1
|
Yu B, Tang W, Fan Y, Ma C, Ye T, Cai C, Xie Y, Shi Y, Baima K, Yang T, Wang Y, Jia P, Yang S. Associations between residential greenness and obesity phenotypes among adults in Southwest China. Health Place 2024; 87:103236. [PMID: 38593578 DOI: 10.1016/j.healthplace.2024.103236] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 02/27/2024] [Accepted: 03/21/2024] [Indexed: 04/11/2024]
Abstract
BACKGROUND Although exposure to greenness has generally benefited human metabolic health, the association between greenness exposure and metabolic obesity remains poorly studied. We aimed to investigate the associations between residential greenness and obesity phenotypes and the mediation effects of air pollutants and physical activity (PA) level on the associations. METHODS We used the baseline of the China Multi-Ethnic Cohort (CMEC) study, which enrolled 87,613 adults. Obesity phenotypes were defined based on obesity and metabolic status, including metabolically unhealthy obesity (MUO), non-obesity (MUNO), metabolically healthy obesity (MHO), and non-obesity (MHNO). Greenness exposure was measured as the 3-year mean values of the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) within the 500-m buffer zones around the participants' residence. Multivariable logistic regression was used to estimate the associations between greenness and obesity phenotypes. Stratified analyses by age, sex, educational level, and urbanicity were performed to identify how the effect varies across different subgroups. Causal mediation analysis was used to examine the mediation effects of air pollutants and PA level. RESULTS Compared with MHNO, each interquartile range (IQR) increase in greenness exposure was associated with reduced risks of MHO (ORNDVI [95% CI] = 0.87 [0.81, 0.93]; OREVI = 0.91 [0.86, 0.97]), MUO (ORNDVI = 0.83 [0.78, 0.88]; OREVI = 0.86 [0.81, 0.91]), and MUNO (ORNDVI = 0.88 [0.84, 0.91]; OREVI = 0.89 [0.86, 0.92]). For each IQR increase in both NDVI and EVI, the risks of MHO, MUO, and MUNO were reduced more in men, participants over 60 years, those with a higher level of education, and those living in urban areas, compared to their counterparts. Concentrations of particulate matter (PM) and PA level partially mediated the associations between greenness exposure and obesity phenotypes. CONCLUSIONS Exposure to residential greenness was associated with decreased risks of MHO, MUO, and MUNO, which was mediated by concentrations of PM and PA level, and modified by sex, age, educational level, and urbanicity.
Collapse
Affiliation(s)
- Bin Yu
- Institute for Disaster Management and Reconstruction, Sichuan University-The Hong Kong Polytechnic University, Chengdu, China; West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Wenge Tang
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, China
| | - Yunzhe Fan
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Chunlan Ma
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Tingting Ye
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Changwei Cai
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yiming Xie
- Jianyang Center for Disease Control and Prevention, Jianyang, China
| | - Yuanyuan Shi
- School of Resource and Environmental Sciences, Wuhan University, Wuhan, China; International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China
| | - Kangzhuo Baima
- High Altitude Health Science Research Center of Tibet University, Lhasa, Tibet, China
| | - Tingting Yang
- School of Public Health, The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, China
| | - Yanjiao Wang
- School of Public Health, Kunming Medical University, Kunming, China
| | - Peng Jia
- School of Resource and Environmental Sciences, Wuhan University, Wuhan, China; International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China; Hubei Luojia Laboratory, Wuhan, China; School of Public Health, Wuhan University, Wuhan, China.
| | - Shujuan Yang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China; International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China.
| |
Collapse
|
2
|
Wang Y, Meng Q, Zhang X, Baima K, Chen L, Dai Y, Yang T, Feng Y, Mi F, Zhou J, Yin J. Life's Essential 8, Life's Simple 7 and the odds of hyperuricaemia: results from the China Multi-Ethnic Cohort Study. Rheumatol Adv Pract 2024; 8:rkae009. [PMID: 38333884 PMCID: PMC10850937 DOI: 10.1093/rap/rkae009] [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] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Accepted: 12/12/2023] [Indexed: 02/10/2024] Open
Abstract
Objective Life's Essential 8 (LE8) is a new comprehensive metric based on Life's Simple 7 (LS7). Few studies have investigated the association between LE8 and the odds of hyperuricaemia (HUA). This study examined the association between LE8, LS7 with odds of HUA. Methods We cross-sectionally analysed data from the China Multi-Ethnic Cohort (CMEC) study. LE8 and LS7 were categorized as low, moderate and high. The CMEC provided an ideal and unique opportunity to characterize the association between LE8, LS7 and the odds of HUA. Results Of the 89 823 participants, 14 562 (16.2%) had HUA. A high level of LE8 was associated with lower odds of HUA after full adjustment. The adjusted odds ratios (ORs) were 1 (reference), 0.70 (95% CI 0.67, 0.73) and 0.45 (0.42, 0.48) across low, moderate and high LE8 groups, respectively (Ptrend < 0.001). Similar results were observed in LS7 and HUA. The adjusted ORs were 1 (reference), 0.68 (95% CI 0.65, 0.71) and 0.46 (95% CI 0.43, 0.49) across low, moderate and high LS7 groups, respectively (Ptrend < 0.001). There were significant interactions between LE8 and age, gender, ethnicity and drinking habits on HUA. Receiver operating characteristics analysis showed that the area under the curve for LE8 and LS7 were similar (0.638 and 0.635, respectively). Conclusion This study indicated a clearly inverse gradient association between the cardiovascular health metrics LE8 and LS7 and the odds of HUA.
Collapse
Affiliation(s)
- Yanjiao Wang
- School of Public Health, Kunming Medical University, Kunming, China
| | - Qiong Meng
- School of Public Health, Kunming Medical University, Kunming, China
| | - Xuehui Zhang
- School of Public Health, Kunming Medical University, Kunming, China
| | - Kangzhuo Baima
- High Altitude Health Science Research Center of Xizang University, Lhasa, Xizang, China
| | - Liling Chen
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- Institute of Chronic Non-Communicable Disease Control and Prevention, Chongqing Center for Disease Control and Prevention, Chongqing, China
| | - Yingxue Dai
- Chengdu Center for Disease Control and Prevention, Chengdu, China
| | - Tingting Yang
- School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, China
| | - Yuemei Feng
- School of Public Health, Kunming Medical University, Kunming, China
| | - Fei Mi
- School of Public Health, Kunming Medical University, Kunming, China
| | - Junmin Zhou
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Jianzhong Yin
- School of Public Health, Kunming Medical University, Kunming, China
- Baoshan College of Traditional Chinese Medicine, Baoshan, China
- Key Laboratory of Nutrition and Food Safety of Yunnan Provincial Education Department, Kunming Medical University, Kunming, China
| |
Collapse
|
3
|
Pan X, Hong F, Li S, Wu J, Xu H, Yang S, Chen K, Baima K, Nima Q, Meng Q, Xia J, Xu J, Guo B, Lin H, Xie L, Zhang J, Zhao X. Long-term exposure to ambient PM 2.5 constituents is associated with dyslipidemia in Chinese adults. Ecotoxicol Environ Saf 2023; 263:115384. [PMID: 37603926 DOI: 10.1016/j.ecoenv.2023.115384] [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: 04/26/2023] [Revised: 08/12/2023] [Accepted: 08/16/2023] [Indexed: 08/23/2023]
Abstract
BACKGROUND Ambient particulate matter with aerodynamic diameter ≤ 2.5 µm (PM2.5) consists of various toxic constituents. However, the health effect of PM2.5 may differ depending on its constituents, but the joint effect of PM2.5 constituents remains incompletely understood. OBJECTIVE Our goal was to evaluate the joint effect of long-term PM2.5 constituent exposures on dyslipidemia and identify the most hazardous chemical constituent. METHODS This study included 67,015 participants from the China Multi-Ethnic Cohort study. The average yearly levels of PM2.5 constituents for all individuals at their residences were assessed through satellite remote sensing and chemical transport modeling. Dyslipidemia was defined as one or more following abnormal blood lipid concentrations: total cholesterol (TC) ≥ 6.22 mmol/L, triglycerides (TG) ≥ 2.26 mmol/L, high-density lipoprotein cholesterol (HDL-C) < 1.04 mmol/L, and low-density lipoprotein cholesterol (LDL-C) ≥ 4.14 mmol/L. The logistic regression model was utilized to examine the single effect of PM2.5 constituents on dyslipidemia, while the weighted quantile sum regression model for the joint effect. RESULTS The odds ratio with a 95 % confidence interval for dyslipidemia positively related to per-SD increase in the three-year average was 1.29 (1.20-1.38) for PM2.5 mass, 1.25 (1.17-1.34) for black carbon, 1.24 (1.16-1.33) for ammonium, 1.33 (1.24-1.43) for nitrate, 1.34 (1.25-1.44) for organic matter, 1.15 (1.08-1.23) for sulfate, 1.30 (1.22-1.38) for soil particles, and 1.12 (1.05-1.92) for sea salt. Stronger associations were observed in individuals < 65 years of age, males, and those with low physical activity. Joint exposure to PM2.5 constituents was positively related to dyslipidemia (OR: 1.09, 95 %CI: 1.05-1.14). Nitrate was identified as the constituent with the largest weight (weighted at 0.387). CONCLUSIONS Long-term exposure to PM2.5 constituents poses a significant risk to dyslipidemia and nitrate might be the most responsible for the risk. These findings indicate that reducing PM2.5 constituent exposures, especially nitrate, could be beneficial to alleviate the burden of disease attributed to PM2.5-related dyslipidemia.
Collapse
Affiliation(s)
- Xianmou Pan
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Feng Hong
- School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, China
| | - Sicheng Li
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Jialong Wu
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Huan Xu
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China; Institute for Disaster Management and Reconstruction, Sichuan University-The Hongkong Polytechnic University, Chengdu, Sichuan, China
| | - Shaokun Yang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Kejun Chen
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Kangzhuo Baima
- School of Medicine, Tibet University, Lhasa, Tibet, China
| | - Qucuo Nima
- Tibet Center for Disease Control and Prevention, Lhasa, Tibet, China
| | - Qiong Meng
- Department of Epidemiology and Health Statistics, School of Public Health, Kunming Medical University, Kunming, Yunnan, China
| | - Jinjie Xia
- Chengdu Center for Disease Control & Prevention, China
| | - Jingru Xu
- Chongqing Municipal Center for Disease Control and Prevention, China
| | - Bing Guo
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Hualiang Lin
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Linshen Xie
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
| | - Juying Zhang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
| | - Xing Zhao
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
| |
Collapse
|
4
|
Nie C, Yang T, Wang Z, Suolang D, Wang S, Baima K, Wei L, Ling H, Liu L, Zeng Q, Qin Z, Zuo H, Hong F. Dietary Patterns and Gallstone Risks in Chinese Adults: A Cross-sectional Analysis of the China Multi-Ethnic Cohort Study. J Epidemiol 2023; 33:471-477. [PMID: 35466159 PMCID: PMC10409532 DOI: 10.2188/jea.je20220039] [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] [Subscribe] [Scholar Register] [Received: 02/13/2022] [Accepted: 04/05/2022] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Little is known about the association between a plant-based diet and the risk of gallstone disease (GD), especially in developing counties. We tested the hypothesis that shifting dietary patterns would be related to the risk of GD, and that the Mediterranean diet (MED) adjusted for China would be beneficial for lowering risk of GD. METHODS Data were extracted from the baseline survey of the China Multi-Ethnic Cohort study. An alternative Mediterranean diet (aMED) score was assessed based on a food frequency questionnaire, and three posteriori dietary patterns (the modern dietary pattern, the coarse grain dietary pattern, and the rice dietary pattern) were identified using factor analysis. Multivariable logistic regression models were developed to evaluate the association between dietary patterns and GD risks. RESULTS A total of 89,544 participants were included. The prevalence of GD was 7.5%. Comparing the highest with lowest quintiles, aMED was associated with an increased risk of GD (OR 1.13; 95% CI, 1.04-1.24; Ptrend = 0.003), whereas the rice dietary pattern was inversely related to GD risk (OR 0.79; 95% CI, 0.71-0.87; Ptrend < 0.001). In stratified analysis, the rice dietary pattern had a stronger inverse association in the subgroups of females, older, urban, and overweight participants, and those with diabetes-factors associated with higher rates of GD in previous studies. CONCLUSION Higher adherence to the rice dietary pattern was associated with a lower risk of GD. For high-risk populations, making some shift to a traditional agricultural diet might help with primary prevention of GD.
Collapse
Affiliation(s)
- Chan Nie
- School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, China
| | - Tingting Yang
- School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, China
| | - Ziyun Wang
- School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, China
| | - Deji Suolang
- Tibet Center for Disease Control and Prevention, Lhasa, China
| | - Songmei Wang
- School of Public Health, Kunming Medical University, Kunming, China
| | - Kangzhuo Baima
- Division of Pulmonary Diseases, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, China
- School of Medicine, Tibet University, Lhasa, China
| | - Li Wei
- Wuhou District Center for Disease Control and Prevention, Chengdu, China
| | - Hua Ling
- Chongqing Center for Disease Control and Prevention, Chongqing, China
| | - Leilei Liu
- School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, China
| | - Qibing Zeng
- School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, China
| | - Zixiu Qin
- School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, China
| | - Haojiang Zuo
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Food Safety Monitoring and Risk Assessment Key Laboratory of Sichuan Province, Chengdu, China
| | - Feng Hong
- School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, China
| |
Collapse
|
5
|
Zhao Y, Liang X, Wang J, Baima K, Nima Q, Gao Y, Yin J, Liu Q, Zhao X. Association between pregnancy termination history and metabolic syndrome in southwestern Chinese women: modification effect of physical activity. Hum Reprod 2023:dead124. [PMID: 37366630 DOI: 10.1093/humrep/dead124] [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] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 05/17/2023] [Indexed: 06/28/2023] Open
Abstract
STUDY QUESTION Is there a relationship between pregnancy termination history and metabolic syndrome (MetS), and if so, is the relationship moderated by physical activity (PA)? SUMMARY ANSWER Induced abortion, and both miscarriage and induced abortion, increased the risk of MetS, while leisure PA attenuated the effects of induced abortion, and both miscarriage and induced abortion, on the risk of MetS. WHAT IS KNOWN ALREADY Pregnancy termination history is a risk factor for cardiovascular disease, but studies on women's history of pregnancy termination and MetS are limited. PA is a preventive behavior for MetS, but its modification effect on any association between pregnancy termination history and MetS is unknown. STUDY DESIGN, SIZE, DURATION The cross-sectional study included 53 702 women (age range of 30-79 years old) from southwestern China who participated in the China Multi-Ethnic Cohort (CMEC) study from May 2018 to September 2019. PARTICIPANTS/MATERIALS, SETTING, METHODS Participants self-reported both the number and type of pregnancy termination. PA was assessed primarily by asking participants about the cumulative time they spent doing PA either as their occupation, transportation, housework, and leisure activity in the past year. MetS was defined according to the National Cholesterol Education Program Adult Treatment Panel III (ATP III) criteria. MAIN RESULTS AND THE ROLE OF CHANCE After adjusting for all confounders, the risk of MetS was significantly increased in women who experienced induced abortion alone, and both miscarriage and induced abortion, with odds ratios (ORs) of 1.08 (95% CI = 1.03-1.13) and 1.20 (95% CI = 1.08-1.33), respectively. A dose-response relationship was observed between the number of induced abortions and MetS, with the risk increasing by 3.0% for every additional induced abortion (OR = 1.03, 95% CI = 1.01-1.05). Leisure PA had a significant modification effect on the relationship between pregnancy termination history and MetS, as leisure PA attenuates the negative effects of induced abortion on MetS. LIMITATIONS, REASONS FOR CAUTION Causality cannot be established in this study. Information on pregnancy termination and PA was collected by self-report, which might be subject to recall bias. WIDER IMPLICATIONS OF THE FINDINGS A history of induced abortion was associated with an increased risk of MetS, and the risk increased with the number of induced abortions. Leisure PA attenuated the negative effect of induced abortion on MetS, whereas occupational and transportation PA amplified the negative effect of induced abortion on glucose. STUDY FUNDING/COMPETING INTEREST(S) This work was supported by the National Key R&D Program of China (grant no.: 2017YFC0907300) and the National Nature Science Foundation of China (grant no.: 82273745). The authors declare no conflicts of interest. TRIAL REGISTRATION NUMBER N/A.
Collapse
Affiliation(s)
- Ying Zhao
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Xian Liang
- Chengdu Center for Disease Control and Prevention, Chengdu, China
| | - Junhua Wang
- School of Public Health, The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, China
| | - Kangzhuo Baima
- Division of Pulmonary Diseases, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, China
- School of Medicine, Tibet University, Lhasa, China
| | - Qucuo Nima
- Tibet Center for Disease Control and Prevention, Lhasa, China
| | - Yang Gao
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, China
| | - Jianzhong Yin
- Baoshan College of Traditional Chinese Medicine, Baoshan, China
- Department of Nutrition and Food Hygiene, School of Public Health, Kunming Medical University, Kunming, China
| | - Qiaolan Liu
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Xing Zhao
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| |
Collapse
|
6
|
Xu H, Yang T, Guo B, Silang Y, Dai Y, Baima K, Gao Y, Tang S, Wei J, Jiang Y, Feng S, Li S, Xiao X, Zhao X. Increased allostatic load associated with ambient air pollution acting as a stressor: Cross-sectional evidence from the China multi-ethnic cohort study. Sci Total Environ 2022; 831:155658. [PMID: 35523330 DOI: 10.1016/j.scitotenv.2022.155658] [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: 03/02/2022] [Revised: 04/28/2022] [Accepted: 04/28/2022] [Indexed: 06/14/2023]
Abstract
BACKGROUND Allostatic load measures the cumulative biological burden imposed by chronic stressors. Emerging experimental evidence supports that air pollution acting as a stressor activates the neuroendocrine system and then produces multi-organ effects, leading to allostatic load. However, relevant epidemiological evidence is limited. OBJECTIVES We aim to explore the relationships between chronic exposure to ambient air pollution (PM1, PM2.5, PM10, and O3) and allostatic load in Chinese adults. METHODS This cross-sectional study included 85,545 participants aged 30-79 from the baseline data of the China Multi-Ethnic Cohort (CMEC). Ambient air pollution levels were evaluated by a satellite-based random forest approach. The previous three-year average exposure concentrations were calculated for each participant based on the residential address. The outcome allostatic load was identified through the sum of the sex-specific scores of twelve biomarkers belonging to four major categories: cardiovascular, metabolic, anthropometric, and inflammatory parameters. We performed statistical analysis using a doubly robust approach which relies on inverse probability weighting and outcome model to adjust for confounding. RESULTS Long-term exposure to ambient air pollution was significantly associated with an increased risk of allostatic load, with relative risk (95% confidence interval) of 1.040 (1.024, 1.057), 1.029 (1. 018, 1. 039), and 1.087 (1.074, 1.101) for each 10 μg/m3 increase in ambient PM2.5, PM10, and O3, respectively. No significant relationship was observed between chronic exposure to PM1 and allostatic load. The associations between air pollution and allostatic load are modified by some intrinsic factors and non-chemical stressors. The people with older, minority, lower education, and lower-income levels had a significantly higher allostatic load induced by air pollution. CONCLUSIONS Chronic exposure to ambient PM2.5, PM10, and O3 may increase the allostatic load. This finding provides epidemiological evidence that air pollution may be a chronic stressor, leading to widespread physiological burdens.
Collapse
Affiliation(s)
- Huan Xu
- Institute for Disaster Management and Reconstruction, Sichuan University-The Hongkong Polytechnic University, Chengdu, Sichuan, China; West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Tingting Yang
- School of Public Health, the key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, Guizhou, China
| | - Bing Guo
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yangzong Silang
- Tibet Center for Disease Control and Prevention, Lhasa, Tibet, China
| | - Yingxue Dai
- Chengdu Center for Disease Control and Prevention, Chengdu, Sichuan, China
| | - Kangzhuo Baima
- School of Medicine, Tibet University, Lhasa, Tibet, China
| | - Yang Gao
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, China
| | - Simei Tang
- Heqing Center for Disease Control and Prevention, Dali Prefecture, Yunnan, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA
| | - Ye Jiang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Shiyu Feng
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Sicheng Li
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xiong Xiao
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
| | - Xing Zhao
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| |
Collapse
|
7
|
Guo YB, He YX, Cui CY, Ouzhu L, Baima K, Duoji Z, Deji Q, Bian B, Peng Y, Bai CJ, Gongga L, Pan YY, Qu L, Kang M, Ciren Y, Baima Y, Guo W, Yang L, Zhang H, Zhang XM, Zheng WS, Xu SH, Chen H, Zhao SG, Cai Y, Liu SM, Wu TY, Qi XB, Su B. GCH1 plays a role in the high-altitude adaptation of Tibetans. Zool Res 2018; 38:155-162. [PMID: 28585439 PMCID: PMC5460084 DOI: 10.24272/j.issn.2095-8137.2017.037] [Citation(s) in RCA: 9] [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] [Indexed: 12/15/2022] Open
Abstract
Tibetans are well adapted to high-altitude hypoxia. Previous genome-wide scans have reported many candidate genes for this adaptation, but only a few have been studied. Here we report on a hypoxia gene ( GCH1, GTP-cyclohydrolase I), involved in maintaining nitric oxide synthetase (NOS) function and normal blood pressure, that harbors many potentially adaptive variants in Tibetans. We resequenced an 80.8 kb fragment covering the entire gene region of GCH1 in 50 unrelated Tibetans. Combined with previously published data, we demonstrated many GCH1 variants showing deep divergence between highlander Tibetans and lowlander Han Chinese. Neutrality tests confirmed a signal of positive Darwinian selection on GCH1 in Tibetans. Moreover, association analysis indicated that the Tibetan version of GCH1 was significantly associated with multiple physiological traits in Tibetans, including blood nitric oxide concentration, blood oxygen saturation, and hemoglobin concentration. Taken together, we propose that GCH1 plays a role in the genetic adaptation of Tibetans to high altitude hypoxia.
Collapse
Affiliation(s)
- Yong-Bo Guo
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou Gansu 730070, China; State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming Yunnan 650223, China
| | - Yao-Xi He
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming Yunnan 650223, China; High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa Tibet 850000, China
| | - Chao-Ying Cui
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa Tibet 850000, China
| | - Luobu Ouzhu
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa Tibet 850000, China
| | - Kangzhuo Baima
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa Tibet 850000, China
| | - Zhuoma Duoji
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa Tibet 850000, China
| | - Quzong Deji
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa Tibet 850000, China
| | - Ba Bian
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa Tibet 850000, China
| | - Yi Peng
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming Yunnan 650223, China
| | - Cai-Juan Bai
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa Tibet 850000, China
| | - Lanzi Gongga
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa Tibet 850000, China
| | - Yong-Yue Pan
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa Tibet 850000, China
| | | | - Min Kang
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa Tibet 850000, China
| | - Yangji Ciren
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa Tibet 850000, China
| | - Yangji Baima
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa Tibet 850000, China
| | - Wei Guo
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa Tibet 850000, China
| | - la Yang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming Yunnan 650223, China
| | - Hui Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming Yunnan 650223, China
| | - Xiao-Ming Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming Yunnan 650223, China
| | - Wang-Shan Zheng
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou Gansu 730070, China; State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming Yunnan 650223, China
| | - Shu-Hua Xu
- Chinese Academy of Sciences Key Laboratory of Computational Biology, Max Planck Independent Research Group on Population Genomics, CAS-MPG Partner Institute for Computational Biology(PICB), Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China; School of Life Science and Technology, Shanghai Tech University, Shanghai 200031, China; Collaborative Innovation Center of Genetics and Development, Shanghai 200438, China
| | - Hua Chen
- Center for Computational Genomics, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
| | - Sheng-Guo Zhao
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou Gansu 730070, China
| | - Yuan Cai
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou Gansu 730070, China
| | - Shi-Ming Liu
- National Key Laboratory of High Altitude Medicine, High Altitude Medical Research Institute, Xining Qinghai 810012, China
| | - Tian-Yi Wu
- National Key Laboratory of High Altitude Medicine, High Altitude Medical Research Institute, Xining Qinghai 810012, China
| | - Xue-Bin Qi
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming Yunnan 650223, China.
| | - Bing Su
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming Yunnan 650223, China.
| |
Collapse
|
8
|
Zheng WS, He YX, Cui CY, Ouzhu L, Deji Q, Peng Y, Bai CJ, Duoji Z, Gongga L, Bian B, Baima K, Pan YY, Qu L, Kang M, Ciren Y, Baima Y, Guo W, Yang L, Zhang H, Zhang XM, Guo YB, Xu SH, Chen H, Zhao SG, Cai Y, Liu SM, Wu TY, Qi XB, Su B. EP300 contributes to high-altitude adaptation in Tibetans by regulating nitric oxide production. Zool Res 2017; 38:163-170. [PMID: 28585440 PMCID: PMC5460085 DOI: 10.24272/j.issn.2095-8137.2017.036] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [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] [Indexed: 12/17/2022] Open
Abstract
The genetic adaptation of Tibetans to high altitude hypoxia likely involves a group of genes in the hypoxic pathway, as suggested by earlier studies. To test the adaptive role of the previously reported candidate gene EP300 (histone acetyltransferase p300), we conducted resequencing of a 108.9 kb gene region of EP300 in 80 unrelated Tibetans. The allele-frequency and haplotype-based neutrality tests detected signals of positive Darwinian selection on EP300 in Tibetans, with a group of variants showing allelic divergence between Tibetans and lowland reference populations, including Han Chinese, Europeans, and Africans. Functional prediction suggested the involvement of multiple EP300 variants in gene expression regulation. More importantly, genetic association tests in 226 Tibetans indicated significant correlation of the adaptive EP300 variants with blood nitric oxide (NO) concentration. Collectively, we propose that EP300 harbors adaptive variants in Tibetans, which might contribute to high-altitude adaptation through regulating NO production.
Collapse
Affiliation(s)
- Wang-Shan Zheng
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou Gansu 730070, China; State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming Yunnan 650223, China
| | - Yao-Xi He
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming Yunnan 650223, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming Yunnan 650204, China
| | - Chao-Ying Cui
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa Tibet 850000, China
| | - Luobu Ouzhu
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa Tibet 850000, China
| | - Quzong Deji
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa Tibet 850000, China
| | - Yi Peng
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming Yunnan 650223, China
| | - Cai-Juan Bai
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa Tibet 850000, China
| | - Zhuoma Duoji
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa Tibet 850000, China
| | - Lanzi Gongga
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa Tibet 850000, China
| | - Ba Bian
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa Tibet 850000, China
| | - Kangzhuo Baima
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa Tibet 850000, China
| | - Yong-Yue Pan
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa Tibet 850000, China
| | - la Qu
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa Tibet 850000, China
| | - Min Kang
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa Tibet 850000, China
| | - Yangji Ciren
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa Tibet 850000, China
| | - Yangji Baima
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa Tibet 850000, China
| | - Wei Guo
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa Tibet 850000, China
| | - la Yang
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa Tibet 850000, China
| | - Hui Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming Yunnan 650223, China
| | - Xiao-Ming Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming Yunnan 650223, China
| | - Yong-Bo Guo
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou Gansu 730070, China; State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming Yunnan 650223, China
| | - Shu-Hua Xu
- Chinese Academy of Sciences Key Laboratory of Computational Biology, Max Planck Independent Research Group on Population Genomics, CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China; School of Life Science and Technology, Shanghai Tech University, Shanghai 200031, China; Collaborative Innovation Center of Genetics and Development, Shanghai 200438, China
| | - Hua Chen
- Center for Computational Genomics, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
| | - Sheng-Guo Zhao
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou Gansu 730070, China
| | - Yuan Cai
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou Gansu 730070, China
| | - Shi-Ming Liu
- National Key Laboratory of High Altitude Medicine, High Altitude Medical Research Institute, Xining Qinghai 810012, China
| | - Tian-Yi Wu
- National Key Laboratory of High Altitude Medicine, High Altitude Medical Research Institute, Xining Qinghai 810012, China
| | - Xue-Bin Qi
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming Yunnan 650223, China.
| | - Bing Su
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming Yunnan 650223, China.
| |
Collapse
|