The mediating role of obesity in the relationship between sleep duration and depressive symptoms: A population-based cross-sectional study.

BackgroundProstate cancer (PCa) is the second most common cancer worldwide and a major cause of cancer-related mortality. Although obesity is an established modifiable risk factor for multiple cancer types, conventional anthropometric measures such as body mass index (BMI) fail to capture body fat distribution, particularly visceral adiposity, which is thought to be strongly associated with carcinogenesis. The body roundness index (BRI) is a novel anthropometric metric that provides a more accurate estimation of percent body fat and visceral adipose tissue (VAT) than traditional indices. However, the association between BRI and PCa risk remains unclear in general population-based studies. Therefore, this study aimed to explore the relationship between BRI and PCa.MethodsData from 18,732 male participants (aged ≥20 years) in the 1999–2018 National Health and Nutrition Examination Survey (NHANES) were analyzed. Participants with missing data on PCa status, BRI, or the covariates were excluded. PCa was defined based on self-reported physician diagnosis. BRI was calculated using validated anthropometric formulas. Multivariable logistic regression models assessed the BRI-PCa relationship, adjusting for age, race, education level, marital status, poverty income ratio (PIR), BMI, alcohol use, smoke, hypertension, diabetes, coronary heart disease, stroke, total cholesterol, high-density lipoprotein cholesterol. Restricted cubic spline (RCS) and subgroup analyses evaluated nonlinearity and interaction effects. Receiver operating characteristic (ROC) curves compared BRI’s predictive performance against BMI, waist circumference, and weight.ResultsA higher BRI was significantly associated with increased PCa risk. In fully adjusted models, each 1-unit increase in BRI raised PCa odds by 17% [odds ratio (OR) =1.17, 95% confidence interval (95% CI): 1.06–1.28, P<0.001]. Individuals in the highest BRI quartile exhibited a PCa risk that was four-fold higher than those in the lowest quartile (OR =4.00, 95% CI: 2.32–6.90, P<0.001). RCS analysis revealed a nonlinear positive correlation. Subgroup analyses confirmed consistent associations in all subgroups. Compared with BMI [area under the curve (AUC) =0.509, 95% CI: 0.486–0.533], waist circumference (AUC =0.594, 95% CI: 0.572–0.615) and body weight (AUC =0.488, 95% CI: 0.465–0.512), BRI showed a moderate and significant improvement in the discriminative ability of PCa (AUC =0.608, 95% CI: 0.587–0.630) (P<0.001).ConclusionsAmong the general population in the United States, BRI is independently and positively correlated with the risk of PCa. BRI showed modest but significant improvement in PCa risk discrimination compared to traditional obesity indicators, suggesting its potential as a complementary anthropometric tool that merits validation in prospective studies with clinical endpoints.

The relationship between body roundness index and depression: A cross-sectional study using data from the National Health and Nutrition Examination Survey (NHANES) 2011–2018

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.

Cardiometabolic syndrome (CMS), marked by abdominal obesity and metabolic dysregulation, is associated with a heightened risk of cardiovascular disease (CVD). Compared to the traditional anthropometric predictors represented by body mass index (BMI) and waist circumference (WC), body roundness index (BRI) appears to provide a more accurate reflection of the abdominal fat distribution associated with metabolic diseases. Therefore, this study intends to investigate the association of BRI with the risk of CVD and its components including congestive heart failure (CHF), coronary heart disease (CHD), angina, heart attack, and stroke in patients with CMS. At the same time, we hypothesized that BRI would identify CVD better than BMI or WC. Data from the 2009-2018 National Health and Nutrition Examination Survey (NHANES). Logistic regression models were mainly utilized to evaluate the relationship between BRI and CVD in patients with CMS, including smooth curve analysis, threshold effects analysis, subgroup analysis and multiple imputation. In addition, receiver operating characteristic (ROC) curves were used to assess the ability of BRI to predict CVD. The logistic regression model showed a positive association between the BRI and CVD. The highest quartile of BRI (Q4) showing the strongest association with CVD. The smoothed curve revealed a linear relationship between BRI and CVD, but a U-shaped association between the BRI and CHF. For CVD, stratified analyses did not show significant difference between strata. For CHF, BMI interacted with the association, with BRI being associated with decreased risk of CHF in a subgroup of normal weight subjects and increased risk of CHF in a subgroup of obese subjects. The multiple imputation further confirmed the robustness of these results. Additionally, the ROC curve indicated that BRI, BMI and WC had predictive power for CVD and CHF (AUC > 0.05). BRI has similar predictive power to WC but better than BMI. An elevated BRI is associated with a heightened risk of CVD in patients with CMS. BRI has similar ability to predict CVD and CHF as WC, but superior to BMI.

Health hazards of obesity have been recognized for centuries, appearing, for example, in writings attributed to Hippocrates. From the later decades of the 20th century through the present, there have been numerous epidemiological studies of the relationship between excess weight and the total, or all-cause, mortality rate,1 a critical cumulative measure of the public health impact of any health condition. Using body mass index (BMI), an indicator of relative weight for height (weight [kg]/height [m]2) and a frequently used surrogate for assessment of excess body fat, these studies have found linear, U-shaped, or J-shaped relationships between total mortality and BMI. That is, in some studies, both the thin and the obese were more likely to die than those in between. There is, however, always a point at which increasing BMI is associated with increasing mortality risk, but the BMI at which this occurs varies across studies and populations.2 Currently,3 overweight in adults is defined as a BMI of 25.0 to <30.0 kg/m2 and obesity as a BMI of ≥30.0 kg/m2 (Table 1). A number of studies have found no significant relationship between BMI in the overweight range and mortality rate4 and have shown the nadir of mortality risk to be in the overweight range. In particular, commentaries in both the lay press5–7 and scientific literature2,8,9 subsequent to recent reports from National Health and Nutrition Examination Surveys (NHANES)10,11 have highlighted the confusion and controversy regarding this issue. Some have interpreted the recent data to mean that overweight is not detrimental to health and is not in itself a public health concern and that drawing attention to the need for weight loss in this range will have negative effects on the health and well-being of the general population.8 Others have argued …

Obesity is a risk factor for stroke. The Body Roundness Index (BRI) is a new obesity indicator based on the eccentricity theory and combined with height and waist circumference, which reflects the level of visceral fat more accurately than traditional indicators. However, its association with stroke remains unclear. This study aims to compare the associations of the BRI and body mass index (BMI) with stroke and its prognosis. The data of 29,745 participants in the National Health and Nutrition Examination Survey (NHANES) from 2003 to 2018 were analyzed. Based on weighted logistic regression, weighted COX regression, and restricted cubic spline, the associations of BRI and BMI with the odds of stroke and the risk of all-cause mortality were analyzed; the receiver operating characteristic (ROC) curve and concordance index were used to evaluate the performance of BRI and BMI in predicting stroke and Survival outcome. After adjusting for all confounding factors, weighted logistic regression and weighted Cox regression respectively showed that both BRI (odds ratio [OR]: 1.06, 95% confidence interval [CI]: 1.02-1.10, P = 0.004) and BMI (OR: 1.01, 95%CI 1.00-1.03, P = 0.03) were independently and positively associated with stroke. Meanwhile, both BRI (hazard ratio [HR]: 0.91, 95%CI 0.86-0.98, P = 0.01) and BMI (HR: 0.95, 95%CI 0.92-0.97, P < 0.0001) significantly reduced the risk of all-cause mortality among stroke survivors. The receiver operating characteristic (ROC) curve showed that the area under the curve (AUC) of BRI for predicting stroke was 0.62, while that of BMI was 0.545, and the difference between the two was significant (PDeLong < 0.001). The time-dependent c-index curve demonstrated that BRI and BMI had comparable abilities to predict the risk of all-cause mortality among stroke survivors. Both the BRI and the BMI have verified the obesity and stroke paradox. BRI and the BMI are significantly positively correlated with stroke, and the BRI has a stronger ability to predict stroke than the BMI; however, both the BRI and the BMI are significantly negatively correlated with the prognosis of stroke survivors and have comparable predictive abilities.

ObjectiveObesity has emerged as a worldwide problem. In recent years, it has been verified that there is an association between sleep duration and obesity indicators. This provides a new approach to control obesity. In this study, the relationship between duration of sleep and body mass index (BMI), waist circumference (WC), and waist-to-height ratio (WHtR) among Americans ≥45 years old was investigated.MethodsData was collected from the National Health and Nutrition Examination Survey (NHANES) between 2005 and 2014. The link between sleep duration and obesity indicators was analysed using multiple regression models and weighted smoothed curve fitting. Subgroup analysis was conducted to assess the consistency of the connection between sleep duration and obesity indicators across various groups.ResultsThis study involved 7,118 males and 7,265 females, with an average age of 62.09. After total adjustment, sleep duration was negatively correlated with BMI (β = −0.19, 95%CI: −0.26, −0.12), WC (β = −0.36, 95%CI: −0.53, −0.19) and WHtR (β = −0.27, 95%CI: −0.38, −0.17). Subgroup analyses revealed more significant negative associations between sleep duration and BMI, WC, and WHtR among non-Hispanic White participants, and those without diabetes and hypertension.ConclusionSleep duration was significantly negatively associated with BMI, WC, and WHtR, suggesting that longer sleep duration may contribute to lower obesity indicators in middle-aged and elderly Americans. Subgroup analysis showed that their negative correlation differed between races, diabetes, or hypertension status. However, additional prospective studies are required to validate these findings and investigate potential causal relationships.

BackgroundSeveral studies have indicated a potential association between obesity, depression, and sleep disorders. However, the role of depression in mediating the relationship between obesity and sleep disorders remains unclear. The Body Roundness Index (BRI), a more precise anthropometric measure of obesity than the traditional body mass index (BMI), is particularly effective in assessing body and visceral fat levels. This study examines the relationship between BRI and sleep disorders, with a focus on whether depression influences this association.MethodsThis study included data from 32,504 participants in the National Health and Nutrition Examination Survey (NHANES) 2005–2018 cycle. The association between BRI and sleep disorders was examined through subgroup analysis, restricted cubic spline (RCS) modeling, threshold effect analysis, and multivariable logistic regression. Furthermore, the predictive capabilities of various anthropometric indices—including BRI, weight-adjusted waist index (WWI), BMI, and weight—on sleep disorder incidence were assessed using Receiver Operating Characteristic (ROC) curve analysis. Finally, a Mediation analysis was also performed to explore the potential role of depression in this relationship.ResultsThis study included 32,504 participants, of whom 4,568 reported sleep disorders. After adjusting for all covariates using multivariable logistic regression, each one-unit increase in BRI was associated with a 13% higher prevalence of sleep disorders (OR = 1.13, 95% CI: 1.09, 1.16) and an 8% higher prevalence of depression (OR = 1.08, 95% CI: 1.05, 1.11). Similar results were obtained when BRI was divided into tertiles, with a significant trend (P for trend < 0.05). RCS and threshold effect analyses revealed a nonlinear relationship between BRI and sleep disorder prevalence, with a breakpoint of 3.508. The ROC curve analysis revealed that BRI had a superior predictive capability compared to traditional obesity indices, with an area under the curve (AUC) of 0.637 (95% CI, 0.628–0.645, all P < 0.001). Mediation analysis further indicated that 14% of the association between BRI and sleep disorders was mediated by depression (P < 0.001).ConclusionElevated BRI levels were linked to a higher prevalence of sleep disorders, with depression acting as a partial mediator in this relationship. These findings emphasize the potential connection between obesity, depression, and sleep disorders, highlighting the importance of managing visceral fat to mitigate the risk of sleep disorders.Clinical trial numberNot applicable.

Obesity significantly contributes to declining serum testosterone levels in men, with chronic inflammation being a crucial potential mechanism; Clinical research evidence directly supporting this pathway remains limited. We investigated how obesity relates to serum testosterone in males, with particular attention to the intermediary role of chronic inflammation. Our study included adult males aged ≥20 years from the National Health and Nutrition Examination Surveys (NHANES) conducted from 2011 to 2016 and from 2021 to 2023. Obesity status was assessed with body mass index (BMI), body roundness index (BRI), and waist circumference (WC). Chronic inflammatory status was assessed with an aggregate index of systemic inflammation (AISI), systemic immune-inflammation index (SII), and systemic inflammation response index (SIRI). Multivariable regression assessed associations between obesity metrics and testosterone. The indirect influence of inflammatory indicators was assessed through mediation analysis. Subgroup analyses were performed by weight status. The study comprised 7,418 participants. Multivariable linear regression revealed that obesity (BMI, WC, BRI) was negatively associated with male serum testosterone. Generalized additive models indicated a nonlinear relationship, showing a clear inverse association. Chronic inflammatory status (SII, SIRI, and AISI) mediated the association between obesity and male serum testosterone. In subgroup analyses, the association was consistent with overall findings, but the mediating effect of chronic inflammatory status was statistically significant only in the group with obesity (BRI ≥4.5, WC ≥102 cm, and BMI ≥30 kg/m2). Obesity was inversely associated with serum testosterone in adult males. Chronic inflammatory status may partly explain this association, particularly among individuals with obesity.

BackgroundChronic pain is a prevalent and debilitating condition that poses a major public health burden. Most existing research on obesity and pain has focused on general obesity, typically assessed using body mass index (BMI). However, BMI fails to capture fat distribution and may not adequately reflect metabolic risks associated with pain. Central obesity, characterized by abdominal fat accumulation, has been increasingly recognized as a more relevant predictor of chronic disease, but its relationship with chronic pain remains underexplored in population-based studies.MethodsData from 2,511 adults in the National Health and Nutrition Examination Survey (NHANES) were analyzed. Weighted logistic regression was used to assess the association between anthropometric indexes, including A Body Shape Index (ABSI), Waist Circumference (WC), Body Roundness Index (BRI), and BMI, and chronic pain. Subgroup and sensitivity analyses were conducted to test robustness. Restricted cubic spline (RCS) was applied to examine nonlinear relationships. Receiver operating characteristic (ROC) analysis compared the predictive performance of the anthropometric indicators.ResultsHigher ABSI was significantly associated with increased odds of chronic pain, even after adjusting for a wide range of covariates including BMI (adjusted OR for highest vs. lowest quartile: 1.74; 95% CI: 1.16–2.59; P = 0.010). In contrast, BRI, WC, and BMI were not significantly associated with chronic pain. RCS analysis indicated a linear relationship between ABSI and chronic pain. ROC analysis showed that central obesity indicators (ABSI, BRI, and WC) had better discriminative ability than BMI. Findings were consistent across subgroup and sensitivity analyses.ConclusionCentral obesity, as measured by ABSI, is significantly associated with chronic pain, independent of BMI and other risk factors. These findings highlight the importance of incorporating central obesity indicators into public health and clinical strategies for chronic pain prevention and management.

ObjectiveInfertility is associated with obesity. The Body Roundness Index (BRI) is a body measurement index related to obesity that more accurately assesses body and visceral fat levels. However, the relationship between BRI and infertility remains unclear. Therefore, this study aims to determine the relationship between BRI and infertility.MethodsThis study utilized data from the National Health and Nutrition Examination Survey (NHANES) from 2013 to 2018 and included 3,528 women aged 18–45 years. Multivariate logistic regression was employed to investigate the association between BRI and infertility. Restricted cubic spline (RCS) analysis explored the linear or non-linear relationship between BRI and infertility. Interaction analyses were conducted on subgroups to validate the findings. To verify the robustness of the results, we performed several sensitivity analyses, including propensity score matching(PSM) and multiple imputations for missing data. Furthermore, the predictive capabilities of various anthropometric indices—including BRI, weight-adjusted waist index (WWI), body mass index (BMI), and weight—on infertility incidence were assessed using Receiver Operating Characteristic (ROC) curve analysis.ResultsThere was a significant positive association between BRI and infertility. After adjusting for covariates, for each unit increase in BRI, there was a 12% increase in the probability of infertility (P < 0.001). This positive correlation persisted when BRI was categorized into quartiles. Moreover, as BRI increased, there was a trend towards higher infertility prevalence (P for trend < 0.001). The dose-response curve indicated a linear association between BRI and infertility, with higher BRI associated with higher infertility risk. The correlation between BRI and infertility persisted in subgroup analysis and multiple imputations. The ROC curve analysis revealed that BRI had a superior predictive capability compared to traditional obesity indices, with an area under the curve (AUC) of 0.618 (95% CI, 0.588–0.648).ConclusionThe results of this study show a strong positive correlation between BRI and the prevalence of infertility.Clinical trial numberNot Applicable.

This study aims to investigate the association between high-density lipoprotein cholesterol (HDL-C) and diabetic retinopathy (DR) in adults with diabetes, and to explore the mediating role of body roundness index (BRI). In this cross-sectional study, a total of 1658 participants with diabetes from the National Health and Nutrition Examination Survey (NHANES) 2005-2008 were included. This specific period was selected as the first NHANES cycle to systematically include fundus photography for diabetic retinopathy assessment. The diagnosis of DR was based on fundus images evaluated using the Early Treatment Diabetic Retinopathy Study (ETDRS) severity scale. HDL-C levels were measured using Roche Diagnostics. BRI was calculated based on height and waist circumference. Multivariable logistic regression models were used to assess the relationship between HDL-C and DR, and mediation analysis was performed to evaluate the potential mediating effect of BRI. The fully adjusted model revealed a significant positive association between HDL-C and DR (OR = 2.08 95% CI: 1.34 ~ 3.22, p = 0.007). In subgroup analyses, positive associations between HDL-C and DR were still observed across various subgroups (including gender, race, smoking status, alcohol use, hypertension history, hyperlipidemia, weight status, and age group). Mediation analysis indicated that BRI played a significant mediating role in the relationship between HDL-C and DR, with a mediation effect of 21.51%. Among adults with diabetes in the United States, elevated HDL-C is positively associated with DR, partially mediated through BRI. Not applicable.

Substantial evidence suggests an association between obesity and sleep. However, research investigating sleep patterns in relation to novel anthropometric indices is limited. Therefore, we conducted a cross-sectional analysis of data from the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2014 to examine the relationship between the body roundness index (BRI) and unhealthy sleep patterns. This study aimed to investigate the association between the BRI and unhealthy sleep patterns among US adults. Data were sourced from NHANES (2007-2014), including respondents aged 20 years and older. Participants were categorized into two groups based on the healthiness of their sleep patterns. The data were weighted, and multiple potential covariates were included in the analysis to provide national estimates and account for the comprehensive sampling design. A multivariable weighted logistic regression model was used, employing restricted cubic spline (RCS) curves to examine potential associations, and subgroup analyses were conducted to determine the stability of the results. Receiver operating characteristic (ROC) analysis was used to compare the diagnostic performance of BRI and body mass index (BMI) in identifying unhealthy sleep patterns. In the fully adjusted multivariable logistic regression model, the prevalence odds ratio (POR) for the association between BRI and unhealthy sleep patterns was 1.09, with a 95% confidence interval (CI) of 1.07-1.10. The RCS analysis found that the nonlinear association between BRI and unhealthy sleep patterns was not significant. Subgroup and sensitivity analyses indicated a consistently positive association between high BRI and unhealthy sleep patterns across most subgroups. ROC diagnostic tests showed that BRI's effectiveness in diagnosing unhealthy sleep patterns was comparable to that of BMI, and it was not inferior to BMI in assessing certain components of sleep patterns. High BRI is positively associated with unhealthy sleep patterns significantly, indicating that BRI could be a promising metric for evaluating sleep health.

Sarcopenic obesity is characterized by a combination of obesity and sarcopenia. Body round index (BRI) is a novel anthropometric index that can more accurately assess body and visceral fat levels than body mass index or waist circumference. This study used data from the National Health and Nutrition Examination Survey (NHANES) to explore the relationship between BRI and handgrip strength (HGS) and muscle quality index (MQI) in American adults aged 20 and over. This study used cross-sectional data from the 2011-2014 National Health and Nutrition Examination Survey (NHANES) with complete data on BRI, HGS, and MQI. We used multivariate linear regression models and smooth curve fitting methods to explore the relationship between BRI and HGS and MQI. In addition, subgroup analyses and interaction tests were performed to further analyze the potential association between these variables. A total of 5466 participants were finally included in this study, of whom 2807 were males and 2659 were females. The results showed that BRI was positively correlated with HGS and negatively correlated with MQI. In the fully adjusted model, the negative correlation between BRI and MQI was (β= -0.08, 95% CI = -0.08, -0.07), while the positive correlation with HGS was (β= 0.3 8, 95% CI = 0.29, 0.46), indicating that for every unit increase in BRI, MQI decreases by 0.08 units and HGS increases by 0.38 units (P < 0.0001). In addition, the relationship between BRI and HGS is an L-shaped curve. An inflection point is determined when BRI reaches 3.42. Before this threshold, for every unit increase in BRI, HGS increases significantly (β = 2.19, 95% CI = 1.66, 2.72). The results showed that BRI was positively correlated with HGS and negatively correlated with MQI, meaning that higher BRI was associated with higher HGS and lower MQI. This highlights the importance of body fat distribution in muscle health and suggests that BRI can be used as an effective anthropometric indicator to predict grip strength and muscle mass.

Objective To explore the risk factors for uric acid-lowering therapy-resistant gout (UALT-RG) and its relationships with the estimated glomerular filtration rate (eGFR), body roundness index (BRI), and visceral adiposity index (VAI) via 2007–2018 National Health and Nutrition Examination Survey (NHANES) data. Methods We calculated the BRI using waist circumference and standing height; the VAI using triglycerides (TGs), high-density lipoprotein cholesterol (HDL-C), and body mass index (BMI); and the eGFR from serum creatinine levels. We also collected gout data. We explored the relationships of the eGFR, BRI, and VAI with UALT-RG risk via univariable and multivariable weighted logistic regression, trend analysis, and restricted cubic splines. Results Among the 1,811 patients with gout, ∼9.08% had UALT-RG; these patients were more likely to have obesity, comorbid diabetes (36% [27–47%] vs. 25% [22–28%]) or impaired kidney function (eGFR < 60 mL/min/1.73 m2, 34.5% [27–43%] vs. 22.5% [20–26%]); be former smokers; and take colchicine (10% [5.6–19%] vs. 4.3% [2.8–6.7%]). Logistic regression and trend analysis suggested that an elevated BRI and decreased eGFR were independent risk factors and potential screening indicators for UALT-RG. Restricted cubic spline analysis revealed a negative linear trend between the eGFR and UALT-RG risk (p-overall < 0.0001) and a significant positive correlation between the BRI and UALT-RG risk (p-overall < 0.0001). Conclusion An increased BRI and decreased eGFR may be independent risk factors and assessment indicators for UALT-RG in U.S. adults. It is necessary to monitor serum urate levels more closely and conduct early multidisciplinary comanagement when gout is comorbid with visceral obesity and chronic kidney disease stages 3–5.