Dataset Information

Using DHS and MICS data to complement or replace NGO baseline health data: an exploratory study.

ABSTRACT: Background: Non-government organizations (NGOs) spend substantial time and resources collecting baseline data in order to plan and implement health interventions with marginalized populations. Typically interviews with households, often mothers, take over an hour, placing a burden on the respondents. Meanwhile, estimates of numerous health and social indicators in many countries already exist in publicly available datasets, such as the Demographic and Health Surveys (DHS) and the Multiple Indicator Cluster Surveys (MICS), and it is worth considering whether these could serve as estimates of baseline conditions. The objective of this study was to compare indicator estimates from non-governmental organizations (NGO) health projects' baseline reports with estimates calculated using the Demographic and Health Surveys (DHS) or the Multiple Indicator Cluster Surveys (MICS), matching for location, year, and season of data collection. Methods: We extracted estimates of 129 indicators from 46 NGO baseline reports, 25 DHS datasets and three MICS datasets, generating 1,996 pairs of matched DHS/MICS and NGO indicators. We subtracted NGO from DHS/MICS estimates to yield difference and absolute difference, exploring differences by indicator. We partitioned variance of the differences by geographical level, year, and season using ANOVA. Results: Differences between NGO and DHS/MICS estimates were large for many indicators but 33% fell within 5% of one another. Differences were smaller for indicators with prevalence <15% or >85%. Difference between estimates increased with increasing year and geographical level differences. However, <1% of the variance of the differences was explained by year, geographical level, and season. Conclusions: There are situations where publicly available data could complement NGO baseline survey data, most importantly when the NGO has tolerance for estimates of low or unknown accuracy.

SUBMITTER: Berti PR

PROVIDER: S-EPMC8145218 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundInfant immunization coverage worldwide has plateaued at about 85%. Using existing survey data to conduct analyses beyond estimating coverage may help immunization programmes better tailor strategies to reach un- and under-immunized children. The Demographic and Health Survey (DHS) and the Multiple Indicators Cluster Survey (MICS), routinely conducted in low and middle-income countries (LMICs), collect immunization data, yet vaccination coverage is often the only indicator reported and used. We conducted a review of published immunization-related analyses to characterize and quantify immunization secondary analyses done using DHS and MICS databases.MethodsWe conducted a systematic search of the literature, of immunization-related secondary analyses from DHS or MICS published between 2006 and August 2018. We searched 15 electronic databases without language restrictions. For the articles included, relevant information was extracted and analyzed to summarize the characteristics of immunization-related secondary analyses. Results are presented following the PRISMA guidelines.ResultsAmong 1411 papers identified, 115 met our eligibility criteria; additionally, one article was supplemented by the Pan American Health Organization. The majority were published since 2012 (77.6%), and most (68.9%) had a first or corresponding author affiliated with institutions in high-income countries (as opposed to LMICs where these surveys are conducted). The median delay between survey implementation and publication of the secondary analysis was 5.4 years, with papers with authors affiliated to institutions in LMIC having a longer median publication delay (p < 0.001). Over 80% of the published analyses looked at factors associated with a specific vaccine or with full immunization. Quality proxies, such as reporting percent of immunization data from cards vs recall; occurrence and handling of missing data; whether survey analyses were weighted; and listing of potential biases or limitations of the original survey or analyses, were infrequently mentioned.ConclusionOur review suggests that more needs to be done to increase the increase the utilization of existing DHS and MICS datasets and improve the quality of the analyses to inform immunization programmes. This would include increasing the proportion of analyses done in LMICs, reducing the time lag between survey implementation and publication of additional analyses, and including more qualitative information about the survey in the publications to better interpret the results.

Project description:BackgroundThe Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS) are the major data sources in low- and middle-income countries (LMICs) for evaluating health service coverage. For certain maternal and child health (MCH) indicators, the two surveys use different recall periods: 5 years for DHS and 2 years for MICS.ObjectiveWe explored whether the different recall periods for DHS and MICS affect coverage trend analyses as well as missing data and coverage estimates.DesignsWe estimated coverage, using proportions with 95% confidence intervals, for four MCH indicators: intermittent preventive treatment of malaria in pregnancy, tetanus vaccination, early breastfeeding and postnatal care. Trends in coverage were compared using data from 1) standard 5-year DHS and 2-year MICS recall periods (unmatched) and 2) DHS restricted to 2-year recall to match the MICS 2-year recall periods (matched). Linear regression was used to explore the relationship between length of recall, missing data and coverage estimates.ResultsDifferences in coverage trends were observed between matched and unmatched data in 7 of 18 (39%) comparisons performed. The differences were in the direction of the trend over time, the slope of the coverage change or the significance levels. Consistent trends were seen in 11 of the 18 (61%) comparisons. Proportion of missing data was inversely associated with coverage estimates in both short (2 years) and longer (5 years) recall of the DHS (r=-0.3, p=0.02 and r=-0.4, p=0.004, respectively). The amount of missing information was increased for longer recall compared with shorter recall for all indicators (significant odds ratios ranging between 1.44 and 7.43).ConclusionsIn a context where most LMICs are dependent on population-based household surveys to derive coverage estimates, users of these types of data need to ensure that variability in recall periods and the proportion of missing data across data sources are appropriately accounted for when trend analyses are conducted.

Project description:The postnatal period represents a vulnerable phase for mothers and newborns where both face increased risk of morbidity and death. WHO recommends postnatal care (PNC) for mothers and newborns to include a first contact within 24 hours following the birth of the child. However, measuring coverage of PNC in household surveys has been variable over time. The two largest household survey programs in low and middle-income countries, the UNICEF-supported Multiple Indicator Cluster Surveys (MICS) and USAID-funded Demographic and Health Surveys (DHS), now include modules that capture these measures. However, the measurement approach is slightly different between the two programs. We attempt to assess the possible measurement differences that might affect comparability of coverage measures.We first review the standard questionnaires of the two survey programs to compare approaches to collecting data on postnatal contacts for mothers and newborns. We then illustrate how the approaches used can affect PNC coverage estimates by analysing data from four countries; Bangladesh, Ghana, Kygyz Republic, and Nepal, with both MICS and DHS between 2010-2015.We found that tools implemented todate by MICS and DHS (up to MICS round 5 and up to DHS phase 6) have collected PNC information in different ways. While MICS dedicated a full module to PNC and distinguishes immediate vs later PNC, DHS implemented a more blended module of pregnancy and postnatal and did not systematically distinguish those phases. The two survey programs differred in the way questions on postnatal care for mothers and newbors were framed. Subsequently, MICS and DHS surveys followed different methodological approach to compute the global indicator of postnatal contacts for mothers and newborns within two days following delivery. Regardless of the place of delivery, MICS estimates for postnatal contacts for mothers and newbors appeared consistently higher than those reported in DHS. The difference was however, far more pronounced in case of newborns.Difference in questionnaires and the methodology adopted to measure PNC have created comparability issues in the coverage levels. Harmonization of survey instruments on postnatal contacts will allow comparable and better assessment of coverage levels and trends.

Project description:BackgroundNon-governmental organisations (NGOs) collect and generate vast amounts of potentially rich data, most of which are not used for research purposes. Secondary analysis of NGO data (their use and analysis in a study for which they were not originally collected) presents an important but largely unrealised opportunity to provide new research insights in critical areas, including the evaluation of health policy and programmes.MethodsA scoping review of the published literature was performed to identify the extent to which secondary analysis of NGO data has been used in health policy and systems research (HPSR). A tiered analytical approach provided a comprehensive overview and descriptive analyses of the studies that (1) used data produced or collected by or about NGOs; (2) performed secondary analysis of the NGO data (beyond the use of an NGO report as a supporting reference); and (3) analysed NGO-collected clinical data.ResultsOf the 156 studies that performed secondary analysis of NGO-produced or collected data, 64% (n = 100) used NGO-produced reports (mostly to a limited extent, as a contextual reference or to critique NGO activities) and 8% (n = 13) analysed NGO-collected clinical data. Of these studies, 55% (n = 86) investigated service delivery research topics and 48% (n = 51) were undertaken in developing countries and 17% (n = 27) in both developing and developed countries. NGOs were authors or co-authors of 26% of the studies. NGO-collected clinical data enabled HPSR within marginalised groups (e.g. migrants, people in conflict-affected areas), albeit with some limitations such as inconsistent and missing data.ConclusionWe found evidence that NGO-collected and produced data are most commonly perceived as a source of supporting evidence for HPSR and not as primary source data. However, these data can facilitate research in under-researched marginalised groups and in contexts that are hard to reach by academics such as conflict-affected areas. NGO-academic collaboration could help address issues of NGO data quality to facilitate their more widespread use in research. The use of NGO data use could enable relevant and timely research in the areas of programme evaluation and health policy and advocacy to improve health and reduce health inequalities, especially in marginalised groups and developing countries.

Project description:BackgroundChildhood pneumonia is the single largest infectious cause of death in children under five worldwide. Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS) provide health information on care sought for sick children in resource poor settings. Despite not being primarily designed to identify childhood pneumonia, there are concerns that reported episodes of "symptoms of acute respiratory infection" in DHS and MICS are often interpreted by other groups as a "proxy" for childhood pneumonia. Using DHS5 and MICS5 survey tools, this study aimed to assess how accurately caregivers report of "symptoms of acute respiratory infection" reflect pneumonia episodes and antibiotic use in children under five.MethodsChildren aged 0 to 59 months presenting with cough and/or difficult breathing were recruited from four study hospitals in Ibadan, Nigeria from August 2015 to March 2017. Children were assessed using World Health Organization (WHO) standard criteria by study physicians to identify whether they had pneumonia. Three hundred and two matched children in each category of 'pneumonia' and "no pneumonia" were followed up at home, either two or eight weeks later, using questions from DHS5 and MICS5 surveys to assess the accuracy of caregiver recall of pneumonia.ResultsThe specificity of DHS5 and MICS5 questions for identifying childhood pneumonia were 87.4 (95% confidence interval (CI) = 83.1-91.0) and 86.1 (95% CI = 81.7-89.8) respectively and the sensitivity of questions were 37.1 (95% CI = 31.6-42.8) and 37.1 (95% CI = 31.6-42.8). Correct recall of antibiotic treatment was poor (kappa statistic = 0.064) but improved with the use of medicine pill boards (kappa statistic = 0.235).ConclusionsDHS5 and MICS5 survey questions are not designed to identify childhood pneumonia and this study confirms that they do not accurately discern episodes of childhood pneumonia from cough/cold in children under five. The proportion of pneumonia episodes appropriately treated with antibiotics cannot be accurately assessed using current DHS and MICS surveys. If these results are used to guide programmatic decisions, it is likely to encourage overuse and inappropriate prescribing of antibiotics for episodes of cough/cold. International agencies who continue to use these household data to monitor the proportion of children with pneumonia who receive antibiotic treatment should be discouraged from doing this as these data are likely to mislead national and global programmes. Medicine pill boards are used in a number of DHS surveys and should be promoted for wider use in national population surveys to improve the accuracy of antibiotic recall.

Project description:BackgroundGlobally, health care seeking for childhood diseases seems to be on the rise. However, progress is slow and still, many cases of infectious diseases in children remain untreated, leading to preventable child mortality. A better understanding of care seeking behaviour may help to further increase the probability that a sick child is taken to a health facility for care.MethodsWe investigated whether mother's and father's age at birth of the child is associated with health care seeking behaviour for childhood diseases and how this association changed over time. For this observational study, we used repeated cross-sectional data, namely all available Demographic and Health Surveys as well as Multi-Indicator Cluster Surveys from Western and Central Africa, 1995 to 2017. We analysed care seeking behaviour for diarrhoea, acute respiratory infections (ARI), and treatment of diarrhoea with oral rehydration solution (ORS). We estimated ordinary least squares regressions, controlling for socioeconomic characteristics of the household and adding survey year- and country-fixed effects. Estimated associations are presented for the entire region and for each country separately to highlight heterogeneity.ResultsOverall, the likelihood that care is sought for a child suffering from diarrhoea or ARI is low in Western and Central Africa. Probability of care seeking for diarrhoea ranges between 49% for mothers above 40 years and 53% for mothers between 25 and 29 years. For ARI, the rates are 60% and 62%, respectively. Treatment of diarrhoea with ORS is even lower, ranging between 23% and 26%. The probability that parents seek health care for their child does not seem to be associated with parents' age at birth. Mother's level of education and household's wealth status seem to be more important factors. There is evidence of the relationship between parents' age and care seeking changing over time, suggesting a stronger association in the past.ConclusionsParents' age at child birth does not seem to have a relevant association with care seeking for common childhood diseases. Identifying relevant factors may help in improving health care seeking behaviour of parents in low- and middle-income countries leading to reductions in child morbidity and mortality.

Project description:BackgroundThirty per cent of all women experience intimate partner violence (IPV) in their lifetime. The aim of this study was to examine the association between the WHO's novel R.E.S.P.E.C.T framework and IPV among women in Kenya.MethodsWe used the 2014 Kenya Demographic and Health Survey (KDHS). Only women selected for the domestic violence module and who were married/living with their partner were eligible for this study (n=3737). We created a summary score for the strategies denoted by R.E.S.P.T based on availability of questions addressing these strategies in the KDHS, and a total score that summed responses across all strategies. Each letter was assessed with Cronbach's alpha. Multiple logistic regression models were used to investigate the relationship between R.E.S.P.T scores and IPV.ResultsAll strategies except for E lowered the odds of IPV. Decision-making (R) was negatively associated with experiencing IPV (OR=0.62 (0.53 to 0.72)). Land and property ownership (E) were positively associated with experiencing IPV (OR=1.25 (1.08 to 1.43)). Access to healthcare (S) was negatively associated with experiencing IPV (OR=0.55 (0.48 to 0.63)). Higher levels of wealth (P) were negatively associated with experiencing IPV (OR=0.47 (0.37 to 0.62)). Not justifying wife-beating in any scenario (T) was negatively associated with experiencing IPV (OR=0.39 (0.29 to 0.53)). After adjusting for demographics, a 1-unit increase in total R.E.S.P.T score was negatively associated with experiencing IPV (AOR=0.63 (0.57 to 0.70)) with a similar finding for IPV in the past 12 months (AOR=0.59 (0.53 to 0.66)). Younger women, higher education and Muslim religion were associated with decreased odds of experiencing IPV while living in a rural location and working were associated with increased odds of experiencing IPV.ConclusionsOur study provides initial evidence that by using the multistrategy R.E.S.P.E.C.T framework, countries can dramatically lower the odds of women experiencing IPV. IPV prevention strategies must have a wide approach. The DHS can be used as a tool to monitor implementation and efficacy of this novel strategy.

Project description:BackgroundWhile the prevalence of childhood diseases and related mortality have been decreasing over the past decades, progress has been unequally distributed. The poorest households often carry the highest disease burden. As morbidity and mortality also decline most slowly among children of the poorest households, socioeconomic status may become a more relevant risk factor for childhood diseases.MethodsWe analysed the association between socioeconomic status and highly prevalent childhood diseases, specifically diarrhoea, acute respiratory infections (ARI), and malaria, and how this association changed over time. For this observational study, we used repeated cross-sectional data, namely all available Demographic and Health Surveys as well as Multi-Indicator Cluster Surveys from Western and Central Africa between 1995 and 2017. We estimated the predicted prevalence of each disease for the entire region in three time periods. We repeated the analysis separately for each country to highlight heterogeneity between countries.ResultsA notable wealth gradient can be seen in the prevalence rates of diarrhoea, ARI, and malaria in Western and Central Africa. Children in the poorest quartile have a much higher morbidity than children in the richest quartile and have experienced a considerably slower decline in prevalence rates. In the period 2010-2017, predicted prevalence of diarrhoea was 17.5% for children in the poorest quartile and 12.5% for children in the richest quartile. Similarly, the predicted prevalence was 11.1% and 8.6% for ARI, and 54.1% and 24.4% for malaria in endemic countries. The pattern does not differ between boys and girls. While exact prevalence rates vary between countries, only few countries have seen a decline in the wealth gradient for childhood diseases.ConclusionsThe increasing wealth gradient in health raises concerns of increasing inequality that goes beyond wealth. It suggests a need to further improve targeting of health programmes. Moreover, these programmes should be adapted to address the interlinked challenges which burden the poorest households.

Dataset Information

Using DHS and MICS data to complement or replace NGO baseline health data: an exploratory study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets