《国民体质测定标准》中肥胖参数与高血压风险关系

目的评价《国民体质测定标准》中肥胖指标与正常偏高血压及高血压风险关系,并确定判定切点,为高血压的预防控制提供参考依据。方法采用分层整群抽样方法对在辽宁省沈阳、丹东、朝阳市3个国民体质监测点抽取的5 809名20～69岁未接受高血压药物治疗的居民进行体格检查。结果 5 809名居民的正常偏高血压率和高血压率分别为16.92%和24.89%,其中男性居民正常偏高血压率和高血压率分别为20.98%和31.57%,均高于女性居民的12.94%和18.33%,差异均有统计学意义(P<0.01);多因素logistic回归分析结果表明,年龄≥40岁和体质指数(BMI)是正常偏高血压的危险因素,女性是正常偏高血压的保护因素;年龄≥30岁、BMI和腰围是高血压的危险因素,女性是高血压的保护因素;控制年龄、性别的影响后,BMI每升高1个标准差,正常偏高血压和高血压的风险分别增大1.38倍(95%CI=1.28～1.50)和1.57倍(95%CI=1.39～1.78);腰围每升高1个标准差,高血压的风险增大1.37倍(95%CI=1.20～1.56);以约登指数最大确定切点,BMI判定正常偏高血压的切点为男性24.0 kg/m2、女性24.3 kg/m2,BMI判定高血压的切点为男性25.1 kg/m2、女性24.3 kg/m2,腰围判定高血压的切点为男性87.0 cm,女性80.6 cm;以灵敏度≥80%确定切点,BMI判定正常偏高血压的切点为男性23.0 kg/m2、女性22.3 kg/m2,BMI判定高血压的切点为男性23.4 kg/m2、女性22.8 kg/m2,腰围判定高血压的切点为男性82.0 cm、女性76.9 cm。结论高血压的风险随BMI及腰围的增加而增大,BMI与高血压的关联强度大于腰围。     

Derivation of anthropometric cut-off levels to define CVD risk in Sri Lankan adults

Obesity is associated with increased cardiovascular risk. Anthropometric cut-off values derived for Caucasians may not be applicable to other populations. The main objective of the present study was to derive population-specific anthropometric cut-off values to define high CVD risk for Sri Lankan adults. A nationally representative sample of 4474 non-institutionalised adults aged ≥?18 years was analysed. Cut-off values to provide optimum sensitivity and specificity were derived using receiver-operating characteristic curve analysis. BMI, waist circumference (WC), waist-to-hip ratio (WHR), blood pressure and overnight fasting venous blood samples were collected to measure glucose, HDL-cholesterol and TAG. An oral glucose tolerance test was also performed. The results suggested that the age-adjusted BMI, WC and WHR were significantly associated with all cardiovascular risk factors (P?相似文献   

Obesity, abdominal obesity, and clustering of cardiovascular risk factors in South Korea

The aim of this study was first, to investigate the prevalence of obesity, abdominal obesity, and clustering of cardiovascular (CVD) risk factors, and secondly, to identify the BMI or waist circumference (WC) level at which clustering increases in South Koreans. A population-based, cross-sectional National Health Examination Survey was carried out in 1998. A total of 8,816 subjects (4,029 men and 4,787 women) aged 15-79 y were selected by stratified multistage probability sampling design. The measurements taken of the subjects included: height, weight, waist and hip circumference, blood pressure, fasting glucose, and lipids. The prevalence of BMI > or = 25 kg/m2 was 25.3% for men and 28.3% for women. The prevalence of WC >90 cm in men, and >80 cm in women was 18.5%, and 38.5%, respectively. Clustering of 3 or more CVD risk factors was 22.7% in men ad 21.7% in women. Using <21 kg/m2; as a referent, subjects with BMI of 23 kg/m2; and 27 kg/m2; had an odds ratio of 3.5 and 10.2 in men, and 3.1 and 6.7 in women, respectively for clustering of CVD risk factors. Using <65 cm as a referent, subjects with a WC of > or = 90 cm in men and > or = 85 cm in women had an odds ratio of 13.4, and 13.6, respectively for clustering of CVD risk factors. Considering the significant associations between clustering of CVD risk factors and BMI or WC, the present study suggests that high prevalence of overweight may have important implications for the health care system, even at a lower level of BMI or WC.     

Evaluation of waist circumference to predict cardiova scular risk factors in an overweight Tehranian population: findings from Tehran Lipid and Glucose Study

This study was conducted to evaluate the waist circumference (WC) cut-off points to predict cardiovascular risk factors in the overweight Tehranian population. Anthropometric measures, blood pressure, and biochemical analyses were evaluated for the 15,005 participants of the Tehran Lipid and Glucose Study. Three thousand sixty-five subjects aged 18-74 years with a body mass index of 25-29.9 were enrolled in this study. Abdominal obesity was defined as WC > or =102 cm for men and > or =88 cm for women. Sensitivity of WC > or =102 cm to detect various cardiovascular risk factors for men aged 35-54 years was between 5% and 14%, and for men aged 55-74 years, was between 12% and 19%. The specificity of this cut-off point was between 93% and 98% and between 86% and 96% for corresponding age-categories, respectively. WC > or =88 cm had a sensitivity of between 28% and 41 % for identifying cardiovascular risk factors in women aged 18-34 years. Sensitivity tended to increase with age and specificity tended to decrease with age in both genders. These cut-off points had the highest positive predictive value for the more prevalent risk factors in both genders. The negative predictive values were different for various risk factors among age groups. The classic cut-off points of WC failed to provide adequate evidence for the use of WC in detecting cardiovascular risk factors. Further studies should be conducted to determine optimal WC cut-off points for Iranians.     

中国成年人代谢异常相关的体质指数和腰围切点研究

目的 研究中国成年人BMI和腰围与各项代谢危险因素之间的相关性,确定超重肥胖的适宜BMI和腰围切点。方法 中国慢性病前瞻性研究于2004-2008年进行基线调查,并于2013-2014年随机抽取了5%的研究对象进行第2次重复调查。本研究剔除体格指标或代谢危险因素变量缺失或极端值、自报患有恶性肿瘤者,基线纳入501 201人,第2次重复调查纳入19 201人。比较不同BMI和腰围下代谢危险因素异常率,通过受试者工作特征（ROC）曲线分析,确定预测高血压、糖尿病、血脂异常和危险因素聚集的适宜BMI和腰围切点。结果 随BMI或腰围的增加,高血压、糖尿病、血脂异常和危险因素聚集患病率均呈现上升的趋势。依据正确指数最大的原则选取BMI超重切点和腰围切点,男性和女性BMI超重切点均接近24.0 kg/m²,男性腰围切点接近85 cm,女性腰围切点约为80~85 cm。男性和女性中,检出各项代谢危险因素特异度达到90%的BMI切点范围为27.0~28.9 kg/m²,多数接近28.0 kg/m²,以28.0 kg/m²作为肥胖切点。结论 本研究在更新开展的大样本调查中进一步验证了中国肥胖问题工作组2002年推荐的超重和肥胖标准,超重和肥胖的BMI切点分别为24.0和28.0 kg/m²;中心性肥胖的腰围适宜切点男性为85 cm,女性为80~85 cm。     

Clothing size as an indicator of adiposity, ischaemic heart disease and cardiovascular risks

OBJECTIVE: To relate subjects' clothing sizes to waist circumference, body mass index (BMI) and to the risks of ischaemic heart disease, hypertension and diabetes mellitus, and to derive cut-off levels of clothing size that correspond to increased health risks. DESIGN: Cross-sectional study. Setting Glasgow Royal Infirmary. PARTICIPANTS: A stratified subsample of 201 men and 161 women aged 27-67 years from the Glasgow monitoring coronary (MONICA) risk factor survey. MAIN OUTCOME MEASURES: Measured waist, weight and height, blood pressure and history of ischaemic heart disease (angina, myocardial infarction or angioplasty), hypertension and diabetes mellitus, and medications. RESULTS: There were 15.5% of men and 11.2% of women with ischaemic heart disease, 14.9% of men and 12.4% of women with hypertension, and 4.5% of men and 3.1% of women with diabetes mellitus. Age and smoking adjusted prevalences of these cardiovascular risks, as well as increased adiposity (waist circumference > or =102 cm in men, > or =88 cm in women or BMI > or = 30 kg m(-2)) rose with increasing clothing size. Clothing size correlated (P < 0.001) linearly with indices of adiposity. Clothing sizes which correspond to waist circumference action level 1 (94 cm in men, 80 cm in women) and action level 2 (102 cm in men, 88 cm in women) or to standardized BMI cut-offs (25 and 30 kg m(-2)) were estimated. Height has minimal influences on clothing size. Compared with men with trouser waist below 36 inches or women with UK dress size below 16, the age and smoking adjusted odds ratios for the risk of having at least one of the major health problems (ischaemic heart disease, hypertension or diabetes mellitus) were 3.9 (95% CI: 1.8-8.3) in men and 7.0 (95% CI: 2.5-19.4) in women who had trouser size > or =38 inches or UK dress size > or =18, respectively. CONCLUSIONS: The present study showed that men and women with large clothing size are at increased risk of ischaemic heart disease, hypertension and diabetes mellitus. Men's trouser size equal or larger than 38 in the UK and USA or 97 in Europe and women's dress size equal or larger than 18 in the UK or 16 in the USA or 48 in Europe could be used to promote self-awareness of increased health risks by the general public.     

不同体重指数和腰围水平与其他心血管病危险因素聚集的关系

目的探讨不同体重指数(BMI)和腰围水平对人群中其他心血管病危险因素聚集的影响.方法将1992～1994年和1998年在我国不同地区中年人群中进行的2次心血管病危险因素调查资料合并共30 561人,比较不同BMI和腰围分组的研究对象其他心血管病危险因素聚集率和聚集的相对危险,其中危险因素聚集定义为同一研究对象具有高血压、高血清总胆固醇、低高密度脂蛋白胆固醇或空腹血糖异常之中的任意2项或2项以上者.结果随着BMI和(或)腰围的增加,人群其他心血管病危险因素的聚集率呈明显上升趋势, 按BMI分层各组中,男女两性腰围与其他心血管病危险因素的聚集率均呈明显的线性上升趋势,同样在不同的腰围分组中,BMI均与其他心血管病危险因素的聚集率呈明显的线性趋势.男性和女性年龄调整心血管病危险因素聚集率在BMI<24 kg/m2、腰围(男/女)<85/80 cm组分别为11.1%和10.4%,BMI<24 kg/m2、腰围(男/女)85～95.9/80～89.9 cm组分别为24.2%和16.9%, BMI 24.0～27.9 kg/m2、腰围(男/女)<85/80 cm组分别为24.0%和17.0%,BMI 24～27.9 kg/m2、腰围(男/女)85～95.9 /80～89.9 cm组分别为34.3%和24.0%. BMI 24.0～27.9 kg/m2、腰围(男/女)≥95/90 cm组分别为40.8%和29.6%,BMI≥28 kg/m2、腰围(男/女)85～95.9/80～89.9 cm组分别为44.2%和29.9%,BMI≥28 kg/m2、腰围(男/女)≥95/90 cm组分别为54.7%和35.4%.结论 BMI和腰围水平均与其他心血管病危险因素的聚集有独立的正相关性.保持BMI和腰围均在正常范围对心血管健康是很重要的.     

Optimal cut-offs of five anthropometric indices and their predictive ability of type 2 diabetes in a nationally representative Kenyan study

BackgroundType 2 diabetes (T2D) is one of the top non-communicable diseases in Kenya and prevention strategies are urgently needed. Intervening to reduce obesity is the most common prevention strategy. However, black populations develop T2D at lower obesity levels and it is unclear which anthropometric cut-offs could provide the best predictive ability for T2D risk. This study, therefore, aimed to determine the optimal anthropometric cut-offs and their predictive ability of T2D in Kenya.MethodsThe study included 2159 participants (59% women) aged 35–70 years from the Kenya STEPwise survey conducted in 2014. Five anthropometric indices were used—body mass index (BMI), waist circumference (WC), waist to hip ratio (WHR), waist to height ratio (WHtR) and waist divided by height^0.5(WHt.5R). Diabetes was defined as a fasting blood glucose of ≥7.0 mmol/l or a previous diagnosis by a health worker. Optimal anthropometric cut-offs and their receiver operating characteristics, such as the area under the curve (AUC), were computed.ResultsOverall, the optimal cut-off for BMI, WC, WHR, WHtR and WHt.5R were 24.8 kg.m⁻², 90 cm, 0.88, 0.54 and 6.9. On disaggregation by sex, the optimal cut-off for BMI, WC, WHR WHtR and WHt.5R was 27.1 kg.m⁻², 87 cm, 0.85, 0.55 and 6.9 in women, and 24.8 kg.m⁻², 91 cm, 0.88, 0.54 and 6.9 in men. Overall, WC (AUC 0.71 (95% confidence interval 0.65, 0.76)) WHtR (AUC 0.71 (0.66, 0.76)) and WHt.5R (AUC 0.70 (0.65,0.75)) had a better predictive ability for T2D than BMI (AUC 0.68 (0.62, 0.73)).ConclusionsWC, WHtR and WHt.5R were better predictors of T2D than BMI and should be used for risk stratification in Kenya. A WC cut-off of 87cm in women and 91cm in men, a WHtR cut-off of 0.54 or a WHt.5R of 6.9 in both men and women should be used to identify individuals at an elevated risk of T2D.     

Varying sensitivity of waist action levels to identify subjects with overweight or obesity in 19 populations of the WHO MONICA Project

It has been suggested in the literature that cut-off points based on waist circumference (waist action levels) should replace cut-off points based on body mass index (BMI) and waist-to-hip ratio in identifying subjects with overweight or obesity. In this article, we examine the sensitivity and specificity of the cut-off points when applied to 19 populations with widely different prevalences of overweight. Our design was a cross-sectional study based on random population samples. A total of 32,978 subjects aged 25–64 years from 19 male and 18 female populations participating in the second MONICA survey from 1987 to 1992 were included in this study. We found that at waist action level 1 (waist circumference ≥94 cm in men and ≥80 cm in women), sensitivity varied between 40% and 80% in men and between 51% and 86% in women between populations when compared with the cut-off points based on BMI (≥25 kg/m²) and waist-to-hip ratio (≥0.95 for men, ≥0.80 for women). Specificity was high (≥90%) in all populations. At waist action level 2 (waist circumference ≥102 cm and ≥88 cm in men and women, respectively, BMI ≥30 kg/m²), sensitivity varied from 22% to 64% in men and from 26% to 67% in women, whereas specificity was >95% in all populations. Sensitivity was in general lowest in populations in which overweight was relatively uncommon, whereas it was highest in populations with relatively high prevalence of overweight. We propose that cut-off points based on waist circumference as a replacement for cut-off points based on BMI and waist-to-hip ratio should be viewed with caution. Based on the proposed waist action levels, very few people would unnecessarily be advised to have weight management, but a varying proportion of those who would need it might be missed. The optimal screening cut-off points for waist circumference may be population specific.     

Discrimination of health risk by combined body mass index and waist circumference

OBJECTIVE: NIH Clinical Guidelines (1998) recommend the measurement of waist circumference (WC, centimeters) within body mass index (BMI, kilograms per square meter) categories as a screening tool for increased health risk. RESEARCH METHODS AND PROCEDURES: The Canada Heart Health Surveys (1986 through 1992) were used to describe the prevalence of the metabolic syndrome in Canada and to test the use of the NIH guidelines for predicting metabolic risk factors. The sample included 7981 participants ages 20 to 74 years who had complete data for WC, BMI, high-density lipoprotein-cholesterol, triglycerides, diabetic status, and systolic and diastolic blood pressures. National Cholesterol Education Program Adult Treatment Panel III risk categories were used to identify the metabolic syndrome and associated risk factors. Logistic regression was used to test the hypothesis that WC improves the prediction of the metabolic syndrome, within overweight (25 to 29.9 kg/m(2)) and obese I (30 to 34.9 kg/m(2)) BMI categories. RESULTS: The prevalence of the metabolic syndrome was 17.0% in men and 13.2% in women. The odds ratios (OR) for the prediction of the metabolic syndrome were elevated in overweight [OR, 1.85; 95% confidence interval (95%CI), 1.02 to 3.35] and obese (OR, 2.35; 95%CI, 1.25 to 4.42) women with a high WC compared with overweight and obese women with a low WC, respectively. On the other hand, WC was not predictive of the metabolic syndrome or component risk factors in men, within BMI categories. DISCUSSION: In women already at increased health risk because of an elevated BMI, the additional measurement of WC may help identify cardiovascular risk.     

体质指数、腰围、腰臀比与高血压、高血糖的关系及三者对高血压、高血糖的预测价值

目的探讨体质指数（BMI）、腰围（WC）、腰臀比（WHR）与高血压、高血糖的关系及三者对高血压高血糖的预防价值。方法2006年4-9月整群抽取黑龙江省电力医院健康检查中心体检的1751人,测量身高、体重、腰围、臀围、血压和空腹血糖。结果①BMI、WC与血压的相关性比WHR好;WHR、WC与血糖的相关性比BMI好;②logistic回归分析表明3个指标中BMI是高血压重要的预测因子,而WC是高血糖及二者聚集重要的预测因子;③BMI、WC与WHR三者之间两两指标同时存在时对高血糖、高血压及二者聚集都存在交互作用;④当BMI≥25kg/m2时,其OR值在3.02-4.01之间,ARP在58.13%-69.21%之间,PARP在43.79%-55.77%之间;当WC≥85cm（男性）、WC≥80cm（女性）时,其OR值在4.04-6.70之间,PARP在56.47%-75.52%之间;敏感度和特异度均较好,正确指数高,具有较高的公共卫生价值。结论BMI、WC分别是高血压、高血糖重要的预测因子,以BMI≥25kg/m2或WC≥85cm（男性）、WC≥80cm（女性）为超重肥胖切点时,诊断价值最高,建议以此为诊断界值。     

Anthropometric cutoff points for predicting chronic diseases in the Mexican National Health Survey 2000

OBJECTIVE: To determine optimum anthropometric cutoffs for predicting the likelihood ratios of type 2 diabetes mellitus (DM) and hypertension (HT) in Mexicans. RESEARCH METHODS AND PROCEDURES: Data from a randomly selected, nationally representative health survey (2000) with 11,730 men [37.4 (+/- 12.9) years] and 26,647 women [37.3(+/- 12.9) years] were assessed for values of body mass index (BMI) and waist circumference (WC) for predicting DM or HT by receiver operating characteristic curve analyses. Likelihood ratios for DM and HT were calculated, and BMIs or WCs for public-health screening were developed. Subanalyses included regional data. RESULTS: Likelihood ratios of DM and HT increased from BMI values of 22 to 24 kg/m(2) in both sexes and with WC values of 75 to 80 cm in men and 70 to 80 cm in women. The best BMI cutoffs for predicting DM were 26.3 to 27.4 kg/m(2) in men and 27.7 to 28.9 kg/m(2) in women, with similar values for HT, i.e., 26.2 to 27.0 kg/m(2) and 27.7 to 28.5 kg/m(2), for men and women, respectively; WC cutoffs for DM were 93 to 98 cm in men and 94 to 99 cm in women, and cutoffs for HT were 92 to 96 cm and 93 to 96 cm for men and women, respectively. The WC cutoffs had higher sensitivity and specificity than those of BMI. DISCUSSION: The risk for DM and HT starts at lower levels of BMI and WC than those suggested by WHO. WC is a better discriminator than BMI measures for use in public health.     

Predicting incident diabetes in Jamaica: the role of anthropometry

OBJECTIVE: To evaluate the performance of the body mass index (BMI), waist circumference, waist-to-hip ratio (WHR), and waist-to-height ratio (WHTR) in predicting incident diabetes in Jamaica. RESEARCH METHODS AND PROCEDURES: A cohort of 728 nondiabetic adults (290 men and 438 women), ages 25 to 74 years and residents of Spanish Town, Jamaica, were followed for a mean of 4 years. Participants had fasting and 2-hour postchallenge glucose concentrations measured at baseline and follow-up. RESULTS: There were 51 cases of incident diabetes (17 men and 34 women). All indices were independent predictors of diabetes, and none was clearly superior. The area under the receiver operating characteristics curves (95% confidence interval) for BMI was 0.74 (0.59 to 0.88) for men and 0.62 (0.51 to 0.72) for women. For waist circumference, these values were 0.78 (0.65 to 0.91) in men and 0.61 (0.50 to 0.71) in women. Similar results were obtained for WHR and WHTR. "Optimal" cut-off points for BMI were 24.8 kg/m(2) (men) and 29.3 kg/m(2) (women). For waist circumference, these were 88 cm and 84.5 cm for men and women, respectively. Corresponding values for WHR were 0.87 and 0.80 and for WHTR were 0.51 and 0.54, respectively. DISCUSSION: Cut-off points for waist circumference and WHR were similar to those proposed in developed countries for women but lower in men. Waist circumference could be useful in health promotion as an alternative to BMI.     

不同体重指数和腰围人群的血压均值及高血压患病率调查

目的：探讨体重指数(BMI和腰围(WC)对人群血压水平和高血压患病率的影响。方法：对1992—1994年和1998年在中国不同地区男女性中年人群中进行的两次心血管病危险因素调查资科合并共35 003人，比较不同BMI和WC分组的平均血压水平及其高血压患病率。结果：随着BMI和／或WC的增加，人群血压水平、高血压患病率呈明显的上升趋势，在多数BMI组中，男女性WC与血压均值和高血压患病车间存在明显的线性相关关系(线性趋势检验P＜0．05)，同样在不同的WC组中，BMI均与血压均值和高血压患病车间存在明显的线性相关关系。男女性按不同BMI及WC标准分组的年龄调整高血压患病率分别为16．5％、14．1％(BMI＜24kg／m^2，男／女：WC＜85／80cm)，29．8％、20．6％(BMI＜24kg／m^2，男／女：WC≥85／80cm)，29．6％、24．7％(BMI：24．0—27．9kg／m^2，男／女：WC＜85／80cm)，39．2％、30．3％(BMI：24．0—27．9kg／m^2，男／女：WC≥85／80cm)，57．5％、43．3％(BMI≥28kg／m^2，男／女：WC≥85／80cm)。结论：BMI和WC均与人群血压有相互独立的关联，保持BMI和WC均在正常范围是预防高血压的有效措施。     

Combination of BMI and Waist Circumference for Identifying Cardiovascular Risk Factors in Whites

OBJECTIVE: BMI (kilograms per meters squared) and waist circumference (WC) (measured in centimeters) are each associated with the risk of developing cardiovascular disease (CVD). Therefore, a combination of the two may be more effective in identifying subjects at risk than either alone. The present study sought to identify the combination of BMI and WC that has the strongest association with CVD risk factors in whites. RESEARCH METHODS AND PROCEDURES: Subjects were 8712 white men and women from the Third National Health and Nutrition Examination Survey. The optimal combination of BMI and WC was developed using logistic regression models with BMI and WC as predictors and CVD risk factors as outcomes. The combined measure of BMI and WC using current cut-off points was also examined. Sensitivity, specificity, and receiver operating characteristics curves were compared between the combined measures and BMI alone. RESULTS: For white men, the optimal combination of BMI and WC for identifying CVD risk factors was 0.68 x BMI + 0.32 x WC. This combination generated a score that better estimated the odds of having CVD risk factors than either alone. For white women, WC alone largely determined the likelihood of having CVD risks. The combination of BMI and WC using current cut-off points may provide an improved measure of CVD risk. Combined measures showed a higher sensitivity or a shorter distance in receiver operating characteristic curves in the identification of CVD risk factors. DISCUSSION: Combined measures of BMI and WC may provide a higher overall test performance for CVD risk factors and may be useful in some ethnic groups as an improved means of screening subjects for further evaluation in the clinical setting.     

简易体脂参数估测腹内型肥胖的可靠性评价

目的：评价体重指数（BMI）、腰围（WC）、腰臀比（WHR）估测腹内型肥胖的最佳临界点及敏感度、特异度。方法：应用核磁共振（MRI）对690名受试者（男305人，女385人）进行腹内脂肪（VA）测量，同时测量BMI、WC、WHR。以受试者工作特性（ROC）曲线评价简易体脂参数对腹内型肥胖的诊断价值。结果：①经MRI诊断，超重／肥胖者中61．7％，正常体重者中14．2％呈腹内型肥胖（VA≥100cm^2）；②BMI、WC、WHR与腹内脂肪面积呈显著正相关，尤以WC的相关性最好;③简易体脂参数估测腹内脂肪积聚的最佳切割点为BMI：26kg/m^2,WC:90cm,WHR:0.93;④BMI≥28kg/m^2、WC≥95cm时，95％的男性及90％左右的女性呈腹内型肥胖。结论：BMI、WC及WHR都可估测腹内型肥胖，但以腰围的准确率稍高。     

Cut-off points for anthropometric indices of adiposity: differential classification in a large population of young women

Anthropometric indices of adiposity include BMI, waist circumference and waist:height ratio. In the recruitment phase of a prospective cohort study carried out between 1998 and 2002 we studied a population sample of 11 786 white Caucasian non-pregnant women in Southampton, UK aged 20-34 years, and explored the extent to which proposed cut-off points for the three indices identified the same or different women and how these indices related to adiposity. Height, weight and waist circumference were measured and fat mass was estimated from skinfold thicknesses; fat mass index was calculated as fat mass/height1.65. Of the subjects, 4869 (42 %) women were overweight (BMI > or = 25 kg/m2) and 1849 (16 %) were obese (BMI > or = 30 kg/m2). A total of 890 (8 %) subjects were not overweight but had a waist circumference > or = 80 cm and 748 (6 %) subjects were overweight but had a waist circumference < 80 cm (6 %). Of the women, 50 % had a BMI > or = 25 kg/m2 or a waist circumference > or = 80 cm or a waist:height ratio > or = 0.5. Of the variation in fat mass index, 85 % was explained by BMI, 76 % by waist circumference and 75 % by waist:height ratio. Our findings demonstrate that many women are differentially classified depending on which index of adiposity is used. As each index captures different aspects of size in terms of adiposity, there is the need to determine how the three indices relate to function and how they can be of use in defining risk of ill health in women.     

Optimal Cut-Off Values of Anthropometric Markers to Predict Hypertension in North Indian Population

The aim of the study was to determine the cut-offs of anthropometric markers for detecting hypertension in an endogamous North Indian population. A cross-sectional study was carried out to collect data from 578 adult Aggarwal Baniya subjects (271 men and 307 women, mean age: 43.4 ± 5.3 and 38.7 ± 4.9 respectively) using multistage, stratified sampling method. Individual body weight, height, waist circumference (WC), hip circumference, blood pressure were assessed. Receiver operating characteristic (ROC) analysis was used to find out the optimal cut-off values of various anthropometric markers to predict hypertension. The likelihood ratios for having hypertension in subjects with various cut-off values were calculated. Logistic regression analysis was used to examine the independent relationship between the anthropometric markers and odds of having hypertension. The BMI cut-off to predict hypertension was 22.8 kg/m² in men and 28.8 kg/m² in women. The optimal WC cut-offs varied from 91–92 cm in both men and women. The WHR cut-off was about 0.90 in men and 0.78 in women respectively, and the optimal WHtR cut-off was 0.56 in men and 0.43 in women. The cut-off levels for BMI, WC and WHtR corresponded to the inflexion points in the likelihood ratio graphs. The area under curve (AUC) and odds ratios showed that the risk of having hypertension was highest with respect to increased BMI and that BMI is the best predictor of having hypertension. The cut-off points for detecting cardiovascular risk factors among our population are lower than the criteria by the World Health Organization. Although these results may not be readily applied to the rest of the Indian populations due to the multiethnic composition, they point to the necessity of similar studies with large randomized samples to find the cut-off levels for chronic conditions in different populations.