The effects of community clustering on under-five mortality in India: a parametric shared frailty modelling approach

Revisiting Factors Influencing Under-Five Mortality in India: The Application of a Generalised Additive Cox Proportional Hazards Model

BACKGROUND

Despite the implementation of various preventive measures, India continues to experience an alarmingly high under-five mortality rate (U5MR). The most recent nationwide data on U5MRs has provided an opportunity to re-examine the associated factors of U5MRs using advanced techniques. This study attempted to identify the associated determinants of U5MRs via the generalised additive Cox proportional hazards method.

METHODS

This study analysed the fifth round of unit-level data for 213,612 children from the National Family Health Survey (NFHS-5) to identify the risk factors associated with U5MRs, employing a generalised additive Cox proportional hazards regression analysis.

RESULTS

The children who had a length of pregnancy of less than 9 months had a 2.621 (95% CI: 2.494, 2.755) times greater hazard of U5MRs than the children who had a gestational period of 9 months or more. The non-linear association with U5MRs was highest in the mother's age, followed by the mother's haemoglobin, the mother's education, and household wealth score. The relationships between the mother's age and the mother's haemoglobin level with the U5MR were found to be U-shaped.

CONCLUSIONS

This study highlights the importance of addressing maternal and socioeconomic factors while improving access to healthcare services in order to reduce U5MRs in India. Furthermore, the findings underscore the necessity for more sophisticated approaches to healthcare delivery that consider the non-linear relationships between predictor variables and U5MRs.

Clustering of child deaths among families in low and middle-income countries: A meta-analysis

Background and Aims

Several studies have examined the phenomenon of "death clustering," in which two or more children born to the same mother or from the same family die at an early age. Therefore, a scientific examination of the results is essential to understand how the survival status of the older siblings affects the survival of the younger siblings. By using meta-analysis, this study aims to provide a quantitative synthesis of the results of studies on "child death clustering" in low- and middle-income countries (LMICs).

Methods

This study followed the PRISMA-P 2015 guidelines. We used four electronic databases-PubMed, Medline, Scopus, and Google Scholar with search and citation analysis capabilities. Initially, 140 studies were identified, but only 27 met the eligibility criteria eventually. These were studies that had used the death of a previous child as a covariate to determine the survival status of the index child. The heterogeneity and the publication bias of the studies were examined using the Cochran test, I 2 statistic, and Egger's meta-regression test.

Results

The pooled estimate of 114 study estimates for LMICs contains some bias. India's 37 study estimates were distributed more or less equally along the middle line, indicating no publication bias, while there was a slight bias in the estimates for Africa, Latin America, and Bangladesh. The odds of experiencing the death of the index child in the selected LMICs were 2.3 times higher for mothers who had lost any prior child as compared to those mothers who had not had any prior child loss. For African mothers, the odds were five times higher, whereas for Indian mothers, the odds were 1.66 times higher. Mothers' characteristics, such as education, occupation, health-seeking behavior, and maternal competence, significantly affect the child's survival status.

Conclusion

Achieving the sustainable development goals would not be possible if mothers in countries experiencing high levels of under-five mortality are not provided with better health and nutrition facilities. Mothers who have lost multiple children should be targeted for assistance.

Differential impact of maternal education on under-five mortality in rural and urban India

Under-five mortality rate (U5MR) differs by rural-urban place of residence and mother's education; however, the rural-urban gap in U5MR by mother's educational attainment is unclear in the existing literature. Using five rounds of the national family health surveys (NFHS I-V) conducted between 1992-93 and 2019-21 in India, this study estimated the main and interaction effects of rural-urban and maternal education on U5MR. The mixed effect Cox proportional hazard (MECPH) model was used to predict the risk of under-five mortality (U5M). The finding shows that unadjusted U5MR remained 50 per cent higher in rural areas than in urban areas across the surveys. Whereas, after controlling for demographic, socioeconomic, and maternal health care predictors of U5M, the MECPH regression results indicated that urban children had a higher risk of death than their rural counterparts in NFHS I-III. However, there are no significant rural-urban differences in the last two surveys (NFHS IV -V). In addition, increasing maternal education levels were associated with lower U5M in all surveys. Though, in recent years, primary education has had no significant effect. The U5M risk was additionally lower for urban children than rural children whose mothers had secondary and higher education by NFHS-III; however, this additional urban advantage was no longer significant in recent surveys. The higher impact of secondary education on U5MR in urban areas in the past may be attributed to poor socio-economic, healthcare conditions in rural areas. Overall, maternal education, particularly secondary education, remained a protective factor for U5M in both rural and urban areas, even after controlling for predictors. Therefore, there is a need to increase the focus on secondary education for girls for a further decline in U5M.

Infant Death Clustering in the Quarter of a Century in India: A Decomposition Analysis

The study aims to examine the clustering of infant deaths in India and the relative contribution of infant death clustering after accounting for the socio-economic and biodemographic factors that explain the decline in infant deaths. The study utilized 10 years of birth history data from three rounds of the National Family Health Survey (NFHS). The random effects dynamic probit model was used to decompose the decline in infant deaths into the contributions by the socio-economic and demographic factors, including the lagged independent variable, the previous infant death measuring the clustering of infant deaths in families. The study found that there has been a decline in the clustering of infant deaths among families during the past two and half decades. The simulation result shows that if the clustering of infant deaths in families in India was completely removed, there would be a decline of nearly 30 percent in the infant mortality rate (IMR). A decomposition analysis based on the dynamic probit model shows that for NFHS-1 and NFHS-3, in the total change of the probability of infant deaths, the rate of change for a given population composition contributed around 45 percent, and about 44 percent was explained by a compositional shift. Between NFHS-3 and NFHS-4, the rate of change for a given population composition contributed 86%, and the population composition for a given rate contributed 10% to the total change in the probability of infant deaths. Within this rate, the contribution of a previous infant was 0.8% and the mother's age was 10%; nearly 31% was contributed by the region of residence, 69% by the mother's education, and around 20% was contributed by the wealth index and around 8.7% by the sex of the child. The mother's unobserved factors contributed more than 50 percent to the variability of infant deaths in all the survey rounds and was also statistically significant (p < 0.01). Bivariate analysis suggests that women with two or more infant losses were much less likely to have full immunization (10%) than women with no infant loss (62%), although institutional delivery was high among both groups of women.