Socio-economic determinants of child mortality in Pakistan and the moderating role of household’s wealth index

Background Child mortality is an important social indicator that describes the health conditions of a country as well as determines the country’s overall socio-economic development. The Government of Pakistan has been struggling to reduce child mortality (67.2 per thousand live births in 2019). Pakistan could not achieve the target set for Millennium Development Goals to reduce child mortality and still working to meet the target set by the Sustainable Development Goals. This study has investigated the socio-economic determinants of child mortality in Pakistan by using household-level data. Socio-economic characteristics related to women (mothers) and households have been considered as possible determinants of child mortality. The moderating role of a household’s wealth index on the association between woman’s education and child mortality has also been investigated. Methods The comprehensive dataset of the Pakistan Demographic and Health Survey 2017–18 has been used to explore the determinants of child mortality by using multivariable logistic regression. The interaction term of women’s education and household wealth index has been used to investigate the moderating role of the household’s wealth index. Results The results indicate that the likelihood of child mortality decreases with an increase in women’s education, their empowerment, their husband’s education, the wealth status of their households, access to clean drinking water, access to toilet facilities, and exposure to mass media. Whereas, an increase in unmet need for family planning increases the likelihood of child mortality. The study also identified the moderating role of a household’s wealth index on the association between woman’s education and child mortality. Conclusions Household wealth status moderates the association between women’s education and child mortality. The absolute slope of the curve showing the association of women’s education and child mortality is higher (more negative) for richer households than poorer households. It implies that a household’s wealth status strengthens the relationship between women’s education and child mortality. With the increase in the household’s wealth status, the effect of a mother’s education on child mortality becomes more pronounced.

Association of breast feeding and birth interval with child mortality in Pakistan: a cross-sectional study using nationally representative Demographic and Health Survey data

ObjectivesThis study analysed the association between breast feeding (BF) and birth interval (BI) (both succeeding and preceding) with neonatal mortality (NM), infant mortality (IM) and under-5 mortality (U5M).DesignThis cross-sectional study used data from the Pakistan Demographic and Health Survey 2017–2018.SettingsAll provinces, Islamabad and Federally Administered Tribal Areas were included in the analysis.ParticipantsA total of 12 769 children born to ever-married multiparous women aged 30–49 years who gave live birth within 5 years preceding the interview. Multiple births are not included.Data analysisMultivariate logistic regression analysis was used.ResultsWe found that BF was associated with nearly 98% lower risk of NM (OR 0.015; 95% CI: 0.01 to 0.03; p<0.001), 96% lower risk of IM (OR 0.038; 95% CI: 0.02 to 0.06; p<0.001) and 94% lower risk of U5M (OR 0.050; 95% CI: 0.03 to 0.08; p<0.001). Compared with optimal preceding birth interval (PBI) (36+ months), short PBI (<18 months) was associated with around six times higher risk of NM (OR 5.661; 95% CI: 2.78 to 11.53; p<0.001), over five times risk of IM (OR 4.704; 95% CI: 2.70 to 8.19; p<0.001) and over five times risk of U5M (OR 4.745; 95% CI: 2.79 to 8.07; p<0.001). Disaggregating the data by child’s gender, place of residence and mother’s occupational status showed that being ever breast fed was associated with a smaller risk of NM, IM and U5M in all three disaggregations. However, the risk of smaller PBI <18 months was generally more pronounced in female children (NM and U5M) or when the children lived in rural areas (NM, IM and U5M). PBI <18 months was associated with greater risk of NM and IM, and smaller risk of U5M when mothers did a paid job.ConclusionThis study’s significance lies in the fact that it has found BF and BI to be consistent protective factors against NM, IM and U5M. Given Pakistan’s economic constraints, optimal BF and BI are the most cost-effective interventions to reduce child mortality.

Quantifying within-city inequalities in child mortality across neighbourhoods in Accra, Ghana: a Bayesian spatial analysis

ObjectiveCountries 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 estimate rates of under-five mortality (U5M) at the neighbourhood level for Ghana’s Greater Accra Metropolitan Area (GAMA) and measure the extent of intraurban inequalities.MethodsWe accessed data on >700 000 women aged 25–49 years living in 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 before age five years. We fitted a Bayesian spatiotemporal model to the neighbourhood U5M probabilities to obtain estimates for the year 2010 and examined their correlations with indicators of neighbourhood living and socioeconomic conditions.ResultsU5M varied almost five-fold across neighbourhoods in GAMA in 2010, ranging from 28 (95% credible interval (CrI) 8 to 63) to 138 (95% CrI 111 to 167) deaths per 1000 live births. U5M was highest in neighbourhoods of the central urban core and industrial areas, with an average of 95 deaths per 1000 live births across these neighbourhoods. Peri-urban neighbourhoods performed better, on average, but rates varied more across neighbourhoods compared with neighbourhoods in the central urban areas. U5M was negatively correlated with multiple indicators of improved living and socioeconomic conditions among peri-urban neighbourhoods. Among urban neighbourhoods, correlations with these factors were weaker or, in some cases, reversed, including with median household consumption and women’s schooling.ConclusionReducing child mortality in high-burden urban neighbourhoods in GAMA, where a substantial portion of the urban population resides, should be prioritised as part of continued efforts to meet the Sustainable Development Goal national target of less than 25 deaths per 1000 live births.

THE MILLENNIUM DEVELOPMENT GOALS (MDGS) AND GLOBAL POVERTY: HAVE WE REALLY FAILED?

MDGs was implemented over the period 2000-2015 by the United Nations along with 189 members states to tackle several crucial issues, namely ‘extreme poverty and hunger, universal primary education, gender equality and woman empowerment, child mortality, maternal health, HIV/AIDS, malaria and other diseases, environmental sustainability and globally developmental partnership’ (United Nations 2014). After 2015, the MDGs which was adopted by 189 members states was evaluated by comparing between the MDGs’ targets and its results. By using archival research data, this paper argues that the MDGs have not really failed in fighting against global poverty, because the MDGs showed a global willingness to alleviate numbers of poverty and the MDGs have achieved prominent improvement.

A Spatial Survival Model for Risk Factors of Under-Five Child Mortality in Kenya

Child mortality is high in Sub-Saharan Africa compared to other regions in the world. In Kenya, the risk of mortality is assumed to vary from county to county due to diversity in socio-economic and even climatic factors. Recently, the country was split into 47 different administrative regions called counties, and health care was delegated to those county governments, further aggravating the spatial differences in health care from county to county. The goal of this study is to evaluate the effects of spatial variation in under-five mortality in Kenya. Data from the Kenya Demographic Health Survey (KDHS-2014) consisting the newly introduced counties was used to analyze this risk. Using a spatial Cox Proportional Hazard model, an Intrinsic Conditional Autoregressive Model (ICAR) was fitted to account for the spatial variation among the counties in the country while the Cox model was used to model the risk factors associated with the time to death of a child. Inference regarding the risk factors and the spatial variation was made in a Bayesian setup based on the Markov Chain Monte Carlo (MCMC) technique to provide posterior estimates. The paper indicate the spatial disparities that exist in the country regarding child mortality in Kenya. The specific counties have mortality rates that are county-specific, although neighboring counties have similar hazards for death of a child. Counties in the central Kenya region were shown to have the highest hazard of death, while those from the western region had the lowest hazard of death. Demographic factors such as the sex of the child and sex of the household head, as well as social economic factors, such as the level of education, accounted for the most variation when spatial differences were factored in. The spatial Cox proportional hazard frailty model performed better compared to the non-spatial non-frailty model. These findings can help the country to plan health care interventions at a subnational level and guide social and health policies by ensuring that counties with a higher risk of Under Five Child Mortality (U5CM) are considered differently from counties experiencing a lower risk of death.

Case Study in the COVID-19 Pandemic: Stunting, Low Birth Weight, Maternal Mortality and Infant Mortality in Semarang, Central Java-Indonesia

Background and Objective: Stunting, low birth weight, maternal death, and child mortality have all become public health issues in recent years, particularly in Semarang, Indonesia. Simultaneously, the COVID-19 pandemic is spreading. Between the years 2019 and 2021. Methods: The Semarang City Health Service's secondary data analysis strategy was combined with a quantitative descriptive research methodology in this study. To evaluate numerical patterns in stunting, low birth weight, maternal death, and infant mortality in the data, simple regression were utilized. Results: According to the findings, the trend of stunting (modeling results y = 35,236 x + 361.77) and maternal mortality (modeling results 0.0218x+1.2921) increased between 2019 and 2021, whereas the trend of low birth weight (modeling results y = - 0.5425x+60.008) and child mortality (modeling results y = -0.0028x+ 2.202) decreased. The number of low birth weight has the lowest trend value, while the stunting rate has the greatest. Conclusion: Stunting rates increased, the low birth weight dropped, maternal mortality increased, and child mortality decreased in Semarang. The conditions of the Covid-19 epidemic have at least influenced this condition.

Child mortality in England during the first year of the COVID-19 pandemic

ObjectivesTo quantify the relative risk (RR) of childhood deaths across the whole of England during the first year of the COVID-19 pandemic, compared with a similar period of 2019.DesignThis work is based on data collected by the National Child Mortality Database (NCMD). Deaths from 1 April 2020 until 31 March 2021 (2020–2021) were compared with those from the same period of 2019–2020. RR and excess mortality were derived for deaths in 2020–2021 vs 2019–2020.SettingAll deaths reported to NCMD in England of children under 18 years of age, between April 2019 and March 2021.Participants6490 deaths of children, under the age of 18 years, reported to the NCMD over the study period.ResultsChildren had similar demographics in the 2 years. There were 356 (198–514) fewer deaths in 2020–2021 than in 2019–2020 (RR 0.90 (0.85 to 0.94), p<0.001). Deaths from infection (RR 0.49 (0.38 to 0.64)) and from other underlying medical conditions (RR 0.75 (0.68 to 0.82)) were lower in 2020–2021 than 2019–2020, and weak evidence (RR 0.50 (0.23 to 1.07), p=0.074) that this was also true of deaths from substance abuse.ConclusionsChildhood mortality in England during the first year of the SARS-CoV-2 pandemic was lower than expected, with over 300 fewer deaths than the preceding 12 months. The greatest reduction was in children less than 10 years old. It is important that we learn from this effect that potentially offers alternative ways to improve the outcome for the most vulnerable children in our society.