Socioeconomic inequalities in skilled birth attendance and child stunting in selected low and middle income countries: Wealth quintiles or deciles?

BACKGROUND: Wealth quintiles derived from household asset indices are routinely used for measuring socioeconomic inequalities in the health of women and children in low and middle-income countries. We explore whether the use of wealth deciles rather than quintiles may be advantageous. METHODS: We selected 46 countries with available national surveys carried out between 2003 and 2013 and with a sample size of at least 3000 children. The outcomes were prevalence of under-five stunting and delivery by a skilled birth attendant (SBA). Differences and ratios between extreme groups for deciles (D1 and D10) and quintiles (Q1 and Q5) were calculated, as well as two summary measures: the slope index of inequality (SII) and concentration index (CIX). RESULTS: In virtually all countries, stunting prevalence was highest among the poor, and there were larger differences between D1 and D10 than between Q1 and Q5. SBA coverage showed pro-rich patterns in all countries; in four countries the gap was greater than 80 pct points. With one exception, differences between extreme deciles were larger than between quintiles. Similar patterns emerged when using ratios instead of differences. The two summary measures provide very similar results for quintiles and deciles. Patterns of top or bottom inequality varied with national coverage levels. CONCLUSION: Researchers and policymakers should consider breakdowns by wealth deciles, when sample sizes allow. Use of deciles may contribute to advocacy efforts, monitoring inequalities over time, and targeting health interventions. Summary indices of inequalities were unaffected by the use of quintiles or deciles in their calculation

Trends in social and demographic inequalities in the prevalence of chronic diseases in Brazil. PNAD: 2003-2008.

The aims of this study are: to evaluate the prevalence of chronic diseases in the Brazilian population comparing data of 2008 with those of 2003; to estimate the impact of chronic conditions on the use of health services and on the restriction of daily activities and to measure the differentials in the prevalence of specific diseases according to educational strata and the affiliation to a private health plan. Data were obtained from PNAD 2008 and 2003. The analysis included estimations of crude and adjusted prevalence ratios, using svy commands from Stata 11 software. The prevalence of at least one disease was higher in: the elderly, women, low schooling level, black or indigenous people, urban residents, migrants and people living in the south region of Brazil. The most frequent diseases were: hypertension, back and spinal cord disorders, arthritis and depression. Between 2003 and 2008, an increase in the prevalence of diabetes, hypertension, cancer and cirrhosis was observed, and there was a reduction in chronic kidney failure and tuberculosis. All the diseases analyzed, with the exception of cancer and tendinitis/tenossinovitis, revealed a higher prevalence in low educational level strata. The greatest social inequalities were in chronic kidney failure, cirrhosis, tuberculosis and arthritis/rheumatism.1693755376

A simple method for estimating relative risk using logistic regression

<p>Abstract</p> <p>Background</p> <p>Odds ratios (OR) significantly overestimate associations between risk factors and common outcomes. The estimation of relative risks (RR) or prevalence ratios (PR) has represented a statistical challenge in multivariate analysis and, furthermore, some researchers do not have access to the available methods. Objective: To propose and evaluate a new method for estimating RR and PR by logistic regression.</p> <p>Methods</p> <p>A provisional database was designed in which events were duplicated but identified as non-events. After, a logistic regression was performed and effect measures were calculated, which were considered RR estimations. This method was compared with binomial regression, Cox regression with robust variance and ordinary logistic regression in analyses with three outcomes of different frequencies.</p> <p>Results</p> <p>ORs estimated by ordinary logistic regression progressively overestimated RRs as the outcome frequency increased. RRs estimated by Cox regression and the method proposed in this article were similar to those estimated by binomial regression for every outcome. However, confidence intervals were wider with the proposed method.</p> <p>Conclusion</p> <p>This simple tool could be useful for calculating the effect of risk factors and the impact of health interventions in developing countries when other statistical strategies are not available.</p