Disentangling the link between social determinants of health and child survival in Nigeria during the Sustainable Development Goals era: a hierarchical path analysis of time-to-event outcome

While social determinants of health have been perennially linked to child survival in resource-limited countries, the precise and tested pathways to effect are not clearly understood. The objective of this study was therefore to identify the critical pathways as posited a priori in a model through which social factors (at maternal, household, and community levels) determine neonatal, infant, and under-five mortalities in Nigeria. Using a novel analytic approach (hierarchical path modelling for predicting accelerated failure time) to estimate (in)direct and total effects of social determinants of child survival, we analysed 30,960 live births (weighted data for representativeness), obtained from the 2016/2017 Nigeria Multiple Indicator Cluster Survey. There were three outcome variables: time until occurrence of neonatal, infant, and under-five mortalities. The independent variables were layered factors related to child, maternal, household and community. Geographical region, rurality of residence, infrastructural development, maternal education, contraceptive use, marital status, and maternal age at birth were found to operate more indirectly on neonatal, infant, and under-five survival. Child survival is due to direct effects of child's sex (female), gestational type (singleton), birth spacing (children whose mothers delivered at least two years apart), and maternal age at delivery (20-34 years). According to the path coefficients, the indirect effects of geographical regions are the most influential determinants of child survival, accounting for 30% (neonatal), 37.1% (infant) and 39.9% (under-five) of the total effects. This study offers comprehensive set of factors, and linked pathways, at the maternal, household, and community levels that are associated with child survival in Nigeria. To accelerate progress towards Sustainable Development Goal targets for child survival and reduce geographical inequities, stakeholders should implement more impactful policies that promote maternal education, contraceptive use and improve living conditions of women (especially in rural areas of northern Nigeria). Future research should focus on identifying the most effective interventions for addressing these social determinants of child survival in Nigeria.

A double-Cox model for non-proportional hazards survival analysis with frailty

The Cox regression, a semi-parametric method of survival analysis, is extremely popular in biomedical applications. The proportional hazards assumption is a key requirement in the Cox model. To accommodate non-proportional hazards, we propose to parameterize the shape parameter of the baseline hazard function using the additional, separate Cox-regression term which depends on the vector of the covariates. This parametrization retains the general form of the hazard function over the strata and is similar to one in Devarajan and Ebrahimi (Comput Stat Data Anal. 2011;55:667-676) in the case of the Weibull distribution, but differs for other hazard functions. We call this model the double-Cox model. We formally introduce the double-Cox model with shared frailty and investigate, by simulation, the estimation bias and the coverage of the proposed point and interval estimation methods for the Gompertz and the Weibull baseline hazards. For real-life applications with low frailty variance and a large number of clusters, the marginal likelihood estimation is almost unbiased and the profile likelihood-based confidence intervals provide good coverage for all model parameters. We also compare the results from the over-parametrized double-Cox model to those from the standard Cox model with frailty in the case of the scale-only proportional hazards. The model is illustrated on an example of the survival after a diagnosis of type 2 diabetes mellitus. The R programs for fitting the double-Cox model are available on Github.

Time to Death and Its Predictors Among Infants in Ethiopia: Multilevel Mixed-Effects Parametric Survival Analysis Using the 2019 Ethiopian Mini Demographic Health Survey

Introduction

Three years ahead of the plan, Ethiopia has met Millennium Development Goal 4 of reducing under-five mortality. Additionally, the nation is on track to achieve the Sustainable Development Goal of putting an end to preventable child mortality. Despite this, recent data from the nation showed that there were 43 infant deaths for every 1000 live births. Moreover, the country has fallen short of the 2015 Health Sector Transformation Plan goal, with an anticipated infant mortality rate of 35 deaths per 1000 live births in 2020. Thus, this study aims to identify the time to death and its predictors among Ethiopian infants.

Methods

This study used the 2019 Mini-Ethiopian Demographic and Health Survey data set to conduct a retrospective study. The analysis used survival curves and descriptive statistics. Multilevel mixed-effects parametric survival analysis was applied to identify the predictors of infant mortality.

Results

The estimated mean survival time of infants was 11.3 months (95% CI: 11.1, 11.4). Women's current pregnancy status, family size, age of women, previous birth interval, place of delivery, and mode of delivery were significant individual-level predictors of infant mortality. Infants born with less than 24 months' birth interval had a 2.29 times higher estimated risk of death (AHR = 2.29, 95% CI: 1.05, 5.02). Infants born at home were 2.48 times more likely to die than those born in a health facility (AHR = 2.48, 95% CI: 1.03, 5.98). At the community level, women's education was the only statistically significant predictor of infant death.

Conclusion

The risk of infant death was higher before the first month of life, typically shortly after birth. Healthcare programs should put a strong emphasis on efforts to space out births and make institutional delivery services more readily accessible to mothers in Ethiopia to address the infant mortality challenges.

Factors affecting the duration of gestation among women taking prenatal care at Gondar referral hospital, Ethiopia

Background

Pregnant women taking prenatal care is vital for the health of the mother and the fetus. The duration of pregnancies provides a useful measure of a woman's natural length of pregnancy and may help in predicting an individual woman's due date. The objective of this study was to understand the factors affecting the duration of gestation among women taking prenatal care in Gondar referral hospital, Ethiopia.

Methods

A quantitative research design using secondary data available in the form of antenatal care (ANC) cards in the Gondar teaching referral hospital data set. Kaplan–Meier estimate was used to explain the median survival time of duration of gestation. A multivariate AFT model was performed to identify the factors related to the duration of gestation among women.

Results

The mean time of the length of pregnancy was 39.5 weeks. The factors such as, the age of women, number of children, number of doctor consultations, and the stage of gestation were found to be statistically significant (p < 0.05) for the survival time of time to birth of pregnant women in Ethiopia. Weibull AFT model was found to be the best model for predicting the time to birth of pregnant women in Ethiopia.

Conclusion

We did not see associations between length of gestation and blood pressure and bleeding during early pregnancy. We also did not find an association with the presence of disease, which has been associated with the length of pregnancy. The frequency of visiting a doctor during the gestation period enhances the length of the gestation period. The shorter gestation period from the due date is dangerous to the health of both mother and her fetus.

Results From 2 Cohort Studies in Central Africa Show That Clearance of Wuchereria bancrofti Infection After Repeated Rounds of Mass Drug Administration With Albendazole Alone Is Closely Linked to Individual Adherence

Background

Two community trials conducted from 2012 to 2018 in the Republic of Congo and the Democratic Republic of the Congo demonstrated the efficacy of semiannual mass drug administration (MDA) with albendazole (ALB) alone on lymphatic filariasis (LF). However, a high interindividual heterogeneity in the clearance of infection was observed.

Methods

We analyzed trial data to assess the effect of individual adherence to ALB MDA on clearance of circulating filarial antigenemia (CFA) and microfilaremia. Community residents were offered a single dose of ALB every 6 months and tested for LF with a rapid test for CFA at baseline and then annually. CFA test results were scored on a semiquantitative scale. At each round, microfilaremia was assessed in CFA-positive individuals. All CFA-positive individuals for whom at least 1 follow-up measure was available were included in the analyses. Parametric survival models were used to assess the influence of treatment adherence on LF infection indicators.

Results

Of 2658 individuals enrolled in the trials, 394 and 129 were eligible for analysis of CFA and microfilaremia clearance, respectively. After adjusting for age, sex, and initial CFA score, the predicted mean time for clearing CFA was shorter in persons who had taken 2 doses of ALB per year (3.9 years) than in persons who had taken 1 or 0 dose (4.4 and 5.3 years; P < .001 for both). A similar pattern was observed for microfilaremia clearance.

Conclusions

These results demonstrate a clear dose-response relationship for the effect of ALB on clearance of CFA and microfilaremia.

Biomechanical tolerance of whole lumbar spines in straightened posture subjected to axial acceleration

Quantification of biomechanical tolerance is necessary for injury prediction and protection of vehicular occupants. This study experimentally quantified lumbar spine axial tolerance during accelerative environments simulating a variety of military and civilian scenarios. Intact human lumbar spines (T12-L5) were dynamically loaded using a custom-built drop tower. Twenty-three specimens were tested at sub-failure and failure levels consisting of peak axial forces between 2.6 and 7.9 kN and corresponding peak accelerations between 7 and 57 g. Military aircraft ejection and helicopter crashes fall within these high axial acceleration ranges. Testing was stopped following injury detection. Both peak force and acceleration were significant (p < 0.0001) injury predictors. Injury probability curves using parametric survival analysis were created for peak acceleration and peak force. Fifty-percent probability of injury (95%CI) for force and acceleration were 4.5 (3.9-5.2 kN), and 16 (13-19 g). A majority of injuries affected the L1 spinal level. Peak axial forces and accelerations were greater for specimens that sustained multiple injuries or injuries at L2-L5 spinal levels. In general, force-based tolerance was consistent with previous shorter-segment lumbar spine testing (3-5 vertebrae), although studies incorporating isolated vertebral bodies reported higher tolerance attributable to a different injury mechanism involving structural failure of the cortical shell. This study identified novel outcomes with regard to injury patterns, wherein more violent exposures produced more injuries in the caudal lumbar spine. This caudal migration was likely attributable to increased injury tolerance at lower lumbar spinal levels and a faster inertial mass recruitment process for high rate load application. Published 2017. This article is a U.S. Government work and is in the public domain in the USA. J Orthop Res 36:1747-1756, 2018.