The WHO recommends the use of some anthropometric parameters as a screening resource for individuals under cardiometabolic risk. However, in the validation of these indicators, Brazilian women were not included. These women have different anthropometric profile compared to women who integrated the samples of the validation studies. We aimed to verify the accuracy of anthropometric indicators as a resource for the screening of women with hypertension. A cross-sectional study, with a probability sample of 3143 women (20–49 years) from the state of Alagoas (northeast of Brazil), was carried out. Hypertension was identified by systolic blood pressure (SBP) ≥140 mm Hg and/or diastolic BP ≥90 mm Hg and/or regular use of antihypertensive drugs. The anthropometric indicators analyzed were BMI, waist circumference, waist-to-hip ratio, waist-to-height ratio (WHtR), body fat percentage, and conicity index. The accuracy definition of the indicators and the identification of best cut-off points were carried out on the basis of ROC curve analysis and Youden index, respectively. The prevalence of hypertension was 21.8%. All indicators used in hypertension identification had area under the ROC curve (AUC) >0.5. The WHtR with cut-off point of 0.54 was the best performance indicator (AUC = 0.72; P < 0.05; sensitivity = 67%, specificity = 66%). The WHtR with cut-off point of 0.54 has constituted the most accurate indicator in the screening of women with hypertension. In the absence of specific studies and considering the largest ethnic proximity and environmental/epidemiological similarity, the findings now obtained can be extended to women of other Brazilian states, especially those in the Northeastern region.

BackgroundUndernutrition in early life (UELife) is a condition associated with greater occurrence of chronic diseases in adulthood. Some studies on this relationship have used short stature as indicator of UELife. However, other non-nutritional factors can also determine short stature. Depending on the severity of UELife, the human body reacts primarily compromising weight and length gain, but prioritizing brain growth, resulting in disproportionate individuals. Based on this premise, this study aimed to validate a new anthropometric indicator of UELife.DesignUsing stature and head circumference data from a probabilistic sample of 3,109 women, the Head-to-Height Index was calculated: HHI = (head × 2.898)/height. A HHI >1.028 (75th percentile) was the best cutoff for predicting obesity (best balance between sensitivity/ specificity, largest area under the receiver operating characteristic curve, and highest correlation coefficient) and was used to define the condition of body disproportionality. The strength of associations with several outcomes was tested for both disproportionality and short stature (height ≤25th percentile: 153.1 cm).ResultsIn adjusted analysis for confounding factors (age, smoking, and education level), the strength of the associations between body disproportionality and the analyzed outcomes was greater than that observed when short stature was used. Respectively, the observed prevalence ratios (95% CI) were (P<0.05 for all comparisons): obesity: 2.61 (2.17–3.15) vs 1.09 (0.92–1.28); abdominal obesity: 2.11 (1.86–2.40) vs 1.42 (1.27– 1.59); high blood pressure: 1.24 (1.02–1.50) vs 0.90 (0.75–1.08); hypercholesterolemia: 2.98 (1.47–6.05) vs 1.65 (0.91–2.99); and hypertriglyceridemia: 1.47 (1.07–2.03) vs 0.91 (0.69–1.21).ConclusionBody disproportionality is a more accurate indicator of UELife than short stature. While short stature may be genetically determined, a high HHI is due to metabolic adaptations to undernutrition in early life.

Objective This study aims to evaluate the prevalence, temporal trends and associated factors with excess weight in mothers of children under five years of age. Methods This is a time-series study using data from two household surveys conducted in 2005 and 2015. A total of 1,436 mothers were evaluated in 2005, and 690 were evaluated in 2015. The dependent variables were excess body weight (Body Mass Index [BMI] ≥25.0kg/m2), high percentage of Body Fat (%BF ≥33%) and abdominal obesity (waist circumference >80cm). The independent variables were the socioeconomic and demographic factors. The changes that occurred between the two surveys were expressed in percentages, and the measure of association was the Prevalence Ratio, calculated by Poisson regression, in both the crude and multivariate analyses. Results There were increases of 33.2%, 59.2% and 31.0%, respectively, for the prevalence of excess weight (PR=1.33, 95% Confidence Interval [CI]:1.21-1.46), abdominal obesity (PR=1.59, 95% CI:1.43-1.77) and high %BF (PR=1.31, 95% CI:1.07-1.60). The factors independently associated with excess weight and abdominal obesity were the highest age group (>30 years), menarche ≤12 years and higher parity (>2 children). The same was observed for high %BF, except for the loss of significance in the adjusted analysis for the variable menarche ≤12 years. Conclusion The prevalence of high body adiposity is a problem of relevant importance in the studied population and has presented an upward trend in the last 10 years. Women over 30 years and with more than two children should be given priority in prevention and control.