Introduction: Obesity is a chronic disease characterized by complex alterations in body composition and metabolic health. Traditional reliance on body weight may overlook important physiological adaptations during lifestyle intervention. Methodology: A cohort of 99 participants at programme entry underwent body composition assessment using bioelectrical impedance analysis. Parameters included percent body fat (PBF), visceral fat area (VFA), skeletal muscle index (SMI), and phase angle (PhA). Correlation analyses were performed to explore relationships between adiposity, muscle mass, and cellular health. Results: Participants demonstrated elevated adiposity (PBF 38.9 ± 8.9%; VFA 142.9 ± 56.1 cm²). PhA was inversely associated with VFA (r ≈ −0.23, p <0.05) and positively associated with SMI (r ≈ 0.49, p <0.001). Notably, a subset of overweight individuals exhibited relatively preserved PhA, indicating heterogeneity in metabolic health despite similar adiposity levels. Conclusion Body composition and PhA provide complementary insights into metabolic health beyond body weight. These findings support the role of bioimpedance-derived parameters in identifying metabolic heterogeneity and guiding personalized obesity management.
Body Composition ; Body Weight ; Workplace ; Obesity

Introduction: Polycystic ovarian syndrome (PCOS) is a complex endocrine disorder that significantly affects adolescent girls, particularly those with overweight or obesity. However, data examining the determinants and metabolic profiles of PCOS among adolescents with overweight and obesity remain limited, especially in Malaysia. This protocol describes a case-control study investigating the cardiometabolic, dietary, and psychosocial determinants of PCOS among adolescents with overweight and obesity. Methodology: This study is designed as a case-control study involving adolescent girls aged 13–16 years with a body mass index z-score >+1 standard deviation. Cases are defined as adolescent girls with a confirmed diagnosis of PCOS based on the recommendations of the 2017 International Consortium of Paediatric Endocrinology (ICPE), while controls are those who do not meet the diagnostic criteria for PCOS. A total sample size of 440 participants is required. Participants will be recruited from 22 secondary schools selected from a list of schools in Kuala Lumpur. Data on sociodemographic characteristics, psychosocial health, physical activity, and dietary intake will be collected using structured questionnaires. Blood samples will be obtained and analyzed for diagnostic testing (free testosterone), exclusion tests (thyroid-stimulating hormone, folliclestimulating hormone, luteinizing hormone, estradiol, prolactin, and dehydroepiandrosterone sulfate), and biochemical parameters (liver function tests, lipid profile, hemoglobin A1c, fasting glucose, fasting insulin, and inflammatory markers). Results: The study is expected to generate comprehensive data on the cardiometabolic, dietary, and psychosocial determinants of PCOS among adolescents with overweight and obesity. The findings will inform early screening strategies and targeted interventions aimed at reducing long-term reproductive and cardiometabolic complications. Conclusion This protocol outlines a structured approach to investigating PCOS in adolescence and addresses current gaps in early identification and risk stratification among highrisk populations.
Adolescent ; Humans ; Case-Control Studies ; Overweight ; Polycystic Ovary Syndrome ; Obesity

OBJECTIVE: To investigate the associations between eight serum per- and polyfluoroalkyl substances (PFASs) and regional fat depots, we analyzed the data from the National Health and Nutrition Examination Survey (NHANES) 2011-2018 cycles. METHODS: Multiple linear regression models were developed to explore the associations between serum PFAS concentrations and six fat compositions along with a fat distribution score created by summing the concentrations of the six fat compositions. The associations between structurally grouped PFASs and fat distribution were assessed, and a prediction model was developed to estimate the ability of PFAS exposure to predict obesity risk. RESULTS: Among females aged 39-59 years, trunk fat mass was positively associated with perfluorooctane sulfonate (PFOS). Higher concentrations of PFOS, perfluorohexane sulfonate (PFHxS), perfluorodecanoate (PFDeA), perfluorononanoate (PFNA), and n-perfluorooctanoate (n-PFOA) were linked to greater visceral adipose tissue in this group. In men, exposure to total perfluoroalkane sulfonates (PFSAs) and long-chain PFSAs was associated with reductions in abdominal fat, while higher abdominal fat in women aged 39-59 years was associated with short-chain PFSAs. The prediction model demonstrated high accuracy, with an area under the curve (AUC) of 0.9925 for predicting obesity risk. CONCLUSION PFAS exposure is associated with regional fat distribution, with varying effects based on age, sex, and PFAS structure. The findings highlight the potential role of PFAS exposure in influencing fat depots and obesity risk, with significant implications for public health. The prediction model provides a highly accurate tool for assessing obesity risk related to PFAS exposure.
Humans ; Fluorocarbons/blood* ; Female ; Adult ; Middle Aged ; Male ; Environmental Pollutants/blood* ; Abdominal Fat ; Nutrition Surveys ; Alkanesulfonic Acids/blood* ; Obesity ; Environmental Exposure

OBJECTIVE: This study aimed to evaluate the association between susceptibility genes and non-alcoholic fatty liver disease (NAFLD) in children with obesity. METHODS: We conducted a two-step case-control study. Ninety-three participants were subjected to whole-exome sequencing (exploratory set). Differential genes identified in the small sample were validated in 1,022 participants using multiplex polymerase chain reaction and high-throughput sequencing (validation set). RESULTS: In the exploratory set, 14 genes from the NAFLD-associated pathways were identified. In the validation set, after adjusting for sex, age, and body mass index, ECI2 rs2326408 (dominant model: OR = 1.33, 95% CI: 1.02-1.72; additive model: OR = 1.22, 95% CI: 1.01-1.47), C6orf201 rs659305 (dominant model: OR = 1.30, 95% CI: 1.01-1.69; additive model: OR = 1.21, 95% CI: 1.00-1.45), CALML5 rs10904516 (pre-ad dominant model: OR = 1.36, 95% CI: 1.01-1.83; adjusted dominant model: OR = 1.40, 95% CI: 1.03-1.91; and pre-ad additive model: OR = 1.26, 95% CI: 1.04-1.66) polymorphisms were significantly associated with NAFLD in children with obesity ( P < 0.05). Interaction analysis revealed that the gene-gene interaction model of CALML5 rs10904516, COX11 rs17209882, and SCD5 rs3733228 was optional ( P < 0.05), demonstrating a negative interaction between the three genes. CONCLUSION In the Chinese population, the CALML5 rs10904516, C6orf201 rs659305, and ECI2 rs2326408 variants could be genetic markers for NAFLD susceptibility.
Humans ; Non-alcoholic Fatty Liver Disease/genetics* ; Child ; Male ; Female ; Genetic Predisposition to Disease ; Case-Control Studies ; Exome Sequencing ; Adolescent ; Polymorphism, Single Nucleotide ; Obesity/complications* ; Pediatric Obesity/complications* ; China

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*

OBJECTIVE: To investigate the association between long-term exposure to ambient fine particulate matter (PM _2.5) and its constituents and the risk of incident type 2 diabetes mellitus (T2DM), and to examine the modification roles of overweight status. METHODS: This prospective study included 27,507 adults living in rural China. The annual mean residential exposure to PM _2.5 and its constituents was estimated using a satellite-based statistical model. Cox models were used to estimate the risk of T2DM associated with PM _2.5 and its constituents. Stratified analysis quantified the role of overweight status in the association between PM _2.5 constituents and T2DM. RESULTS: Over a median follow-up of 9.4 years, 3,001 new T2DM cases were identified. The hazard ratio ( HR) for a 10 μg/m ³ increase in ambient PM _2.5 was 1.30 (95% confidence interval [ CI]: 1.17, 1.45). Among the constituents, the strongest association was observed with black carbon. Being overweight significantly modified the association between certain constituents and the risk of T2DM. Participants who were overweight and exposed to the highest quartile of PM _2.5 constituents had the highest risk of T2DM ( HR: 2.46, 95% CI: 2.04, 2.97). CONCLUSIONS Our findings indicate that PM _2.5 was associated with an increased risk of T2DM, with black carbon potentially being the primary contributor. Being overweight appeared to enhance the association between PM _2.5 and T2DM. This suggests that controlling both PM _2.5 exposure and overweight status may reduce the burden of T2DM.
Humans ; Diabetes Mellitus, Type 2/chemically induced* ; China/epidemiology* ; Particulate Matter/analysis* ; Overweight/epidemiology* ; Female ; Male ; Middle Aged ; Rural Population ; Air Pollutants/analysis* ; Adult ; Prospective Studies ; Environmental Exposure/adverse effects* ; Aged ; Risk Factors

The gut microbiota is closely related to human health, and various gut microbiota health indices have been developed to assist in evaluating the health of the gut microbiota and even the overall health of the human body. Diets are one of the main factors that regulate the gut microbiota, while there is still no good method for evaluating the regulatory effects of dietary factors. To assess the regulatory effects of dietary factors on the gut microbiota of overweight individuals, we conducted an in vitro fermentation experiment based on 17 dietary factors, and developed an evaluation method for the regulatory effects of dietary factors based on the health index with principal component analysis (hiPCA). The results showed that most dietary factors had positive regulatory effects on the gut microbiota of overweight individuals. Galactooligosaccharides (GOS) and puerarin were the most significant dietary factors in regulating the gut microbiota of overweight individuals. The analysis of the contribution of species to the hiPCA indicated that GOS and puerarin might inhibit the activities of bacteria associated with overweight by regulating Eubacterium dolichum, Lactobacillus salivarius, Clostridium clostridioforme, Clostridium citroniae, and Lachnospiraceae bacterium 9_1_43BFAA. In addition, GOS may further enhance the inhibition of these activities by regulating Lachnospiraceae bacterium 6_1_63FAA, thereby reducing the gut health risks in overweight individuals. In summary, this study evaluated the health effects of dietary factors based on the hiPCA and specifically analyzed the role of different dietary factors in regulating the gut microbiota of overweight individuals. This provides new ideas and methods for improving gut microbiota health and has potential applications in the field of precision nutrition.
Humans ; Gastrointestinal Microbiome/physiology* ; Isoflavones/pharmacology* ; Overweight/microbiology* ; Diet ; Fermentation ; Oligosaccharides/pharmacology* ; Principal Component Analysis

Objective To explore the effects of time reallocation among moderate-to-vigorous physical activity(MVPA),light physical activity(LPA),sedentary behavior(SB),and sleep on a body shape index(ABSI),body roundness index(BRI),conicity index(CI),and relative fat mass(RFM)of college students by the compositional isotemporal substitution method,thus providing measures for alleviating the obesity problem of college students. Methods Two hundred and ten college students(111 males and 99 females)aged 18-22 years old were recruited from Tianjin University of Science and Technology from April to June in 2023.Three-dimensional acceleration sensors were used to collect data of MVPA,LPA,SB,and sleep of college students.The body height,body weight,and waist circumference were measured,and four novel obesity indicators(ABSI,BRI,CI,and RFM)were calculated.The effects of substituting each activity behavior for 15 min on the obesity indicators were predicted,and the dose-effect relationship was explored at intervals of 5 min from -30 to 30 min.Results MVPA was negatively correlated with ABSI(β=-0.03,P=0.001),BRI(β=-0.27,P=0.049),CI(β=-0.10,P=0.001),and RFM(β=-9.95,P=0.004).LPA was negatively correlated with CI(β=-0.05,P=0.011)and RFM(β=-8.74,P=0.007).Neither SB nor sleep had correlations with ABSI,BRI,CI,and RFM.The results of 15 min isotemporal substitutions showed that increasing the MVPA time decreased the ABSI,BRI,CI,and RFM by 0.006-0.008,0.306-0.393,0.162-0.205,and 2.468-2.897,respectively.Decreasing the MVPA time increased the ABSI,BRI,CI,and RFM by 0.012-0.014,0.548-0.632,0.286-0.328,and 4.358-4.748,respectively.In the dose-effect relationship from -30 min to 30 min,MVPA was irreplaceable,and the negative benefits from substituting MVPA for other activity behaviors were much greater than the positive benefits from substituting MVPA for other activity behaviors.Conclusions Future research should take 24 hours activity behaviors as a whole.Increasing the time spent on MVPA and LPA and decreasing the time spent on SB is one of the effective ways to alleviate the obesity problem among college students.
Humans ; Male ; Students ; Female ; Young Adult ; Obesity ; Sleep ; Adolescent ; Exercise ; Universities ; Sedentary Behavior ; Body Mass Index ; Body Weight

BACKGROUND

Maternal malnutrition is a major cause of low birth weight (LBW) newborn outcome especially among adolescent mothers. It is one of the key drivers of child stunting and initiates the vicious cycle of intergenerational malnutrition. The body mass index prior to pregnancy or at the initial trimester is currently being used to establish the desired weight gain throughout pregnancy. However, Filipino adolescents often delay their first antenatal visit at a later stage of pregnancy. Without a baseline weight, the establishment of appropriate weight gain and nutritional status is often challenging. Mid-upper arm circumference (MUAC) was proven to be a good proxy measure of acute malnutrition, however, there was no global consensus on what MUAC cut-off point to use to identify pregnant adolescents at risk for delivering LBW babies. Finding the optimal cut-off could facilitate early identification and intervention of pregnant adolescents who are nutritionally at risk and could eventually break the cycle of intergenerational malnutrition.

The study aims to determine the association of maternal MUAC and the birth weight outcomes among newborn deliveries of adolescents in a tertiary hospital for a period of six months and to identify the optimal maternal MUAC cut-off point that can be used to predict low birth weight outcome among newborn deliveries of adolescents in a tertiary hospital.

A cross-sectional study was conducted among adolescents ages 10 to 19 years who delivered babies in a tertiary hospital in the Philippines for a period of six months. Maternal MUAC and LBW outcome were documented, and their association was determined using a logistic regression analysis. To measure diagnostic accuracy, the sensitivity, specificity, and the area under the curve were taken for each MUAC point. A receiver operating characteristic (ROC) curve was used to aid the MUAC cut-off determination.

Out of 237 newborn deliveries, 35% were noted with low birth weight while 65% had normal birth weight. Most of the mothers were in their late adolescence at 78%. The crude association for the MUAC cut-offs ≤23.00 cm, ≤23.50 cm, and ≤24.00 cm and LBW showed a significant value of 2.19, 2.25, and 2.39 at 95% CI, respectively. However, it is only the cut-off ≤24.00 cm that showed significant results for adjusted association by the logistic regression analysis. The MUAC cut-off ≤24.00 cm also showed a better trade-off value between the sensitivity and specificity. Furthermore, the optimal maternal MUAC measurement that predicts LBW newborn outcome points to ≤24.00 cm cut-off based on the ROC curve.

This study shows that the maternal MUAC is predictive of LBW outcome among adolescent deliveries.A MUAC cut-off of ≤24.00 cm was superior to lower cut-offs studied. The pregnant adolescents might need a higher MUAC cut-off than adults to allow timely intervention and prevention of poor neonatal outcomes. By doing this simple screening test, suspected pregnant adolescents can be easily identified and referred for further confirmatory testing.

Objective To investigate the internalized weight bias and weight control beliefs regarding the current status,influencing factors,and impacts on eating behaviors of women losing weight. Methods A convenient sampling method was used to select the females who underwent physical examination in the Peking Union Medical College Hospital from August to December 2023.The general information questionnaire,Weight Bias Internalization Scale,Weight Control Belief Questionnaire,and Chinese version of Three-Factor Eating Questionnaire were utilized for investigation.Latent class analysis was conducted to explore the potential categories based on the characteristics of internalized weight bias and weight control beliefs.Univariate analysis and multiple-factor linear regression analysis were performed to explore influencing factors of potential categories and their effects on eating behaviors. Results A total of 518 subjects were included in this study.The internalized weight bias and weight control beliefs could be classified into three potential categories: low weight bias tolerance type(53.7%),medium weight bias persistence type(29.5%),and high weight bias overcritical type(16.8%).Logistic regression analysis showed that body mass index,unmarriage,and divorce were the influencing factors of the high weight bias overcritical type.The scores of non-control eating and emotional eating in medium weight bias persistence type and high weight bias overcritical type were higher than those in low weight bias tolerance type(all P<0.001). Conclusions The attitudes of Chinese women towards body weight can be categorized into low weight bias tolerance type,medium weight bias persistence type,and high weight bias overcritical type.The high weight bias overcritical type is characterized by high weight bias and high personal responsibility attribution,and it is closely associated with negative eating behaviors.A high body mass index,unmarriage,and divorce are high-risk factors for developing the high weight bias overcritical type.
Humans ; Female ; Feeding Behavior/psychology* ; Surveys and Questionnaires ; Adult ; Body Mass Index ; Weight Loss ; Body Weight ; Body Image ; Middle Aged ; Weight Prejudice