Dataset Information

Geospatial estimation of reproductive, maternal, newborn and child health indicators: a systematic review of methodological aspects of studies based on household surveys.

ABSTRACT:

Background

Geospatial approaches are increasingly used to produce fine spatial scale estimates of reproductive, maternal, newborn and child health (RMNCH) indicators in low- and middle-income countries (LMICs). This study aims to describe important methodological aspects and specificities of geospatial approaches applied to RMNCH coverage and impact outcomes and enable non-specialist readers to critically evaluate and interpret these studies.

Methods

Two independent searches were carried out using Medline, Web of Science, Scopus, SCIELO and LILACS electronic databases. Studies based on survey data using geospatial approaches on RMNCH in LMICs were considered eligible. Studies whose outcomes were not measures of occurrence were excluded.

Results

We identified 82 studies focused on over 30 different RMNCH outcomes. Bayesian hierarchical models were the predominant modeling approach found in 62 studies. 5 × 5 km estimates were the most common resolution and the main source of information was Demographic and Health Surveys. Model validation was under reported, with the out-of-sample method being reported in only 56% of the studies and 13% of the studies did not present a single validation metric. Uncertainty assessment and reporting lacked standardization, and more than a quarter of the studies failed to report any uncertainty measure.

Conclusions

The field of geospatial estimation focused on RMNCH outcomes is clearly expanding. However, despite the adoption of a standardized conceptual modeling framework for generating finer spatial scale estimates, methodological aspects such as model validation and uncertainty demand further attention as they are both essential in assisting the reader to evaluate the estimates that are being presented.

SUBMITTER: Ferreira LZ

PROVIDER: S-EPMC7552506 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Publications

Geospatial estimation of reproductive, maternal, newborn and child health indicators: a systematic review of methodological aspects of studies based on household surveys.

Ferreira Leonardo Z LZ Blumenberg Cauane C Utazi C Edson CE Nilsen Kristine K Hartwig Fernando P FP Tatem Andrew J AJ Barros Aluisio J D AJD

International journal of health geographics 20201013 1

<h4>Background</h4>Geospatial approaches are increasingly used to produce fine spatial scale estimates of reproductive, maternal, newborn and child health (RMNCH) indicators in low- and middle-income countries (LMICs). This study aims to describe important methodological aspects and specificities of geospatial approaches applied to RMNCH coverage and impact outcomes and enable non-specialist readers to critically evaluate and interpret these studies.<h4>Methods</h4>Two independent searches were ...[more]

PMID: 33050935

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Project description:BackgroundHousehold survey data are frequently used to measure reproductive, maternal, newborn, child and adolescent health (RMNCAH) service utilisation in low and middle income countries. However, these surveys are typically only undertaken every 5 years and tend to be representative of larger geographical administrative units. Investments in district health management information systems (DHMIS) have increased the capability of countries to collect continuous information on the provision of RMNCAH services at health facilities. However, reliable and recent data on population distributions and demographics at subnational levels necessary to construct RMNCAH coverage indicators are often missing. One solution is to use spatially disaggregated gridded datasets containing modelled estimates of population counts. Here, we provide an overview of various approaches to the production of gridded demographic datasets and outline their potential and their limitations. Further, we show how gridded population estimates can be used as alternative denominators to produce RMNCAH coverage metrics in combination with data from DHMIS, using childhood vaccination as examples.MethodsWe constructed indicators on the percentage of children one year old for diphtheria, pertussis and tetanus vaccine dose 3 (DTP3) and measles vaccine dose (MCV1) in Zambia and Nigeria at district levels. For the numerators, information on vaccines doses was obtained from each country's respective DHMIS. For the denominators, the number of children was obtained from 3 different sources including national population projections and aggregated gridded estimates derived using top-down and bottom-up geospatial methods.ResultsIn Zambia, vaccination estimates utilising the bottom-up approach to population estimation substantially reduced the number of districts with > 100% coverage of DTP3 and MCV1 compared to estimates using population projection and the top-down method. In Nigeria, results were mixed with bottom-up estimates having a higher number of districts > 100% and estimates using population projections performing better particularly in the South.ConclusionsGridded demographic data utilising traditional and novel data sources obtained from remote sensing offer new potential in the absence of up to date census information in the estimation of RMNCAH indicators. However, the usefulness of gridded demographic data is dependent on several factors including the availability and detail of input data.

Project description:BackgroundGeographical variations in the levels and trajectory of health indicators at local level can inform the adaptation of interventions and development of targeted approaches for efficient scale-up of intervention impact. We examined the hypothesis that time trends of a set of reproductive, maternal, newborn, and child health and nutrition (RMNCHN) indicators varied at block-level during the statewide scale-up phase of the Ananya program in Bihar, India.MethodsWe used data on 22 selected indicators from four rounds of the Community-based Household Survey carried out between 2014 and 2017. Indicator levels at each round were estimated for each block. We used hierarchical Bayesian spatiotemporal modelling to smooth the raw estimates for each block with the estimates from its neighbouring blocks, and to examine space-time interaction models for evidence of variations in trends of indicators across blocks. We expressed the uncertainty around the smoothed levels and the trends with 95% credible intervals.ResultsThere was evidence of variations in trends at block level in all but three indicators: facility delivery, public facility delivery, and age-appropriate initiation of complementary feeding. Fifteen indicators showed trends in opposite directions (increases in some blocks and declines in others). All blocks had at least 97.5% probability of a rise in immediate breastfeeding, early pregnancy registration, and having at least four antenatal care visits. All blocks had at least 97.5% probability of a decline in seeking care for pregnancy complications.ConclusionsThe findings underscore the value of monitoring and evaluation at local level for targeted implementation of RMNCHN interventions. There is a need for identifying systematic factors leading to universal trends, or variable contextual or implementation factors leading to variable trends, in order to optimise primary health care program impact.Study registrationClinicalTrials.gov number NCT02726230.

Project description:Diet quality indicators (DQIns) are tools that aim to assess an individual's overall diet quality. Previous reviews focused mainly on health-related outcomes but did not provide detailed information about components, assessment variables, or important methodological issues for the development and application of DQIns in the pediatric age. The current mapping review aims to provide comprehensive guidance regarding DQIns developed through a priori methodology in children aged ≤14 y that have been applied worldwide. A mapping review was conducted, whereby 1665 original articles describing the development, modifications, and updates of DQIns, published up to June 26, 2020, in English and Spanish, were retrieved. A total of 139 articles were identified and classified into 13 subgroups. There were 10 overall DQIns: Healthy Eating Indexes (n = 25), Dietary Diversity Scores (n = 20), Diet Quality Indexes (n = 16), Food Variety Scores (n = 11), Healthy and Unhealthy Scores (n = 11), Feeding and Eating Indexes (n = 10), Diet Quality Scores (n = 5), Nutritional Adequacy and Micronutrients Indexes (n = 5), Dietary Guidelines Indexes (n = 5), and Other Healthy Diet Indexes (n = 13). Three additional subgroups of dietary and lifestyle indicators found were Mediterranean Diet Indexes (n = 10), Diet-Lifestyle Indexes (n = 5), and Breakfast Quality Indexes (n = 3). This compilation of DQIns will help researchers select the most appropriate tool for future epidemiological studies by considering a careful selection of information about the assessment components, scoring methods, and key methodological issues. The main limitations of this review are that, due to its nature, a risk-of-bias assessment was not performed and the article screening was completed in 2 databases (PubMed/MEDLINE and Scopus). More research is needed to identify health-related outcomes associated with DQIns in the pediatric population, using clearer and more standardized methodological criteria.

Project description:BackgroundAside from breastfeeding, there are little data on use of essential newborn care practices, such as thermal protection and hygienic cord care, in high mortality countries. These practices have not typically been measured in national household surveys, often the main source for coverage data in these settings. The Every Newborn Action Plan proposed early breastfeeding as a tracer for essential newborn care due to data availability and evidence for the benefits of breastfeeding. In the past decade, a few national surveys have added questions on other practices, presenting an opportunity to assess the performance of early breastfeeding initiation as a tracer indicator.MethodsWe identified twelve national surveys between 2005-2014 that included at least one indicator for immediate newborn care in addition to breastfeeding. Because question wording and reference populations varied, we standardized data to the extent possible to estimate coverage of newborn care practices, accounting for strata and multistage survey design. We assessed early breastfeeding as a tracer by: 1) examining associations with other indicators using Pearson correlations; and 2) stratifying by early breastfeeding to determine differences in coverage of other practices for initiators vs non-initiators in each survey, then pooling across surveys for a meta-analysis, using the inverse standard error as the weight for each observation.FindingsAssociations between pairs of coverage indicators are generally weak, including those with breastfeeding. The exception is drying and wrapping, which have the strongest association of any two interventions in all five surveys where measured; estimated correlations for this range from 0.47 in Bangladesh's 2007 DHS to 0.83 in Nepal's 2006 DHS. The contrast in coverage for other practices by early breastfeeding is generally small; the greatest absolute difference was 6.7%, between coverage of immediate drying for newborns breastfed early compared to those who were not.ConclusionsEarly initiation of breastfeeding is not a high performing tracer indicator for essential newborn care practices measured in previous national surveys. To have informative data on whether newborns are getting life-saving services, standardized questions about specific practices, in addition to breastfeeding initiation, need to be added to surveys.

Project description:BackgroundCurrently many measures of intervention coverage obtained from household surveys do not measure actual health intervention/service delivery, resulting in a need for linking reports of care-seeking with assessments of the service environment in order to improve measurements. This systematic review aims to identify evidence of different methods used to link household surveys and service provision assessments, with a focus on reproductive, maternal, newborn and child health care, in low- and middle-income countries.MethodsUsing pre-defined search terms, articles published in peer-reviewed journals and the grey literature after 1990 were identified, their reference lists scanned and linking methods synthesized.FindingsA total of 59 articles and conference presentations were carefully reviewed and categorized into two groups based on the linking method used: 1) indirect/ecological linking that included studies in which health care-seeking behavior was linked to all or the nearest facilities or providers of certain types within a geographical area, and 2) direct linking/exact matching where individuals were linked with the exact provider or facility where they sought care. The former approach was employed in 51 of 59 included studies, and was particularly common among studies that were based on independent sources of household and facility data that were nationally representative. Only eight of the 59 reviewed studies employed direct linking methods, which were typically done at the sub-national level (eg, district level) and often in rural areas, where the number of providers was more limited compared to urban areas.ConclusionsDifferent linking methods have been reported in the literature, each category has its own set of advantages and limitations, in terms of both methodology and practicality for scale-up. Future studies that link household and provider/facility data should also take into account factors such as sources of data, the timing of surveys, the temporality of data points, the type of services and interventions, and the scale of the study in order to produce valid and reliable results.

Project description:BackgroundAnalysis of health inequalities by ethnicity is critical to achieving the Sustainable Development Goals. In Ecuador, similar to other Latin American countries, indigenous and afro-descendant populations have long been subject to racism, discrimination, and inequitable treatment. Although in recent years, Ecuador has made progress in health indicators, particularly those related to the coverage of Reproductive, Maternal, Neonatal and Child Health (RMNCH) interventions, little is known as to whether inequalities by ethnicity persist.MethodsAnalysis was based on two nationally representative health surveys (2004 and 2012). Ethnicity was self-reported and classified into three categories (Indigenous/Afro-Ecuadorian/Mixed ancestry). Coverage data for six RMNCH health interventions were stratified for each ethnic group by level of education, area of residence and wealth quintiles. Absolute inequality measures were computed and multivariate analysis using Poisson regression was undertaken.FindingsIn 2012, 74.4% of women self-identifying as indigenous did not achieve the secondary level of education and 50.7% were in the poorest quintile (Q1); this profile was relatively unchanged since 2004. From 2004 to 2012, the coverage of RMNCH interventions increased for all ethnic groups, and absolute inequality decreased. However, in 2012, regardless of education level, area of residence and wealth quintiles, ethnic inequalities remained for almost all RMNCH interventions. Indigenous women had 24% lower prevalence of modern contraceptive use (Prevalence ratio [PR] = 0.76; 95% IC: 0.7-0.8); 28% lower prevalence of antenatal care (PR = 0.72; 95% IC: 0.6-0.8); and 35% lower prevalence of skilled birth attendance and institutional delivery (PR = 0.65; 95% IC: 0.6-0.7 and PR = 0.65; 95% IC: 0.6-0.7 respectively), compared with the majority ethnic group in the country.InterpretationWhile the gaps have narrowed, indigenous people in Ecuador continue in a situation of structural racism and are left behind in terms of access to RMNCH interventions. Strategies to reduce ethnic inequalities in the coverage services need to be collaboratively redesigned/co-designed.FundingThis paper was made possible with funds from the Bill & Melinda Gates Foundation [Grant Number: INV-007,594/OPP1148933].

Project description:BackgroundLinking facility and household surveys through geographic methods is a popular technique to draw conclusions about the relationship between health services and population health outcomes at local levels. These methods are useful tools for measuring effective coverage and tracking progress towards Universal Health Coverage, but are understudied. This paper compares the appropriateness of several geospatial methods used for linking individuals (within displaced survey cluster locations) to their source of family planning (at undisplaced health facilities) at a national level.MethodsIn Malawi, geographic methods linked a population health survey, rural clusters from the Woman's Questionnaire of the 2015 Malawi Demographic and Health Survey (MDHS 2015), to Malawi's national health facility census to understand the service environment where women receive family planning services. Individuals from MDHS 2015 clusters were linked to health facilities through four geographic methods: (i) closest facility, (ii) buffer (5 km), (iii) administrative boundary, and (iv) a newly described theoretical catchment area method. Results were compared across metrics to assess the number of unlinked clusters (data lost), the number of linkages per cluster (precision of linkage), and the number of women linked to their last source of modern contraceptive (appropriateness of linkage).ResultsThe closest facility and administrative boundary methods linked every cluster to at least one facility, while the 5-km buffer method left 288 clusters (35.3%) unlinked. The theoretical catchment area method linked all but one cluster to at least one facility (99.9% linked). Closest facility, 5-km buffer, administrative boundary, and catchment methods linked clusters to 1.0, 1.4, 21.1, and 3.3 facilities on average, respectively. Overall, the closest facility, 5-km buffer, administrative boundary, and catchment methods appropriately linked 64.8%, 51.9%, 97.5%, and 88.9% of women to their last source of modern contraceptive, respectively.ConclusionsOf the methods studied, the theoretical catchment area linking method loses a marginal amount of population data, links clusters to a relatively low number of facilities, and maintains a high level of appropriate linkages. This linking method is demonstrated at scale and can be used to link individuals to qualities of their service environments and better understand the pathways through which interventions impact health.

Project description:BackgroundData collection is the most critical stage in any population health study and correctly implementing fieldwork enhances the quality of collected information. However, even the most carefully planned large-scale household surveys can encounter many context-specific issues. This paper reflected on our research team's recent experience conducting surveys for a quasi-experimental evaluation of a reproductive health program in urban areas of Karachi, Pakistan. We aim to describe the issues encountered and lessons learned from this process, and present some potential solutions for conducting future household surveys in similar urban environments.MethodsThe study followed a three-stage random sampling design. Initially, a Geographical Information System (GIS) was used to construct the sampling frame with union council (UC) area mapping and cluster demarcation followed by random selection of clusters in the selected UCs within the intervention and control sites. The second stage involved a complete household listing in selected clusters and the final stage was a random sampling of households with eligible women.ResultThis paper describes the issues that were encountered including technical problems related to GIS demarcation of cluster boundaries and hand-held devices for computer assisted personal interviews (CAPI), household listing, interviewing respondents on sensitive topics and their expectations, and ensuring privacy during the survey.ConclusionThis study identifies a number of unique barriers to conducting household surveys in Karachi and highlights some key lessons for survey research in urban settlements. GIS mapping technology is a cost-effective method for developing sampling frames in resource-constrained settings. Secondly, the strategy of interviewing women immediately after the cluster is listed may be applied to make it easier to re-locate selected respondents and to reduce loss-to-follow up. Understanding local norms and developing culturally appropriate strategies to build trust with communities may significantly improve survey participation. Researchers should hire experienced female enumerators and provide continuous training on best practices for interviewing women on sensitive reproductive health topics in urban communities.

Dataset Information

Geospatial estimation of reproductive, maternal, newborn and child health indicators: a systematic review of methodological aspects of studies based on household surveys.

Background

Methods

Results

Conclusions

Publications

Geospatial estimation of reproductive, maternal, newborn and child health indicators: a systematic review of methodological aspects of studies based on household surveys.

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