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Gholami F, Karimi Z, Samadi M, Sovied N, Yekaninejad MS, Keshavarz SA, Javdan G, Bahrampour N, Wong A, Clark CCT, Mirzaei K. The association between dietary pattern and visceral adiposity index, triglyceride-glucose index, inflammation, and body composition among Iranian overweight and obese women. Sci Rep 2023; 13:13162. [PMID: 37574495 PMCID: PMC10423716 DOI: 10.1038/s41598-023-39653-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2023] [Accepted: 07/28/2023] [Indexed: 08/15/2023] Open
Abstract
The aim of the present study was to investigate the association between dietary patterns, derived through latent class analysis (LCA), with visceral adiposity index (VAI), Triglyceride-Glucose Index (TyG), inflammation biomarkers, and body composition in overweight and obese Iranian women. For this cross-sectional study, dietary exposure was assessed using a validated 147-item semi-quantitative food frequency questionnaire (FFQ). Dietary patterns were derived through LCA. Binary logistic was performed to test the associations of dietary patterns with VAI, TyG, inflammation biomarkers, and body composition. Health centers in Tehran, Iran. 376 obese and overweight women, aged > 18 years. Two dietary patterns were identified using LCA modeling: healthy and unhealthy. Women in the unhealthy class were characterized by higher consumption of fast food, sweetened beverages, grains, unhealthy oils, butter and margarine, and snacks. Compared with the healthy class, the unhealthy class was associated with an increased risk of higher fasting blood sugar (FBS) (OR = 6.07; 95% CI: 1.33-27.74, P value = 0.02), c-reactive protein (CRP) (OR = 1.72; 95% CI: 1.05-2.80; P value = 0.02), and lower fat free mass index (FFMI) (OR = 0.56; 95% CI: 0.35-0.88, P value = 0.01), after adjusting for confounders. We found that adherence to an unhealthy dietary pattern was associated with decreased FFMI and increased FBS and CRP using LCA, but not with the rest of the variables. Further studies should be conducted to confirm the veracity of these findings.
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Affiliation(s)
- Fatemeh Gholami
- Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences (TUMS), P.O. Box: 14155-6117, Tehran, Iran
| | - Zahra Karimi
- Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Science, Tehran, Iran
| | - Mahsa Samadi
- Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences (TUMS), P.O. Box: 14155-6117, Tehran, Iran
| | - Neda Sovied
- Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences (TUMS), P.O. Box: 14155-6117, Tehran, Iran
| | - Mir Saeid Yekaninejad
- Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Science, Tehran, Iran
| | - Seyed Ali Keshavarz
- Department of Clinical Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences, Tehran, Iran
| | - Gholamali Javdan
- Food Health Research Center, Hormozgan University of Medical Sciences, Bandar Abbas, Iran
| | - Niki Bahrampour
- Department of Nutrition, Science and Research Branch, Islamic Azad University (SRBIAU), Tehran, Iran
| | - Alexei Wong
- Department of Health and Human Performance, Marymount University, Arlington, VA, USA
| | - Cain C T Clark
- Centre for Intelligent Healthcare, Coventry University, Coventry, CV1 5FB, UK
| | - Khadijeh Mirzaei
- Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences (TUMS), P.O. Box: 14155-6117, Tehran, Iran.
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Zang Z, Liu Y, Wang J, Liu Y, Zhang S, Zhang Y, Zhang L, Zhao D, Liu F, Chao L, Wang X, Zhang C, Song G, Zhang Z, Li Y, Yan Z, Wen Y, Ge Y, Niu C, Feng W, Nakyeyune R, Shen Y, Shao Y, Guo X, Yang A, Liu F, Wang G. Dietary patterns and severity of symptom with the risk of esophageal squamous cell carcinoma and its histological precursor lesions in China: a multicenter cross-sectional latent class analysis. BMC Cancer 2022; 22:95. [PMID: 35062901 PMCID: PMC8783423 DOI: 10.1186/s12885-022-09206-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Accepted: 01/18/2022] [Indexed: 12/20/2022] Open
Abstract
Background Dietary patterns and symptoms research among Chinese with esophageal squamous cell carcinoma (ESCC) and its precursor lesions is limited, especially as it relates to multiple food consumption and multiple co-occurring symptoms. The aim of our study was to identify the dietary patterns and severity of symptom classes with the risk of esophageal squamous cell carcinoma and its histological precursor lesions, and develop a risk prediction model for different stages of esophageal disease. Methods We analyzed data from a multicenter cross-sectional study carried out in ESCC high incidence areas between 2017 and 2018, which included 34,707 individuals aged 40–69 years. Dietary patterns and severity of symptom classes were derived by applying a latent class analysis (LCA). A multiple logistic regression model was used to derive the odds ratio (ORs) and corresponding 95% confidence intervals (CIs) for ESCC and the different stages of esophageal disease according to the dietary patterns and severity of symptom classes identified. We built the risk prediction model by using a nomogram. Results We identified five dietary patterns and three severity of symptom classes. The dietary patterns were classified as follows: “Healthy”, “Western”, “Lower consumers-combination”, “Medium consumers-combination” and “Higher consumers-combination” patterns based on the intake of foods such as red meat, vegetables and fruits. The severity of symptoms was categorized into “Asymptomatic”, “Mild symptoms” and “Overt symptoms” classes based on health-related symptoms reported by the participants. Compared to the “Healthy” pattern, the other four patterns were all associated with an increased risk of esophageal disease. Similarly, the other two symptom classes present different degrees of increased risk of esophageal disease compared to the “Asymptomatic”. The nomograms reflect the good predictive ability of the model. Conclusion Among individuals aged 40–69 years in high incidence regions of upper gastrointestinal cancer, the results supplied that subjects with diets rich in livestock and poultry meat and low in fruits and vegetables and subjects with typical symptoms were at increased ESCC risk. The findings highlight the importance of considering food and symptom combinations in cancer risk evaluation. Supplementary Information The online version contains supplementary material available at 10.1186/s12885-022-09206-y.
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Tang XY, Cheng M, Geater A, Deng QY, Zhong G, Lin YD, Chen N, Lan T, Jiang LY, Zhu MT, Li Q. Multi-level determinants of failure to receive timely and complete measles vaccinations in Southwest China: a mixed methods study. Infect Dis Poverty 2021; 10:102. [PMID: 34294157 PMCID: PMC8296749 DOI: 10.1186/s40249-021-00885-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Accepted: 07/12/2021] [Indexed: 04/04/2024] Open
Abstract
BACKGROUND Measles outbreaks re-emerged in 2013-2014 in Guangxi Zhuang Autonomous Region of China, where measles immunisation coverage is high. The discrepancy between the vaccination coverage and outbreaks indicates that timeliness is crucial, yet there is limited knowledge on the health system barriers to timely vaccination. Using integrated evidence at the household, village clinic, and township hospital levels, this study aimed to identify the determinants of failure in receiving timely measles vaccinations among children in rural Guangxi. METHODS A multi-stage stratified cluster sampling survey with a nested qualitative study was conducted among children aged 18-54 months in Longan, Zhaoping, Wuxuan, and Longlin counties of Guangxi from June to August 2015. The status of timely vaccinations for the first dose of measles-containing vaccine (MCV1) and the second dose of measles-containing vaccine (MCV2) was verified via vaccination certificates. Data on household-level factors were collected using structured questionnaires, whereas data on village and township-level factors were obtained through in-depth interviews and focus group discussions. Determinants of untimely measles vaccinations were identified using multilevel logistic regression models. RESULTS A total of 1216 target children at the household level, 120 villages, and 20 township hospitals were sampled. Children were more likely to have untimely vaccination when their primary guardian had poor vaccination knowledge [MCV1, odds ratio (OR) = 1.72; MCV2, OR = 1.51], had weak confidence in vaccines (MCV1, OR = 1.28-4.58; MCV2, OR = 1.42-3.12), had few practices towards vaccination (MCV1, OR = 12.5; MCV2, OR = 3.70), or had low satisfaction with vaccination service (MCV1, OR = 2.04; MCV2, OR = 2.08). This trend was also observed in children whose village doctor was not involved in routine vaccination service (MCV1, OR = 1.85; MCV2, OR = 2.11) or whose township hospital did not provide vaccination notices (MCV1, OR = 1.64; MCV2, OR = 2.05), vaccination appointment services (MCV1, OR = 2.96; MCV2, OR = 2.74), sufficient and uniformly distributed sessions for routine vaccination (MCV1, OR = 1.28; MCV2, OR = 1.17; MCV1, OR = 2.08), or vaccination service on local market days (MCV1, OR = 2.48). CONCLUSIONS Guardians with poor knowledge, weak beliefs, and little practice towards vaccination; non-involvement of village doctors in routine vaccinations; and inconvenient vaccination services in township hospitals may affect timely measles vaccinations among children in rural China.
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Affiliation(s)
- Xian-Yan Tang
- Department of Epidemiology and Biostatistics, School of Public Health, Guangxi Medical University, China. No. 22nd, Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China.
| | - Man Cheng
- Department of Epidemiology and Biostatistics, School of Public Health, Guangxi Medical University, China. No. 22nd, Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China
| | - Alan Geater
- Epidemiology Unit, Faculty of Medicine, Prince of Songkla University, Hat Yai, Thailand
| | - Qiu-Yun Deng
- Institute of Vaccination, Guangxi Centre for Disease Control and Prevention, Nanning, Guangxi Zhuang Autonomous Region, China
| | - Ge Zhong
- Institute of Vaccination, Guangxi Centre for Disease Control and Prevention, Nanning, Guangxi Zhuang Autonomous Region, China
| | - Yue-Dong Lin
- Department of Epidemiology and Biostatistics, School of Public Health, Guangxi Medical University, China. No. 22nd, Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China
| | - Ning Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Guangxi Medical University, China. No. 22nd, Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China
| | - Tao Lan
- Department of Epidemiology and Biostatistics, School of Public Health, Guangxi Medical University, China. No. 22nd, Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China
| | - Long-Yan Jiang
- Department of Epidemiology and Biostatistics, School of Public Health, Guangxi Medical University, China. No. 22nd, Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China
| | - Man-Tong Zhu
- Department of Epidemiology and Biostatistics, School of Public Health, Guangxi Medical University, China. No. 22nd, Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China
| | - Qiao Li
- Department of Epidemiology and Biostatistics, School of Public Health, Guangxi Medical University, China. No. 22nd, Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China.
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