Social inequalities in child development: the role of differential exposure and susceptibility to stressful family conditions.

BACKGROUND: Stressful family conditions may contribute to inequalities in child development because they are more common among disadvantaged groups (ie, differential exposure) and/or because their negative effects are stronger among disadvantaged groups (ie, differential impact/susceptibility). We used counterfactual mediation analysis to investigate to what extent stressful family conditions contribute to inequalities in child development via differential exposure and susceptibility. METHODS: We used data from the Generation R Study, a population-based birth cohort in the Netherlands (n=6842). Mother's education was used as the exposure. Developmental outcomes, measured at age 13 years, were emotional and behavioural problems (Youth Self-Report), cognitive development (Wechsler Intelligence Scale for Children) and secondary education entry level. Financial and social stress at age 9 years were the putative mediators. RESULTS: Differential exposure to financial stress caused a 0.07 (95% CI -0.12 to -0.01) SD worse emotional and behavioural problem -score, a 0.05 (95% CI -0.08 to -0.02) SD lower intelligence score and a 0.05 (95% CI -0.05 to -0.01) SD lower secondary educational level, respectively, among children of less-educated mothers compared with children of more-educated mothers. This corresponds to a relative contribution of 54%, 9% and 6% of the total effect of mother's education on these outcomes, respectively. Estimates for differential exposure to social stress, and differential susceptibility to financial or social stress, were much less pronounced. CONCLUSION: Among children of less-educated mothers, higher exposure to financial stress in the family substantially contributes to inequalities in socioemotional development, but less so for cognitive development and educational attainment.

Exploring multilevel social determinants of depressive symptoms for Tanzanian adolescents: evidence from a cross-sectional study.

BACKGROUND: Depression has substantial and enduring impacts for adolescents, particularly those living in poverty. Yet, evidence on its determinants in low-income countries remains scarce. We examined the social determinants of depressive symptoms for Tanzanian adolescents. METHODS: We used cross-sectional data for 2458 adolescents (aged 14-19), to describe associations with depressive symptoms within and across five domains-demographic, economic, neighbourhood, environmental and social-cultural-using linear mixed models. We estimated depressive symptoms using the 10-item Centre for Epidemiological Studies Depression Scale, which ranges from 0 to 30 and increases with additional symptoms. RESULTS: Factors associated with depressive symptoms in the fully adjusted models included experiencing five or more household economic shocks (ß=2.40; 95% CI 1.48 to 3.32), experiencing droughts/floods (ß=0.76; 95% CI 0.36 to 1.17), being in a relationship (ß=1.82; 95% CI 1.30 to 2.33), and having moderate (ß=1.26; 95% CI 0.80 to 1.71) or low (ß=2.27; 95% CI 1.81 to 2.74) social support. Exclusive schooling was protective compared with being engaged in both school and paid work (ß=1.07; 95% CI 0.05 to 2.61) and not engaged in either (ß=0.73; 95% CI 0.24 to 1.22). Household size and relationship status were more important factors for girls, while employment status, and extreme precipitation were more important for boys. CONCLUSION: Mental health is associated with determinants from multiple domains. Results suggest that environmental shocks related to climate change contribute to poor mental health in adolescents, highlighting an important area for intervention and research.

Targeting the poorest in a performance-based financing programme in northern Cameroon.

Performance-Based Financing (PBF) is a promising approach to improve health system performance in developing countries, but there are concerns that it may inadequately address inequalities in access to care. Incentives for reaching the poor may prove beneficial, but evidence remains limited. We evaluated a system of targeting the poorest of society ('indigents') in a PBF programme in Cameroon, examining (under)coverage, leakage and perceived positive and negative effects. We conducted a documentation review, 59 key informant interviews and 33 focus group discussions with community members (poor and vulnerable people-registered as indigents and those not registered as such). We found that community health workers were able to identify very poor and vulnerable people with a minimal chance of leakage to non-poor people. Nevertheless, the targeting system only reached a tiny proportion (≤1%) of the catchment population, and other poor and vulnerable people were missed. Low a priori set objectives and implementation problems-including a focus on easily identifiable groups (elderly, orphans), unclarity about pre-defined criteria, lack of transport for identification and insufficient motivation of community health workers-are likely to explain the low coverage. Registered indigents perceived improvements in access, quality and promptness of care, and improvements in economic status and less financial worries. However, lack of transport and insufficient knowledge about the targeting benefits, remained barriers for health care use. Negative effects of the system as experienced by indigents included negative reactions (e.g. jealousy) of community members. In conclusion, a system of targeting the poorest of society in PBF programmes may help reduce inequalities in health care use, but only when design and implementation problems leading to substantial under-coverage are addressed. Furthermore, remaining barriers to health care use (e.g. transport) and negative reactions of other community members towards indigents deserve attention.

Community mobilisation with women's groups facilitated by Accredited Social Health Activists (ASHAs) to improve maternal and newborn health in underserved areas of Jharkhand and Orissa: study protocol for a cluster-randomised controlled trial.

BACKGROUND: Around a quarter of the world's neonatal and maternal deaths occur in India. Morbidity and mortality are highest in rural areas and among the poorest wealth quintiles. Few interventions to improve maternal and newborn health outcomes with government-mandated community health workers have been rigorously evaluated at scale in this setting.The study aims to assess the impact of a community mobilisation intervention with women's groups facilitated by ASHAs to improve maternal and newborn health outcomes among rural tribal communities of Jharkhand and Orissa. METHODS/DESIGN: The study is a cluster-randomised controlled trial and will be implemented in five districts, three in Jharkhand and two in Orissa. The unit of randomisation is a rural cluster of approximately 5000 population. We identified villages within rural, tribal areas of five districts, approached them for participation in the study and enrolled them into 30 clusters, with approximately 10 ASHAs per cluster. Within each district, 6 clusters were randomly allocated to receive the community intervention or to the control group, resulting in 15 intervention and 15 control clusters. Randomisation was carried out in the presence of local stakeholders who selected the cluster numbers and allocated them to intervention or control using a pre-generated random number sequence. The intervention is a participatory learning and action cycle where ASHAs support community women's groups through a four-phase process in which they identify and prioritise local maternal and newborn health problems, implement strategies to address these and evaluate the result. The cycle is designed to fit with the ASHAs' mandate to mobilise communities for health and to complement their other tasks, including increasing institutional delivery rates and providing home visits to mothers and newborns. The trial's primary endpoint is neonatal mortality during 24 months of intervention. Additional endpoints include home care practices and health care-seeking in the antenatal, delivery and postnatal period. The impact of the intervention will be measured through a prospective surveillance system implemented by the project team, through which mothers will be interviewed around six weeks after delivery. Cost data and qualitative data are collected for cost-effectiveness and process evaluations. STUDY REGISTRATION: ISRCTN: ISRCTN31567106.

Comparison of physical, public and human assets as determinants of socioeconomic inequalities in contraceptive use in Colombia - moving beyond the household wealth index.

BACKGROUND: Colombia is a lower-middle income country that faces the challenge of addressing health inequalities. This effort includes the task of developing measures of socioeconomic position (SEP) to describe and analyse disparities in health and health related outcomes. This study explores the use of a multidimensional approach to SEP, in which socioeconomic inequalities in contraceptive use are investigated along multiple dimensions of SEP. We tested the hypothesis that provision of Public capital compensated for low levels of Human capital. METHODS: This study used the 2005 Colombian Demographic and Health Survey (DHS) dataset. The outcome measures were 'current non-use' and 'never use' of contraception. Inequalities in contraceptive behaviour along four measures of SEP were compared: the Household wealth index (HWI), Physical capital (housing, consumer durables), Public capital (publicly provided services) and Human capital (level of education). Principal component analysis was applied to construct the HWI, Physical capital and Public capital measures. Logistic regression models were used to estimate relative indices of inequality (RII) for each measure of SEP with both outcomes. RESULTS: Socio-economic inequalities among rural women tended to be larger than those among urban women, for all measures of SEP and for both outcomes. In models mutually adjusted for Physical, Public and Human capital and age, Physical capital identified stronger gradients in contraceptive behaviour in urban and rural areas (Current use of contraception by Physical capital in urban areas RII 2.37 95% CI (1.99-2.83) and rural areas RII 3.70 (2.57-5.33)). The impact of women's level of education on contraceptive behaviour was relatively weak in households with high Public capital compared to households with low Public capital (Current use of contraception in rural areas, interaction p = < 0.001). Reduced educational inequalities attributable to Public capital were partly explained by differences in household wealth but not at all by health insurance cover. CONCLUSIONS: A multidimensional approach provides a framework for disentangling socioeconomic inequalities in contraceptive behaviour. We provide evidence that material circumstances indexed by Physical capital are important socioeconomic determinants while higher provision of Public capital may compensate for low levels of Human capital with respect to modern contraceptive behaviour.

Using relative and absolute measures for monitoring health inequalities: experiences from cross-national analyses on maternal and child health.

BACKGROUND: As reducing socio-economic inequalities in health is an important public health objective, monitoring of these inequalities is an important public health task. The specific inequality measure used can influence the conclusions drawn, and there is no consensus on which measure is most meaningful. The key issue raising most debate is whether to use relative or absolute inequality measures. Our paper aims to inform this debate and develop recommendations for monitoring health inequalities on the basis of empirical analyses for a broad range of developing countries. METHODS: Wealth-group specific data on under-5 mortality, immunisation coverage, antenatal and delivery care for 43 countries were obtained from the Demographic and Health Surveys. These data were used to describe the association between the overall level of these outcomes on the one hand, and relative and absolute poor-rich inequalities in these outcomes on the other. RESULTS: We demonstrate that the values that the absolute and relative inequality measures can take are bound by mathematical ceilings. Yet, even where these ceilings do not play a role, the magnitude of inequality is correlated with the overall level of the outcome. The observed tendencies are, however, not necessities. There are countries with low mortality levels and low relative inequalities. Also absolute inequalities showed variation at most overall levels. CONCLUSION: Our study shows that both absolute and relative inequality measures can be meaningful for monitoring inequalities, provided that the overall level of the outcome is taken into account. Suggestions are given on how to do this. In addition, our paper presents data that can be used for benchmarking of inequalities in the field of maternal and child health in low and middle-income countries.

Measuring health inequality among children in developing countries: does the choice of the indicator of economic status matter?

BACKGROUND: Currently, poor-rich inequalities in health in developing countries receive a lot of attention from both researchers and policy makers. Since measuring economic status in developing countries is often problematic, different indicators of wealth are used in different studies. Until now, there is a lack of evidence on the extent to which the use of different measures of economic status affects the observed magnitude of health inequalities. METHODS: This paper provides this empirical evidence for 10 developing countries, using the Demographic and Health Surveys data-set. We compared the World Bank asset index to three alternative wealth indices, all based on household assets. Under-5 mortality and measles immunisation coverage were the health outcomes studied. Poor-rich inequalities in under-5 mortality and measles immunisation coverage were measured using the Relative Index of Inequality. RESULTS: Comparing the World Bank index to the alternative indices, we found that (1) the relative position of households in the national wealth hierarchy varied to an important extent with the asset index used, (2) observed poor-rich inequalities in under-5 mortality and immunisation coverage often changed, in some cases to an important extent, and that (3) the size and direction of this change varied per country, index, and health indicator. CONCLUSION: Researchers and policy makers should be aware that the choice of the measure of economic status influences the observed magnitude of health inequalities, and that differences in health inequalities between countries or time periods, may be an artefact of different wealth measures used.