Waist-to-height ratio is the best anthropometric predictor of hypertension: A population-based study with women from a state of northeast of Brazil.

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.

Prevalence and Factors Associated with Food Insecurity in the Context of the Economic Crisis in Brazil.

Background: The Brazilian economy has been officially in recession since 2014. Since then, there has been an increase in the unemployment rate, cost of food, and cuts in the budgets of social programs, among other situations that may interfere with the food security of the population. Objectives: The aims of this study were to identify the prevalence of and factors associated with food insecurity (FI) in Alagoas, one of the poorest states in Brazil, and to discuss the results in the context of the national economic crisis. Methods: This was a cross-sectional study in a probabilistic sample of 3366 families. FI was identified on the basis of the Brazilian Food Insecurity Measurement. The associations with independent variables that achieved P < 0.2 (by chi-square test) in the crude analysis were submitted to multivariable analysis. Results: The observed prevalence of FI was 58.3% (33.1%, 17.9%, and 7.3% for mild, moderate, and severe FI, respectively), which is considerably higher than the 34.6% found in 2013 by the Brazilian Institute of Geography and Statistics before the worsening of the economic crisis. The factors independently associated with FI in this study included the following: female head of household, head of the family having no income, female head of household being overweight, ≥4 family members, ≤4 rooms in the house, household income less than the minimum wage, family belonging to the lower economic classes (D or E), using the Bolsa Família program, residing in a nonmasonry house, or not residing in their own house. Conclusions: The prevalence of FI in Alagoas is very high, and considering previous studies, there was a marked increase in FI during the Brazilian economic crisis. All associated factors are related to the greater social vulnerability of the family. The present data point to the need to strengthen public policies for health promotion, education, employment, and income and to ensure the human right to adequate food, with the aim of reducing social vulnerability within the family in a sustainable way. In addition, this study contributes to the understanding of how national conditions can influence household-level FI.