OBJECTIVE: This study examines the association between caffeine intake and obesity prevalence in children and adolescents aged 2 to 19.
METHODS: This study used the database from the National Health and Nutrition Examination Survey (NHANES, 2011-2020 March) to perform a cross-sectional study. A total of 10,001 classified children and adolescents were included in this analysis. All data were survey-weighted, and corresponding logistic regression models were performed to examine the associations between caffeine intake and the prevalence of obesity.
RESULTS: In a fully adjusted model, a per-quartile increase in caffeine intake was associated with a 0.05% increased prevalence of obesity. In the subgroup analysis, the multivariate-adjusted ORs (95% CIs) of the prevalence of obesity for per-quartile 1.3497 (1.2014, 1.5163) increments in caffeine intake were 1.5961 (1.3127, 1.9406) for boys and 1.4418 (1.1861, 1.7525) for girls, 1.5807 (1.3131, 1.9027) for white race and 1.3181 (1.0613, 1.6370), 1.0500 (0.6676, 1.6515) for the age of 2-5, 1.4996 (1.1997, 1.8745) for the age of 6-12, and 1.2321 (0.9924, 1597) for the age of 13-19.
CONCLUSION: The study suggested that higher caffeine intake may have a protective effect against obesity in specific subgroups, particularly among no overweight individuals. However, the association was not significant in other groups, indicating the need for a nuanced understanding of caffeine's impact on obesity in diverse populations.
OBJECTIVE: The first objective is to identify the PA levels and screen time of students in middle school. The second objective of the study is to examine the PA levels and screen time among students of different genders.
METHODS: Participants from four consecutive two-year cycles of National Health and Nutrition Examination Survey (NHANES, 2011-2012, 2013-2014, 2015-2016, and 2017-2018) were included in this study. Spearman correlation model was used to identify the correlation between participants' demographics, PA, and screen time data. Negative binomial regression model was used to describe students' PA and screen time (Dependent variable) in different grades (Independent variables). Gender and Age were taken as control variables.
RESULTS: After the data preprocessing, 2516 participants were included in this study. A significant correlation has been found between grade and PA, instead of screen time. Negative binomial regression shows that students have the lowest PA in their transition year grade 6, and their screen time decreased with the grade increased. Significant differences can be found across gender. Future efforts should focus on developing school transition support programs designed to improve PA.
DESIGN: Two-stage stratified sample.
SETTING: Nationally representative of rural Bangladesh.
SUBJECTS: Households (n 5503) and individuals (n 24 198).
RESULTS: Fish consumption in poor households was almost half that in wealthiest households; and lower in females than males in all groups, except the wealthiest, and for those aged ≥15 years (P<0·01). In infants of complementary feeding age, 56 % did not consume ASF on the survey day, despite 78 % of mothers knowing this was recommended. Non-farmed fish made a larger contribution to Fe, Zn, Ca, vitamin A and vitamin B12 intakes than farmed fish (P<0·0001).
CONCLUSIONS: Policies and programmes aimed to increase fish consumption as a means to improve nutrition in rural Bangladesh should focus on women and young children, and on the poorest households. Aquaculture plays an important role in increasing availability and affordability of fish; however, non-farmed fish species are better placed to contribute to greater micronutrient intakes. This presents an opportunity for aquaculture to contribute to improved nutrition, utilising diverse production technologies and fish species, including small fish.
METHODS: We obtained information on medication use and cancer diagnosis from National Health and Nutrition Examination Survey participants. After propensity score matching, we conducted survey-weighted multivariate logistic regression and restricted cubic spline analysis to assess the observed correlation between medication use and cancer while adjusting for multiple covariates. We also performed MR analysis to investigate causality based on summary data from genome-wide association studies on medication use and cancers. We performed sensitivity analyses, replication analysis, genetic correlation analysis, and reverse MR analysis to improve the reliability of MR findings.
RESULTS: We found that the use of agents acting on the renin-angiotensin system was associated with reduced risk of prostate cancer (odds ratio (OR) = 0.42; 95% confidence interval (CI) = 0.27-0.63, P