Many studies have used Body Mass Index (BMI) to define obesity and examine its potential link to adult asthma. However, BMI overlooks body fat distribution, which may significantly impact health. Unlike BMI, the Body Roundness Index (BRI) can more accurately reflect body fat distribution. Therefore, this study examined BRI's relationship with asthma prevalence in U.S. adults.

This study was based on data from the National Health and Nutrition Examination Survey (NHANES) between 2001 and 2018 and covered 40,052 adult participants. Participants were categorized into four quartile groups based on their BRI levels: Quartile 1 (1.05, 3.80); Quartile 2 (3.80, 5.06); Quartile 3 (5.06, 6.61); Quartile 4 (6.61, 23.48). The association between BRI and asthma prevalence was assessed via weighted multivariate logistic regression, smoothed curve fitting, threshold effects, subgroup, and sensitivity analysis. BRI's predictive power was compared to BMI and waist circumference using z-scores.

Of the study population, 5,605 participants had asthma (13.99% prevalence). After adjusting for possible confounders, the results showed that higher BRI was linked to greater asthma prevalence (OR = 1.41, 95% CI:1.27, 1.56, p < 0.0001). A J-shaped relationship between BRI and asthma prevalence (p-nonlinearity = 0) was found, with asthma prevalence rising significantly when BRI surpassed 4.34. BRI outperformed BMI and waist circumference in predicting asthma (BRI: OR = 1.180; BMI: OR = 1.169; W.C.: OR = 1.166). Subgroup and sensitivity analyses confirmed our results' robustness.

Adult asthma prevalence increases with increasing BRI levels, showing a J-shaped relationship. Keeping BRI under 4.34 is vital for lowering asthma prevalence, especially for overweight or obese individuals. In addition, BRI outperformed BMI and waist circumference in predicting asthma occurrence.

Abdominal adipose tissue consists of visceral and subcutaneous fat deposits, each with unique metabolic and functional properties. Identifying the characteristics that influence different obesity phenotypes can support targeted prevention and intervention strategies.

To identify predictive factors associated with visceral and subcutaneous adipose tissue accumulation.

This is a cross-sectional study including adults of both sexes aged ≥20 years under outpatient care in a public healthcare service in Northeast Brazil. Visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) were measured via ultrasound. Anthropometric, clinical, sociodemographic, and behavioral variables were incorporated into the predictive model.

A total of 347 individuals were included. They were median age of 47.0 years (interquartile range: 39.0 to 56.0). Visceral obesity was found in 79.3% of the sample. Adjusted analysis demonstrated that physical inactivity (OR 2.3; 95% CI 1.1-4.7; p = 0.023) and elevated waist circumference (WC) (OR 6.4; 95% CI 2.6-15.8 p < 0.001) were associated with VAT accumulation. Alcohol consumption increased the likelihood of SAT accumulation by 2.2 times (95% CI 1.3-3.7; p = 0.005), while elevated WC raised this likelihood by 4.5 times (95% CI 2.1-9.8; p < 0.001). The VAT/SAT ratio was significantly higher in older adults (OR 5.5; 95%CI 2.0-14.8; p = 0.001), among individuals of Mixed Race and Black, those with lower educational levels (OR 2.4; 95%CI 1.1-5.2; p = 0.028), and in diabetics (OR 2.4; 95%CI 1.2-4.9; p = 0.017).

Distinct factors influence visceral and subcutaneous obesity. Sedentary behavior emerged as an independent predictor of visceral obesity, while alcohol consumption was associated with a subcutaneous obesity pattern. Diabetes and sociodemographic factors (older age, non-White race, and lower education) were predictive of an elevated VAT/SAT ratio.

Obesity is a major global health issue, driving high morbidity and mortality rates. The body roundness index (BRI), which includes waist circumference, offers a more accurate measure of visceral and total body fat. However, despite evidence of BRI's effectiveness in predicting obesity-related diseases, national-level data, especially from non-Western populations like China, remain limited.

This study utilized data from the China Health and Retirement Longitudinal Study (CHARLS), a large, nationally representative cohort of Chinese adults, to examine the temporal trends of BRI, identify associated risk factors, and investigate the longitudinal associations between BRI and cardiovascular disease (CVD) outcomes. BRI was calculated using height and waist circumference measurements. Temporal trends and risk factors were analyzed cross-sectionally, while longitudinal associations were examined using Cox proportional hazards models adjusted for confounders. Mediation analyses were conducted to assess the role of intermediate factors such as hypertension and diabetes in the relationship between BRI and CVD.

A total of 12,902 participants were included for risk factor analysis, 10,525 for longitudinal analysis, and 7,310 for cumulative analysis. BRI continued to rise slowly across survey cycles but was higher in women, older adults, and urban residents. Multivariable analysis identified age, alcohol consumption, elevated blood pressure, and diabetes as positive predictors of BRI, while male sex, rural residence, and smoking were negatively associated. Higher baseline BRI was significantly associated with increased CVD risk (HR: 1.44, 95% CI: 1.22-1.69), stroke (HR: 1.49, 95% CI: 1.12-1.98), and heart disease (HR: 1.47, 95% CI: 1.22-1.77). Cumulative BRI similarly predicted increased risks of CVD, stroke, and heart disease. Mediation analysis showed that hypertension accounted for 20.69% of the association between BRI and CVD risk.

BRI is a robust predictor of CVD risk. Targeting hypertension and other metabolic conditions could mitigate the elevated CVD risk associated with high BRI in Chinese adults. These findings underscore the importance of incorporating BRI into public health strategies to better manage obesity-related health risks in China.

Overweight and obesity pose a huge burden on individuals and society. While the relationship between lifestyle factors and overweight and obesity is well-established, the relative contribution of specific lifestyle factors remains unclear. To address this gap in the literature, this study utilizes interpretable machine learning methods to identify the relative importance of specific lifestyle factors as predictors of overweight and obesity in adults.

Data were obtained from 46,057 adults in the China Health and Nutrition Survey (2004-2011) and the National Health and Nutrition Examination Survey (2007-2014). Basic demographic information, self-reported lifestyle factors, including physical activity, macronutrient intake, tobacco and alcohol consumption, and body weight status were collected. Three machine learning models, namely decision tree, random forest, and gradient-boosting decision tree, were employed to predict body weight status from lifestyle factors. The SHapley Additive exPlanation (SHAP) method was used to interpret the prediction results of the best-performing model by determining the contributions of specific lifestyle factors to the development of overweight and obesity in adults.

The performance of the gradient-boosting decision tree model outperformed the decision tree and random forest models. Analysis based on the SHAP method indicates that sedentary behavior, alcohol consumption, and protein intake were important lifestyle factors predicting the development of overweight and obesity in adults. The amount of alcohol consumption and time spent sedentary were the strongest predictors of overweight and obesity, respectively. Specifically, sedentary behavior exceeding 28-35 h/week, alcohol consumption of more than 7 cups/week, and protein intake exceeding 80 g/day increased the risk of being predicted as overweight and obese.

Pooled evidence from two nationally representative studies suggests that recognizing demographic differences and emphasizing the relative importance of sedentary behavior, alcohol consumption, and protein intake are beneficial for managing body weight status in adults. The specific risk thresholds for lifestyle factors observed in this study can help inform and guide future research and public health actions.

Cardiovascular diseases (CVDs) are a major cause of death globally, and minority communities are at higher risk of chronic health outcomes. A combination of lifestyle, including physical activity (PA), good nutrition, and reduced stress, can improve life expectancy. This study aimed to analyze the association between CVDs and PA among the adult population (N = 3,956) based on the World Health Organization (WHO) STEPwise Approach to Surveillance (STEPS) survey in Afghanistan. Descriptive statistics, logistic regression, and spatial analytical techniques were used to analyze the data. Based on the WHO STEPS data, the computed prevalence of CVDs, obesity, hypertension, diabetes, and high cholesterol were 7.41%, 45.57%, 34.06%, 9.51%, and 12.16%, respectively. Multivariate logistic analysis indicated that moderate work-related PA was associated with higher odds of CVDs and high cholesterol while inversely associated with obesity. Moderate leisure-related PA was positively associated with obesity. Vigorous leisure-related PA was associated with lower risks of CVDs, obesity, and high cholesterol but had a positive association with hypertension. Spatial analysis revealed a CVD hotspot in the southern region and the risk factors clustered in the northern region. These findings offer valuable insights for community and public health practitioners to design targeted interventions for reducing the burden of CVDs and risk factors in communities in developing countries.

Sleep problems increase the risk of premature illness and death. We evaluated the association between sedentary time and sleep disturbances.

A cross-sectional analysis of the US nationally representative data of 21,414 adults (aged > = 18 years) from National Health and Nutrition Examination Survey (NHANES) (2005-2014) was performed. The data of sleep disturbances were assessed using NHANES questionnaire results, which included the question, "{Have you/has sp} ever been told by a doctor or other health professional that {you have/s/he has} a sleep disorder?". All participants were stratified by quartiles of sedentary behavior distribution, which was the explanatory variable (sedentary time quartile cut points: Q1, 0 < = Q1 < 3 h; Q2, 3 < = Q2 < 5 h; Q3, 5 < = Q3 < 8 h; Q4, 8 < = Q4 < 20 h). We used multivariable logistic regression and the restricted cubic splines (RCS) model to assess the relationship between sedentary time and sleep disturbances.

In the unadjusted multivariable logistic regression model (crude model), there was a demonstrated tendency for the odds of sleep disturbances to increase with the sedentary time (Q1 as reference, Q2: OR, 1.31 [95% CI 1.09-1.58] P = 0.005; Q3: OR, 1.62 [95% CI 1.39-1.88] P < 0.001; Q4: OR, 1.75 [95% CI 1.48-2.06] P < 0.001; P for trend < 0.001). In the adjusted model 4, adjustment for gender, age, marital type, education type, race, family poverty index ratio, waist circumference, recreational type, smoke status, drink status, diabetes mellitus status, cardiovascular disease status, sleep duration type, body mass index, the OR in Q2 subgroup didn't significantly increase (Q1 as reference. Q2: OR, 1.18 [95% CI 0.96-1.44] P = 0.1). However, the ORs in Q3 and Q4 (Q3: OR, 1.35 [95% CI 1.14-1.59] P < 0.001; Q4: OR, 1.45 [95% CI 1.21-1.75] P < 0.001) both revealed that the risk of sleep disturbances increased with increasing sedentary time, P for trend < 0.001. The unadjusted RCS model revealed that the risk of sleep disturbances increased non-linearly with increasing sedentary time for total participants (P for non-linearity < 0.001). After adjusting for all covariates, the RCS results revealed that the risk of sleep disturbances increased non-linearly with increasing sedentary time for total participants (P for non-linearity = 0.012).

This study suggested that the longer sedentary time was strongly associated with the sleep disturbances. The protective effect of recreational activities on sleep disturbance, has not been significantly demonstrated.

The objective of the present study is to analyze the urinary metabolome profile of patients with obesity and overweight and relate it to different obesity profiles. This is a prospective, cross-sectional study in which patients with a body mass index (BMI) ≥25 kg/m were selected. Anthropometric data were assessed by physical examination and body composition was obtained by bioimpedance (basal metabolic rate, body fat percentile, skeletal muscle mass, gross fat mass and visceral fat). Urine was collected for metabolomic analysis. Patients were classified according to abdominal circumference measurements between 81 and 93, 94 and 104, and >104 cm; visceral fat up to 16 kilos and less than; and fat percentiles of <36%, 36-46% and >46%. Spectral alignment of urinary metabolite signals and bioinformatic analysis were carried out to select the metabolites that stood out. NMR spectrometry was used to detect and quantify the main urinary metabolites and to compare the groups. Seventy-five patients were included, with a mean age of 38.3 years, and 72% females. The urinary metabolomic profile showed no differences in BMI, abdominal circumference and percentage of body fat. Higher concentrations of trigonelline (p = 0.0488), sarcosine (p = 0.0350) and phenylalanine (p = 0.0488) were associated with patients with visceral fat over 16 kg. The cutoff points obtained by the ROC curves were able to accurately differentiate between patients according to the amount of visceral fat: sarcosine 0.043 mg/mL; trigonelline 0.068 mg/mL and phenylalanine 0.204 mg/mL. In conclusion, higher visceral fat was associated with urinary levels of metabolites such as sarcosine, related to insulin resistance; trigonelline, related to muscle mass and strength; and phenylalanine, related to glucose metabolism and abdominal fat. Trigonelline, sarcosine and phenylalanine play significant roles in regulating energy balance and metabolic pathways essential for controlling obesity. Our findings could represent an interesting option for the non-invasive estimation of visceral fat through biomarkers related to alterations in metabolic pathways involved in the pathophysiology of obesity.

Leisure-time physical activity decreases allostatic load, a measure of burden of chronic stress. However, the role of occupational physical activity is unknown. This study examined associations of occupational physical activity and leisure-time physical activity with allostatic load among workers in the U.S.

This cross-sectional study included 6,944 U.S. workers aged 20-64 years from the National Health and Nutrition Examination Survey (2007-2018). Physical activity was assessed using the Global Physical Activity Questionnaire. Allostatic load was calculated using biomarkers of cardiovascular, metabolic, and immune systems. Associations of occupational physical activity and leisure-time physical activity with allostatic load were examined using negative binomial regressions. Analyses were conducted between August 2022 and March 2023.

Vigorous leisure-time physical activity inversely associated with allostatic load among all workers (count ratio=0.68, 95% CI=0.62, 0.76) and in each sex- and age-stratified group as well as in each race/ethnicity-stratified group. Vigorous occupational physical activity positively associated with allostatic load only among females aged 20-44 years (1.38, 95% CI=1.10, 1.73). Inverse associations of vigorous leisure-time physical activity with allostatic load were similar in young females with high or low vigorous occupational physical activity.

Increasing vigorous leisure-time physical activity associates with a lower allostatic load for all workers, whereas increasing vigorous occupational physical activity associates with a higher allostatic load only in young females. Promoting vigorous leisure-time physical activity reduces allostatic load among young females with either low or high vigorous occupational physical activity.

Muscle quality index (MQI) is an emerging health indicator obtained by dividing handgrip strength by body mass index (BMI) that needs to be studied in morbidly obese patients (defined by BMI ≥ 35 kg/m²).

To determine the association between MQI, metabolic syndrome (MetS) markers, and cardiorespiratory fitness (CRF), and as a second objective to determine the potential mediation role of MQI in the relationship between abdominal obesity and systolic blood pressure (SBP) in this sample.

This cross-sectional study included 86 severely/morbidly obese patients (age = 41.1 ± 11.9 y, nine men). MQI, metabolic syndrome markers, CRF, and anthropometric parameters were measured. Two groups were developed according to MQI; High-MQI (n = 41) and Low-MQI (n = 45).

The Low-MQI group reported higher abdominal obesity (High-MQI: 0.7 ± 0.1 vs. Low-MQI: 0.8 ± 0.1 WC/height; p = 0.011), SBP (High-MQI: 133.0 ± 17.5 vs. Low-MQI: 140.1 ± 15.1 mmHg; p = 0.048), and lower CRF (High-MQI; 26.3 ± 5.9 vs. Low-MQI; 22.4 ± 6.1 mL/kg/min, p = 0.003) than the High-MQI group. Waist-to-height ratio (β: -0.07, p = 0.011), SBP (β: -18.47, p = 0.001), and CRF (β: 5.21, p = 0.011) were linked to MQI. In a mediation model, the indirect effect confirms that MQI is a partial mediator of the association between abdominal obesity with SBP.

MQI in morbidly obesity patients reported an inverse association with MetS markers and a positive association with CRF (VO2_max). It mediates the relationship between abdominal obesity and SBP.

Background: This study examined the association between sedentary behavior, sleep duration, breakfast skipping, and abdominal obesity among postmenopausal women in South Korea. Materials and Methods: A total of 7,270 postmenopausal women were included in this cross-sectional, secondary analysis study, using a nationally representative dataset from the Korea National Health and Nutrition Examination Survey. Results: Sleep duration of fewer than 5 hours/day was associated with an increased risk of abdominal obesity (odds ratio [OR] = 1.29; 95% confidence interval [CI], [1.02-1.63]), compared to sleep duration of 6-8 hours/day after controlling for covariates. Additionally, breakfast skipping was associated with an increased risk of abdominal obesity (OR = 1.45; 95% CI [1.02-2.06]), compared to breakfast eating after covariate adjustment. There was no significant association between sedentary behavior and abdominal obesity. Conclusions: The findings of this study demonstrate that special consideration should be given to behavior modification strategies to improve sleep duration and decrease breakfast skipping to decrease the risk of abdominal obesity in postmenopausal women.

Cardiovascular disease (CVD) is the leading cause of morbidity and mortality globally. A physically active lifestyle can improve the health-related quality of life (HRQoL) of people with CVD. Nevertheless, adherence to a physically active lifestyle is poor. This study examined the longitudinal (pre-event, 6-, 12-, 24-, and 36-month follow-ups) physical activity profiles in 275 patients (mean age = 57.1 years; SD = 7.87; 84% men) after the first acute coronary event. Moreover, it investigated the associations among physical activity, sense of coherence (SOC), and HRQoL. Physical activity profiles were identified through latent class growth analysis, and linear regressions were then performed to explore the association between physical activity, SOC, and HRQoL. After the cardiovascular event, 62% of patients reached adequate physical activity levels and maintained them over time (virtuous profile). The remaining 38% could not implement (23%) or maintain (15%) a healthy behavior. A strong SOC at baseline (standardized β = 0.19, p = 0.002) predicted the probability of belonging to the virtuous profile. Moreover, a strong SOC at baseline (standardized β = 0.27, p < 0.001), together with the probability of belonging to the virtuous profile (standardized β = 0.16, p = 0.031), predicted a better HRQoL at the final follow-up. Findings showed a strong relationship between SOC, the ability to adopt a physically active lifestyle stably over time, and HRQoL in patients with CVD. They suggest the importance of tailoring physical activity interventions by promoting resilience resources such as SOC to improve patients’ quality of life after an acute coronary event.

The aim of this study was to investigate how early-life exposure to famine affected the development of overweight, general obesity and abdominal obesity in Chinese adults.

This study was a 22-year cohort study.

Data were derived from the China Health and Nutrition Survey, which is a national prospective cohort study. All participants born between 1949 and 1966 were potentially eligible. Height, weight and waist circumference (WC) were measured by trained healthcare workers. Height and weight were used to calculate body mass index, which was used to define general obesity and WC was used to define abdominal obesity. Exposure to famine was defined using the birth date as follows: no exposure (participants born between 1962 and 1966); fetal exposure (participants born between 1959 and 1961); early childhood exposure (participants born between 1956 and 1958); mid-childhood exposure (participants born between 1953 and 1955); and late childhood exposure (participants born between 1949 and 1952).

In total, 6957 participants were included in this study. Results indicate that exposure to famine was linked to a lower risk of being overweight. Exposure to famine in mid-childhood decreased the risk of general obesity in both males (hazard ratio [HR] 0.485, 95% confidence interval [CI] 0.292-0.807 [P = 0.005]) and females (HR 0.426, 95% CI 0.256-0.709 [P = 0.001]). Exposure to famine during any period of childhood decreased the risk of abdominal obesity (P < 0.001).

Exposure to famine in early childhood decreased the risk of overweight and abdominal obesity in adulthood; however, exposure to famine only had a weak role in the development of general obesity.

There are well-known racial/ethnic disparities in the prevalence of obesity and physical inactivity, as well as breast cancer risk and survival. However, most of the current scientific evidence that serves as a foundation for nutrition and physical activity guidelines is based on studies conducted in predominantly non-Hispanic White populations. Similarly, exercise, diet, or lifestyle intervention trials for breast cancer prevention and survivorship are scarce in racial/ethnic minority populations. We review the current evidence for racial/ethnic disparities in obesity and breast cancer risk and survival (we are focusing on obesity, because this is considered an ASCO priority, and studies conducted in the United States), discuss the evolution of nutrition/physical activity guidelines for cancer prevention and control, and provide an overview of lifestyle interventions, including barriers and facilitators in implementation and dissemination science among minority populations underrepresented in research. There is a critical need to include racially/ethnically diverse populations in cancer prevention and control research or to specifically target minority populations in which disparities are known to exist to achieve much needed health equity.