Inequality in Child Mortality Persists Between Generations in the Netherlands, 1835–1919

Mind the gap: Temporal trends in inequalities in infant and child mortality in India (1992–2016)

Although the association between child mortality and socioeconomic status is well established, it is unclear whether child mortality differences by socioeconomic position are present at all ages. The association of one-parent families with mortality, and whether any such association is due to associated low socioeconomic position, is also not clear. In all, 480 of 693 (69%) 0-14 year old deaths during 1991-1994 were linked to 1991 census records. Analyses were weighted to adjust for potential linkage bias. There was approximately twofold higher mortality among the lowest compared with the highest socioeconomic categories of education, income, car access, and neighbourhood deprivation. Occupational class differences were weaker. These socioeconomic differences in mortality were strongest among infants (particularly sudden infant death syndrome [SIDS] mortality), but similar across other age groups (1-4, 5-9, and 10-14 years). The socioeconomic differences were of a similar magnitude for unintentional injury, cancer, congenital, and other deaths. Multivariable analyses demonstrated persistent independent associations of education, income, car access, and neighbourhood deprivation with mortality. Rate ratios (adjusted for age and ethnicity) for one-parent families compared with two-parent or other families were 1.2 (95% CI: 1.0, 1.5) and 1.8 (95% CI: 1.2, 2.5) for all-cause and unintentional injury mortality, respectively. Further adjustment for socioeconomic factors reduced these associations to 0.8 (95% CI: 0.6, 1.2) and 1.2 (95% CI: 0.7, 2.2), respectively. There does not appear to be notable variation in relative risk terms of socioeconomic differences in child mortality by age or cause of death. Any association of one-parent families with child mortality is due to associated low socioeconomic position.

BackgroundThere has been an unprecedented rise in infant mortality rates in the UK since 2014, especially in disadvantaged areas. This trend is concerning since infant mortality is a sensitive indicator...

Background: Socioeconomic inequalities in child mortality are known to exist; however the trends in these inequalities have not been well examined. This study examines the trends in child mortality inequality...

Previous studies of inequality in health and mortality have largely focused on income-based inequality. Maternal education plays an important role in determining access to water and sanitation, and inequalities in child mortality arising due to differential access, especially in low- and middle-income countries such as Peru. This article aims to explain education-related inequalities in child mortality in Peru using a regression-based decomposition of the concentration index of child mortality. The analysis combines a concentration index created along a cumulative distribution of the Demographic and Health Surveys sample ranked according to maternal education, and decomposition measures the contribution of water and sanitation to educational inequalities in child mortality. We observed a large education-related inequality in child mortality and access to water and sanitation. There is a need for programs and policies in child health to focus on ensuring equity and to consider the educational stratification of the population to target the most disadvantaged segments of the population.

Mortality had declined dramatically by the end of the nineteenth century and the early twentieth century. Little is known about the development of social differentials in infant and child mortality in Stockholm at the turn of the century. This study investigates social differentials in child mortality during the years 1885, 1891 and 1910 in one parish in Stockholm. Individual entries from computerised records originally collected for civil registration purposes in Stockholm for 1878-1925 (the Roteman Archives) were analysed with respect to social class of the head of household and marital status of the mother for 36,718 children aged 0-14 years. Age- and cause-specific mortality rates were calculated for each year of study. Cox' regression analysis was used to analyse the mortality risk (relative rates (RRs) of mortality) by socioeconomic group and by marital status of the mother. Child mortality rates were nearly halved between 1885 and 1910. Socioeconomic differentials in mortality between the four social classes emerged from 1891 as the overall mortality declined. The decline was sharpest in the upper and middle social classes. Children born out of wedlock had higher mortality rates than children of married mothers in all 3 years studied. The social differentials in child mortality risk were substantial and the gradient emerged sharper from 1891 to 1910. The results are in line with studies from England and Wales, Germany and the USA for the same time period. The differentials mostly increased because of a greater decline in mortality among higher socioeconomic groups.

Ethiopia is among the five countries which account for half of the global under-five deaths, with the under-five mortality rate of 67 deaths/1000 live births in 2016. Ethiopia had significant inequalities in child mortality between rural and urban areas where the risk of child mortality is largely higher in rural than urban areas. Inequalities in the distribution of factors influencing child mortality need to explain the gap between and within urban-rural areas. The study used the risk of child mortality as an outcome variable. Multilevel logistic regression was used as a standard model for assessing the effect of socioeconomic and contextual factors on child mortality. Furthermore, the Blinder-Oaxaca decomposition technique was used to explain the urban-rural, intra-rural, and intra-urban inequalities in child mortality. The birth order and sanitation type seem to be the most important explanatory factors, followed by wealth status in explaining the rural-urban inequality of 39 deaths/1000 children. Mean proportion indicates that there would be 47 deaths/1000 children for urban poor and 21 deaths/1000 children for urban non-poor, resulting in 26 deaths/1000 children change in urban poor when applying the urban non-poor coefficient and characteristics to urban poor behavior. The findings showed that some residential inequalities in child mortality occur at a level that could be addressed by targeting children, households, and some occurs at a community level that could be addressed by targeting regions. Therefore, any residential sensitive and specific interventions should consider child’s and household’s characteristics, and geographical location.

BACKGROUND AND AIM: Countries in sub-Saharan Africa suffer the highest rates of child mortality worldwide. Urban areas tend to have lower mortality than rural areas, but these comparisons likely mask large within-city inequalities. We aimed to quantify variation in child mortality across neighbourhoods of Accra – Ghana’s capital city. METHODS: We accessed data on 700,000 women aged 25-49 years living in the Greater Accra Metropolitan Area (GAMA) using the most recent Ghana census (2010). We summarised counts of child births and deaths by five-year age group of women and neighbourhood (n=406) and applied indirect demographic methods to convert the summaries to yearly probabilities of death under-five years of age. We fitted a Bayesian spatio-temporal model to the neighbourhood child mortality probabilities to obtain estimates for 2010, and examined the correlation with indicators of neighbourhood environmental and socio-economic conditions. RESULTS:Child mortality varied almost five-fold across neighbourhoods in the GAMA in 2010, ranging from 28 (95% credible interval (CrI): 8-63) to 138 (95% CrI: 111-167) deaths per 1000 live births. Child mortality was highest in the urban core and industrial districts, with a neighbourhood average of 95 deaths per 1000 live births. Peri-urban neighbourhoods performed better, on average, but had greater within-district variation (up to 3.8-fold). Child mortality was negatively correlated with multiple indicators of improved living and socio-economic conditions among peri-urban neighbourhoods. Among urban neighbourhoods however, correlations were weaker or in some cases reversed, including with neighbourhood median household consumption and levels of women’s schooling. CONCLUSIONS:We found substantial child mortality inequalities between and within GAMA’s districts and identified urban neighbourhoods being left behind in child mortality reductions. Improved neighbourhood environmental and socioeconomic conditions in the inner city did not correspond to lower levels of child mortality. Universal access to quality healthcare services can mitigate mortality inequalities where children are born into different circumstances. KEYWORDS: Mortality, Children's environmental health, Spatial statistics, International collaboration

This paper analyses the trend of the socioeconomic inequalities in infant mortality rates in Egypt over the period 1995–2014, using repeated cross-sectional data from the National Demographic and Health Survey. A multivariate logistic regression and concentration indices are used to examine the demographic and socioeconomic correlates of infant mortality, and how the degree of socioeconomic disparities in child mortality rates has evolved over time. We find a significant drop in infant mortality rates from 63 deaths per 1000 live births in 1995 to 22 deaths per 1000 live births in 2014. However, analyzing trends over the study period reveals no corresponding progress in narrowing the socioeconomic disparities in childhood mortality. Infant mortality rates remain higher in rural areas and among low-income families than the national average. Results show an inverse association between infant mortality rates and living standard measures, with the poor bearing the largest burden of early child mortality. Though the estimated concentration indices show a decline in the degree of socioeconomic inequality in child mortality rates over time, infant mortality rate among the poor remains twice the rate of the richest wealth quintile. Nonetheless, this decline in the degree of socioeconomic inequality in child mortality is not supported by the results of the multivariate logistic regression model. Results of the logistic model show higher odds of infant mortality among rural households, children who are twins, households with risky birth intervals. We find no statistically significant association between infant mortality and child’s sex, access to safe water, mothers’ work, and mothers’ nutritional status. Infant mortality is negatively associated with household wealth and regular health care during pregnancy. Concerted effort and targeting intervention measures are still needed to reduce the degree of socioeconomic and regional inequalities in child health, including infant mortality, in Egypt.

BackgroundThe existence of socio-economic inequalities in child mortality is well documented. African cities grow faster than cities in most other regions of the world; and inequalities in African cities are thought to be particularly large. Revealing health-related inequalities is essential in order for governments to be able to act against them. This study aimed to systematically compare inequalities in child mortality across 10 major African cities (Cairo, Lagos, Kinshasa, Luanda, Abidjan, Dar es Salaam, Nairobi, Dakar, Addis Ababa, Accra), and to investigate trends in such inequalities over time.MethodsData from two rounds of demographic and health surveys (DHS) were used for this study (if available): one from around the year 2000 and one from between 2007 and 2011. Child mortality rates within cities were calculated by population wealth quintiles. Inequality in child mortality was assessed by computing two measures of relative inequality (the rate ratio and the concentration index) and two measures of absolute inequality (the difference and the Erreyger’s index).ResultsMean child mortality rates ranged from about 39 deaths per 1,000 live births in Cairo (2008) to about 107 deaths per 1,000 live births in Dar es Salaam (2010). Significant inequalities were found in Kinshasa, Luanda, Abidjan, and Addis Ababa in the most recent survey. The difference between the poorest quintile and the richest quintile was as much as 108 deaths per 1,000 live births (95% confidence interval 55 to 166) in Abidjan in 2011–2012. When comparing inequalities across cities or over time, confidence intervals of all measures almost always overlap. Nevertheless, inequalities appear to have increased in Abidjan, while they appear to have decreased in Cairo, Lagos, Dar es Salaam, Nairobi and Dakar.ConclusionsConsiderable inequalities exist in almost all cities but the level of inequalities and their development over time appear to differ across cities. This implies that inequalities are amenable to policy interventions and that it is worth investigating why inequalities are higher in one city than in another. However, larger samples are needed in order to improve the certainty of our results. Currently available data samples from DHS are too small to reliably quantify the level of inequalities within cities.

This paper measures the degree of inequality in child mortality rates across districts in India using data from the 1981, 1991 and 2001 Indian population censuses. Results show that child mortality is more concentrated in less developed districts in all three census years. Furthermore, between 1981 and 2001, the inequality in child mortality seems to have increased to the advantage of the more developed districts. In the decomposition analysis, it is found that while a more equitable distribution of medical facilities and safe drinking water across districts has contributed to reducing inequality in child mortality between 1981 and 1991, different levels of structural change among districts have been responsible for a very large part of the inequality in child mortality to the advantage of the more developed districts in all three census years. The paper concludes with some brief comments on the policy implications of the findings.

SummaryFrom analysis of the 1974 Korean National Fertility Survey data, the changing patterns of demographic and socioeconomic determinants of infant and child mortality are generalized. The pattern for infant mortality is: (1) in a traditional society demographic factors affect infant mortality more than socioeconomic factors; (2) at the early stage of development, demographic factors are replaced by socioeconomic factors as the main determinants; (3) when the difference in living standards between social classes narrows, the socioeconomic differentials in mortality also diminish; and (4) at the stage of high development the effects of demographic factors remain although the absolute differences are very small. But the pattern of changing determinants of child mortality is nearly the reverse of that of infant mortality.

Background:We aimed to measure changes in socioeconomic inequality in child mortality in Iran.Methods:A secondary data analysis of two Demographic and Health Surveys (DHS 2000 and 2010) was undertaken. Neonatal, infant and under-5 mortality rates were estimated directly from complete birth history. Economic quintiles were constructed using principal component analysis. Changes in inequality were measured using odds ratios, mortality rates, and concentration curves and indices.Results:Based on the compared measures, inequalities in neonatal, infant, and under-5 mortality declined between the two surveys. The poorest-to-richest neonatal, infant and under-5 mortality odds ratios in 2000 were 1.69 (95% CI= 1.3–2.07), 2.85 (95% CI= 1.96–4.1) and 1.98 (95% CI= 1.64–2.3), respectively. Whereas these mortality odds ratios in 2010 had fallen to 1.65 (95% CI= 0.95–2.9), 1.47 (95% CI=0.5–4) and 1.85 (95% CI=1.13–3), respectively. Moreover, mortality rates in all economic quintiles experienced a decreasing trend. Neonatal, infant, and under-5 mortality concentration indices in 2000 were −0.15, −0.26, and −0.17 respectively. Whereas concentration indices in 2010 had dropped to −0.13, −0.11, and −0.14, respectively. Concentration curves dominance test revealed that there was a statistically significant reduction in inequality in infant and under-5 mortalities.Conclusion:Despite substantial reduction in child mortality rates and narrowing of the gap between poor and rich people, socioeconomic inequality in child mortalities disfavoring worse-off groups still exists. Combination of child health-related efforts that aim to reach to those children born in poor households alongside with pro-equity programs in other sectors of society may further reduce infant, under-5, and particularly neonatal mortality across economic quintiles in Iran.

In low- and middle-income countries (LMICs), the probability of dying in childhood is strongly related to the socio-economic position of the parents or household in which the child is born. This article reviews the evidence on the magnitude of socio-economic inequalities in childhood mortality within LMICs, discusses possible causes and highlights entry points for intervention. Sources of data Evidence on socio-economic inequalities in childhood mortality in LMICs is mostly based on data from household surveys and demographic surveillance sites. Childhood mortality is systematically and considerably higher among lower socio-economic groups within countries. Also most proximate mortality determinants, including malnutrition, exposure to infections, maternal characteristics and health care use show worse levels among more deprived groups. The magnitude of inequality varies between countries and over time, suggesting its amenability to intervention. Reducing inequalities in childhood mortality would substantially contribute to improving population health and reaching the Millennium Development Goals (MDGs). The contribution of specific determinants, including national policies, to childhood mortality inequalities remains uncertain. What works to reduce these inequalities, in particular whether policies should be universal or targeted to the poor, is much debated. The increasing political attention for addressing health inequalities needs to be accompanied by more evidence on the contribution of specific determinants, and on ways to ensure that interventions reach lower socio-economic groups.

This paper examines the trends in economic inequalities with respect to infant and child mortality in India using three rounds of the Indian National Family Health Survey conducted in 1992–1993, 1998–1999, and 2005–2006. The paper uses concentration index, and pooled discrete-time survival regression model to examine the aforementioned trends and regional patterns. The findings suggest a decreasing trend in economic inequality in infant mortality but an upward trend in economic inequality in child mortality in India. Economic inequalities in infant mortality have narrowed in the southern region, whereas they have widened in the western region and risen in the northern region. However, mixed trends in concentration indices were found in the different regions of India in the case of child mortality.