospital of Occupational Disease for Chemical Industry, Beijing 100093, China
| | - J Li
- Central Laboratory, The Beijing Prevention and Treatment Hospital of Occupational Disease for Chemical Industry, Beijing 100093, China
| | - X F Pan
- Central Laboratory, The Beijing Prevention and Treatment Hospital of Occupational Disease for Chemical Industry, Beijing 100093, China
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25
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Lv J, Guo L, Gu Y, Xu Y, Xue Q, Yang X, Wang QN, Meng XM, Xu DX, Pan XF, Xu S, Huang Y. National temporal trend for organophosphate pesticide DDT exposure and associations with chronic kidney disease using age-adapted eGFR model. Environ Int 2022; 169:107499. [PMID: 36087379 DOI: 10.1016/j.envint.2022.107499] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Revised: 08/04/2022] [Accepted: 08/31/2022] [Indexed: 06/15/2023]
Abstract
Whilst certain environmental organochlorine pesticide exposure may still pose significant burden, the associations between dichloro-diphenyl-trichloroethane (DDT) and chronic kidney disease (CKD) remain disputable notwithstanding the potentially inaccurate disease definition between age groups. National DDT exposure burden atlas was depicted from 92,061 participants by measuring their serum concentrations of DDT congeners and major metabolite in the US from 1999 to 2016. Temporal analyses of these toxicant exposure suggested that although serum DDT concentrations exhibited recent decline, the detection rates remain up to 99.8% every year, posing great concern for exposure risk. A total of 3,039 US adults were further included from these participants demonstrating the weighted CKD prevalence of 40.2% using the new age-adapted CKD-EPI40 model compared to 28.0% using the current CKD-EPI method. After adjustment for covariates, logistic regression model results showed individual metabolites and total DDT burden were positively, yet monotonically, associated with risk of CKD incidence (P-trend for all < 0.05), particularly among adults 40 years of age and older. Much heightened renal disease risk was also observed with high DDT exposure (OR, 1.55; 95 % CI, 1.11-2.15) in those who were hypertensive (P for heterogeneity < 0.001) but not with diabetes. The current high DDT exposure risk combined with elevated probability for CKD incidence call for health concerns and management for the environmentally persistent pollutants.
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Affiliation(s)
- Jia Lv
- Department of Toxicology, School of Public Health, Key Laboratory of Environmental Toxicology of Anhui Higher Education Institutes, Anhui Medical University, Hefei, China
| | - Lijuan Guo
- Department of Toxicology, School of Public Health, Key Laboratory of Environmental Toxicology of Anhui Higher Education Institutes, Anhui Medical University, Hefei, China
| | - Yue Gu
- Department of Nephrology, Henan Provincial Clinical Research Center for Kidney Disease, Henan Provincial People's Hospital, Zhengzhou University People's Hospital, Zhengzhou, China
| | - Ying Xu
- Kidney Disease Center, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Qingping Xue
- Department of Epidemiology and Biostatistics, Public School, Chengdu Medical College, Chengdu, China
| | - Xue Yang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Qu-Nan Wang
- Department of Toxicology, School of Public Health, Key Laboratory of Environmental Toxicology of Anhui Higher Education Institutes, Anhui Medical University, Hefei, China
| | - Xiao-Ming Meng
- School of Pharmacy, Anhui Medical University, The Key Laboratory of Anti-Inflammatory of Immune Medicines, Ministry of Education, Hefei, China
| | - De-Xiang Xu
- Department of Toxicology, School of Public Health, Key Laboratory of Environmental Toxicology of Anhui Higher Education Institutes, Anhui Medical University, Hefei, China
| | - Xiong-Fei Pan
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, West China Second University Hospital, Sichuan University, Wenjiang Institute of Women's and Children's Health, Wenjiang Maternal and Child Health Hospital, Chengdu, China.
| | - Shen Xu
- Department of Urology, Second Affiliated Hospital, Anhui Medical University, Hefei, China
| | - Yichao Huang
- Department of Toxicology, School of Public Health, Key Laboratory of Environmental Toxicology of Anhui Higher Education Institutes, Anhui Medical University, Hefei, China.
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Pan XF, Chen ZZ, Wang TJ, Shu X, Cai H, Cai Q, Clish CB, Shi X, Zheng W, Gerszten RE, Shu XO, Yu D. Plasma metabolomic signatures of obesity and risk of type 2 diabetes. Obesity (Silver Spring) 2022; 30:2294-2306. [PMID: 36161775 PMCID: PMC9633360 DOI: 10.1002/oby.23549] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2022] [Revised: 06/12/2022] [Accepted: 07/14/2022] [Indexed: 01/21/2023]
Abstract
OBJECTIVE The mechanisms linking obesity to type 2 diabetes (T2D) are not fully understood. This study aimed to identify obesity-related metabolomic signatures (MESs) and evaluated their relationships with incident T2D. METHODS In a nested case-control study of 2076 Chinese adults, 140 plasma metabolites were measured at baseline, linear regression was applied with the least absolute shrinkage and selection operator to identify MESs for BMI and waist circumference (WC), and conditional logistic regression was applied to examine their associations with T2D risk. RESULTS A total of 32 metabolites associated with BMI or WC were identified and validated, among which 14 showed positive associations and 3 showed inverse associations with T2D; 8 and 18 metabolites were selected to build MESs for BMI and WC, respectively. Both MESs showed strong linear associations with T2D: odds ratio (95% CI) comparing extreme quartiles was 4.26 (2.00-9.06) for BMI MES and 9.60 (4.22-21.88) for WC MES (both p-trend < 0.001). The MES-T2D associations were particularly evident among individuals with normal WC: odds ratio (95% CI) reached 6.41 (4.11-9.98) for BMI MES and 10.38 (6.36-16.94) for WC MES. Adding MESs to traditional risk factors and plasma glucose improved C statistics from 0.79 to 0.83 (p < 0.001). CONCLUSIONS Multiple obesity-related metabolites and MESs strongly associated with T2D in Chinese adults were identified.
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Affiliation(s)
- Xiong-Fei Pan
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Zsu-Zsu Chen
- Division of Endocrinology, Diabetes, and Metabolism, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Thomas J. Wang
- Department of Internal Medicine, UT Southwestern Medical Center, Dallas, TX, USA
| | - Xiang Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Hui Cai
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Qiuyin Cai
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Clary B. Clish
- Metabolomics Platform, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
| | - Xu Shi
- Broad Institute of Massachusetts Institute of Technology and Harvard & Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Robert E. Gerszten
- Broad Institute of Massachusetts Institute of Technology and Harvard & Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Danxia Yu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University Medical Center, Nashville, TN, USA
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Wang Y, Wu P, Huang Y, Ye Y, Yang X, Sun F, Ye YX, Lai Y, Ouyang J, Wu L, Li Y, Li Y, Zhao B, Wang Y, Liu G, Pan XF, Chen D, Pan A. BMI and lipidomic biomarkers with risk of gestational diabetes in pregnant women. Obesity (Silver Spring) 2022; 30:2044-2054. [PMID: 36046944 DOI: 10.1002/oby.23517] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Revised: 05/05/2022] [Accepted: 05/20/2022] [Indexed: 11/07/2022]
Abstract
OBJECTIVE The study aimed to identify BMI-related lipids and to explore the role of lipids linking BMI and gestational diabetes mellitus (GDM). METHODS Plasma lipidome, height, and weight were measured in early pregnancy among 1008 women. Pearson correlation analyses and least absolute shrinkage and selection operator regression (LASSO) were performed to identify BMI-associated lipids. Based on these lipids, a lipid score was created using LASSO, and its association with GDM risk was evaluated by conditional logistic regression. The causal relationships between BMI and lipids were tested by Mendelian randomization analysis with genotyping data. Mediation analysis was conducted to evaluate the mediating effect of lipids on the association of BMI with GDM. RESULTS Of 366 measured lipids, BMI was correlated with 28 lipids, which mainly belong to glycerophospholipids and glycerolipids. A total of 10 lipid species were associated with BMI, and a lipid score was established. A causal relationship between BMI and lysophosphatidylcholine 14:0 was observed. The lipid score was associated with a 1.69-fold increased risk of GDM per 1-point increment (95% CI: 1.33-2.15). Furthermore, BMI-associated lipids might explain 66.4% of the relationship between BMI and GDM. CONCLUSIONS Higher BMI in early pregnancy was associated with altered lipid metabolism that may contribute to the increased risk of GDM.
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Affiliation(s)
- Yi Wang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ping Wu
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yichao Huang
- School of Environment and Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou, China
- Department of Toxicology, School of Public Health, Anhui Medical University, Hefei, China
| | - Yi Ye
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xue Yang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Fengjiang Sun
- School of Environment and Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou, China
| | - Yi-Xiang Ye
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yuwei Lai
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jing Ouyang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Linjing Wu
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yue Li
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yanqin Li
- Department of Obstetrics, Shuangliu Maternal and Child Health Hospital, Chengdu, China
| | - Bin Zhao
- Antenatal Care Clinics, Shuangliu Maternal and Child Health Hospital, Chengdu, China
| | - Yixin Wang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Gang Liu
- Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiong-Fei Pan
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, China
- Shuangliu Institute of Women's and Children's Health, Shuangliu Maternal and Child Health Hospital, Chengdu, China
| | - Da Chen
- School of Environment and Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou, China
| | - An Pan
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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Yang X, Xue Q, Wen Y, Huang Y, Wang Y, Mahai G, Yan T, Liu Y, Rong T, Wang Y, Chen D, Zeng S, Yang CX, Pan XF. Environmental polycyclic aromatic hydrocarbon exposure in relation to metabolic syndrome in US adults. Sci Total Environ 2022; 840:156673. [PMID: 35700788 DOI: 10.1016/j.scitotenv.2022.156673] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/26/2022] [Revised: 06/09/2022] [Accepted: 06/09/2022] [Indexed: 06/15/2023]
Abstract
The present study examined the associations of polycyclic aromatic hydrocarbon (PAH) exposure with metabolic syndrome (MetS) and its components. Data were from 5181 US adults recruited in the National Health and Nutrition Examine Survey 2001-2012. Environmental PAH exposure was estimated as concentrations of urinary PAH metabolites. Weighted quantile sum (WQS) regression and modified Poisson regression were separately conducted to estimate the associations of mixed and single PAH metabolites with MetS and its components. WQS regression analyses showed that participants with higher mixed PAH exposure had increased prevalence of MetS (prevalence ratio, 1.12; 95 % confidence interval, 1.06, 1.19), elevated waist circumference (1.07; 1.02, 1.12), elevated fasting blood glucose (1.07; 1.00, 1.14), elevated triglycerides (1.19; 1.09, 1.30), and reduced high-density lipoprotein cholesterol (1.11; 1.03, 1.20). In the models for single PAH metabolites, higher levels of 1-hydroxynaphthalene (1.15; 1.00, 1.32), 2-hydroxynaphthalene (1.20; 1.05, 1.38), 1-hydroxyphenanthrene (1.18; 1.04, 1.34), 2-hydroxyphenanthrene (1.38; 1.22, 1.57), and 1-pyrene (1.19; 1.05, 1.34) were respectively associated with increased prevalence of MetS (highest tertile vs lowest tertile). In addition, linear trends were noted for the associations of these PAH metabolites with MetS (all P for linear association ≤0.047). Smokers, drinkers, and participants with poor diet quality showed stronger associations between certain PAH metabolite with MetS. The findings suggest that the prevalence of MetS and its components increases when PAH exposure is at a high level, and that lifestyle factors, such as cigarette smoking, alcohol consumption, and diet quality, could modify the positive associations of certain PAH exposure with MetS.
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Affiliation(s)
- Xue Yang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China; Non-communicable Diseases Research Center, West China-PUMC C.C. Chen Institute of Health, Sichuan University, Chengdu, Sichuan, China; Key Laboratory of Birth Defects and Related Diseases of Women and Children, Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China; Shuangliu Institute of Women's and Children's Health, Shuangliu Maternal and Child Health Hospital, Chengdu, Sichuan, China
| | - Qingping Xue
- Department of Epidemiology and Biostatistics, School of Public Health, Chengdu Medical College, Chengdu, Sichuan, China
| | - Ying Wen
- Shenzhen Center for Disease Control and Prevention, Shenzhen, Guangdong, China
| | - Yichao Huang
- Department of Toxicology, School of Public Health, Anhui Medical University, Hefei, China
| | - Yi Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Gaga Mahai
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, State Key Laboratory of Environmental Health (Incubation), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Tong Yan
- Center for Obesity and Metabolic Health, The Third People's Hospital of Chengdu & The Affiliated Hospital of Southwest Jiaotong University, Chengdu, Sichuan, China
| | - Yanjun Liu
- Center for Obesity and Metabolic Health, The Third People's Hospital of Chengdu & The Affiliated Hospital of Southwest Jiaotong University, Chengdu, Sichuan, China; Center of Gastrointestinal and Minimally Invasive Surgery, Department of General Surgery, The Third People's Hospital of Chengdu & The Affiliated Hospital of Southwest Jiaotong University, Chengdu, Sichuan, China
| | - Tao Rong
- Department of Endocrinology and Metabolism, The Third People's Hospital of Chengdu & The Affiliated Hospital of Southwest Jiaotong University, Chengdu, Sichuan, China
| | - Yixin Wang
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Da Chen
- School of Environment and Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou, Guangdong, China
| | - Shuqin Zeng
- Key Laboratory of Birth Defects and Related Diseases of Women and Children, Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Chun-Xia Yang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China; Non-communicable Diseases Research Center, West China-PUMC C.C. Chen Institute of Health, Sichuan University, Chengdu, Sichuan, China
| | - Xiong-Fei Pan
- Key Laboratory of Birth Defects and Related Diseases of Women and Children, Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China; Shuangliu Institute of Women's and Children's Health, Shuangliu Maternal and Child Health Hospital, Chengdu, Sichuan, China.
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Ye Y, Wu P, Wang Y, Yang X, Ye Y, Yuan J, Liu Y, Song X, Yan S, Wen Y, Qi X, Yang C, Liu G, Lv C, Pan XF, Pan A. Adiponectin, leptin, and leptin/adiponectin ratio with risk of gestational diabetes mellitus: A prospective nested case-control study among Chinese women. Diabetes Res Clin Pract 2022; 191:110039. [PMID: 35985429 DOI: 10.1016/j.diabres.2022.110039] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Revised: 05/24/2022] [Accepted: 08/11/2022] [Indexed: 11/25/2022]
Abstract
AIMS To examine the associations of serum concentrations of adiponectin and leptin and leptin/adiponectin ratio (LAR) in early pregnancy with risk of gestational diabetes mellitus (GDM) in Chinese women. The predictive ability of those biomarkers for GDM was also assessed. METHODS Within the Tongji-Shuangliu Birth Cohort, a nested case-control study was established with 332 GDM cases and 664 matched controls at 1:2 ratio on age (±3 years) and gestational age (±4 weeks). Serum adiponectin and leptin levels were measured in early pregnancy (median gestational week, 11; range, 6-15). Conditional logistic regression models with adjustment for potential covariates were used to evaluate the associations. RESULTS Multivariable-adjusted odds ratios (ORs) comparing extreme quartiles of adiponectin, leptin and LAR were 0.55 (95 % CI, 0.35, 0.85), 1.96 (95 % CI, 1.19, 3.24), and 2.72 (95 % CI, 1.63, 4.54) for GDM, respectively (All P-trend < 0.02). Adding adiponectin and leptin to a conventional prediction model (including traditional risk factors and fasting glucose) increased the C-statistics from 0.708 (95 % CI, 0.674, 0.741) to 0.728 (95 % CI, 0.695, 0.760), and achieved a net reclassification improvement of 0.292. CONCLUSIONS Our findings indicate that adiponectin is inversely associated with GDM, while leptin and LAR are positively associated with GDM in Chinese pregnant women.
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Affiliation(s)
- Yi Ye
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ping Wu
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yi Wang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xue Yang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yixiang Ye
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jiaying Yuan
- Department of Science and Education, Shuangliu Maternal and Child Health Hospital, Chengdu, China
| | - Yan Liu
- Department of Science and Education, Shuangliu Maternal and Child Health Hospital, Chengdu, China
| | - Xingyue Song
- Department of Emergency, Hainan Clinical Research Center for Acute and Critical Diseases, The Second Affiliated Hospital of Hainan Medical University, Haikou, China
| | - Shijiao Yan
- Research Unit of Island Emergency Medicine, Chinese Academy of Medical Sciences, Hainan Medical University, Haikou, China; School of Public Health, Hainan Medical University, Haikou, China
| | - Ying Wen
- Department of Communicable Diseases Control and Prevention, Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Xiaorong Qi
- Department of Gynecology and Obstetrics, West China Second Hospital, State Key Laboratory of Biotherapy, Sichuan University, Chengdu, China
| | - Chunxia Yang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Gang Liu
- Department of Nutrition & Food Hygiene, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Chuanzhu Lv
- Research Unit of Island Emergency Medicine, Chinese Academy of Medical Sciences, Hainan Medical University, Haikou, China; Key Laboratory of Emergency and Trauma of Ministry of Education, Hainan Medical University, Haikou, China; Emergency Medicine Center, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
| | - Xiong-Fei Pan
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, China; Shuangliu Institute of Women's and Children's Health, Shuangliu Maternal and Child Health Hospital, Chengdu, Sichuan 610200, China.
| | - An Pan
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
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Yang JJ, Keohane LM, Pan XF, Qu R, Shu XO, Lipworth L, Braun K, Steinwandel MD, Dai Q, Shrubsole M, Zheng W, Blot WJ, Yu D. Association of Healthy Lifestyles With Risk of Alzheimer Disease and Related Dementias in Low-Income Black and White Americans. Neurology 2022; 99:e944-e953. [PMID: 35697505 PMCID: PMC9502739 DOI: 10.1212/wnl.0000000000200774] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Accepted: 04/08/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES Although the importance of healthy lifestyles for preventing Alzheimer disease and related dementias (ADRD) has been recognized, epidemiologic evidence remains limited for non-White or low-income individuals who bear disproportionate burdens of ADRD. This population-based cohort study aims to investigate associations of lifestyle factors, individually and together, with the risk of ADRD among socioeconomically disadvantaged Americans. METHODS In the Southern Community Cohort Study, comprising two-thirds self-reported Black and primarily low-income Americans, we identified incident ADRD using claims data among participants enrolled in Medicare for at least 12 consecutive months after age 65 years. Five lifestyle factors-tobacco smoking, alcohol consumption, leisure-time physical activity (LTPA), sleep hours, and diet quality-were each scored 0 (unhealthy), 1 (intermediate), or 2 (healthy) based on the health guidelines. A composite lifestyle score was created by summing all scores. Cox regression was used to estimate hazard ratios (HRs, 95% CIs) for incident ADRD, treating death as a competing risk. RESULTS We identified 1,694 patients with newly diagnosed ADRD among 17,209 participants during a median follow-up of 4.0 years in claims data; the mean age at ADRD diagnosis was 74.0 years. Healthy lifestyles were individually associated with an 11%-25% reduced risk of ADRD: multivariable-adjusted HR (95% CI) was 0.87 (0.76-0.99) for never vs current smoking, 0.81 (0.72-0.92) for low-to-moderate vs no alcohol consumption, 0.89 (0.77-1.03) for ≥150 minutes of moderate or ≥75 minutes of vigorous LTPA each week vs none, 0.75 (0.64-0.87) for 7-9 hours vs >9 hours of sleep, and 0.85 (0.75-0.96) for the highest vs lowest tertiles of the Healthy Eating Index. The composite lifestyle score showed a dose-response association with up to 36% reduced risk of ADRD: multivariable-adjusted HRs (95% CIs) across quartiles were 1 (ref), 0.88 (0.77-0.99), 0.79 (0.70-0.90), and 0.64 (0.55-0.74); p trend <0.001. The beneficial associations were observed regardless of participants' sociodemographics (e.g., race, education, and income) and health conditions (e.g., history of cardiometabolic diseases and depression). DISCUSSION Our findings support significant benefits of healthy lifestyles for ADRD prevention among socioeconomically disadvantaged Americans, suggesting that promoting healthy lifestyles and reducing barriers to lifestyle changes are crucial to tackling the growing burden and disparities posed by ADRD.
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Affiliation(s)
- Jae Jeong Yang
- From the Division of Epidemiology (J.J.Y., X.-F.P., R.Q., X.-O.S., L.L., Q.D., M.S., W.Z., W.J.B., D.Y.), Department of Medicine, Vanderbilt University Medical Center; Department of Health Policy (L.M.K., K.B.), Vanderbilt University School of Medicine; and International Epidemiology Field Station (M.D.S.), Vanderbilt University Medical Center, Nashville, TN
| | - Laura M Keohane
- From the Division of Epidemiology (J.J.Y., X.-F.P., R.Q., X.-O.S., L.L., Q.D., M.S., W.Z., W.J.B., D.Y.), Department of Medicine, Vanderbilt University Medical Center; Department of Health Policy (L.M.K., K.B.), Vanderbilt University School of Medicine; and International Epidemiology Field Station (M.D.S.), Vanderbilt University Medical Center, Nashville, TN
| | - Xiong-Fei Pan
- From the Division of Epidemiology (J.J.Y., X.-F.P., R.Q., X.-O.S., L.L., Q.D., M.S., W.Z., W.J.B., D.Y.), Department of Medicine, Vanderbilt University Medical Center; Department of Health Policy (L.M.K., K.B.), Vanderbilt University School of Medicine; and International Epidemiology Field Station (M.D.S.), Vanderbilt University Medical Center, Nashville, TN
| | - Ruiqi Qu
- From the Division of Epidemiology (J.J.Y., X.-F.P., R.Q., X.-O.S., L.L., Q.D., M.S., W.Z., W.J.B., D.Y.), Department of Medicine, Vanderbilt University Medical Center; Department of Health Policy (L.M.K., K.B.), Vanderbilt University School of Medicine; and International Epidemiology Field Station (M.D.S.), Vanderbilt University Medical Center, Nashville, TN
| | - Xiao-Ou Shu
- From the Division of Epidemiology (J.J.Y., X.-F.P., R.Q., X.-O.S., L.L., Q.D., M.S., W.Z., W.J.B., D.Y.), Department of Medicine, Vanderbilt University Medical Center; Department of Health Policy (L.M.K., K.B.), Vanderbilt University School of Medicine; and International Epidemiology Field Station (M.D.S.), Vanderbilt University Medical Center, Nashville, TN
| | - Loren Lipworth
- From the Division of Epidemiology (J.J.Y., X.-F.P., R.Q., X.-O.S., L.L., Q.D., M.S., W.Z., W.J.B., D.Y.), Department of Medicine, Vanderbilt University Medical Center; Department of Health Policy (L.M.K., K.B.), Vanderbilt University School of Medicine; and International Epidemiology Field Station (M.D.S.), Vanderbilt University Medical Center, Nashville, TN
| | - Kyle Braun
- From the Division of Epidemiology (J.J.Y., X.-F.P., R.Q., X.-O.S., L.L., Q.D., M.S., W.Z., W.J.B., D.Y.), Department of Medicine, Vanderbilt University Medical Center; Department of Health Policy (L.M.K., K.B.), Vanderbilt University School of Medicine; and International Epidemiology Field Station (M.D.S.), Vanderbilt University Medical Center, Nashville, TN
| | - Mark D Steinwandel
- From the Division of Epidemiology (J.J.Y., X.-F.P., R.Q., X.-O.S., L.L., Q.D., M.S., W.Z., W.J.B., D.Y.), Department of Medicine, Vanderbilt University Medical Center; Department of Health Policy (L.M.K., K.B.), Vanderbilt University School of Medicine; and International Epidemiology Field Station (M.D.S.), Vanderbilt University Medical Center, Nashville, TN
| | - Qi Dai
- From the Division of Epidemiology (J.J.Y., X.-F.P., R.Q., X.-O.S., L.L., Q.D., M.S., W.Z., W.J.B., D.Y.), Department of Medicine, Vanderbilt University Medical Center; Department of Health Policy (L.M.K., K.B.), Vanderbilt University School of Medicine; and International Epidemiology Field Station (M.D.S.), Vanderbilt University Medical Center, Nashville, TN
| | - Martha Shrubsole
- From the Division of Epidemiology (J.J.Y., X.-F.P., R.Q., X.-O.S., L.L., Q.D., M.S., W.Z., W.J.B., D.Y.), Department of Medicine, Vanderbilt University Medical Center; Department of Health Policy (L.M.K., K.B.), Vanderbilt University School of Medicine; and International Epidemiology Field Station (M.D.S.), Vanderbilt University Medical Center, Nashville, TN
| | - Wei Zheng
- From the Division of Epidemiology (J.J.Y., X.-F.P., R.Q., X.-O.S., L.L., Q.D., M.S., W.Z., W.J.B., D.Y.), Department of Medicine, Vanderbilt University Medical Center; Department of Health Policy (L.M.K., K.B.), Vanderbilt University School of Medicine; and International Epidemiology Field Station (M.D.S.), Vanderbilt University Medical Center, Nashville, TN
| | - William J Blot
- From the Division of Epidemiology (J.J.Y., X.-F.P., R.Q., X.-O.S., L.L., Q.D., M.S., W.Z., W.J.B., D.Y.), Department of Medicine, Vanderbilt University Medical Center; Department of Health Policy (L.M.K., K.B.), Vanderbilt University School of Medicine; and International Epidemiology Field Station (M.D.S.), Vanderbilt University Medical Center, Nashville, TN
| | - Danxia Yu
- From the Division of Epidemiology (J.J.Y., X.-F.P., R.Q., X.-O.S., L.L., Q.D., M.S., W.Z., W.J.B., D.Y.), Department of Medicine, Vanderbilt University Medical Center; Department of Health Policy (L.M.K., K.B.), Vanderbilt University School of Medicine; and International Epidemiology Field Station (M.D.S.), Vanderbilt University Medical Center, Nashville, TN.
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Yang X, Ye Y, Wang Y, Wu P, Lu Q, Liu Y, Yuan J, Song X, Yan S, Qi X, Wang YX, Wen Y, Liu G, Lv C, Yang CX, Pan A, Zhang J, Pan XF. Association between early-pregnancy serum C-peptide and risk of gestational diabetes mellitus: a nested case-control study among Chinese women. Nutr Metab (Lond) 2022; 19:56. [PMID: 35996181 PMCID: PMC9396763 DOI: 10.1186/s12986-022-00691-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 08/01/2022] [Indexed: 11/10/2022] Open
Abstract
OBJECTIVE To examine the association of early-pregnancy serum C-peptide with incident gestational diabetes mellitus (GDM) and the predictive ability of maternal C-peptide for GDM. METHODS A nested case-control study of 332 GDM cases and 664 controls was established based on the Tongji-Shuangliu Birth Cohort. The GDM cases and controls were matched at 1:2 on maternal age (± 3 years) and gestational age (± 4 weeks). Multivariable conditional logistic regression was applied to assess the association of C-peptide with risk of GDM. Partial Spearman's correlation coefficients were estimated for the correlations between C-peptide and multiple metabolic biomarkers. C-statistics were calculated to assess the predictive ability of early-pregnancy C-peptide for GDM. RESULTS Of 996 pregnant women, median maternal age was 28.0 years old and median gestational age was 11.0 weeks. After adjustment for potential confounders, the odds ratio of GDM comparing the extreme quartiles of C-peptide was 2.28 (95% confidence interval, 1.43, 3.62; P for trend < 0.001). Partial correlation coefficients ranged between 0.07 and 0.77 for the correlations of C-peptide with fasting insulin, homeostatic model of insulin resistance, leptin, fasting blood glucose, triglycerides, glycosylated hemoglobin, waist-hip ratio, systolic blood pressure, and low-density lipoprotein cholesterol (P ≤ 0.025), and were - 0.11 and - 0.17 for high-density lipoprotein cholesterol and adiponectin (P < 0.001). Serum C-peptide slightly improved the predictive performance of the model with conventional predictive factors (0.66 vs. 0.63; P = 0.008). CONCLUSION While the predictive value for subsequent GDM should be validated, early-pregnancy serum C-peptide may be positively associated with risk of GDM.
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Affiliation(s)
- Xue Yang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, 610041, Sichuan, China.,Non-Communicable Diseases Research Center, West China-PUMC C.C. Chen Institute of Health, Sichuan University, Chengdu, 610041, Sichuan, China.,Wenjiang Institute of Women's and Children's Health, Wenjiang Maternal and Child Health Hospital, Chengdu, 611130, Sichuan, China
| | - Yi Ye
- Department of Epidemiology and Biostatistics, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China.,Ministry of Education and Ministry of Environmental Protection Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (Incubation), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
| | - Yi Wang
- Department of Epidemiology and Biostatistics, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China.,Ministry of Education and Ministry of Environmental Protection Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (Incubation), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
| | - Ping Wu
- Department of Epidemiology and Biostatistics, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China.,Ministry of Education and Ministry of Environmental Protection Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (Incubation), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
| | - Qi Lu
- Department of Epidemiology and Biostatistics, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China.,Ministry of Education and Ministry of Environmental Protection Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (Incubation), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
| | - Yan Liu
- Department of Obstetrics and Gynecology, Shuangliu Maternal and Child Health Hospital, Chengdu, 610200, Sichuan, China
| | - Jiaying Yuan
- Department of Science and Education, Shuangliu Maternal and Child Health Hospital, Chengdu, 610200, Sichuan, China
| | - Xingyue Song
- Department of Emergency, Hainan Clinical Research Center for Acute and Critical Diseases, The Second Affiliated Hospital of Hainan Medical University, Haikou, 571199, Hainan, China.,Key Laboratory of Emergency and Trauma of Ministry of Education, Hainan Medical University, Haikou, 571199, Hainan, China
| | - Shijiao Yan
- Research Unit of Island Emergency Medicine, Chinese Academy of Medical Sciences, Hainan Medical University, Haikou, 571199, Hainan, China.,School of Public Health, Hainan Medical University, Haikou, 571199, Hainan, China
| | - Xiaorong Qi
- Department of Gynecology and Obstetrics, West China Second Hospital, State Key Laboratory of Biotherapy, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Yi-Xin Wang
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, 02115, USA
| | - Ying Wen
- Department of Communicable Diseases Control and Prevention, Shenzhen Center for Disease Control and Prevention, Shenzhen, 518055, Guangdong, China
| | - Gang Liu
- Ministry of Education and Ministry of Environmental Protection Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (Incubation), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China.,Department of Nutrition and Food Hygiene, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
| | - Chuanzhu Lv
- Department of Emergency, Hainan Clinical Research Center for Acute and Critical Diseases, The Second Affiliated Hospital of Hainan Medical University, Haikou, 571199, Hainan, China.,Key Laboratory of Emergency and Trauma of Ministry of Education, Hainan Medical University, Haikou, 571199, Hainan, China.,Research Unit of Island Emergency Medicine, Chinese Academy of Medical Sciences, Hainan Medical University, Haikou, 571199, Hainan, China
| | - Chun-Xia Yang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, 610041, Sichuan, China.,Non-Communicable Diseases Research Center, West China-PUMC C.C. Chen Institute of Health, Sichuan University, Chengdu, 610041, Sichuan, China
| | - An Pan
- Department of Epidemiology and Biostatistics, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China.,Ministry of Education and Ministry of Environmental Protection Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (Incubation), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
| | - Jianli Zhang
- Wenjiang Institute of Women's and Children's Health, Wenjiang Maternal and Child Health Hospital, Chengdu, 611130, Sichuan, China.
| | - Xiong-Fei Pan
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, 610041, Sichuan, China. .,NMPA Key Laboratory for Technical Research on Drug Products in Vitro and in Vivo Correlation, West China Second University Hospital, Sichuan University, Chengdu, 610041, Sichuan, China. .,Shuangliu Institute of Women's and Children's Health, Shuangliu Maternal and Child Health Hospital, Chengdu, 610200, Sichuan, China.
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Wu P, Wang Y, Ye Y, Yang X, Lu Q, Yuan J, Zha L, Liu Y, Song X, Yan S, Wen Y, Qi X, Yang CX, Wang Y, Liu G, Lv C, Pan XF, Pan A. Serum Fetuin-A and Risk of Gestational Diabetes Mellitus: An Observational Study and Mendelian Randomization Analysis. J Clin Endocrinol Metab 2022; 107:e3841-e3849. [PMID: 35640639 DOI: 10.1210/clinem/dgac335] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Indexed: 11/19/2022]
Abstract
CONTEXT Fetuin-A was reported to be associated with risk of type 2 diabetes, but its association with incident gestational diabetes mellitus (GDM) was less studied. OBJECTIVE We aimed to examine the association between fetuin-A levels in early pregnancy and risk of incident GDM and to evaluate whether this association was causal. METHODS A total of 332 pregnant women with GDM and 664 matched controls were included in this nested case-control study. Multivariable conditional logistic regression was applied to investigate the prospective association between serum fetuin-A in early pregnancy and subsequent risk of GDM. Two-sample Mendelian randomization (MR) analysis was used to examine the causal association, using summary statistics from the CHARGE Consortium and the FinnGen consortium. RESULTS The mean age of the participants was 28.0 years, and the mean gestational age was 11.0 weeks (range 6-15) at enrollment. In the final model, the odds ratio (OR) for GDM comparing the extreme quartiles of fetuin-A levels was 1.78 (95% CI 1.06, 2.98; P for trend = 0.009), and the restricted cubic spline analysis indicated a linear association (P for nonlinearity = 0.83). This positive association was found in women with waist circumference <80 cm but not in those with waist circumference ≥80 cm (P for interaction = 0.04). However, MR analyses showed no evidence of a causal association with an OR of 0.91 (95% CI 0.67, 1.23) per unit increment of fetuin-A. CONCLUSIONS Serum fetuin-A levels in early pregnancy were positively associated with risk of GDM, particularly in those with normal waist circumference. However, we found no genetic evidence for a causal association.
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Affiliation(s)
- Ping Wu
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yi Wang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yi Ye
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xue Yang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Qi Lu
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Jiaying Yuan
- Department of Science and Education, Shuangliu Maternal and Child Health Hospital, Chengdu, China
| | - Li Zha
- Department of Obstetrics and Gynecology, Shuangliu Maternal and Child Health Hospital, Chengdu, China
| | - Yan Liu
- Department of Obstetrics and Gynecology, Shuangliu Maternal and Child Health Hospital, Chengdu, China
| | - Xingyue Song
- Department of Emergency, Hainan Clinical Research Center for Acute and Critical Diseases, The Second Affiliated Hospital of Hainan Medical University, Haikou, China
| | - Shijiao Yan
- Research Unit of Island Emergency Medicine, Chinese Academy of Medical Sciences, Hainan Medical University, Haikou, China
- School of Public Health, Hainan Medical University, Haikou, China
| | - Ying Wen
- Department of Communicable Diseases Control and Prevention, Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Xiaorong Qi
- Department of Gynecology and Obstetrics, West China Second Hospital, State Key Laboratory of Biotherapy, Sichuan University, Chengdu, China
| | - Chun-Xia Yang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yixin Wang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Gang Liu
- Department of Nutrition & Food Hygiene, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Chuanzhu Lv
- Research Unit of Island Emergency Medicine, Chinese Academy of Medical Sciences, Hainan Medical University, Haikou, China
- Key Laboratory of Emergency and Trauma of Ministry of Education, Hainan Medical University, Haikou, China
- Emergency Medicine Center, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China
| | - Xiong-Fei Pan
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, China
- Shuangliu Institute of Women's and Children's Health, Shuangliu Maternal and Child Health Hospital, Chengdu, China
| | - An Pan
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
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Zhang YB, Li Y, Geng TT, Pan XF, Zhou YF, Liu G, Pan A. Overall lifestyles and socioeconomic inequity in mortality and life expectancy in China: the China health and nutrition survey. Age Ageing 2022; 51:6632481. [PMID: 35796136 DOI: 10.1093/ageing/afac167] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 05/19/2022] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND socioeconomic inequity in mortality and life expectancy remains inconclusive in low- and middle-income countries, and to what extent the associations are mediated or modified by lifestyles remains debatable. METHODS we included 21,133 adults from China Health and Nutrition Survey (1991-2011) and constructed three parameters to reflect participants' overall individual- (synthesising income, education and occupation) and area-level (urbanisation index) socioeconomic status (SES) and lifestyles (counting the number of smoking, physical inactivity and unhealthy diet and bodyweight). HRs for mortality and life expectancy were estimated by time-dependent Cox model and life table method, respectively. RESULTS during a median follow-up of 15.2 years, 1,352 deaths were recorded. HRs (95% CIs) for mortality comparing low versus high individual- and area-level SES were 2.38 (1.75-3.24) and 1.84 (1.51-2.24), respectively, corresponding to 5.7 (2.7-8.6) and 5.0 (3.6-6.3) life-year lost at age 50. Lifestyles explained ≤11.5% of socioeconomic disparity in mortality. Higher lifestyle risk scores were associated with higher mortality across all socioeconomic groups. HR (95% CI) for mortality comparing adults with low individual-level SES and 3-4 lifestyle risk factors versus those with high SES and 0-1 lifestyle risk factors was 7.06 (3.47-14.36), corresponding to 19.1 (2.6-35.7) life-year lost at age 50. CONCLUSION this is the first nationwide cohort study reporting that disadvantaged SES was associated with higher mortality and shorter life expectancy in China, which was slightly mediated by lifestyles. Risk lifestyles were related to higher mortality across all socioeconomic groups, and those with risk lifestyles and disadvantaged SES had much higher mortality risks.
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Affiliation(s)
- Yan-Bo Zhang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yue Li
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ting-Ting Geng
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiong-Fei Pan
- Key Laboratory of Birth Defects and Related Diseases of Women and Children, Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, China
| | - Yan-Feng Zhou
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Gang Liu
- Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - An Pan
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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Sun Y, Wang YX, Mustieles V, Zhang Y, Pan XF, Messerlian C. Blood trihalomethane concentrations and lung function in US adolescents: a nationally representative cross-sectional study. Eur Respir J 2022; 60:2200753. [PMID: 35680146 DOI: 10.1183/13993003.00753-2022] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Accepted: 05/12/2022] [Indexed: 11/05/2022]
Affiliation(s)
- Yang Sun
- Department of Environmental Health and Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Yi-Xin Wang
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Vicente Mustieles
- University of Granada, Center for Biomedical Research (CIBM), Granada, Spain
- Instituto de Investigación Biosanitaria Ibs Granada, Granada, Spain
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Granada, Spain
| | - Yu Zhang
- Department of Environmental Health and Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Xiong-Fei Pan
- Key Laboratory of Birth Defects and Related Diseases of Women and Children, Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, China
| | - Carmen Messerlian
- Department of Environmental Health and Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
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Yan T, Huang Y, Wu JHY, Zhuang XD, Pan XF. Editorial: Insulin Resistance, Metabolic Syndrome, and Cardiovascular Disease. Front Cardiovasc Med 2022; 9:959680. [PMID: 35811727 PMCID: PMC9257250 DOI: 10.3389/fcvm.2022.959680] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Accepted: 06/09/2022] [Indexed: 11/22/2022] Open
Affiliation(s)
- Tong Yan
- Department of General Surgery, Center for Obesity and Metabolic Health, The Third People's Hospital of Chengdu and the Affiliated Hospital of Southwest Jiaotong University, Chengdu, China
| | - Yuli Huang
- Department of Cardiology, Shunde Hospital, Southern Medical University, Guangzhou, China
| | - Jason H. Y. Wu
- The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
| | - Xiao-Dong Zhuang
- Cardiology Department, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Xiong-Fei Pan
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, China
- Shuangliu Institute of Women's and Children's Health, Shuangliu Maternal and Child Health Hospital, Chengdu, China
- *Correspondence: Xiong-Fei Pan
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Du H, Shi Q, Song P, Pan XF, Yang X, Chen L, He Y, Zong G, Zhu Y, Su B, Li S. Global Burden Attributable to High Low-Density Lipoprotein-Cholesterol From 1990 to 2019. Front Cardiovasc Med 2022; 9:903126. [PMID: 35757342 PMCID: PMC9218272 DOI: 10.3389/fcvm.2022.903126] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Accepted: 05/02/2022] [Indexed: 01/29/2023] Open
Abstract
Background High low-density lipoprotein-cholesterol (LDL-C) is a public health issue contributing to ischemic heart disease (IHD) and stroke. Method In this ecological study, we collected summary exposure values (SEVs), deaths, disability-adjusted life of years (DALYs), and Social Demographic Index (SDI) of high LDL-C from 1990 to 2019 using the query tool from the Global Burden of Disease (GBD) Collaborative Network. Outcomes include SEVs, deaths, and DALYs attributable to high LDL-C stratified by sex, age, region, SDI, countries, and territories. Estimated annual percentage changes (EAPCs) were applied to estimate annual trends of changes in these outcomes. We applied the weighted segmented regression with break-point estimation to detect the linear piecewise relationship between SDI and high LDL-C disease burden. Results Globally, 3.00 million (95% uncertainty interval [UI], 2.35–3.76 million) people in 1990 and 4.40 million (95% UI, 3.30–5.65 million) people died from high LDL-C in 2019. The absolute annual burden from deaths and DALYs attributed to high LDL-C increased by 46% (95% UI, 35–56%) and 41% (95% UI, 31–50%) from 1990 to 2019. The age-standardized SEV, death, and DALY was decreased by 9% (95% UI, −11 to −8%), 37% (95% UI, −41−33%), and 32% (95% UI, −37 to −28%), respectively, during the study period. There was a negative association between SDI and high LDL-C-related age-standardized death and DALY rates when SDI surpassed 0.71 and 0.71, respectively. Conclusion Although the overall age-standardized burden of high LDL-C is controlled in the past 30 years, it remains increasing in moderate SDI countries, and decreasing trends are disappearing in high SDI countries. New challenges require new actions stratified by countries with different SDI levels.
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Affiliation(s)
- Heyue Du
- Department of Endocrinology and Metabolism, West China Hospital, Sichuan University, Chengdu, China
- Department of Nephrology, West China Hospital, Sichuan University, Chengdu, China
| | - Qingyang Shi
- Department of Guideline and Rapid Recommendation, Chinese Evidence-Based Medicine Center, Cochrane China Center and MAGIC China Center, West China Hospital, Sichuan University, Chengdu, China
| | - Peige Song
- School of Public Health, Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China
| | - Xiong-Fei Pan
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
- Ministry of Education Key Laboratory of Environment and Health and State Environmental Protection Key Laboratory of Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
| | - Xueli Yang
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin Medical University, Tianjin, China
- Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin, China
| | - Lingmin Chen
- Department of Anesthesiology and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
- Research Units of West China, Chinese Academy of Medical Sciences, Chengdu, China
| | - Yazhou He
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Geng Zong
- CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Ye Zhu
- Department of Cardiology, West China Hospital, Sichuan University, Chengdu, China
| | - Baihai Su
- Department of Nephrology, West China Hospital, Sichuan University, Chengdu, China
| | - Sheyu Li
- Department of Endocrinology and Metabolism, West China Hospital, Sichuan University, Chengdu, China
- Department of Guideline and Rapid Recommendation, Chinese Evidence-Based Medicine Center, Cochrane China Center and MAGIC China Center, West China Hospital, Sichuan University, Chengdu, China
- *Correspondence: Sheyu Li, ;
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Chen YJ, Liu C, Tu ZZ, Lu Q, Messerlian C, Mustieles V, Sun Y, Lu WQ, Pan XF, Mao C, Wang YX. Associations of Urinary Trichloroacetic Acid Concentrations with Spermatozoa Apoptosis and DNA Damage in a Chinese Population. Environ Sci Technol 2022; 56:6491-6499. [PMID: 35472294 DOI: 10.1021/acs.est.1c07725] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Exposure to trichloroacetic acid (TCAA) has been associated with impaired semen quality; however, its association with spermatozoa apoptosis and DNA damage remains unclear. We, therefore, collected single semen and repeated urine samples from male partners of couples attending a reproductive center, which were measured for spermatozoa apoptosis and DNA damage parameters and TCAA concentrations, respectively. Multivariable linear regression models were used to explore the associations between urinary TCAA concentrations and spermatozoa apoptosis (n = 462) and DNA damage parameters (n = 512). After adjusting for potential confounders, positive dose-response relationships were found between urinary TCAA concentrations and percentage of tail DNA (tail%) and tail-distributed moment (TDM) (both p for trend <0.10). Compared with men in the lowest tertile of urinary TCAA concentrations, men in the highest tertile had a greater tail% and TDM of 6.2% (95% CI: 0.7, 12.2%) and 8.9% (95% CI: -1.9, 20.5%), respectively. Urinary TCAA concentrations were unrelated to spermatozoa apoptosis parameters in a dose-response manner. However, urinary TCAA concentrations were positively associated with the percentage of Annexin V+/PI- spermatozoa (apoptotic cells), when urinary TCAA concentrations were modeled as continuous variables. Our results suggest that exposure to TCAA at concentrations in real-world scenarios may be associated with spermatozoa apoptosis and DNA damage.
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Affiliation(s)
- Ying-Jun Chen
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong Province 510515, China
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Chong Liu
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, P. R. China
| | - Zhou-Zheng Tu
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Qi Lu
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Carmen Messerlian
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 02115, United States
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 02115, United States
| | - Vicente Mustieles
- Center for Biomedical Research (CIBM), University of Granada, 18016 Granada, Spain
- Instituto de Investigación Biosanitaria Ibs GRANADA, 18012 Granada, Spain
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), 28029 Madrid, Spain
| | - Yang Sun
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 02115, United States
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 02115, United States
| | - Wen-Qing Lu
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Xiong-Fei Pan
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Chen Mao
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong Province 510515, China
| | - Yi-Xin Wang
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 02115, United States
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Liu Y, Ye YX, Wang Y, Wang F, Huang YC, Chen D, Pan XF, Pan A. [Associations between plasma n-3 polyunsaturated fatty acids and gestational diabetes mellitus in the second trimester]. Zhonghua Yu Fang Yi Xue Za Zhi 2022; 56:312-321. [PMID: 35381652 DOI: 10.3760/cma.j.cn112150-20210428-00422] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Objective: To examine the associations between plasma n-3 polyunsaturated fatty acids (PUFAs) in the second trimester and gestational diabetes mellitus (GDM) among Chinese pregnant women. Methods: Based on data from the Tongji-Shuangliu Birth Cohort enrolled from 2017 to 2019 in the Shuangliu Maternal and Child Health Hospital, it conducted a case-control study among 269 GDM cases who were diagnosed by 75 g oral glucose tolerance test, and 538 non-GDM controls matched at a 1∶2 ratio on maternal age and gestational weeks. The age range of the 807 women was 18-40 years. Fasting plasma n-3 PUFAs were determined by gas chromatography-mass spectrometry in the second trimester (24-28 weeks). Participants were categorized into quartiles (Q1-Q4) of plasma n-3 PUFAs based on distributions in the control group. Conditional logistic regression models were applied to estimate the associations between plasma n-3 PUFAs and GDM. Results: The median (interquartile) relative concentrations of plasma n-3 PUFA C22∶5n-3 was significantly lower in women with GDM 0.87 (0.72, 1.07) compared with women without GDM 0.94 (0.75, 1.19)(P=0.001). Plasma n-3 PUFA C22∶5n-3 was inversely associated with GDM, with an OR (95%CI) of 0.75 (0.62-0.90) for each SD increase of relative concentration. Compared with the Q1 group, the OR values and 95%CIs of Q2, Q3, and Q4 groups were 0.97 (0.62-1.51), 0.72 (0.45-1.15), and 0.54 (0.32-0.90), respectively (Ptrend<0.05). However, there were no significant associations of C18∶3n-3, C20∶5n-3, C22∶6n-3, and total n-3 PUFAs with GDM. Conclusion: Plasma n-3 PUFA C22∶5n-3 was inversely associated with GDM during the second trimester.
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Affiliation(s)
- Y Liu
- Chengdu Shuangliu District Maternal and Child Health Hospital, Chengdu 610000, China
| | - Y X Ye
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Y Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - F Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Y C Huang
- Department of Health Toxicology, School of Public Health, Anhui Medical University, Hefei 230032, China
| | - D Chen
- College of Environment, Jinan University, Guangzhou 510632, China
| | - X F Pan
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu 610041, China
| | - An Pan
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
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Yang X, Xie Y, Wang Y, Yu Y, Jin X, Xiu P, Wu JHY, Yu D, Pan A, Zhao J, Yang CX, Pan XF. Arthritis is associated with an increased risk of incident diabetes in Chinese adults: A nationwide cohort study and updated meta-analysis. Diabetes Metab Res Rev 2022; 38:e3487. [PMID: 34289224 DOI: 10.1002/dmrr.3487] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Revised: 04/19/2021] [Accepted: 05/29/2021] [Indexed: 02/05/2023]
Abstract
AIMS To prospectively examine the association between arthritis and type 2 diabetes (T2D) in the Chinese population and confirm this association through a comprehensive meta-analysis of cohort studies. METERIALS AND METHODS Data were from the China Health and Retirement Longitudinal Study which was started in 2011-2013 and followed up in 2013-2014 and 2015-2016. Arthritis was defined as self-reported physician diagnosis at baseline, and incident T2D was determined by self-reported physician diagnosis, fasting blood glucose ≥7.0 mmol/L or glycosylated haemoglobin ≥6.5% during the follow-ups. Cox proportional hazards regression models were used to assess the association between arthritis and risk for T2D. A meta-analysis was conducted to pool our effect estimate and those from other cohort studies using a random-effects model. RESULTS Eleven thousand four hundred and eight participants (47.9% men; mean age: 59.3 years) were included in final analyses. During a 4-year follow-up, 981 participants reported incident T2D. Compared with individuals without arthritis, those with arthritis at baseline had an 18% higher risk for incident T2D (multivariable-adjusted hazard ratio: 1.18; 95% confidence interval: 1.04, 1.34). In the meta-analysis of 13 cohort studies including ours, a total of 2,473,514 participants were included with 121,851 incident diabetes. The pooling HR was 1.32 (95% CI: 1.21, 1.44) for the association between arthritis and diabetes. CONCLUSION Arthritis was associated with an increased risk of incident diabetes in Chinese adults, and the positive association was confirmed in the meta-analysis of cohort studies. Our work can inform clinical trials to assess the effectiveness of arthritis treatments in reducing risk of diabetes.
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Affiliation(s)
- Xue Yang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yue Xie
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yi Wang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health and State Key Laboratory of Environmental Health (incubation), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yong Yu
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xingzhong Jin
- Centre for Big Data Research in Health, University of New South Wales, Sydney, New South Wales, Australia
| | - Peng Xiu
- Department of Orthopedics, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Jason H Y Wu
- The George Institute for Global Health, University of New South Wales, Sydney, New South Wales, Australia
| | - Danxia Yu
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - An Pan
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health and State Key Laboratory of Environmental Health (incubation), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Jian Zhao
- The Ministry of Education - Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chun-Xia Yang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xiong-Fei Pan
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health and State Key Laboratory of Environmental Health (incubation), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- The George Institute for Global Health, University of New South Wales, Sydney, New South Wales, Australia
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
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Wu P, Wang Y, Ye Y, Yang X, Lu Q, Liu Y, Zeng H, Song X, Yan S, Wen Y, Qi X, Yang CX, Liu G, Lv C, Pan XF, Pan A. Serum retinol-binding protein 4 levels and risk of gestational diabetes mellitus: A nested case-control study in Chinese women and an updated meta-analysis. Diabetes Metab Res Rev 2022; 38:e3496. [PMID: 34537998 DOI: 10.1002/dmrr.3496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/22/2021] [Revised: 07/25/2021] [Accepted: 08/11/2021] [Indexed: 11/11/2022]
Abstract
AIMS We prospectively evaluated the association of circulating retinol-binding protein 4 (RBP4) levels in early pregnancy and risk of incident gestational diabetes mellitus (GDM) in pregnant women. METHODS A nested case-control study was conducted among 332 women who developed GDM and 664 matched controls based on the Tongji-Shuangliu Birth Cohort. GDM was diagnosed during 24-28 weeks of gestation according to the International Association of Diabetes and Pregnancy Study Group criteria. Serum RBP4 levels in early pregnancy (6-15 weeks of gestation) were determined by ELISA assay. Multivariable conditional logistic regression models were used to analyse the association and generated the odds ratio (OR) and 95% confidence interval (CI). EMBASE and PubMed were searched up to 30 November 2020 to identify studies investigating the association between blood RBP4 levels in early pregnancy and incident GDM. RESULTS In the multivariable model with adjustment of potential risk factors, the OR comparing the extreme quartiles of serum RBP4 levels was 2.26 (95% CI: 1.34, 3.81; p for trend <0.001), and each standard deviation (SD) increment of RBP4 was associated with 1.39-fold (95% CI: 1.15, 1.69) higher risk of GDM. The results were confirmed in a meta-analysis that included additional four studies with an overall OR of 1.47 (95% CI: 1.18, 1.83) per 1-SD increment of RBP4. CONCLUSIONS Serum RBP4 levels in early pregnancy, independent of metabolic risk factors, are positively associated with the risk of GDM in pregnant women. Our findings may provide new insights into the mechanisms underlying the aetiology of GDM.
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Affiliation(s)
- Ping Wu
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yi Wang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yi Ye
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xue Yang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Qi Lu
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yan Liu
- Department of Obstetrics and Gynecology, Shuangliu Maternal and Child Health Hospital, Chengdu, Sichuan, China
| | - Huayan Zeng
- Nutrition Department, Shuangliu Maternal and Child Health Hospital, Chengdu, Sichuan, China
| | - Xingyue Song
- Department of Emergency, Hainan Clinical Research Center for Acute and Critical Diseases, The Second Affiliated Hospital of Hainan Medical University, Haikou, Hainan, China
| | - Shijiao Yan
- Research Unit of Island Emergency Medicine, Chinese Academy of Medical Sciences, Hainan Medical University, Haikou, Hainan, China
- School of Public Health, Hainan Medical University, Haikou, Hainan, China
| | - Ying Wen
- Department of Communicable Diseases Control and Prevention, Shenzhen Center for Disease Control and Prevention, Shenzhen, Guangdong, China
| | - Xiaorong Qi
- Department of Gynecology and Obstetrics, West China Second Hospital, State Key Laboratory of Biotherapy, Sichuan University, Chengdu, Sichuan, China
| | - Chun-Xia Yang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Gang Liu
- Department of Nutrition & Food Hygiene, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Chuanzhu Lv
- Research Unit of Island Emergency Medicine, Chinese Academy of Medical Sciences, Hainan Medical University, Haikou, Hainan, China
- Key Laboratory of Emergency and Trauma of Ministry of Education, Hainan Medical University, Haikou, Hainan, China
- Emergency Medicine Center, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Xiong-Fei Pan
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - An Pan
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
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Wang Y, Sun F, Wu P, Huang Y, Ye Y, Yang X, Yuan J, Liu Y, Zeng H, Wen Y, Qi X, Yang CX, Wang Y, Liu G, Chen D, Li L, Pan XF, Pan A. A Prospective Study of Early-pregnancy Thyroid Markers, Lipid Species, and Risk of Gestational Diabetes Mellitus. J Clin Endocrinol Metab 2022; 107:e804-e814. [PMID: 34453541 DOI: 10.1210/clinem/dgab637] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Revised: 08/23/2021] [Indexed: 11/19/2022]
Abstract
CONTEXT While the associations between thyroid markers and gestational diabetes mellitus (GDM) have been extensively studied, the results are inconclusive and the mechanisms remain unclear. OBJECTIVE We aimed to investigate the prospective associations of thyroid markers in early gestation with GDM risk, and examine the mediating effects through lipid species. METHODS This study included 6068 pregnant women from the Tongji-Shuangliu Birth Cohort. Maternal serum thyroid markers (free triiodothyronine (fT3), free thyroxine (fT4), thyroid-stimulating hormone, thyroid peroxidase antibody, and thyroglobulin antibody) were measured before 15 weeks. Deiodinase activity was assessed by fT3/fT4 ratio. Plasma lipidome were quantified in a subset of 883 participants. RESULTS Mean age of the participants was 26.6 ± 3.7 years, and mean gestational age was 10.3 ± 2.0 weeks. Higher levels of fT4 were associated with a decreased risk of GDM (OR = 0.73 comparing the extreme quartiles; 95% CI 0.54, 0.98, Ptrend = .043), while higher fT3/fT4 ratio was associated with an increased risk of GDM (OR = 1.43 comparing the extreme quartiles; 95% CI 1.06, 1.93, Ptrend = .010) after adjusting for potential confounders. Multiple linear regression suggested that fT3/fT4 ratio was positively associated with alkylphosphatidylcholine 36:1, phosphatidylethanolamine plasmalogen 38:6, diacylglyceride 18:0/18:1, sphingomyelin 34:1, and phosphatidylcholine 40:7 (false discovery rate [FDR] adjusted P < .05). Mediation analysis indicated 67.9% of the association between fT3/fT4 ratio and GDM might be mediated through the composite effect of these lipids. CONCLUSION Lower concentration of serum fT4 or higher fT3/fT4 ratio in early pregnancy was associated with an increased risk of GDM. The association of fT3/fT4 ratio with GDM was largely mediated by specific lipid species.
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Affiliation(s)
- Yi Wang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Fengjiang Sun
- School of Environment and Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou 511436, China
| | - Ping Wu
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Yichao Huang
- School of Environment and Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou 511436, China
- Department of Toxicology, School of Public Health, Anhui Medical University, Hefei 230032, China
| | - Yi Ye
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Xue Yang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, China
| | - Jiaying Yuan
- Department of Science and Education, Shuangliu Maternal and Child Health Hospital, Chengdu 610200, China
| | - Yan Liu
- Department of Obstetrics and Gynecology, Shuangliu Maternal and Child Health Hospital, Chengdu 610200, China
| | - Huayan Zeng
- Nutrition Department, Shuangliu Maternal and Child Health Hospital, Chengdu 610200, China
| | - Ying Wen
- Department of Communicable Diseases Control and Prevention, Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, China
| | - Xiaorong Qi
- Department of Gynecology and Obstetrics, West China Second Hospital, State Key Laboratory of Biotherapy, Sichuan University, Chengdu 610041, China
| | - Chun-Xia Yang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, China
| | - Yixin Wang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Gang Liu
- Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Da Chen
- School of Environment and Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou 511436, China
| | - Liangzhong Li
- State Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510655, China
| | - Xiong-Fei Pan
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - An Pan
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
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Xue Q, Yang X, Huang Y, Zhu D, Wang Y, Wen Y, Zhao J, Liu Y, Yang CX, Pan J, Yan T, Pan XF. Association between baseline and changes in high-sensitive C-reactive protein and metabolic syndrome: a nationwide cohort study and meta-analysis. Nutr Metab (Lond) 2022; 19:2. [PMID: 34991636 PMCID: PMC8734319 DOI: 10.1186/s12986-021-00632-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Accepted: 11/30/2021] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND We aimed to prospectively evaluate the associations between the baseline and changes in high-density C-reactive protein (hs-CRP) and incident metabolic syndrome (MetS) in China and update the evidence based on a meta-analysis of cohort studies in different populations. METHODS Data from the China Health and Retirement Longitudinal Study among adults aged 45 years or older were analyzed. Participants who were recruited in the study in 2011-2012 without MetS and successfully followed up to 2015-2016 were included in our final analysis. Logistic regressions were applied to examine the prospective associations of baseline and changes in hs-CRP with incident MetS and estimate corresponding odds ratios (ORs) and 95% confidence intervals (95% CIs). A meta-analysis was conducted to synthesize effect estimates from our findings and other cohort studies on this topic. RESULTS Among 4,116 participants, 535 developed MetS after a 4-year follow-up. Compared with the participants with hs-CRP in the lowest quartile, those with hs-CRP in the second, third, and highest quartiles had higher odds of MetS, with multivariable-adjusted ORs (95% CIs) of 1.51 (1.12, 2.06), 1.50 (1.11, 2.04), and 1.83 (1.37, 2.47). For the hs-CRP changes, ORs (95% CIs) were 3.24 (2.51, 4.02), 3.34 (2.56, 4.38), and 3.34 (2.54, 4.40) respectively. One unit (log of 1 mg/L) increase in hs-CRP was associated with 23% higher risk of MetS (OR 1.23; 95% CI 1.10, 1.38). In a meta-analysis of 6 cohort studies, the pooled relative risk for MetS was 1.63 (1.38, 1.93) for the highest versus lowest level of hs-CRP. In addition, the pooled relative risk for MetS was 1.29 (1.05, 1.59) for each unit increase of hs-CRP after log-transformation. CONCLUSIONS Both higher baseline hs-CRP and longitudinal hs-CRP increases were associated with higher risks of incident MetS. Individuals with high hs-CRP levels may need to be closely monitored for future risk of MetS.
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Affiliation(s)
- Qingping Xue
- Department of Epidemiology and Biostatistics, School of Public Health, Chengdu Medical College, Chengdu, Sichuan, China
- HEOA Group, Institute for Healthy Cities and West China Research Center for Rural Health Development, Sichuan University, Chengdu, Sichuan, China
| | - Xue Yang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yuli Huang
- Department of Cardiology, Shunde Hospital, Southern Medical University, Foshan, Guangdong, China
- The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
| | - Dongshan Zhu
- Center for Health Management and Policy Research, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China
| | - Yi Wang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health and State Key Laboratory of Environmental Health (Incubation), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Ying Wen
- Department of Communicable Diseases Control and Prevention, Shenzhen Center for Disease Control and Prevention, Shenzhen, Guangdong, China
| | - Jian Zhao
- The Ministry of Education - Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yanjun Liu
- Center of Gastrointestinal and Minimally Invasive Surgery, Department of General Surgery, The Third People's Hospital of Chengdu and The Affiliated Hospital of Southwest Jiaotong University, Chengdu, Sichuan, China
- Center for Obesity and Metabolic Health, The Third People's Hospital of Chengdu and The Affiliated Hospital of Southwest Jiaotong University, Chengdu, Sichuan, China
| | - Chun-Xia Yang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Jay Pan
- HEOA Group, Institute for Healthy Cities and West China Research Center for Rural Health Development, Sichuan University, Chengdu, Sichuan, China
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Tong Yan
- Center for Obesity and Metabolic Health, The Third People's Hospital of Chengdu and The Affiliated Hospital of Southwest Jiaotong University, Chengdu, Sichuan, China.
| | - Xiong-Fei Pan
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China.
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Mai S, Zhu H, Li M, Zeng Y, Zhang Y, Huo Y, Pan XF, Huang Y. Blood pressure measurement in the elderly with atrial fibrillation: an observational study comparing different noninvasive sphygmomanometers. Ther Adv Chronic Dis 2022; 13:20406223221137040. [DOI: 10.1177/20406223221137040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2022] [Accepted: 10/19/2022] [Indexed: 11/16/2022] Open
Abstract
Background: Atrial fibrillation (AF) has affected millions of adults in the world. It is important to monitor and manage blood pressure (BP) in AF patients. The accuracy of BP monitoring in AF patients with noninvasive methods remains questionable, however. Objectives: To compare the accuracy of different noninvasive BP devices (oscillographic sphygmomanometer and pulse wave device) for BP measurement in elderly patients with AF, with a mercury sphygmomanometer as a reference. Design: This study was an observational study. Methods: Patients with AF from the inpatient department of cardiology were included from 1 January to 31 December 2020. BP measurements were performed by two trained nurses using a tee junction connection on the cuff to connect three sphygmomanometers. The Bland–Altman plot analysis was conducted to compare the agreement of BP measurements. We also compared the agreement of BP measurements through metrics such as accuracy, bias, and precision. Results: A total of 202 patients (54.5% female) were included. The Bland–Altman plot analysis showed that the lower and upper limits of agreement (LoAs) of pulse wave/reference were similar to the predefined acceptable clinical limits (10/5 mmHg). The bias and precision in both systolic and diastolic BP were significantly less in pulse wave/reference (a bias of 1.8 and 0.77 mmHg and a precision of 5.20 and 4.66 mmHg, respectively), with corresponding higher accuracy readings (98.51% for P10 in systolic BP and 85.64% for P5 in diastolic BP). Conclusion: A novel noninvasive sphygmomanometer – pulse wave device has a good concordance with a mercury sphygmomanometer in BP monitoring, and may be applicable to perform BP measurements in the elderly with AF.
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Affiliation(s)
- Shaojun Mai
- Department of Cardiology, Shunde Hospital, Southern Medical University, Guangdong, China
| | - Hailan Zhu
- Department of Cardiology, Shunde Hospital, Southern Medical University, Guangdong, China
| | - Meijun Li
- Department of Cardiology, Shunde Hospital, Southern Medical University, Guangdong, China
| | - Yanfang Zeng
- Department of Cardiology, Shunde Hospital, Southern Medical University, Guangdong, China
| | - Yang Zhang
- Department of Cardiology, Shunde Hospital, Southern Medical University, Guangdong, China
| | - Yanchang Huo
- Department of Cardiology, Shunde Hospital, Southern Medical University, Jiazi Road 1, Lunjiao Town, Shunde District, Foshan, Guangdong 523808, China
| | - Xiong-Fei Pan
- Key Laboratory of Birth Defects and Related Diseases of Women and Children, Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, China
| | - Yuli Huang
- Department of Cardiology, Shunde Hospital, Southern Medical University, Jiazi Road 1, Lunjiao Town, Shunde District, Foshan, Guangdong 523808, China
- The George Institute for Global Health, Newtown, NSW, Australia
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44
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Liu W, Yang X, Jin X, Xiu P, Wen Y, Wu N, Zhao J, Zhou D, Pan XF. Prospective Evaluation of the Association Between Arthritis and Cognitive Functions in Middle-Aged and Elderly Chinese. Front Aging Neurosci 2021; 13:687780. [PMID: 34776923 PMCID: PMC8579809 DOI: 10.3389/fnagi.2021.687780] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Accepted: 10/07/2021] [Indexed: 02/05/2023] Open
Abstract
Background: Assessing the relation between arthritis and cognitive impairment could expand the understanding of health consequences of arthritis. The aim was to prospectively examine the association between arthritis and cognitive functions among middle-aged and elderly Chinese. Methods: Our analyses were based on data from the nationwide China Health and Retirement Longitudinal Study (2011–2016). Arthritis was ascertained by self-reported doctor diagnosis during the baseline survey. Cognitive functions were evaluated in three domains including episodic memory, mental status, and global cognition. Linear mixed models were employed to assess the association between baseline arthritis and cognition functions. Results: Of 7,529 Chinese adults, 49.79% were men, and mean age was 57.53 years. During a follow-up of 4 years, participants with baseline arthritis showed lower scores of episodic memory [β = −0.08; 95% confidence interval (CI): −0.14, −0.03], mental status (β = −0.14; 95% CI: −0.22, −0.05), and global cognition (β = −0.22; 95% CI: −0.34, −0.11), compared to those without arthritis. In addition, participants with arthritis showed increased rates of decline in mental status and global cognition by 0.04 (95% CI: 0.01, 0.08) and 0.05 (95% CI: 0.01, 0.09) units per year, respectively. Conclusion: Arthritis was associated with subsequent risk of poorer cognitive functions and slightly faster declines in cognitive functions among Chinese middle-aged and elderly adults. Our findings should be confirmed in future large prospective studies in Chinese and other populations.
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Affiliation(s)
- Wenyu Liu
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | - Xue Yang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Xingzhong Jin
- Centre for Big Data Research in Health, University of New South Wales, Sydney, NSW, Australia
| | - Peng Xiu
- Department of Orthopedics, West China Hospital, Sichuan University, Chengdu, China
| | - Ying Wen
- Department of Communicable Diseases Control and Prevention, Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Nianwei Wu
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Jian Zhao
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.,MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
| | - Dong Zhou
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | - Xiong-Fei Pan
- Ministry of Education Key Laboratory of Environment and Health and State Environmental Protection Key Laboratory of Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States.,Faculty of Medicine, The George Institute for Global Health, University of New South Wales, Sydney, NSW, Australia
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Zhu H, Zheng H, Xu T, Liu X, Liu X, Sun L, Pan XF, Mai W, Cai X, Huang Y. Effects of statins in primary and secondary prevention for venous thromboembolism events: A meta analysis. Vascul Pharmacol 2021; 142:106931. [PMID: 34763100 DOI: 10.1016/j.vph.2021.106931] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Revised: 10/11/2021] [Accepted: 11/03/2021] [Indexed: 01/14/2023]
Abstract
OBJECTIVE The associations between statins use and incidence or recurrence of venous thromboembolism (VTE) are controversial. We aimed to conduct a meta-analysis to reconcile the conflicting results. METHODS We searched PubMed, Embase and Cochrane Library for studies published from database inception until May 31, 2021. Cohort studies and Randomized Controlled Trials that reported incidence or recurrence of VTE using statins compared with placebo or non-statins were included for meta-analysis. RESULTS A total of 43 studies comprising over 8.6 million participants were included for analysis. The median follow-up duration was 38.1 months. Compared with no statins treatment, statins appeared to have a protective effect in primary prevention of VTE (RR 0.78, 95% CI 0.72-0.85), but significant heterogeneity was found among included studies (I2 = 81%). Statins was also associated with a 26% reduced risk of recurrent VTE (RR 0.74, 95% CI 0.70-0.78), even in patients receiving anticoagulant therapy (RR 0.77, 95% CI 0.65-0.92). In patients with a history of VTE, statins was associated with a reduced risk of bleeding and all cause mortality. The NNT of statins to prevent one case of VTE in the cancer population, and one case of recurrent VTE in patients with a history of VTE was 103.1 and 90.7 person-years respectively. CONCLUSION In high-risk patients, statins treatment may reduce the incidence of VTE. Statins can also reduce the risk of recurrent VTE and all-cause mortality in patients with a history of VTE.
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Affiliation(s)
- Hailan Zhu
- Department of Cardiology, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde), NO. 1 Jiazi Road, Lunjiao, Shunde District, Foshan city, Guangdong 528308, China
| | - Haoxiao Zheng
- Department of Cardiology, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde), NO. 1 Jiazi Road, Lunjiao, Shunde District, Foshan city, Guangdong 528308, China
| | - Tianyu Xu
- State Key Laboratory of Cardiovascular Disease, Heart Failure Center, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, 167 Beilishi Road, Beijing 100037, China
| | - Xinyue Liu
- Department of Cardiology, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde), NO. 1 Jiazi Road, Lunjiao, Shunde District, Foshan city, Guangdong 528308, China
| | - Xiong Liu
- Department of Cardiology, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde), NO. 1 Jiazi Road, Lunjiao, Shunde District, Foshan city, Guangdong 528308, China
| | - Lichang Sun
- Department of Cardiology, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde), NO. 1 Jiazi Road, Lunjiao, Shunde District, Foshan city, Guangdong 528308, China
| | - Xiong-Fei Pan
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Weiyi Mai
- Department of Cardiology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou 510080, China
| | - Xiaoyan Cai
- Department of Scientific Research and Education, Shunde Hospital, Southern Medical University, Foshan, China
| | - Yuli Huang
- Department of Cardiology, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde), NO. 1 Jiazi Road, Lunjiao, Shunde District, Foshan city, Guangdong 528308, China; The George Institute for Global Health, NSW 2042, Australia.
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46
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Wang Y, Huang Y, Wu P, Ye Y, Sun F, Yang X, Lu Q, Yuan J, Liu Y, Zeng H, Song X, Yan S, Qi X, Yang CX, Lv C, Wu JHY, Liu G, Pan XF, Chen D, Pan A. Plasma lipidomics in early pregnancy and risk of gestational diabetes mellitus: a prospective nested case-control study in Chinese women. Am J Clin Nutr 2021; 114:1763-1773. [PMID: 34477820 DOI: 10.1093/ajcn/nqab242] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2021] [Accepted: 06/28/2021] [Indexed: 01/21/2023] Open
Abstract
BACKGROUND Lipid metabolism plays an important role in the pathogenesis of diabetes. There is little evidence regarding the prospective association of the maternal lipidome with gestational diabetes mellitus (GDM), especially in Chinese populations. OBJECTIVES We aimed to identify novel lipid species associated with GDM risk in Chinese women, and assess the incremental predictive capacity of the lipids for GDM. METHODS We conducted a nested case-control study using the Tongji-Shuangliu Birth Cohort with 336 GDM cases and 672 controls, 1:2 matched on age and week of gestation. Maternal blood samples were collected at 6-15 wk, and lipidomes were profiled by targeted ultra-HPLC-tandem MS. GDM was diagnosed by oral-glucose-tolerance test at 24-28 wk. The least absolute shrinkage and selection operator is a regression analysis method that was used to select novel biomarkers. Multivariable conditional logistic regression was used to estimate the associations. RESULTS Of 366 detected lipids, 10 were selected and found to be significantly associated with GDM independently of confounders: there were positive associations with phosphatidylinositol 40:6, alkylphosphatidylcholine 36:1, phosphatidylethanolamine plasmalogen 38:6, diacylglyceride 18:0/18:1, and alkylphosphatidylethanolamine 40:5 (adjusted ORs per 1 log-SD increment range: 1.34-2.86), whereas there were inverse associations with sphingomyelin 34:1, dihexosyl ceramide 24:0, mono hexosyl ceramide 18:0, dihexosyl ceramide 24:1, and phosphatidylcholine 40:7 (adjusted ORs range: 0.48-0.68). Addition of these novel lipids to the classical GDM prediction model resulted in a significant improvement in the C-statistic (discriminatory power of the model) to 0.801 (95% CI: 0.772, 0.829). For every 1-point increase in the lipid risk score of the 10 lipids, the OR of GDM was 1.66 (95% CI: 1.50, 1.85). Mediation analysis suggested the associations between specific lipid species and GDM were partially explained by glycemic and insulin-related indicators. CONCLUSIONS Specific plasma lipid biomarkers in early pregnancy were associated with GDM in Chinese women, and significantly improved the prediction for GDM.
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Affiliation(s)
- Yi Wang
- Department of Epidemiology & Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.,Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yichao Huang
- School of Environment, Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou, Guangdong, China
| | - Ping Wu
- Department of Epidemiology & Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.,Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yi Ye
- Department of Epidemiology & Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.,Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Fengjiang Sun
- School of Environment, Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou, Guangdong, China
| | - Xue Yang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Qi Lu
- Department of Epidemiology & Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.,Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Jiaying Yuan
- Department of Science and Education, Shuangliu Maternal and Child Health Hospital, Chengdu, Sichuan, China
| | - Yan Liu
- Department of Obstetrics and Gynecology, Shuangliu Maternal and Child Health Hospital, Chengdu, Sichuan, China
| | - Huayan Zeng
- Nutrition Department, Shuangliu Maternal and Child Health Hospital, Chengdu, Sichuan, China
| | - Xingyue Song
- Department of Emergency, Hainan Clinical Research Center for Acute and Critical Diseases, The Second Affiliated Hospital of Hainan Medical University, Haikou, Hainan, China.,Key Laboratory of Emergency and Trauma of Ministry of Education, Hainan Medical University, Haikou, Hainan, China
| | - Shijiao Yan
- Research Unit of Island Emergency Medicine, Chinese Academy of Medical Sciences, Hainan Medical University, Haikou, Hainan, China.,School of Public Health, Hainan Medical University, Haikou, Hainan, China
| | - Xiaorong Qi
- Department of Gynecology and Obstetrics, West China Second Hospital, State Key Laboratory of Biotherapy, Sichuan University, Chengdu, Sichuan, China
| | - Chun-Xia Yang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Chuanzhu Lv
- Department of Emergency, Hainan Clinical Research Center for Acute and Critical Diseases, The Second Affiliated Hospital of Hainan Medical University, Haikou, Hainan, China.,Key Laboratory of Emergency and Trauma of Ministry of Education, Hainan Medical University, Haikou, Hainan, China.,Research Unit of Island Emergency Medicine, Chinese Academy of Medical Sciences, Hainan Medical University, Haikou, Hainan, China
| | - Jason H Y Wu
- The George Institute for Global Health, University of New South Wales, Sydney, New South Wales, Australia
| | - Gang Liu
- Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xiong-Fei Pan
- Department of Epidemiology & Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.,Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.,The George Institute for Global Health, University of New South Wales, Sydney, New South Wales, Australia.,Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Da Chen
- School of Environment, Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou, Guangdong, China
| | - An Pan
- Department of Epidemiology & Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.,Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
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47
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Yang X, Tao S, Peng J, Zhao J, Li S, Wu N, Wen Y, Xue Q, Yang CX, Pan XF. High-sensitivity C-reactive protein and risk of type 2 diabetes: A nationwide cohort study and updated meta-analysis. Diabetes Metab Res Rev 2021; 37:e3446. [PMID: 33686799 DOI: 10.1002/dmrr.3446] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/07/2020] [Revised: 01/11/2021] [Accepted: 02/07/2021] [Indexed: 02/05/2023]
Abstract
OBJECTIVE To prospectively examine the association of high sensitivity C-reactive protein (hs-CRP) with incident type 2 diabetes mellitus (T2DM) among middle-aged and elderly Chinese, and validate the association in an updated meta-analysis of prospective studies. METHODS We used data from the China Health and Retirement Longitudinal Study, started in 2011-2012 with follow ups in 2013-2014 and 2015-2016. Multivariable Cox proportional hazard regressions were applied to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between hs-CRP level and incident T2DM. An updated meta-analysis was conducted to combine our estimates with those in previous prospective studies. RESULTS Included in the analyses were 7985 participants (mean age: 59.38 years; men: 46.73%). Higher hs-CRP was associated with increased risk of T2DM (multivariable-adjusted HR, 1.30; 95% CI: 1.03, 1.64 for comparing extreme quartiles). The association was stronger in participants with body mass index (BMI) of 24.0 kg/m2 or higher than those with a BMI lower than 24.0 kg/m2 (p for interaction = 0.038). In a meta-analysis of 28 cohorts, 2 case-cohort, and 6 nested case-control studies among 125,356 participants with 10,759 cases, the pooled relative risk for T2DM was 1.77 (95% CI: 1.60, 1.96) for the highest versus lowest level of hs-CRP. CONCLUSIONS Hs-CRP was associated with higher risk of T2DM in middle-aged and elderly Chinese, and this association was confirmed by an updated meta-analysis of prospective studies. Our findings highlight the role of elevated hs-CRP in the development of T2DM.
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Affiliation(s)
- Xue Yang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Siyuan Tao
- Department of Infection Control, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Jieru Peng
- Department of Medical Records Statistics, Chengdu Women and Children' s Central Hospital, University of Electronic Science and Technology, Chengdu, Sichuan, China
| | - Jian Zhao
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Sheyu Li
- Department of Endocrinology and Metabolism, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Nianwei Wu
- Department of Health and Social Behavior, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Ying Wen
- Department of Communicable Diseases Control and Prevention, Shenzhen Center for Disease Control and Prevention, Shenzhen, Guangdong, China
| | - Qingping Xue
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Chun-Xia Yang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xiong-Fei Pan
- Department of Medicine, Division of Epidemiology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health and State Environmental Protection Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, New South Wales, Australia
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Wu N, Xia J, Chen S, Yu C, Xu Y, Xu C, Yan T, Li N, Liu Y, Pan XF. Serum uric acid and risk of incident chronic kidney disease: a national cohort study and updated meta-analysis. Nutr Metab (Lond) 2021; 18:94. [PMID: 34666784 PMCID: PMC8524911 DOI: 10.1186/s12986-021-00618-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Accepted: 09/25/2021] [Indexed: 11/25/2022] Open
Abstract
Background We prospectively examined the association between serum uric acid (SUA) levels and chronic kidney disease (CKD) in China and updated the evidence through a comprehensive meta-analysis of prospective studies worldwide. Methods Our original analyses were based on data from the China Health and Retirement Longitudinal Study. The primary exposure of interest was SUA at baseline, and the main outcome was incident CKD. Logistic regression models were used to examine the association between SUA levels and incident CKD. A meta-analysis was performed to pool our effect estimate and those from other cohort studies. Results During a 4-year follow-up, 180 participants developed incident CKD. Participants in the highest SUA quartile were 2.73 times as likely to develop incident CKD compared to those in the lowest quartile (multivariable-adjusted OR, 2.73; 95% CI, 1.65–4.50). Each 1 mg/dL increment in the SUA levels was associated with a 49% increased risk of incident CKD (multivariable-adjusted OR, 1.49; 95% CI, 1.28–1.74). In the meta-analysis of 30 cohort studies (including the current study), pooled relative risks (95% CIs) of incident CKD were 1.15 (1.10–1.21) for SUA each 1 mg/dL increment, 1.22 (1.14–1.30) for the highest versus lowest SUA group, and 1.17 (1.12–1.23) for hyperuricemia versus no hyperuricemia. Conclusions Baseline SUA levels were associated with higher risk of incident CKD in middle-aged and elderly Chinese adults, and this positive association was confirmed in the meta-analysis of multiple cohort studies. Our findings may imply that SUA levels need to be routinely monitored for future CKD risk. Supplementary Information The online version contains supplementary material available at 10.1186/s12986-021-00618-4.
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Affiliation(s)
- Nianwei Wu
- Department of Health and Social Behavior, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Jing Xia
- Department of Health and Social Behavior, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Sen Chen
- Department of Health and Social Behavior, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Chuan Yu
- Department of Health and Social Behavior, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Ying Xu
- Kidney Disease Center, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Chengfu Xu
- Department of Gastroenterology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Tong Yan
- Center for Obesity and Metabolic Health, The Third People's Hospital of Chengdu & The Affiliated Hospital of Southwest Jiaotong University, Chengdu, Sichuan, China
| | - Ningxiu Li
- Department of Health and Social Behavior, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yanjun Liu
- Center for Obesity and Metabolic Health, The Third People's Hospital of Chengdu & The Affiliated Hospital of Southwest Jiaotong University, Chengdu, Sichuan, China. .,Center of Gastrointestinal and Minimally Invasive Surgery, Department of General Surgery, The Third People's Hospital of Chengdu & The Affiliated Hospital of Southwest Jiaotong University, Chengdu, Sichuan, China.
| | - Xiong-Fei Pan
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University Medical Center, Nashville, TN, USA. .,Department of Epidemiology and Biostatistics, and Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China. .,The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia.
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Sun Y, Xia PF, Korevaar TIM, Mustieles V, Zhang Y, Pan XF, Wang YX, Messerlian C. Relationship between Blood Trihalomethane Concentrations and Serum Thyroid Function Measures in U.S. Adults. Environ Sci Technol 2021; 55:14087-14094. [PMID: 34617747 DOI: 10.1021/acs.est.1c04008] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Toxicological studies show that exposure to disinfection byproducts, including trihalomethanes (THMs), negatively affects thyroid function; however, few epidemiological studies have explored this link. This study included 2233 adults (ages ≥20 years) from the 2007-2008 National Health and Nutrition Examination Survey (NHANES) who were measured for blood THM concentrations [chloroform (TCM), bromodichloromethane (BDCM), dibromochloromethane (DBCM), or bromoform (TBM)] and serum thyroid function biomarkers [thyroid-stimulating hormone, free thyroxine (FT4), total thyroxine (TT4), free triiodothyronine (FT3), total triiodothyronine (TT3), thyroid peroxidase antibody (TPOAb), and thyroglobulin antibody (TgAb)]. Multivariable linear regression models showed positive associations between blood TCM, BDCM, and total THMs (the sum of all four THMs) concentrations and serum FT4, whereas inverse associations were found between blood DBCM and total brominated THM (Br-THM; the sum of BDCM, DBCM, and TBM) concentrations and serum TT3 (all p < 0.05). Besides, positive associations were observed between blood TCM concentrations and FT4/FT3 ratio, between BDCM, DBCM, and Br-THM concentrations and TT4/TT3 ratio, and between DBCM and Br-THM concentrations and FT3/TT3 ratio (all p < 0.05). Blood THM concentrations were unrelated to the serum levels of thyroid autoantibodies TgAb or TPOAb. In summary, exposure to THMs was associated with altered serum biomarkers of thyroid function but not with thyroid autoimmunity among U.S. adults.
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Affiliation(s)
- Yang Sun
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 02115, United States
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 02115, United States
| | - Peng-Fei Xia
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - T I M Korevaar
- Department of Internal Medicine and Academic Center for Thyroid Diseases, Erasmus University Medical Center, 3015 GE Rotterdam, The Netherlands
| | - Vicente Mustieles
- Center for Biomedical Research (CIBM), University of Granada, 18016 Granada, Spain
- Instituto de Investigación Biosanitaria Ibs GRANADA, 18012 Granada, Spain
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), 28029 Madrid, Spain
| | - Yu Zhang
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 02115, United States
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 02115, United States
| | - Xiong-Fei Pan
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee 37203, United States
| | - Yi-Xin Wang
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 02115, United States
| | - Carmen Messerlian
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 02115, United States
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 02115, United States
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Wu N, Qin Y, Chen S, Yu C, Xu Y, Zhao J, Yang X, Li N, Pan XF. Association between metabolic syndrome and incident chronic kidney disease among Chinese: A nation-wide cohort study and updated meta-analysis. Diabetes Metab Res Rev 2021; 37:e3437. [PMID: 33469988 DOI: 10.1002/dmrr.3437] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Revised: 11/30/2020] [Accepted: 01/02/2021] [Indexed: 12/22/2022]
Abstract
AIMS We prospectively examined the relationship between metabolic syndrome (MetS) and incident chronic kidney disease (CKD) among middle-aged and elderly Chinese, and conducted a systematic review and meta-analysis of all cohort studies on this topic. MATERIALS AND METHODS Our research data were derived from the China Health and Retirement Longitudinal Study. Participants (n=5752, age ≥45 years) without CKD (defined as estimated glomerular filtration rate <60 ml/min/1.73m2 ) at baseline were followed up for 4 years. We applied logistic regressions to examine the association of MetS with incident CKD. In addition, we pooled our effect estimates and those from previous cohort studies in the meta-analysis. RESULTS In a 4-years follow-up, 61 (4.27%) developed CKD in participants with MetS versus 102 (2.36%) in participants without MetS. After adjustment for potential confounders, odds ratio for incident CKD was 1.82 [95% confidence interval (95% CI): 1.19-2.78] comparing participants with MetS with those without MetS. There was a linear positive association between the number of MetS components and incident CKD (p for trend <0.001). In the updated meta-analysis of 25 studies among 350,655 participants with 29,368 incident cases of CKD, the pooled relative risk of developing CKD in participants with MetS was 1.34 (95% CI: 1.28-1.39), compared with those without MetS. CONCLUSIONS Individuals with MetS had higher risk of incident CKD in middle-aged and elderly Chinese adults, which was supported by a comprehensive review of cohort studies from multiple populations. It may be advisable to routinely monitor renal functions among individuals with MetS.
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Affiliation(s)
- Nianwei Wu
- Department of Health and Social Behavior, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yao Qin
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Sen Chen
- Department of Health and Social Behavior, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Chuan Yu
- Department of Health and Social Behavior, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Ying Xu
- Kidney Disease Center, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Jian Zhao
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Xue Yang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Ningxiu Li
- Department of Health and Social Behavior, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xiong-Fei Pan
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Epidemiology and Biostatistics, Ministry of Education & Ministry of Environmental Protection Key Laboratory of Environment and Health, State Key Laboratory of Environmental Health (incubation), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, New South Wales, Australia
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