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Interethnic differences in the accuracy of anthropometric indicators of obesity in screening for high risk of coronary heart disease.

ABSTRACT: Cut points for defining obesity have been derived from mortality data among Whites from Europe and the United States and their accuracy to screen for high risk of coronary heart disease (CHD) in other ethnic groups has been questioned.To compare the accuracy and to define ethnic and gender-specific optimal cut points for body mass index (BMI), waist circumference (WC) and waist-to-hip ratio (WHR) when they are used in screening for high risk of CHD in the Latin-American and the US populations.We estimated the accuracy and optimal cut points for BMI, WC and WHR to screen for CHD risk in Latin Americans (n=18 976), non-Hispanic Whites (Whites; n=8956), non-Hispanic Blacks (Blacks; n=5205) and Hispanics (n=5803). High risk of CHD was defined as a 10-year risk > or =20% (Framingham equation). The area under the receiver operator characteristic curve (AUC) and the misclassification-cost term were used to assess accuracy and to identify optimal cut points.WHR had the highest AUC in all ethnic groups (from 0.75 to 0.82) and BMI had the lowest (from 0.50 to 0.59). Optimal cut point for BMI was similar across ethnic/gender groups (27 kg/m(2)). In women, cut points for WC (94 cm) and WHR (0.91) were consistent by ethnicity. In men, cut points for WC and WHR varied significantly with ethnicity: from 91 cm in Latin Americans to 102 cm in Whites, and from 0.94 in Latin Americans to 0.99 in Hispanics, respectively.WHR is the most accurate anthropometric indicator to screen for high risk of CHD, whereas BMI is almost uninformative. The same BMI cut point should be used in all men and women. Unique cut points for WC and WHR should be used in all women, but ethnic-specific cut points seem warranted among men.

SUBMITTER: Herrera VM

PROVIDER: S-EPMC2687093 | biostudies-literature | 2009 May

REPOSITORIES: biostudies-literature

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Interethnic differences in the accuracy of anthropometric indicators of obesity in screening for high risk of coronary heart disease.

Herrera V M VM Casas J P JP Miranda J J JJ Perel P P Pichardo R R González A A Sanchez J R JR Ferreccio C C Aguilera X X Silva E E Oróstegui M M Gómez L F LF Chirinos J A JA Medina-Lezama J J Pérez C M CM Suárez E E Ortiz A P AP Rosero L L Schapochnik N N Ortiz Z Z Ferrante D D Diaz M M Bautista L E LE

International journal of obesity (2005) 20090224 5

<h4>Background</h4>Cut points for defining obesity have been derived from mortality data among Whites from Europe and the United States and their accuracy to screen for high risk of coronary heart disease (CHD) in other ethnic groups has been questioned.<h4>Objective</h4>To compare the accuracy and to define ethnic and gender-specific optimal cut points for body mass index (BMI), waist circumference (WC) and waist-to-hip ratio (WHR) when they are used in screening for high risk of CHD in the Lat ...[more]

PMID: 19238159

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Project description:BackgroundPrevious studies have reported an association between obesity and risk of sepsis. However, the results have been inconsistent, and no causal inference can be drawn from them. Therefore, we conducted a Mendelian-randomization (MR) study to investigate causal relationships between available obesity-related anthropometric indicators and sepsis risk.MethodsWe performed MR analyses using genome-wide association study (GWAS) summary statistics on 14 anthropometric indicators [namely body mass index (BMI), waist and hip circumferences (WC, HC), basal metabolic rate (BMR), whole-body fat mass (WBFM), trunk fat mass (TFM), leg fat mass (LFM), arm fat mass (AFM), body fat percentage (BFP), whole-body fat-free mass (WBFFM), trunk fat-free mass (TFFM), leg fat-free mass (LFFM), arm fat-free mass (AFFM), and whole-body water mass (WBWM)], sepsis, critical care sepsis, and 28-day death due to sepsis from the UK Biobank and FinnGen cohort. The primary method of MR analysis was inverse variance-weighted average method. Sensitivity analyses, including heterogeneity and horizontal-pleiotropy tests, were conducted to assess the stability of the MR results. Additionally, we applied multiple-variable MR (MVMR) to evaluate the effect of BMI on the relationship between each anthropometric indicator and sepsis risk.ResultsOur MR analysis demonstrated causal relationships between 14 anthropometric indicators and sepsis of different severities. After we adjusted for BMI, MVMR analyses indicated that WC, BMR, LFM, WBFFM, TFFM, AFFM, and WBWM remained significantly associated with the presence of sepsis (all p < 0.05). A sensitivity analysis confirmed the reliability of our MR results, and no significant horizontal pleiotropy was detected.ConclusionThis MR study revealed that increases in obesity-related anthropometric indicators had causal associations with a higher risk of sepsis, which might provide important insights for the identification of individuals at risk for sepsis in community and hospital settings.

Project description:BackgroundStudies relating obesity to cognition in older people show conflicting results, which may be explained by the choice of obesity indicators.ObjectivesThis study aimed to investigate the relationship between obesity-related indicators and cognitive impairment, especially between different age or gender subgroups, and explore whether obesity-related indicators were related to specific cognitive domains.MethodsThis was a cross-sectional study on 1753 participants aged ≥ 60 years (41.0% men; aged 71.36 ± 5.96 years). Obesity-related indicators included body mass index (BMI), waist circumference (WC), calf circumference (CC), waist to hip ratio (WHR), waist to calf circumstance ratio (WCR), fat to fat-free mass ratio (FM/FFM). The Mini-Mental State Examination scale (MMSE) was used to assess cognitive function. Cognitive impairment was defined as a score ≤ 17 for illiterates, ≤ 20 for participants with primary school education, and ≤ 24 for those with junior high school degrees or above. Multiple logistic regression analysis was used to estimate multivariable-adjusted odds ratios (ORs) and 95% confidence intervals (CIs). Restricted cubic splines were used to analyze and visualize the linear relationships.ResultsThe prevalence of cognitive impairment was 18.77%. In the fully adjusted model, CC was negatively associated with cognitive impairment (OR = 0.94, 95% CI: 0.90-0.98). Further analysis showed that CC correlated positively with recall and place orientation. A higher FM/FFM was found to be associated with a higher prevalence of cognitive impairment (OR: 1.44, 95%CI: 0.88-2.35, P for trend = 0.029); this association was notable in women (P for trend = 0.002) and the oldest (P for trend = 0.009), and so did the potential effect of BMI on cognitive impairment (70-80 years: P for trend = 0.011; ≥ 80 years: P for trend = 0.013). No statistically significant association was found between cognitive impairment and WC, WHR, or WCR.ConclusionCC and FM/FFM were associated with cognitive impairment in older people. Future research needs to distinguish the effects of fat and muscle mass on cognitive function, with special attention to different ages and genders.

Project description:BackgroundTo determine the optimal cut-off values and evaluate the associations of body mass index (BMI), waist circumference (WC) and waist-height ratio (WHtR) with cardiovascular disease (CVD) risk factors.MethodsA large-scale cross-sectional survey was conducted among 35,256 adults aged 20-74 years in Shanghai between June 2016 and December 2017. Receiver operating characteristic (ROC) analyses were conducted to assess the optimal cut-off anthropometric indices of CVD risk factors including hypertension, diabetes, dyslipidemia and hyperuricemia. Multivariate Logistic regression models were preformed to evaluate the odds ratio of CVD risk factors.ResultsThe area under the curve (AUC) of WHtR was significantly greater than that of BMI or WC in the prediction of hypertension and diabetes, and AUCs were higher in women than men. The optimal cut-off values of WHtR were approximately 0.51 in both sexes, while the cut-off values of BMI and WC were higher for men compared with women. The optimal cutoff values of BMI and WC varied greatly across different age groups, but the difference in WHtR was relatively slight. Among women, the optimal threshold of anthropometric indices appeared to increase with age for hypertension and diabetes. The odds ratio between anthropometric indices and CVD risk factors were attenuated with age. WHtR had the greatest odds ratio for CVD risk factors among adults under 60 years old except for women with hypertension, while among 60-74 years, BMI yielded the greatest odds ratio in terms of all CVD outcomes except for women with diabetes.ConclusionsWHtR had the best performance for discriminating hypertension and diabetes and potentially be served as a standard screening tool in public health. The associations between three anthropometric indices and CVD risk factors differed by sex and decreased with age. These findings indicated a need to develop age- and gender-specific difference and make effective strategies for primary prevention of CVDs.

Dataset Information

Interethnic differences in the accuracy of anthropometric indicators of obesity in screening for high risk of coronary heart disease.

Publications

Interethnic differences in the accuracy of anthropometric indicators of obesity in screening for high risk of coronary heart disease.

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