Dataset Information

Nonadult Supervision of Children in Low- and Middle-Income Countries: Results from 61 National Population-Based Surveys.

ABSTRACT: Despite scarce empirical research in most countries, evidence has shown that young children are unsupervised or under the supervision of another young child while their adult caregivers attend work or engage in other activities outside the home. Lack of quality supervision has been linked to unintentional childhood injuries and other negative outcomes. Nationally representative, population-based data from rounds four and five of the Multiple Indicator Cluster Surveys (MICS) and four to eight of the Demographic and Health Surveys (DHS) from 61 low- and middle-income countries were used to estimate prevalence and socio-economic factors associated with leaving children under five years old home alone or under the care of another child younger than 10 years of age. Socio-economic factors included age and sex of the child, rurality, wealth, maternal education, and household composition. Large variations in the prevalence rates (0.1?35.3% for children home alone and 0.2?50.6% for children supervised by another child) and associated factors have been recorded within and across regions and countries. Understanding why and under what conditions children are home alone or under the supervision of another child is crucial to the development of suitable policies and interventions to protect young children, promote healthy growth, and support caregivers.

SUBMITTER: Ruiz-Casares M

PROVIDER: S-EPMC6121274 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature

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Nonadult Supervision of Children in Low- and Middle-Income Countries: Results from 61 National Population-Based Surveys.

Ruiz-Casares Mónica M Nazif-Muñoz José Ignacio JI Iwo René R Oulhote Youssef Y

International journal of environmental research and public health 20180724 8

Despite scarce empirical research in most countries, evidence has shown that young children are unsupervised or under the supervision of another young child while their adult caregivers attend work or engage in other activities outside the home. Lack of quality supervision has been linked to unintentional childhood injuries and other negative outcomes. Nationally representative, population-based data from rounds four and five of the Multiple Indicator Cluster Surveys (MICS) and four to eight of ...[more]

PMID: 30042321

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Project description:Gestational weight gain (GWG) estimates enable the identification of populations of women at risk for adverse outcomes. We described GWG distribution in low- and middle-income countries (LMICs). Demographic and Health Surveys and other national surveys were used to calculate the average GWG by regressing the weight of pregnant women (15-49 years) at the time of the interview on their gestational age, adjusting for sociodemographic factors. A mixed-effects hierarchical model was built with survey-specific GWG as the dependent variable and restricted cubic splines for survey year, super-region, and country-level covariates (total fertility rate, gross domestic product, and average female body mass index) to predict the national, regional, and income level average GWG in 2020. Uncertainty ranges (UR) were obtained using bootstrap. Estimates were compared with the Institute of Medicine's GWG recommendations for women with normal weight (11.5kg) and underweight (12.5kg). Survey data were available for 70 LMICs (234 data points, 1991-2022). Predicted country-specific GWG for 2020 ranged from 2.6 to 13.5kg. Ten countries presented estimates above the recommendation for women with underweight; nine of which were from Central Europe, Eastern Europe, and Central Asia; apart from one, these were upper-middle income. Regional GWG was estimated at 5.4kg (95%UR 3.1,7.7) in Sub-Saharan Africa; 6.2kg (95%UR 3.4,9.0) in North Africa and the Middle East; 8.6kg (95%UR 6.0,11.3) in South Asia; 9.3kg (95%UR 6.2,12.3) in Southeast Asia, East Asia, and Oceania; 10.0kg (95%UR 7.1,12.9) in Latin America and the Caribbean; and 13.0kg (95%UR 9.0,16.9) in Central and Eastern Europe, and Central Asia. A gradient was observed across income: 5.3kg (95%UR 2.7,7.9) for low-income, 7.6kg (95%UR 5.2,10.1) for lower-middle-income, and 9.8kg (95%UR 7.1,12.5) for upper-middle-income countries. No income group achieved the minimum recommended weight gain. GWG was estimated to be insufficient in almost all LMICs. Improved data and monitoring are crucial for impactful interventions.

Project description:BackgroundThe strength of a health system-and ultimately the health of a population-depends to a large degree on health worker performance. However, insufficient support to build, manage and optimize human resources for health (HRH) in low- and middle-income countries (LMICs) results in inadequate health workforce performance, perpetuating health inequities and low-quality health services.MethodsThe USAID-funded Human Resources for Health in 2030 Program (HRH2030) conducted a systematic review of studies documenting supervision enhancements and approaches that improved health worker performance to highlight components associated with these interventions' effectiveness. Structured by a conceptual framework to classify the inputs, processes, and results, the review assessed 57 supervision studies since 2010 in approximately 29 LMICs.ResultsOf the successful supervision approaches described in the 57 studies reviewed, 44 were externally funded pilots, which is a limitation. Thirty focused on community health worker (CHW) programs. Health worker supervision was informed by health system data for 38 approaches (67%) and 22 approaches used continuous quality improvement (QI) (39%). Many successful approaches integrated digital supervision technologies (e.g., SmartPhones, mHealth applications) to support existing data systems and complement other health system activities. Few studies were adapted, scaled, or sustained, limiting reports of cost-effectiveness or impact.ConclusionBuilding on results from the review, to increase health worker supervision effectiveness we recommend to: integrate evidence-based, QI tools and processes; integrate digital supervision data into supervision processes; increase use of health system information and performance data when planning supervision visits to prioritize lowest-performing areas; scale and replicate successful models across service delivery areas and geographies; expand and institutionalize supervision to reach, prepare, protect, and support frontline health workers, especially during health emergencies; transition and sustain supervision efforts with domestic human and financial resources, including communities, for holistic workforce support. In conclusion, effective health worker supervision is informed by health system data, uses continuous quality improvement (QI), and employs digital technologies integrated into other health system activities and existing data systems to enable a whole system approach. Effective supervision enhancements and innovations should be better integrated, scaled, and sustained within existing systems to improve access to quality health care.

Project description:BackgroundUnderstanding subnational variation in age-specific fertility rates (ASFRs) and total fertility rates (TFRs), and geographical clustering of high fertility and its determinants in low-income and middle-income countries, is increasingly needed for geographical targeting and prioritising of policy. We aimed to identify variation in fertility rates, to describe patterns of key selected fertility determinants in areas of high fertility.MethodsWe did a subnational analysis of ASFRs and TFRs from the most recent publicly available and nationally representative cross-sectional Demographic and Health Surveys and Multiple Indicator Cluster Surveys collected between 2010 and 2016 for 70 low-income, lower-middle-income, and upper-middle-income countries, across 932 administrative units. We assessed the degree of global spatial autocorrelation by using Moran's I statistic and did a spatial cluster analysis using the Getis-Ord Gi* local statistic to examine the geographical clustering of fertility and key selected fertility determinants. Descriptive analysis was used to investigate the distribution of ASFRs and of selected determinants in each cluster.FindingsTFR varied from below replacement (2·1 children per women) in 36 of the 932 subnational regions (mainly located in India, Myanmar, Colombia, and Armenia), to rates of 8 and higher in 14 subnational regions, located in sub-Saharan Africa and Afghanistan. Areas with high-fertility clusters were mostly associated with areas of low prevalence of women with secondary or higher education, low use of contraception, and high unmet needs for family planning, although exceptions existed.InterpretationSubstantial within-country variation in the distribution of fertility rates highlights the need for tailored programmes and strategies in high-fertility cluster areas to increase the use of contraception and access to secondary education, and to reduce unmet need for family planning.FundingWellcome Trust, the UK Foreign, Commonwealth and Development Office, and the Bill & Melinda Gates Foundation.

Dataset Information

Nonadult Supervision of Children in Low- and Middle-Income Countries: Results from 61 National Population-Based Surveys.

Publications

Nonadult Supervision of Children in Low- and Middle-Income Countries: Results from 61 National Population-Based Surveys.

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