Ahmad Reza Hosseinpoor

Socioeconomic inequality in malnutrition in developing countries

OBJECTIVE The objectives of this study were to report on socioeconomic inequality in childhood malnutrition in the developing world, to provide evidence for an association between socioeconomic inequality and the average level of malnutrition, and to draw attention to different patterns of socioeconomic inequality in malnutrition. METHODS Both stunting and wasting were measured using new WHO child growth standards. Socioeconomic status was estimated by principal component analysis using a set of household assets and living conditions. Socioeconomic inequality was measured using an alternative concentration index that avoids problems with dependence on the mean level of malnutrition. FINDINGS In almost all countries investigated, stunting and wasting disproportionately affected the poor. However, socioeconomic inequality in wasting was limited and was not significant in about one third of countries. After correcting for the concentration indexs dependence on mean malnutrition, there was no clear association between average stunting and socioeconomic inequality. The latter showed different patterns, which were termed mass deprivation, queuing and exclusion. Although average levels of malnutrition were higher with the new WHO reference standards, estimates of socioeconomic inequality were largely unaffected by changing the growth standards. CONCLUSION Socioeconomic inequality in childhood malnutrition existed throughout the developing world, and was not related to the average malnutrition rate. Failure to tackle this inequality is a cause of social injustice. Moreover, reducing the overall rate of malnutrition does not necessarily lead to a reduction in inequality. Policies should, therefore, take into account the distribution of childhood malnutrition across all socioeconomic groups.

Malnutrition and the disproportional burden on the poor: the case of Ghana

BackgroundMalnutrition is a major public health and development concern in the developing world and in poor communities within these regions. Understanding the nature and determinants of socioeconomic inequality in malnutrition is essential in contemplating the health of populations in developing countries and in targeting resources appropriately to raise the health of the poor and most vulnerable groups.MethodsThis paper uses a concentration index to summarize inequality in childrens height-for-age z-scores in Ghana across the entire socioeconomic distribution and decomposes this inequality into different contributing factors. Data is used from the Ghana 2003 Demographic and Health Survey.ResultsThe results show that malnutrition is related to poverty, maternal education, health care and family planning and regional characteristics. Socioeconomic inequality in malnutrition is mainly associated with poverty, health care use and regional disparities. Although average malnutrition is higher using the new growth standards recently released by the World Health Organization, socioeconomic inequality and the associated factors are robust to the change of reference population.ConclusionChild malnutrition in Ghana is a multisectoral problem. The factors associated with average malnutrition rates are not necessarily the same as those associated with socioeconomic inequality in malnutrition.

Socioeconomic inequality in infant mortality in Iran and across its provinces

OBJECTIVE To measure the socioeconomic inequality in infant mortality in Iran (the Islamic Republic of Iran). METHODS We analysed data from the provincially representative Demographic and Health Survey, which was done in Iran in 2000. We used a dichotomous hierarchical ordered probit model to develop an indicator of socioeconomic status of households. We assessed the inequality in infant mortality by using the odds ratio of infant mortality between the lowest and highest socioeconomic quintiles at both the provincial and national levels, and the concentration index, an inequality measure based on the entire socioeconomic distribution. RESULTS We found a decreasing trend in the infant mortality rate in relation to socioeconomic quintiles. The poorest to richest odds ratio was 2.34 (95% CI = 1.78-3.09). The concentration index of infant mortality in Iran was -0.1789 (95% CI = -0.2193--0.1386). Furthermore, the inequality of infant mortality between the lowest and highest quintiles was significant and favoured the better-off in most of the provinces. However, this inequality varied between provinces. CONCLUSION Socioeconomic inequality in infant mortality favours the better-off in the country as a whole and in most of its provinces, but the degree of this inequality varies between the provinces. As well as its national average, it is important to consider the provincial distribution of this indicator of population health.

Socioeconomic inequalities in risk factors for non communicable diseases in low-income and middle-income countries: results from the World Health Survey

BackgroundMonitoring inequalities in non communicable disease risk factor prevalence can help to inform and target effective interventions. The prevalence of current daily smoking, low fruit and vegetable consumption, physical inactivity, and heavy episodic alcohol drinking were quantified and compared across wealth and education levels in low- and middle-income country groups.MethodsThis study included self-reported data from 232,056 adult participants in 48 countries, derived from the 2002–2004 World Health Survey. Data were stratified by sex and low- or middle-income country status. The main outcome measurements were risk factor prevalence rates reported by wealth quintile and five levels of educational attainment. Socioeconomic inequalities were measured using the slope index of inequality, reflecting differences in prevalence rates, and the relative index of inequality, reflecting the prevalence ratio between the two extremes of wealth or education accounting for the entire distribution. Data were adjusted for confounding factors: sex, age, marital status, area of residence, and country of residence.ResultsSmoking and low fruit and vegetable consumption were significantly higher among lower socioeconomic groups. The highest wealth-related absolute inequality was seen in smoking among men of low- income country group (slope index of inequality 23.0 percentage points; 95% confidence interval 19.6, 26.4). The slope index of inequality for low fruit and vegetable consumption across the entire distribution of education was around 8 percentage points in both sexes and both country income groups. Physical inactivity was less prevalent in populations of low socioeconomic status, especially in low-income countries (relative index of inequality: (men) 0.46, 95% confidence interval 0.33, 0.64; (women) 0.52, 95% confidence interval 0.42, 0.65). Mixed patterns were found for heavy drinking.ConclusionsDisaggregated analysis of the prevalence of non-communicable disease risk factors demonstrated different patterns and varying degrees of socioeconomic inequalities across low- and middle-income settings. Interventions should aim to reach and achieve sustained benefits for high-risk populations.

Social determinants of smoking in low- and middle-income countries: results from the World Health Survey.

Introduction Tobacco smoking is a leading cause of premature death and disability, and over 80% of the worlds smokers live in low- or middle-income countries. The objective of this study is to assess demographic and socioeconomic determinants of current smoking in low- and middle-income countries. Methods We used data, from the World Health Survey in 48 low-income and middle-income countries, to explore the impact of demographic and socioeconomic factors on the current smoking status of respondents. The data from these surveys provided information on 213,807 respondents aged 18 years or above that were divided into 4 pooled datasets according to their sex and country income group. The overall proportion of current smokers, as well as the proportion by each relevant demographic and socioeconomic determinant, was calculated within each of the pooled datasets, and multivariable logistic regression was used to assess the association between current smoking and these determinants. Results The odds of smoking were not equal in all demographic or socioeconomic groups. Some factors were fairly stable across the four datasets studied: for example, individuals were more likely to smoke if they had little or no education, regardless of if they were male or female, or lived in a low or a middle income country. Nevertheless, other factors, notably age and wealth, showed a differential effect on smoking by sex or country income level. While women in the low-income country group were twice as likely to smoke if they were in the lowest wealth quintile compared with the highest, the association was absent in the middle-income country group. Conclusion Information on how smoking is distributed among low- or middle-income countries will allow policy makers to tailor future policies, and target the most vulnerable populations.

Socioeconomic inequality in the prevalence of noncommunicable diseases in low- and middle-income countries: Results from the World Health Survey

BackgroundNoncommunicable diseases are an increasing health concern worldwide, but particularly in low- and middle-income countries. This study quantified and compared education- and wealth-based inequalities in the prevalence of five noncommunicable diseases (angina, arthritis, asthma, depression and diabetes) and comorbidity in low- and middle-income country groups.MethodsUsing 2002–04 World Health Survey data from 41 low- and middle-income countries, the prevalence estimates of angina, arthritis, asthma, depression, diabetes and comorbidity in adults aged 18 years or above are presented for wealth quintiles and five education levels, by sex and country income group. Symptom-based classification was used to determine angina, arthritis, asthma and depression rates, and diabetes diagnoses were self-reported. Socioeconomic inequalities according to wealth and education were measured absolutely, using the slope index of inequality, and relatively, using the relative index of inequality.ResultsWealth and education inequalities were more pronounced in the low-income country group than the middle-income country group. Both wealth and education were inversely associated with angina, arthritis, asthma, depression and comorbidity prevalence, with strongest inequalities reported for angina, asthma and comorbidity. Diabetes prevalence was positively associated with wealth and, to a lesser extent, education. Adjustments for confounding variables tended to decrease the magnitude of the inequality.ConclusionsNoncommunicable diseases are not necessarily diseases of the wealthy, and showed unequal distribution across socioeconomic groups in low- and middle-income country groups. Disaggregated research is warranted to assess the impact of individual noncommunicable diseases according to socioeconomic indicators.

Equity-oriented monitoring in the context of universal health coverage.

As part of the Universal Health Coverage Collection, Ahmad Reza Hosseinpoor and colleagues discuss methodological considerations for equity-oriented monitoring of universal health coverage, and propose recommendations for monitoring and target setting.

Socioeconomic Inequality in Smoking in Low-Income and Middle-Income Countries: Results from the World Health Survey

Objectives To assess the magnitude and pattern of socioeconomic inequality in current smoking in low and middle income countries. Methods We used data from the World Health Survey [WHS] in 48 low-income and middle-income countries to estimate the crude prevalence of current smoking according to household wealth quintile. A Poisson regression model with a robust variance was used to generate the Relative Index of Inequality [RII] according to wealth within each of the countries studied. Results In males, smoking was disproportionately prevalent in the poor in the majority of countries. In numerous countries the poorest men were over 2.5 times more likely to smoke than the richest men. Socioeconomic inequality in women was more varied showing patterns of both pro-rich and pro-poor inequality. In 20 countries pro-rich relative socioeconomic inequality was statistically significant: the poorest women had a higher prevalence of smoking compared to the richest women. Conversely, in 9 countries women in the richest population groups had a statistically significant greater risk of smoking compared to the poorest groups. Conclusion Both the pattern and magnitude of relative inequality may vary greatly between countries. Prevention measures should address the specific pattern of smoking inequality observed within a population.

Socioeconomic inequality in domains of health: results from the World Health Surveys

BackgroundIn all countries people of lower socioeconomic status evaluate their health more poorly. Yet in reporting overall health, individuals consider multiple domains that comprise their perceived health state. Considered alone, overall measures of self-reported health mask differences in the domains of health. The aim of this study is to compare and assess socioeconomic inequalities in each of the individual health domains and in a separate measure of overall health.MethodsData on 247,037 adults aged 18 or older were analyzed from 57 countries, drawn from all national income groups, participating in the World Health Survey 2002-2004. The analysis was repeated for lower- and higher-income countries. Prevalence estimates of poor self-rated health (SRH) were calculated for each domain and for overall health according to wealth quintiles and education levels. Relative socioeconomic inequalities in SRH were measured for each of the eight health domains and for overall health, according to wealth quintiles and education levels, using the relative index of inequality (RII). A RII value greater than one indicated greater prevalence of self-reported poor health among populations of lower socioeconomic status, called pro-rich inequality.ResultsThere was a descending gradient in the prevalence of poor health, moving from the poorest wealth quintile to the richest, and moving from the lowest to the highest educated groups. Inequalities which favor groups who are advantaged either with respect to wealth or education, were consistently statistically significant in each of the individual domains of health, and in health overall. However the size of these inequalities differed between health domains. The prevalence of reporting poor health was higher in the lower-income country group. Relative socioeconomic inequalities in the health domains and overall health were higher in the higher-income country group than the lower-income country group.ConclusionsUsing a common measurement approach, inequalities in health, favoring the rich and the educated, were evident in overall health as well as in every health domain. Existent differences in averages and inequalities in health domains suggest that monitoring should not be limited only to overall health. This study carries important messages for policy-making in regard to tackling inequalities in specific domains of health. Targeting interventions towards individual domains of health such as mobility, self-care and vision, ought to be considered besides improving overall health.

Socioeconomic Inequality in Disability Among Adults: A Multicountry Study Using the World Health Survey

OBJECTIVES We compared national prevalence and wealth-related inequality in disability across a large number of countries from all income groups. METHODS Data on 218,737 respondents participating in the World Health Survey 2002-2004 were analyzed. A composite disability score (0-100) identified respondents who experienced significant disability in physical, mental, and social functioning irrespective of their underlying health condition. Disabled persons had disability composite scores above 40. Wealth was evaluated using an index of economic status in households based on ownership of selected assets. Socioeconomic inequalities were measured using the slope index of inequality and the relative index of inequality. RESULTS Median age-standardized disability prevalence was higher in the low- and lower middle-income countries. In all the study countries, disability was more prevalent in the poorest than in the richest wealth quintiles. Pro-rich inequality was statistically significant in 43 of 49 countries, with disability prevalence higher among populations with lower wealth. Median relative inequality was higher in the high- and upper middle-income countries. CONCLUSIONS Integrating equity components into the monitoring of disability trends would help ensure that interventions reach and benefit populations with greatest need.