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Objective To investigate the relationship between nonalcoholic fatty liver disease (NAFLD) and various obesity indicators, as well as to investigate their predictive value for NAFLD. Methods A total of 3 102 participants who underwent health examinations from April to August 2023 at the Xinshi Street Community Health Service Center in Baiyun District, Guangzhou, and the Junan Community Health Service Center in Shunde District, Foshan, were selected and divided into NAFLD and non-NAFLD groups. Logistic regression analysis was employed to examine the relationship between body mass index (BMI), weight-adjusted waist index (WWI), waist-height ratio (WHtR), waist circumference (WC), and NAFLD. Receiver operating characteristic (ROC) curves were used to evaluate the predictive ability of individual and combined obesity indicators for NAFLD. Results The prevalence of NAFLD in this study was 34.9%. All obesity indicators in the NAFLD group were significantly higher than those in the non-NAFLD group (all P<0.001). Multivariate logistic regression results indicated that all obesity indicators were associated with the risk of NAFLD (all P<0.05). ROC curve analysis showed that each obesity indicator could predict the risk of NAFLD (AUC>0.5 for all). Among females, BMI exhibited the best predictive power (P<0.05), while the AUC values for BMI (overall population) and WC (males) were slightly higher than those for the other three indicators, though without statistical significance (P>0.05). Compared to traditional obesity indicators, WWI did not demonstrate superior predictive power (P<0.05). In all populations, combined indicators showed better predictive efficacy than single obesity indicators (P<0.05), and the AUC value for the combined indicators of BMI and WC was slightly higher in all three populations but did not show significant statistical meaning (P>0.05). Conclusion BMI, WC, WHtR, and WWI are associated with the prevalence of NAFLD. The best predictive indicator for females is BMI. The new indicator WWI do not show better predictive ability compared to traditional obesity indicators across the three populations. Combined indicators demonstrate better predictive efficacy than single indicators. [ABSTRACT FROM AUTHOR]

BackgroundThe association between obesity indicators and sleep quality remains unclear among elderly Chinese people. Therefore, we aimed to assess this association by utilizing data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS).MethodsA total of 10,505 participants aged 65 and above from the 2018 CLHLS were included. Calculate body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR) and weight-adjusted-waist index (WWI) based on measured weight, height, and waist circumference. Based on BMI values, individuals were classified as underweight (

Abstract Background Cardiovascular disease (CVD) is closely associated with the triglyceride glucose (TyG) index and its related indicators, particularly its combination with obesity indices. However, there is limited research on the relationship between changes in TyG-related indices and CVD, as most studies have focused on baseline TyG-related indices. Methods The data for this prospective cohort study were obtained from the China Health and Retirement Longitudinal Study. The exposures were changes in TyG-related indices and cumulative TyG-related indices from 2012 to 2015. The K-means algorithm was used to classify changes in each TyG-related index into four classes (Class 1 to Class 4). Multivariate logistic regressions were used to evaluate the associations between the changes in TyG-related indices and the incidence of CVD. Results In total, 3243 participants were included in this study, of whom 1761 (54.4%) were female, with a mean age of 57.62 years at baseline. Over a 5-year follow-up, 637 (19.6%) participants developed CVD. Fully adjusted logistic regression analyses revealed significant positive associations between changes in TyG-related indices, cumulative TyG-related indices and the incidence of CVD. Among these changes in TyG-related indices, changes in TyG-waist circumference (WC) showed the strongest association with incident CVD. Compared to the participants in Class 1 of changes in TyG-WC, the odds ratio (OR) for participants in Class 2 was 1.41 (95% confidence interval (CI) 1.08–1.84), the OR for participants in Class 3 was 1.54 (95% CI 1.15–2.07), and the OR for participants in Class 4 was 1.94 (95% CI 1.34–2.80). Moreover, cumulative TyG-WC exhibited the strongest association with incident CVD among cumulative TyG-related indices. Compared to the participants in Quartile 1 of cumulative TyG-WC, the OR for participants in Quartile 2 was 1.33 (95% CI 1.00–1.76), the OR for participants in Quartile 3 was 1.46 (95% CI 1.09–1.96), and the OR for participants in Quartile 4 was 1.79 (95% CI 1.30–2.47). Conclusions Changes in TyG-related indices are independently associated with the risk of CVD. Changes in TyG-WC are expected to become more effective indicators for identifying individuals at a heightened risk of CVD.

Background: Cardiovascular disease (CVD) is closely associated with the triglyceride glucose (TyG) index and its related indicators, particularly its combination with obesity indices. However, there is limited research on the relationship between changes in TyG-related indices and CVD, as most studies have focused on baseline TyG-related indices. Methods: The data for this prospective cohort study were obtained from the China Health and Retirement Longitudinal Study. The exposures were changes in TyG-related indices and cumulative TyG-related indices from 2012 to 2015. The K-means algorithm was used to classify changes in each TyG-related index into four classes (Class 1 to Class 4). Multivariate logistic regressions were used to evaluate the associations between the changes in TyG-related indices and the incidence of CVD. Results: In total, 3243 participants were included in this study, of whom 1761 (54.4%) were female, with a mean age of 57.62 years at baseline. Over a 5-year follow-up, 637 (19.6%) participants developed CVD. Fully adjusted logistic regression analyses revealed significant positive associations between changes in TyG-related indices, cumulative TyG-related indices and the incidence of CVD. Among these changes in TyG-related indices, changes in TyG-waist circumference (WC) showed the strongest association with incident CVD. Compared to the participants in Class 1 of changes in TyG-WC, the odds ratio (OR) for participants in Class 2 was 1.41 (95% confidence interval (CI) 1.08–1.84), the OR for participants in Class 3 was 1.54 (95% CI 1.15–2.07), and the OR for participants in Class 4 was 1.94 (95% CI 1.34–2.80). Moreover, cumulative TyG-WC exhibited the strongest association with incident CVD among cumulative TyG-related indices. Compared to the participants in Quartile 1 of cumulative TyG-WC, the OR for participants in Quartile 2 was 1.33 (95% CI 1.00–1.76), the OR for participants in Quartile 3 was 1.46 (95% CI 1.09–1.96), and the OR for participants in Quartile 4 was 1.79 (95% CI 1.30–2.47). Conclusions: Changes in TyG-related indices are independently associated with the risk of CVD. Changes in TyG-WC are expected to become more effective indicators for identifying individuals at a heightened risk of CVD. [ABSTRACT FROM AUTHOR]

Abstract Background The association between obesity indicators and mortality in individuals with diabetes remains unclear, and data on cardiovascular mortality are scarce. Therefore, we investigated the associations between the five adiposity indices and both all-cause and cardiovascular mortality in patients with diabetes. Methods This cohort study included 34,686 adults with diabetes who underwent a standard health-screening program between 1996 and 2017 in Taiwan. The dates and causes of death till January 2022 were retrieved from the National Death Registry. Cox proportional hazards models were used to calculate the hazard ratios (HR) and 95% confidence intervals (CI) for all-cause and cardiovascular mortality in relation to body mass index (BMI), waist circumference, waist-hip ratio (WHR), body fat percentage (BF%), and A Body Shape Index (ABSI), using the third quintile as the reference group. Results During a median follow-up of 15 years, there were 8,324 deaths, of which 1,748 were attributed to cardiovascular disease. After adjusting for demographics, lifestyle factors and comorbidities, ABSI was associated with all-cause mortality in an exposure-response manner; the HR (95% CI) for first and fifth vs. third quintile was 0.78 (0.69–0.89) and 1.24 (1.14–1.35), respectively. A similar but weaker exposure-response relationship was found between WHR and mortality. People with a lower BMI and BF% had an increased risk of mortality (HR [95% CI] for the first vs. third quintiles, 1.33 [1.22, 1.44] and 1.42 [1.30, 1.56], respectively). No association was observed between waist circumference categories and risk of mortality. Similar results were observed for the association of BF%, waist circumference, and ABSI with cardiovascular mortality. However, no significant association was observed between BMI and cardiovascular mortality. The association between WHR and cardiovascular mortality was stronger than that between WHR and all-cause mortality. Conclusions ABSI demonstrated a consistent exposure-response relationship with both all-cause and cardiovascular mortality in this Asian cohort with diabetes. Our findings highlight the importance of monitoring ABSI, a surrogate index of central adiposity, in patients with diabetes.

The purpose of this research was to evaluate the lipid accumulation product (LAP)'s accuracy and predictive value for identifying metabolic syndrome (MS) in the general Chinese population compared with other obesity indicators. Baseline survey information from a population-based cohort study carried out in Shanghai's Songjiang District was used in this research. Odds ratios (OR) and a 95% confidence interval (CI) were obtained by logistic regression. The ability of each variable to detect MS was assessed using the receiver operating characteristic curve (ROC). The optimum cut-off point for each indicator was selected using Youden's index. The survey involved 35,446 participants in total. In both genders, the prevalence of MS rose as the LAP increased (p < 0.001). The LAP's AUC was 0.901 (95%CI: 0.895–0.906) in males and 0.898 (95%CI: 0.893–0.902) in females, making it substantially more predictive of MS than other variables (BMI, WC, WHR, WHtR). The optimal cutoff point of the LAP for men and women was 36.04 (Se: 81.91%, Sp: 81.06%) and 34.95 (Se: 80.93%, Sp: 83.04%). The Youden index of the LAP was 0.64 for both sexes. Our findings imply that the LAP, compared to other obesity markers in China, is a more accurate predictor of MS. [ABSTRACT FROM AUTHOR]

Background: Nutritional interventions such as the planetary health diet, which the EAT-Lancet commission proposed, may be an effective strategy for reducing type 2 diabetes risks and its associated complications. The planetary health diet demonstrates the significant role of diet in associating human health with environmental sustainability and the significance of transforming food systems in order to ensure that the UN's Sustainable Development Goals and the Paris Agreement are achieved. Therefore, the aim of this review is to examine the association of the planetary health diet (PHD) with the risk of type 2 diabetes and its related complications. Method: The systematic review was conducted in line with established guidelines. The searches were carried out in health sciences research databases through EBSCOHost. The population, intervention, comparator and outcomes framework was used in order to define the research question and the search terms. The searches were carried out from the inception of the databases to 15 November 2022. Search terms including synonyms and medical subject headings were combined using Boolean operators (OR/AND). Results: Seven studies were included in the review and four themes were identified, including incidence of diabetes; cardiovascular risk factors and other disease risks; indicators of obesity and indicators of environmental sustainability. Two studies examined the association between the PHD and the incidence of type 2 diabetes and found that high adherence to the reference diet (EAT-Lancet reference diet) was correlated with a lower incidence of type 2 diabetes. High adherence to the PHD was also associated with some cardiovascular risk factors and environmental sustainability. Conclusion: This systematic review has shown that high adherence to the PHD is associated with a reduced risk of type 2 diabetes and may be associated with a lower risk of subarachnoid stroke. In addition, an inverse relationship was found between adherence to the PHD and markers of obesity and environmental sustainability. Adherence to the reference diet was also associated with lower values of some markers of cardiovascular risk. More studies are needed to fully examine the relationship between the planetary health diet, type 2 diabetes and its related conditions. [ABSTRACT FROM AUTHOR]

Background: The association between obesity indicators and sleep quality remains unclear among elderly Chinese people. Therefore, we aimed to assess this association by utilizing data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS)., Methods: A total of 10,505 participants aged 65 and above from the 2018 CLHLS were included. Calculate body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR) and weight-adjusted-waist index (WWI) based on measured weight, height, and waist circumference. Based on BMI values, individuals were classified as underweight (<18.5 kg/m 2 ), normal weight (18.5-23.9 kg/m 2 ) and overweight or obesity (BMI ≥24 kg/m 2 ). In the survey, sleep quality was rated in a 5-point format ("1 = very good," "2 = good," "3 = fair," "4 = poor," or "5 = very poor"), and we categorized "1" and "2" as good sleep quality and "3," "4," and "5" as poor sleep quality. Logistic regression models were used to evaluate odds ratios (ORs) and 95% confidence intervals (CIs), with subgroup analysis and restricted-cubic-spline (RCS) conducted., Results: The prevalence of poor sleep quality was 47.06%. There are significant differences in obesity indicators and other factors between the two groups of people with good sleep and poor sleep. After adjusting for potential confounding factors (including demographics, socioeconomic status, lifestyle behaviors, health-related issues and activities of daily living), our analyses revealed significant negative associations of BMI [OR 0.96 (95% CI 0.95-0.98)], WC [OR 0.99 (95% CI 0.98-0.99)] and WHtR [OR 0.18 (95% CI 0.09-0.35)] with poor sleep quality. RCS regression also showed that BMI, WC, WHtR and WWI were all strongly negatively correlated with poor sleep quality., Conclusions: In elderly Chinese people, overweight/obese elderly people may have a better sleep quality compared to elderly people with normal weight, while underweight elderly people are unfavorable for sleep quality., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Liang, Jin, Huang and Chen.)

Aims: To explore the association between decreased levels of particulate matter (≤2.5 µm; PM2.5) due to the implementation of environmental protection policies and the incidence of obesity in adolescents in Chongqing, China through a prospective cohort study. Methods: A total of 2105 children (52.02% male; aged 7.33 ± 0.60 years at baseline) were enrolled from the Chongqing Children’s Health Cohort. A mixed linear regression model was used to analyse the relationships of PM2.5 levels with obesity indicators after adjusting for covariates. Additionally, a Poisson regression model was used to determine the relationship between PM2.5 exposure and the incidence of overweight/obesity. Results: The average PM2.5 exposure levels from participant conception to 2014, from 2015 to 2017, and from 2018 to 2019 were 66.64 ± 5.33 μg/m3, 55.49 ± 3.78 μg/m3, and 42.50 ± 1.87 μg/m3, respectively; these levels significantly decreased over time (P

Background: There is still controversy surrounding the precise characterization of prediabetic population. We aim to identify and examine factors of demographic, behavioral, clinical, and biochemical characteristics, and obesity indicators (anthropometric characteristics and anthropometric prediction equation) for prediabetes according to different definition criteria of the American Diabetes Association (ADA) in the Chinese population. Methods: A longitudinal study consisted of baseline survey and two follow-ups was conducted, and a pooled data were analyzed. Prediabetes was defined as either impaired fasting glucose (IFG), impaired glucose tolerance (IGT), or elevated glycosylated hemoglobin (HbA1c) according to the ADA criteria. Robust generalized estimating equation models were used. Results: A total of 5,713 (58.42%) observations were prediabetes (IGT, 38.07%; IGT, 26.51%; elevated HbA1c, 23.45%); 9.66% prediabetes fulfilled all the three ADA criteria. Among demographic characteristics, higher age was more evident in elevated HbA1c [adjusted OR (aOR)=2.85]. Female individuals were less likely to have IFG (aOR=0.70) and more likely to suffer from IGT than male individuals (aOR=1.41). Several inconsistency correlations of biochemical characteristics and obesity indicators were detected by prediabetes criteria. Body adiposity estimator exhibited strong association with prediabetes (D10: aOR=4.05). For IFG and elevated HbA1c, the odds of predicted lean body mass exceed other indicators (D10: aOR=3.34; aOR=3.64). For IGT, predicted percent fat presented the highest odds (D10: aOR=6.58). Conclusion: Some correlated factors of prediabetes under different criteria differed, and obesity indicators were easily measured for target identification. Our findings could be used for targeted intervention to optimize preventions to mitigate the obviously increased prevalence of diabetes. [ABSTRACT FROM AUTHOR]

In view of the epidemic proportions of obesity in South Africa and its relationship to cardiometabolic diseases, such as hypertension, a cross sectional study was conducted to investigate the utility of obesity indicators for predicting hypertension among older persons (≥60 years, n = 350) in the Limpopo Province of South Africa. The WHO STEPwise approach was used to collect data on demographic and lifestyle factors. Anthropometrics and blood pressure were measured according to the standard procedures. Receiver operating characteristic curves (ROC) were used to investigate and compare the ability of obesity indicators to predict overall hypertension and either increased systolic (SBP) or increased diastolic (DBP) blood pressure. The area under the ROC curve (AUC) was used to assess a certain indicator's potential to predict overall hypertension and either increased SBP or increased DBP. Multivariate logistic regression analysis was used to determine the relationship of hypertension with obesity indicators. The mean age of the participants was 69 years (±SD = 7), and hypertension (46%), general obesity (36%) and abdominal obesity (57%) were prevalent among older persons. The obesity indicator body mass index (BMI) (AUC = 0.603 (0.52; 0.69)) was the best predictor of hypertension in older men. Waist circumference (WC) (AUC = 0.640 (0.56; 0.72)) and waist-to-height ratio (WHtR) (AUC = 0.605 (0.52; 0.69)) were better predictors of hypertension than BMI and waist-to-hip ratio (WHR) in older women. After adjustment for risk factors, only WC (AOR = 1.22 (1.16; 1.79)) was significantly associated with hypertension in older women, proposing WC as a screening tool for the prediction of hypertension in South African older women. [ABSTRACT FROM AUTHOR]

AimsTo explore the effect of long-term exposure to particulate matter with an aerodynamic diameter of 2.5 μm or less (PM2.5) on childhood obesity based on a cohort study in Chongqing.MethodsA total of 4,284 children aged 6–8 years at baseline were enrolled from the Chongqing Children Health Cohort in 2014–2015 and were followed up in 2019. A stratified cluster sampling was applied to select the participants. A Mixed-effects linear regression model was used to examine the effect of long-term exposure to PM2.5 on the growth curve of obesity indicators [including body mass index (BMI), BMI Z-score (BMIz), and waist-to-height ratio (WHtR)]. A mixed-effects logistic regression model was used to study the dose relationship between PM2.5 exposure and the risk of obesity indicators.ResultsA higher level of accumulating exposure to PM2.5 was associated with an increased childhood obesity index, and the effect was the most significant for WHtR than BMI and BMIz. This effect was more pronounced in boys than in girls except for WHtR, and it was the most significant under the PM2.5 exposure period from pregnancy to 6 years old. Compared the annual average PM2.5 exposure level of

Background: Adiposity is an established risk factor for diabetes. The different measurements of adiposity for predicting diabetes have been compared in recent studies in Western countries. However, similar researches among Chinese adults are limited. Methods: Data were collected from a national survey conducted during September 2014 and May 2015 Among Chinese adults aged 40 years and older across 30 China's provinces. Multilevel model analysis was performed to examine the impacts of different obesity indices [body mass index (BMI), waist circumference (WC), lipid accumulation product index (LAP), visceral adiposity index (VAI), and body adiposity index (BAI)] on the risk of diabetes. Results: A total of 162 880 participants were included in this study. Of them, 54.47% were female. With an increase in BMI, WC, LAP, VAI, and BAI, the prevalence of diabetes significantly grew (P < 0.001). The multilevel model analysis showed that WC has the strongest impact on diabetes prevalence, while BAI was the weakest. For one SD increment in BMI, WC, LAP, VAI, and BAI, the prevalence of diabetes increased by 27.0% (Odds Ratio (OR) = 1.270, 95% Confidence interval (CI) = 1.251–1.289), 37.4% (OR = 1.374, 95% CI = 1.346–1.401), 28.1% (OR = 1.281, 95% CI = 1.266–1.297), 22.0% (OR = 1.220, 95% CI = 1.204–1.236), and 17.4% (OR = 1.174, 95% CI = 1.151–1.192), respectively. Conclusion: Obesity indicators of BMI, WC, LAP, VAI, and BAI have significant positive relationships with the risk of diabetes. WC has the strongest impact on diabetes, while BAI has the weakest. [ABSTRACT FROM AUTHOR]

In view of the epidemic proportions of obesity in South Africa and its relationship to cardiometabolic diseases, such as hypertension, a cross sectional study was conducted to investigate the utility of obesity indicators for predicting hypertension among older persons (≥60 years, n = 350) in the Limpopo Province of South Africa. The WHO STEPwise approach was used to collect data on demographic and lifestyle factors. Anthropometrics and blood pressure were measured according to the standard procedures. Receiver operating characteristic curves (ROC) were used to investigate and compare the ability of obesity indicators to predict overall hypertension and either increased systolic (SBP) or increased diastolic (DBP) blood pressure. The area under the ROC curve (AUC) was used to assess a certain indicator’s potential to predict overall hypertension and either increased SBP or increased DBP. Multivariate logistic regression analysis was used to determine the relationship of hypertension with obesity indicators. The mean age of the participants was 69 years (±SD = 7), and hypertension (46%), general obesity (36%) and abdominal obesity (57%) were prevalent among older persons. The obesity indicator body mass index (BMI) (AUC = 0.603 (0.52; 0.69)) was the best predictor of hypertension in older men. Waist circumference (WC) (AUC = 0.640 (0.56; 0.72)) and waist-to-height ratio (WHtR) (AUC = 0.605 (0.52; 0.69)) were better predictors of hypertension than BMI and waist-to-hip ratio (WHR) in older women. After adjustment for risk factors, only WC (AOR = 1.22 (1.16; 1.79)) was significantly associated with hypertension in older women, proposing WC as a screening tool for the prediction of hypertension in South African older women.

Objectives: The objective of this study was to demonstrate the association between changes in different obesity indicators and the risk of incident hypertension by the age-group among community-dwelling residents in southern China. Methods: A total of 6,959 non-hypertensive participants aged ≥18 years old were enrolled in this cohort study and completed questionnaire interviews and anthropometric measurements at baseline (2010) and follow-up (2017). A time-dependent covariate Cox proportional hazard model considered the changes in obesity indicators during the follow-up period and calculated the hazard ratios (HRs) to analyze the risk of incident hypertension according to different obesity indicators. Results: During a mean follow-up of 7.1 years, 1,904 participants were newly diagnosed with hypertension. The body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR) were significantly positively associated with an increased future risk of incident hypertension, and BMI was the best predictive indicator of hypertension (obesity in men: HR = 2.65, 95% confidence interval (CI) = 2.20–3.20; obesity in women: HR = 2.80, 95% CI = 2.27–3.45). Compared with the middle-aged and older group, the risk of incident hypertension was highest in the younger group which had the highest baseline obesity indicators. Conclusions: Changes in obesity indicators were significantly associated with the risk of incident hypertension in all age-groups, and the risk of future incident hypertension increased with the increase in baseline obesity indicators. [ABSTRACT FROM AUTHOR]

Obesity indicators are known to predict the presence of type 2 diabetes mellitus (T2DM); however, evidence for which indicator best identifies undiagnosed T2DM in the Indian population is still very limited. In the present study we examined the utility of different obesity indicators to identify the presence of undiagnosed T2DM and determined their appropriate cut point for each obesity measure. Individuals were recruited from the large-scale population-based Kerala Diabetes Prevention Program. Oral glucose tolerance tests was performed to diagnose T2DM. Receiver operating characteristic (ROC) curve analyses were used to compare the association of different obesity indicators with T2DM and to determine the optimal cut points for identifying T2DM. A total of 357 new cases of T2DM and 1352 individuals without diabetes were identified. The mean age of the study participants was 46⋅4 (sd 7⋅4) years and 62 % were men. Waist circumference (WC), waist:hip ratio (WHR), waist:height ratio (WHtR), BMI, body fat percentage and fat per square of height were found to be significantly higher (P < 0⋅001) among those with diabetes compared with individuals without diabetes. In addition, ROC for WHR (0⋅67; 95 % 0⋅59, 0⋅75), WHtR (0⋅66; 95 % 0⋅57, 0⋅75) and WC (0⋅64; 95 % 0⋅55, 0⋅73) were shown to better identify patients with T2DM. The proposed cut points with an optimal sensitivity and specificity for WHR, WHtR and WC were 0⋅96, 0⋅56 and 86 cm for men and 0⋅88, 0⋅54 and 83 cm for women, respectively. The present study has shown that WHR, WHtR and WC are better than other anthropometric measures for detecting T2DM in the Indian population. Their utility in clinical practice may better stratify at-risk patients in this population than BMI, which is widely used at present.

Obesity indicators are known to predict the presence of type 2 diabetes mellitus (T2DM); however, evidence for which indicator best identifies undiagnosed T2DM in the Indian population is still very limited. In the present study we examined the utility of different obesity indicators to identify the presence of undiagnosed T2DM and determined their appropriate cut point for each obesity measure. Individuals were recruited from the large-scale population-based Kerala Diabetes Prevention Program. Oral glucose tolerance tests was performed to diagnose T2DM. Receiver operating characteristic (ROC) curve analyses were used to compare the association of different obesity indicators with T2DM and to determine the optimal cut points for identifying T2DM. A total of 357 new cases of T2DM and 1352 individuals without diabetes were identified. The mean age of the study participants was 46⋅4 (sd 7⋅4) years and 62 % were men. Waist circumference (WC), waist:hip ratio (WHR), waist:height ratio (WHtR), BMI, body fat percentage and fat per square of height were found to be significantly higher (P < 0⋅001) among those with diabetes compared with individuals without diabetes. In addition, ROC for WHR (0⋅67; 95 % 0⋅59, 0⋅75), WHtR (0⋅66; 95 % 0⋅57, 0⋅75) and WC (0⋅64; 95 % 0⋅55, 0⋅73) were shown to better identify patients with T2DM. The proposed cut points with an optimal sensitivity and specificity for WHR, WHtR and WC were 0⋅96, 0⋅56 and 86 cm for men and 0⋅88, 0⋅54 and 83 cm for women, respectively. The present study has shown that WHR, WHtR and WC are better than other anthropometric measures for detecting T2DM in the Indian population. Their utility in clinical practice may better stratify at-risk patients in this population than BMI, which is widely used at present. [ABSTRACT FROM AUTHOR]

This study evaluated the associations between cardiac autonomic nervous system (ANS) activity and cardiometabolic disease (CMD) risk factors among black South African children. The participants included 34 black South African children (11.85 ± 0.89 y). CMD risk factors included waist circumference (WC), hip circumference (HC), body mass index z-score (BMI z-score), blood pressure (SBP, DBP), total cholesterol (TC), high density lipoprotein cholesterol (HDL), low density lipoprotein cholesterol (LDL), fasting glucose (FG), fasting insulin (FINS), and vessel stiffness index (SI). Heart rate variability was used to quantify cardiac ANS activity. lnRMSSD, pNN50 and lnSD1 were inversely associated with FINS (r = −0.33, p = 0.05; r = −0.36, p = 0.03; r = −0.41, p = 0.01), WC (r = −0.45, p = 0.01; r = −0.39, p = 0.02; r = −0.45, p = 0.01), and HC (r = −0.41, p = 0.01; r = −0.36, p = 0.03; r = −0.43, p = 0.01). HDL was positively associated with lnRMSSD (r = 0.37; p = 0.03) and lnSD1 (r = 0.37; p = 0.03) while, LDL was negatively associated with HF (r = −0.41; p = 0.01). Regression analysis identified WC as the primary predictor for parasympathetic modulation in time domain (lnRMSSD: r2 = 0.21, p = 0.01; pNN50: r2 = 0.18, p = 0.01) and non-linear domain (lnSD1: r2 = 0.21, p = 0.01). Elevated resting parasympathetic activity in children is associated with lower CMD risk factors and an elevation in the protective HDL. [ABSTRACT FROM AUTHOR]

Obesity indicators are useful clinical tools in the measurement of obesity, but it is important for clinicians to appropriately interpret their values in individuals with different ethnicities. Future research is needed to identify optimal cut-offs that can predict the occurrence of cardio-metabolic comorbidities in individuals of different ethnic descent. Assessment of more recently developed indicators like the Edmonton Obesity Staging System and visceral adipose tissue are able to appropriately identify metabolically at-risk individuals. [ABSTRACT FROM AUTHOR]

Background: Obesity is a significant risk factor for metabolic disorders including increase in blood pressure. Body mass index (BMI), waist circumference (WC) and Waist/Hip ratio (WHR) are simple and effective indicators of obe­sity. The objectives of this study were to examine the relationships between obesity anthropometric indicators and hy­pertension and to identify the best anthropometric indicator/s that can predict hypertension risk among youth in the UAE.Methods: A 110 first year students in a Medical University in Ajman, UAE, during the year 2009-2010 were included in a cross-sectional study. The height, weight, WC, hip circumference and blood pressure were measured and the BMI and WHR were calculated for each student and used in the analyses.Results: The mean values for BMI, WC, hip circumference and WHR, were significantly higher in the Pre/Hyperten­sive group compared to normal blood pressure group. The risk of Pre/ hypertension was significantly increased by 4.3 times for participants who had general obesity (BMI³ 30) or abdominal obesity (identified from high WC). Highly sig­nificant correlations were noticed between systolic and diastolic blood pressure and all anthropometric indicators except that for Hip circumference and systolic blood pressure. Step-wise linear regression model showed that when all obesity indicators were studied together, the waist circumference was the only indicator which showed significant relationship with both systolic and diastolic blood pressure.Conclusion: Waist circumference is the best anthropometric indicator that can predict hypertension risk among youth in the UAE.

To explore the association between decreased levels of particulate matter (≤2.5 µm; PM 2.5) due to the implementation of environmental protection policies and the incidence of obesity in adolescents in Chongqing, China through a prospective cohort study. A total of 2105 children (52.02% male; aged 7.33 ± 0.60 years at baseline) were enrolled from the Chongqing Children's Health Cohort. A mixed linear regression model was used to analyse the relationships of PM 2.5 levels with obesity indicators after adjusting for covariates. Additionally, a Poisson regression model was used to determine the relationship between PM 2.5 exposure and the incidence of overweight/obesity. The average PM 2.5 exposure levels from participant conception to 2014, from 2015 to 2017, and from 2018 to 2019 were 66.64 ± 5.33 μg/m3, 55.49 ± 3.78 μg/m3, and 42.50 ± 1.87 μg/m3, respectively; these levels significantly decreased over time (P < 0.001). Throughout the entire follow-up period, the incidence of overweight/obesity after a ≥ 25 μg/m3 decrease in the PM 2.5 level was 4.57% among females; this incidence was the lowest among females who experienced remarkable decreases in PM 2.5 exposure. A 1-µg/m3 decrease in the PM 2.5 level significantly decreased the body mass index (BMI), BMI z score (BMI z), and weight of adolescents (all P < 0.001). Compared with a < 20-μg/m3 decrease in the PM 2.5 level, a ≥ 25-μg/m3 decrease protected against increased BMI (net difference= −0.93; 95% confidence interval [CI]: (−1.23,−0.63) kg/m2), BMI z (−0.28 (−0.39, −0.17)), weight (−1.59 (−2.44, −0.74) kg), and incidence of overweight/obesity (0.48 (0.37, 0.62), P < 0.001). Moreover, compared with a < 20-μg/m3 decrease in the PM 2.5 level, a ≥ 25-μg/m3 decrease resulted in significant absolute differences in BMI (−1.26 (−1.56, −0.96) kg/m2), BMI z (−0.53 (−0.65, −0.40)) and weight (−3.01 (−3.8, −2.19) kg) (all P < 0.001). This study showed the etiological relevance of declining PM 2.5 concentrations for the incidence of obesity in children and adolescents, suggesting that controlling ambient air pollutants may prevent the development of obesity in this age group. Continuous implementation of environmental protection policies in China has led to substantial health benefits. • Environmental control policies in China have achieved remarkable health benefits. • The relationship between the declining PM2.5 level and obesity was illustrated. • Controlling air pollutants may prevent the occurrence of obesity in adolescents. [ABSTRACT FROM AUTHOR]

Summary Introduction In previous study, we found that in order to prevent MS in women aged <65 years, the cutoff points of obesity indicators should be lowered. Objective To investigate whether our proposed cutoff points of obesity indicators predict the occurrence of hypertension (HT), diabetes mellitus (DM), and hyperlipidemia in premenopausal women with greater sensitivity and specificity compared to reference cutoff points of obesity that are currently being used. Methods Using the database of the “2002 Survey on the Prevalence of Hypertension, Hyperglycemia and Hyperlipidemia in Taiwan” provided by the Bureau of Health Promotion, Taiwan as research material, data from 2270 premenopausal women aged 20–65 years were used for the analyses. The receiver-operating characteristic curves (ROC) of the body-mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR) were used to predict HT, DM, and hyperlipidemia. Results Obesity is not a good predictor of the occurrence of hyperlipidemia in premenopausal women aged <65 years. However, our proposed cutoff points had greater sensitivity and specificity than did the reference cutoff points. To prevent the risk of HT and DM in premenopausal women, the cutoff points of obesity indicators should be reduced. The proposed values are as follows: a WHR of 0.79; a WC of 74.7 cm; a WHtR of 0.49; and a BMI of 22.3 kg/m 2 . [ABSTRACT FROM AUTHOR]

Objective: -To evaluate and compare predictor for Diabetes mellitus among anthropometric indicators of obesity (Body Mass Index, Waist circumference and Waist to Hip Ratio). Method: - The present study was conducted among policemen of the Bhavnagar city, total 260 policemen of ≥ 30 years of age included in the study (Response rate 83 %). The fasting and 2 hour postprandial blood glucose test was done for diagnosis of the diabetes and According to American Diabetes Association (2004) criteria subjects was diagnosed as a diabetic, prediabetic (Impaired Fasting Glucose and Impaired Glucose Tolerance) and normoglycemic. BMI, waist circumference and Waist to hip ratio of every subject was measured. Receiver operator characteristic curve was constructed to determine the optimal value of each parameter to diagnose the diabetes and compare the all three anthropometric indicator for predicting the diabetes. Result: Higher area under curve was found with WHR, than WC and lowest with BMI. It was 0.764, 0.751, and 0.611 for WHR, WC and BMI respectively. Optimum cut off points for predicting diabetes are 0.948, 98 cm and 25 for WHR, WC and BMI respectively. Higher Youden index found for WHR and WC than BMI. Conclusion: our study shows that the anthropometric indicators of central obesity (WHR and WC) are better predictive of diabetes mellitus than Anthropometric indicator of general obesity (BMI).

Objective: To investigate the relationship between obesity indicators and dyslipidemia and hypertension in the Yao population of Guangxi., Methods: In 2015, we examined the body composition data of 784 Yao residents aged 18 years or older in Guangxi using a multi-stage whole-group random sampling method, analyzed the association between 10 indicators responding to the degree of obesity and dyslipidemia and hypertension, and analyzed the predictive value of each obesity indicator for dyslipidemia and hypertension by receiver operating characteristic(ROC) curves., Results: There were 58.80% of Yao adults with dyslipidemia, with no difference between men and women(χ~2=0.24, P&gt;0.05); 15.94% of Yao adults had hypertension, with a higher prevalence in men than in women(χ~2=4.76, P&lt;0.05). ROC curves plotted with dyslipidemia as the dependent variable showed that the best predictor of risk of dyslipidemia prevalence in the Yao adult population was waist-to-hip ratio(WHR)(AUC=0.62, 95% CI 0.56-0.68) with a cut point of 0.86 in men and waist circumference(AUC=0.64, 95% CI 0.59-0.69) with a cut point of 75.50 cm in women. The ROC curves were plotted with hypertension as the dependent variable, and the result showed that the best predictor of risk of hypertension in the Yao adult population was: visceral fat content(AUC=0.62, 95% CI 0.56-0.68) with a cut point of 0.65 kg in men and WHR(AUC=0.67, 95% CI 0.62-0.72) with a cut point of 0.82 in women., Conclusion: Compared with indicators reflecting general obesity such as body mass index and percentage of body fat, indicators reflecting abdominal obesity such as waist circumference, WHR and visceral fat content are more closely related to two metabolic diseases such as dyslipidemia and hypertension in the Yao population.

Background: There is still controversy surrounding the precise characterization of prediabetic population. We aim to identify and examine factors of demographic, behavioral, clinical, and biochemical characteristics, and obesity indicators (anthropometric characteristics and anthropometric prediction equation) for prediabetes according to different definition criteria of the American Diabetes Association (ADA) in the Chinese population., Methods: A longitudinal study consisted of baseline survey and two follow-ups was conducted, and a pooled data were analyzed. Prediabetes was defined as either impaired fasting glucose (IFG), impaired glucose tolerance (IGT), or elevated glycosylated hemoglobin (HbA1c) according to the ADA criteria. Robust generalized estimating equation models were used., Results: A total of 5,713 (58.42%) observations were prediabetes (IGT, 38.07%; IGT, 26.51%; elevated HbA1c, 23.45%); 9.66% prediabetes fulfilled all the three ADA criteria. Among demographic characteristics, higher age was more evident in elevated HbA1c [adjusted OR (aOR)=2.85]. Female individuals were less likely to have IFG (aOR=0.70) and more likely to suffer from IGT than male individuals (aOR=1.41). Several inconsistency correlations of biochemical characteristics and obesity indicators were detected by prediabetes criteria. Body adiposity estimator exhibited strong association with prediabetes (D10: aOR=4.05). For IFG and elevated HbA1c, the odds of predicted lean body mass exceed other indicators (D10: aOR=3.34; aOR=3.64). For IGT, predicted percent fat presented the highest odds (D10: aOR=6.58)., Conclusion: Some correlated factors of prediabetes under different criteria differed, and obesity indicators were easily measured for target identification. Our findings could be used for targeted intervention to optimize preventions to mitigate the obviously increased prevalence of diabetes., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Zhu, Yang, He, Hu, Yin, Bai, Li, Cai, Guo, Li, Yan, Li, Shen, Sun, Liu, Sun and Wang.)

Aims: To explore the effect of long-term exposure to particulate matter with an aerodynamic diameter of 2.5 μm or less (PM2.5) on childhood obesity based on a cohort study in Chongqing., Methods: A total of 4,284 children aged 6-8 years at baseline were enrolled from the Chongqing Children Health Cohort in 2014-2015 and were followed up in 2019. A stratified cluster sampling was applied to select the participants. A Mixed-effects linear regression model was used to examine the effect of long-term exposure to PM2.5 on the growth curve of obesity indicators [including body mass index (BMI), BMI Z-score (BMIz), and waist-to-height ratio (WHtR)]. A mixed-effects logistic regression model was used to study the dose relationship between PM2.5 exposure and the risk of obesity indicators., Results: A higher level of accumulating exposure to PM2.5 was associated with an increased childhood obesity index, and the effect was the most significant for WHtR than BMI and BMIz. This effect was more pronounced in boys than in girls except for WHtR, and it was the most significant under the PM2.5 exposure period from pregnancy to 6 years old. Compared the annual average PM2.5 exposure level of <60 μg/m 3 , the WHtR and BMI were increased by 0.019 [(95% CIs): 0.014, 0.024] and 0.326 [(95% CIs): 0.037, 0.616] Kg/m 2 for participants living with the PM2.5 exposure level of 70-75 μg/m 3 , respectively. For every 5 μg/m 3 increase in PM2.5 levels (from pregnancy to 6 years old), the risk of central obesity was increased by 1.26 {odds ratio [OR] (95% CIs): 1.26 (1.16, 1.37), p < 0.001} times., Conclusions: This study confirmed a dose-response relationship between PM2.5 exposure and childhood obesity, especially central obesity, suggesting that controlling ambient air pollution can prevent the occurrence of obesity in children and adolescents., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Tong, Ren, Liu, Liang, Tang, Huang, An and Liang.)

Objective: The global prevalence of obesity is increasing and has nearly doubled in the last decade, disproportionately impacting less-developed countries. The aim of this cross-sectional study was to analyse health-related quality of life (HRQOL) in morbidly obese women attending a bariatric clinic in India, and assess potential obesity indicators that can be utilised in under-resourced settings, to better understand HRQOL of individual patients., Methods: Anthropometric measurements were collected, including waist circumference, hip circumference, waist-hip ratio, waist-height ratio and body mass index (BMI). HRQOL was assessed using an obesity-related quality-of-life questionnaire focused on the impact of obesity on physical distress, self-esteem, sexual life and work life., Results: The average BMI of study participants was 39.6 kg/m2, with an average HRQOL of 40.2%. The strongest correlation was noted between BMI and HRQOL (R2=0.16). Exploratory analyses demonstrated that patients with higher BMI quartiles had lower scores for physical impact and psychosocial impact, and higher scores for sexual health, comfort with food, and experience with dieting compared to patients in lower quartiles., Conclusion: In South Indian, middle-aged, morbidly obese women, HRQOL is lower than average and is highly correlated with BMI, with different BMI levels having higher impacts in different subcategories, supporting the need for an individualised therapeutic focus for each patient., Competing Interests: Disclosures: Shobana Ramasamy, Mini Joseph, Stephen Amarjeet Jiwanmall, Dheeraj Kattula, Munaf Babajan Nandyal, Vijay Abraham, Inian Samarasam, Sandhiya Paravathareddy, Thomas V Paul, Simon Rajaratnam, Nihal Thomas and Nitin Kapoor have no financial or non-financial relationships or activities to declare in relation to this article., (© Touch Medical Media 2020.)