OBJECTIVE: This study aimed to explore the interplay between the life-course body mass index (BMI) trajectories and insulin resistance (IR) on incident diabetes. METHODS: This longitudinal cohort included 2,336 participants who had BMI repeatedly measured 3-8 times between 1989 and 2009, as well as glucose and insulin measured in 2009. BMI trajectories were identified using a latent class growth mixed model. The interplay between BMI trajectories and IR on diabetes was explored using the four-way effect decomposition method. Logistic regression and mediation models were used to estimate the interaction and mediation effects, respectively. RESULTS: Three distinct BMI trajectory groups were identified: low-stable ( n = 1,625), medium-increasing ( n = 613), and high-increasing ( n = 98). Both interaction and mediation effects of BMI trajectories and IR on incident diabetes were significant ( P < 0.05). The proportion of incident diabetes was higher in the IR-obesity than in the insulin-sensitivity (IS) obesity group (18.9% vs. 5.8%, P < 0.001). After adjusting for covariates, the odds ratios (95% confidence intervals) of the IR, IS-obesity, and IR-obesity groups vs. the normal group were 3.22 (2.05, 5.16), 2.05 (1.00, 3.97), and 7.98 (5.19, 12.62), respectively. IR mediated 10.7% of the total effect of BMI trajectories on incident diabetes ( P < 0.001). CONCLUSION We found strong interactions and weak mediation effects of IR on the relationship between life-course BMI trajectories and incident diabetes. IS-obesity is associated with a lower risk of incident diabetes than IR-obesity.
Humans ; Insulin Resistance ; Body Mass Index ; Male ; Female ; Middle Aged ; China/epidemiology* ; Adult ; Longitudinal Studies ; Incidence ; Diabetes Mellitus/epidemiology* ; Aged ; Obesity/epidemiology* ; Diabetes Mellitus, Type 2/epidemiology* ; East Asian People

OBJECTIVE: This study aimed to explore the association between body mass index (BMI) and mortality based on the 10-year population-based multicenter prospective study. METHODS: A general population-based multicenter prospective study was conducted at four sites in rural China between 2013 and 2023. Multivariate Cox proportional hazards models and restricted cubic spline analyses were used to assess the association between BMI and mortality. Stratified analyses were performed based on the individual characteristics of the participants. RESULTS: Overall, 19,107 participants with a sum of 163,095 person-years were included and 1,910 participants died. The underweight (< 18.5 kg/m ²) presented an increase in all-cause mortality (adjusted hazards ratio [ aHR] = 2.00, 95% confidence interval [ CI]: 1.66-2.41), while overweight (≥ 24.0 to < 28.0 kg/m ²) and obesity (≥ 28.0 kg/m ²) presented a decrease with an aHR of 0.61 (95% CI: 0.52-0.73) and 0.51 (95% CI: 0.37-0.70), respectively. Overweight ( aHR = 0.76, 95% CI: 0.67-0.86) and mild obesity ( aHR = 0.72, 95% CI: 0.59-0.87) had a positive impact on mortality in people older than 60 years. All-cause mortality decreased rapidly until reaching a BMI of 25.7 kg/m ² ( aHR = 0.95, 95% CI: 0.92-0.98) and increased slightly above that value, indicating a U-shaped association. The beneficial impact of being overweight on mortality was robust in most subgroups and sensitivity analyses. CONCLUSION This study provides additional evidence that overweight and mild obesity may be inversely related to the risk of death in individuals older than 60 years. Therefore, it is essential to consider age differences when formulating health and weight management strategies.
Humans ; Body Mass Index ; China/epidemiology* ; Male ; Female ; Middle Aged ; Prospective Studies ; Rural Population/statistics & numerical data* ; Aged ; Follow-Up Studies ; Adult ; Mortality ; Cause of Death ; Obesity/mortality* ; Overweight/mortality*

This study investigated the impact of metabolic syndrome (MetS) and its components on prostate volume (PV) in the general Chinese population. In total, 43 455 participants in The First Medical Center of the Chinese PLA General Hospital (Beijing, China) from January 1, 2012, to December 31, 2022, undergoing health examinations were included in the study. Participants were categorized into four groups according to PV quartiles: Q1 (PV ≤24.94 ml), Q2 (PV >24.94 ml and ≤28.78 ml), Q3 (PV >28.78 ml and ≤34.07 ml), and Q4 (PV >34.07 ml), with Q1 serving as the reference group. Logistic regression analyses were used to examine the association between MetS and PV, with subgroup analyses conducted by age. Among the participants, 18 787 (43.2%) were diagnosed with MetS. In the multivariate analysis model, a significant correlation between MetS and PV was observed, with odds ratios (ORs) increasing as PV increased (Q2, OR = 1.203, 95% confidence interval [CI]: 1.139-1.271; Q3, OR = 1.300, 95% CI: 1.230-1.373; and Q4, OR = 1.556, 95% CI: 1.469-1.648). Analysis of MetS components revealed that all components were positively associated with PV, with abdominal obesity showing the most significant effect. The number of MetS components was identified as a dose-dependent risk factor for elevated PV. The impact of MetS, its components, and component count on PV exhibited a decreasing trend with advancing age. Overall, the influence of MetS, its components, and component count on PV was predominantly observed in the age groups of 40-49 years and 50-59 years. Early intervention targeting MetS can significantly alleviate the increase in PV, particularly benefiting individuals aged 40-59 years who have abdominal obesity.
Humans ; Male ; Metabolic Syndrome/complications* ; Middle Aged ; Cross-Sectional Studies ; Aged ; Prostate/diagnostic imaging* ; Adult ; Age Factors ; Organ Size ; China/epidemiology* ; Obesity, Abdominal ; Risk Factors

OBJECTIVES: To systematically evaluate the prevalence and risk factors of non-alcoholic fatty liver disease (NAFLD) in overweight and obese children and adolescents in China. METHODS: Databases including China National Knowledge Infrastructure, Wanfang Data, VIP Database, China Biomedical Literature Database, PubMed, Embase, Web of Science, and Cochrane Library were searched, from database inception to October 2024. Two researchers independently screened the literature, extracted data, and assessed the quality of the studies according to inclusion and exclusion criteria. A Meta analysis was conducted using Stata 16.0 software. RESULTS: A total of 42 studies involving 16 481 overweight and obese children and adolescents were included. The Meta analysis results showed that the prevalence of NAFLD among overweight and obese children in China was 43% (95%CI: 37%-48%). Factors associated with NAFLD included being male (OR=1.61, 95%CI: 1.17-2.04), increased weight (MD=10.33, 95%CI: 9.08-11.57), increased waist circumference (MD=5.49, 95%CI: 3.36-7.62), longer duration of obesity (MD=0.31, 95%CI: 0.02-0.61), higher body mass index (MD=3.11, 95%CI: 2.07-4.16), elevated fasting blood glucose levels (MD=0.17, 95%CI: 0.06-0.29), higher triglyceride levels (MD=0.32, 95%CI: 0.17-0.47), elevated total cholesterol levels (MD=0.15, 95%CI: 0.10-0.21), higher low-density lipoprotein cholesterol levels (MD=0.14, 95%CI: 0.04-0.23), increased alanine aminotransferase levels (MD=24.39, 95%CI: 18.57-30.20), increased aspartate aminotransferase levels (MD=12.49, 95%CI: 9.67-15.32), elevated serum insulin levels (MD=4.47, 95%CI: 2.57-6.36), higher homeostasis model assessment-insulin resistance (MD=0.45, 95%CI: 0.30-0.59), and elevated uric acid levels (MD=55.91, 95%CI: 35.49-76.32) (P<0.05). CONCLUSIONS The prevalence of NAFLD among overweight and obese children and adolescents in China is high. Male gender, increased weight, increased waist circumference, prolonged obesity duration, higher body mass index, dyslipidemia, and elevated levels of fasting blood glucose, liver enzymes, serum insulin, homeostasis model assessment-insulin resistance, and uric acid are potential risk factors for NAFLD in this population.
Humans ; Non-alcoholic Fatty Liver Disease/etiology* ; Risk Factors ; Adolescent ; Child ; Overweight/complications* ; Prevalence ; China/epidemiology* ; Obesity/complications* ; Male ; Female

OBJECTIVES: To explore the association between Chinese visceral adiposity index (CVAI) and the risk of nephrolithiasis. METHODS: This cross-sectional study analyzed data from 78 438 Chinese adults who underwent ultrasound examinations during health screening at the Health Examination Center of Affiliated Hospital of Yangzhou University. Participants were divided into quartiles (Q1-Q4 groups) based on CVAI. Multivariate logistic regression models were utilized to evaluate the association between CVAI and nephrolithiasis risk, followed by subgroup analyses to further explore potential relationships. The performance of CVAI in predicting the risk of nephrolithiasis was evaluated using receiver operating characteristic (ROC) curves. RESULTS: Increased CVAI was significantly associated with a higher risk of nephrolithiasis, with prevalence rising from 3.36% in the Q1 group to 10.67% in the Q4 group (P<0.01). In adjusted models, CVAI was positively correlated with the prevalence rate of nephrolithiasis (OR=1.002, 95%CI: 1.001-1.004, P<0.01). The risks of nephrolithiasis in the Q2, Q3, and Q4 groups were 1.196-fold (95%CI: 1.069-1.338, P<0.01), 1.260-fold (95%CI: 1.109-1.433, P<0.01), and 1.316-fold (95%CI: 1.125-1.539, P<0.01) higher than in the Q1 group, respectively. Subgroup analysis revealed that CVAI was positively associated with the risk of nephrolithiasis in male participants, individuals aged <60 years, the hypertension group, populations with or without diabetes mellitus, and the normal body mass index subgroup. Genders and age had an interaction effect on the correlation between CVAI and the risk of nephrolithiasis development (both P<0.05). The ROC curve analysis demonstrated that CVAI exhibited superior predictive efficacy compared to waist circumference, body mass index, visceral adiposity index, weight-adjusted waist index, cardiometabolic index and body shape index, with an area under the curve of 0.622. CONCLUSIONS In Chinese adults, CVAI is positively associated with the risk of nephrolithiasis development, which may serve as a potential predictive marker for nephrolithiasis.
Humans ; Nephrolithiasis/etiology* ; Male ; Female ; Middle Aged ; Cross-Sectional Studies ; Adult ; Intra-Abdominal Fat ; Risk Factors ; China/epidemiology* ; Adiposity ; Aged ; Logistic Models ; Obesity, Abdominal/epidemiology* ; East Asian People

BACKGROUND: Recent studies have provided compelling evidence that exposure to brominated flame retardants (BFRs) can adversely affect human health. We aim to explore the potential impact of BFRs on adiposity and central obesity. METHODS: Data from the National Health and Nutrition Examination Surveys (NHANES) cycles conducted between 2009 and 2014 was used to study the connections between variables. After filtering, we analyzed a sample of 4,110 adults aged 20 years and above. Our goal was to examine the potential association between BFRs and consequences and investigate the part played by oxidative stress and inflammatory markers as intermediaries. To achieve this, we used advanced statistical methods such as weighted quantile sum (WQS) regression, quantile-based g-computation (QGC), and the Bayesian kernel machine regression (BKMR). RESULTS: The findings showed that among the examined chemicals, exposure to PBDE85 (weight: 41%), PBDE100 (24%), and PBB153 (23%) may be the dominant contributors to general obesity risk. Upon controlling for all variables that could impact the results, it was found that the QGC outcomes indicated a positive correlation between exposure to mixtures of brominated flame retardants and the occurrence of abdominal obesity (OR = 1.187, 95% CI: 1.056-1.334, p = 0.004). Significant contributions were made by PBDE85 (52%), PBB153 (27%), and PBDE100 (21%). Mediation analysis shows that lymphatic cells (LC) and albumin (ALB) partially mediate the link between brominated flame retardants and obesity. The results of BKMR are generally consistent with those of WQS and QGC. CONCLUSION At a population level, our research has revealed a noteworthy correlation between BFRs and obesity. However, further investigation is required through prospective cohort studies and in-depth mechanistic exploratory studies.
Humans ; Flame Retardants/adverse effects* ; Oxidative Stress/drug effects* ; Adult ; Male ; Female ; Middle Aged ; Inflammation/epidemiology* ; Obesity/chemically induced* ; Biomarkers/blood* ; Nutrition Surveys ; Mediation Analysis ; Young Adult ; United States/epidemiology* ; Environmental Exposure/adverse effects* ; Aged ; Environmental Pollutants/adverse effects* ; Halogenated Diphenyl Ethers/adverse effects*

BACKGROUND: Despite some studies identifying a potential association between obesity and chronic obstructive pulmonary disease (COPD) risk, previous research had overlooked the dynamic nature of body weight over time, leading to inconsistent findings. The purpose of this study is to elucidate the relationship between adult weight change and COPD risk by adjusting for potential confounding factors. METHODS: We conducted a retrospective analysis using data from ten NHANES cycles (1999-2018), including adults aged 40-74 years. Weight change patterns were assessed using BMI at three time points and classified into five categories per period. Absolute weight change was also grouped into five levels. Multivariate logistic regression models, incorporating sampling weights, were used to examine associations between weight change and COPD, adjusting for demographic and lifestyle covariates. RESULTS: Compared with participants who maintained normal weight, stable obesity participants had increased risk of COPD from age 25 years to 10 years before the survey (OR = 1.45, 95% CI = 1.15 to 1.83), in the 10 years period before the survey (OR = 1.75, 95% CI = 1.47 to 2.08), and from age 25 years to survey (OR = 1.84, 95% CI = 1.46 to 2.31). Three periods indicate that weight gain in adulthood was associated with risk of COPD. In addition, substantial weight gain of more than 20 kg was associated with a higher risk of COPD. In stratified analyses, we also observed a more significant association between weight change and the risk of COPD in never smokers compared to former smokers. CONCLUSIONS Our study suggested that stable obesity and weight gain in adulthood were associated with an increased risk of COPD compared to those who maintain a normal weight, and that the association between weight gain and the incidence of COPD appears closer in patients who have never smoked.
Humans ; Pulmonary Disease, Chronic Obstructive/etiology* ; Middle Aged ; Male ; Female ; Adult ; Aged ; Retrospective Studies ; Weight Gain ; Obesity/complications* ; Risk Factors ; United States/epidemiology* ; Nutrition Surveys ; Body Mass Index

BACKGROUND: To date, results on relationship between CYP3A4 gene polymorphism were limited and inconclusive, and no study focused on the influence of CYP3A4 gene-obesity interaction on breast cancer risk, especially in Chinese women. The purpose of this study was to evaluate the impact of four single nucleotide polymorphisms (SNPs) of CYP3A4 gene, the SNP-SNP and gene-environment interactions on the susceptibility to breast cancer in Chinese women. METHODS: Logistic regression was used to explore the relationship between four SNPs of CYP3A4 gene and the risk of breast cancer. Generalized multifactor dimensionality reduction (GMDR) was used to screen the best SNP-SNP and gene-abdominal obesity interaction combinations among four SNPs and abdominal obesity. Haplotype examination among 4 SNPs was conducted using the SHEsis web-based platform. RESULTS: Logistic regression analysis showed that carriers of rs2242480- T allele have significantly higher breast cancer risk, than those with rs2242480- CC genotype, adjusted OR (95%CI) was 1.68 (1.23-2.16) and 2.03 (1.53-2.58) for participants with CT genotype and TT genotype under additive model. We did not find any notable interactions between the four SNPs within the CYP3A4 gene. GMDR model found a significant association in a two-locus model involving rs2242480 and obesity, with a p-value of 0.018. Stratified analysis found that breast cancer risk was the highest in obese participants with rs2242480- CT or TT genotype, compared to those non-obese participants with rs2242480- CC genotype, OR (95%CI) was 3.02 (1.83-4.25). We found that all haplotype combinations were not correlated with breast cancer risk. CONCLUSIONS We found that the T allele of rs2242480 within the CYP3A4 gene and interaction between rs2242480 and obesity were associated with an increased risk of breast cancer. However, the results of this study were only applicable to the Han ethnic group and cannot be generalized to other ethnic groups in China, and more SNPs of CYP3A4 gene should been enrolled in the analysis in the future, to verify the results obtained in this study.
Adult ; Aged ; Female ; Humans ; Middle Aged ; Breast Neoplasms/etiology* ; China/epidemiology* ; Cytochrome P-450 CYP3A/metabolism* ; Gene-Environment Interaction ; Genetic Predisposition to Disease ; Haplotypes ; Obesity/epidemiology* ; Polymorphism, Single Nucleotide ; Risk Factors ; East Asian People

Multiple myeloma (MM) is a common hematologic malignancy that originates from precursor conditions such as monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM). Identifying its risk factors is crucial for early intervention. The etiology of MM is multifactorial, involving race, familial clustering, gender, age, obesity, cytogenetic abnormalities, and environmental exposures. Among these, cytogenetic abnormalities and modifiable factors play pivotal roles in MM pathogenesis and progression. 1) cytogenetic abnormalities. Primary abnormalities [e.g., hyperdiploidy, t(11;14), t(14;16)] emerge at the MGUS stage, while secondary abnormalities [e.g., 1q+, del(17p)] drive disease progression. The accumulation of 1q+ promotes clonal evolution, and del(17p) is associated with significantly reduced survival. 2) modifiable risk factors. Obesity promotes MM via the acetyl-CoA synthetase 2 (ACSS2)-interferon regulatory factor 4 (IRF4) pathway. Vitamin D deficiency weakens immune surveillance. Exposure to herbicides such as Agent Orange and glyphosate increases MGUS incidence. Insufficient UV exposure, by reducing vitamin D synthesis, elevates MM risk. Gut microbiota dysbiosis (enrichment of nitrogen-cycle bacteria and depletion of short-chain fatty acids producers) induces chromosomal instability through the ammonium ion-solute carrier family 12 member 22 (SLC12A2)-NEK2 axis. Therefore, risk-based screening among high-risk populations (e.g., those who are obese, elderly, or chemically exposed), along with early interventions targeting cytogenetic abnormalities [e.g., B cell lymphoma 2 (Bcl-2) inhibitors for t(11;14), ferroptosis inducers for t(4;14)] and modifiable factors (e.g., vitamin D supplementation, gut microbiota modulation), may effectively delay disease progression and improve prognosis.
Humans ; Multiple Myeloma/epidemiology* ; Risk Factors ; Obesity/complications* ; Chromosome Aberrations ; Monoclonal Gammopathy of Undetermined Significance/etiology* ; Gastrointestinal Microbiome ; Vitamin D Deficiency/complications* ; Precancerous Conditions/genetics*

OBJECTIVES: The prevalence of overweight and obesity among children and adolescents continues to rise, becoming one of the most serious global public health issues of the 21st century. Given the differing growth and development environments between urban and rural children, associated risk factors also vary. This study aims to explore the distribution characteristics and influencing factors of overweight and obesity among urban and rural primary and secondary school students in Hunan Province, providing scientific evidence for targeted interventions. METHODS: A stratified, randomized cluster sampling method was used to select participants. A total of 197 084 students from primary and secondary schools across 14 prefectures in Hunan Province underwent physical examinations and questionnaire surveys. Population and spatial distribution characteristics of overweight and obesity were analyzed. Spatial distribution maps and spatial autocorrelation analyses were conducted using ArcGIS. Multivariate Logistic regression was used to identify influencing factors for overweight and obesity. RESULTS: The overall overweight and obesity rates among students in Hunan Province were 14.7% and 10.9%, respectively. Both rates were higher in urban areas than in rural counties (16.0% vs 13.9% for overweight; 12.1% vs 10.2% for obesity). Among both urban and rural students, boys had higher rates of overweight and obesity than girls. Higher-grade students had a higher overweight rate but a lower obesity rate than lower-grade students. In urban areas, the overweight and obesity rates of Han Chinese primary and secondary school students are lower than those of ethnic minority students (both P<0.05). In rural areas, the obesity rate of Han primary and secondary school students is lower than that of ethnic students (P<0.05). Across cities and prefectures, urban overweight and obesity rates ranged from 14.7% to 18.7% and 8.4% to 20.6% respectively, while rural rates ranged from 10.9% to 17.2% and 6.6% to 13.7% respectively. Spatial autocorrelation analysis revealed high-value clusters of overweight/obesity in urban areas of Changde and Zhangjiajie, and in rural areas of Loudi, Huaihua, and Shaoyang. Multivariate Logistic regression showed that gender, school stage, ethnicity, frequency of fresh vegetable intake, and sleep duration were associated with overweight and/or obesity in both urban and rural students. In urban students, frequency of fried food and fresh fruit intake, breakfast habits, physical activity on weekdays and holidays, and screen time on computers were also significant. In rural students, TV viewing time and sedentary duration were additional relevant factors. CONCLUSIONS The situation of overweight and obesity among primary and secondary school students in Hunan Province remains concerning. Greater attention should be paid to regions with high-value clusters of overweight/obesity, and targeted interventions should be developed based on urban-rural differences in influencing factors.
Humans ; China/epidemiology* ; Adolescent ; Male ; Female ; Rural Population/statistics & numerical data* ; Child ; Overweight/epidemiology* ; Students/statistics & numerical data* ; Urban Population/statistics & numerical data* ; Risk Factors ; Prevalence ; Obesity/epidemiology* ; Surveys and Questionnaires ; Pediatric Obesity/epidemiology* ; Schools