Anthropometric predictors for the risk of chronic disease in non-diabetic, non-hypertensive young Mexican women

Abstract

Objectives: To assess the ability of anthropometric measurements to identify young women at risk of developing diabetes, hypertension and heart disease in the future and to compare cut-off points for common anthropometric measures established with receiver-operating characteristic (ROC) curves with those reported in the literature. Design: Cross-sectional study. Subjects: Eight hundred and two young Mexican women living in semi-urban poverty. Measurements/methods: The ability of anthropometric measures of fatness and fat distribution (body mass index (BMI), summed skinfold thickness (SST), waist circumference (WC), waist-to-hip ratio (WHR), conicity index (CI), abdominal volume index (AVI)) to predict risk of future disease (pre-diabetes: fasting blood glucose 100-126 mg dl 21 ; pre-hypertension: systolic blood pressure 120-139 mmHg and/or diastolic blood pressure 80-89 mmHg; hypertriglyceridaemia: triglycerides $150 mg dl 21 ; or a combination of risk factors) was assessed using ROC curve analysis. Results: Twenty-three of the 802 women who were interviewed had incomplete data and 50 (6.4%) were eliminated from the analysis due to hypertension and/or diabetes. Mean age of the remaining 729 women was 29.6 6 5.4 years and mean BMI was 27.7 6 4.5 kg m 22 . There were no significant differences in the area under the ROC curve for BMI, WC, AVI or SST for any of the four outcomes. However, these indices performed significantly better than WHR and CI (P , 0.05). The BMI cut-off points that maximised sensitivity and specificity for the four outcomes were in the range of 27.7-28.4 kg m 22 , and for WC were 89.3-91.2 cm. To detect 90% of the cases of any metabolic alteration, the necessary BMI cut-off was 26.1 kg m 22 . Younger women (,25 years) were at greater risk than older women for a given BMI increment (P , 0.05). Conclusions: We found that BMI and WC cut-off points commonly used for the identification of risk of existing disease were also appropriate in this population for the identification of risk in the future among women without diabetes or hypertension. The early identification of at-risk individuals, prior to the onset of disease, is fundamental particularly in the context of a country with scarce resources that is rapidly undergoing nutrition transition.

Abdominal volume index and conicity index in predicting metabolic abnormalities in young women of different socioeconomic class

“…Few studies in populations of Asian origin have reported WHR to have superior predictive capacity than WC only, while similar studies in North American population have reported WC to be superior to WHR. [10] Although in our study, we found BMI and sum of skin fold thickness as the only two parameters suggesting an indicator of risk in prehypertensive subjects. The other parameters were not statistically significant; these values were similar to the study results of Neufeld et al [10] In the risk factor of hypertriglyceridemia, only BMI was the lone anthropometric indicator suggesting an correlating risk factor, and no other parameter suggested any relation, which is in conjunction to study predicted by Neufeld et al [10] Recent studies have produced differing conclusions about which anthropometric measure has the best predictive capacity for detecting disease risk.…”

Maternal Depressive Symptoms and Physical Activity in Very Low-Income Children

“…The psychosocial measures, including maternal depressive symptoms when the children were 15 months old (Time 1) were assessed as part of a sub-study (n=242) designed to look at maternal caregiving practices and growth and development outcomes 27. From April to August 2005 (Time 2), we attempted to relocate all women from the original sample with the objective of monitoring weight change and chronic disease risk factors over time 28–30. Additional funds were obtained for the assessment of anthropometry, physical activity and potential predictors of these of a sample of 265 children.…”

Utility of anthropometric traits and indices in predicting the risk of coronary artery disease in the adult men of southern Andhra Pradesh

“…In resource-poor countries, targeting high-risk people for preventive measures is likely to reduce both the economic and disease burden. High-risk groups can be identified by using anthropometric measurements, but cutoff values vary with country, population, and ethnic group 11 . Finding population-specific cutoff values for anthropometric variables is therefore useful for research and clinical practice 12 .…”