Delivery and postnatal care among women in 71 low- and middle-income countries: analyzing coverage gaps using household surveys.

BACKGROUND: High levels of maternal morbidity and mortality persist in low- and middle-income countries, despite increases in coverage of facility delivery and skilled assistance at delivery. We compared levels of facility birth to a summary delivery care measure and quantified gaps. METHODS: We approximated a delivery care score from type of delivery (home, lower-level facility, or hospital), skilled attendant at delivery, a stay of 24-or-more-hours after delivery, and a health check within 48-h after delivery. Data were obtained from 333,316 women aged 15-49 who had a live birth in the previous 2 years, and from 71 countries with nationally representative surveys between 2013 and 2020. We computed facility delivery and delivery care coverage estimates to assess the gap. We stratified the analysis by country characteristics, including the national maternal mortality ratio (MMR), to assess the size of coverage gaps, and we assessed missed opportunities through coverage cascades. We looked at the association between MMR and delivery care coverage. RESULTS: Delivery care coverage varied by country, ranging from 24% in Sudan to 100% in Cuba. Median coverage was 70% with an interquartile range of 30 percentage points (55% and 85%). The cascade showed that while 76% of women delivered in a facility, only 41% received all four interventions. Coverage gaps exist across all MMR levels. Gaps between highest and lowest wealth quintiles were greatest in countries with MMR levels of 100 or higher, and the gap narrowed in countries with MMR levels below 100. The delivery care indicator had a negative association with MMR. CONCLUSIONS: In addition to providing high-quality evidenced-based care to women during birth and the postpartum period, there is also a need to address gaps in delivery care, which occur within and between countries, wealth quintiles, and MMR phases.

Measuring consumption over the phone: Evidence from a survey experiment in urban Ethiopia.

The paucity of reliable, timely household consumption data in many low- and middle-income countries have made it difficult to assess how global poverty has evolved during the COVID-19 pandemic. Standard poverty measurement requires collecting household consumption data, which is rarely collected by phone. To test the feasibility of collecting consumption data over the phone, we conducted a survey experiment in urban Ethiopia, randomly assigning households to either phone or in-person interviews. In the phone survey, average per capita consumption is 23 percent lower and the estimated poverty headcount is twice as high than in the in-person survey. We observe evidence of survey fatigue occurring early in phone interviews but not in in-person interviews; the bias is correlated with household characteristics. While the phone survey mode provides comparable estimates when measuring diet-based food security, it is not amenable to measuring consumption using the 'best practice' approach originally devised for in-person surveys.

District-level estimation of vaccination coverage: Discrete vs continuous spatial models.

Health and development indicators (HDIs) such as vaccination coverage are regularly measured in many low- and middle-income countries using household surveys, often due to the unreliability or incompleteness of routine data collection systems. Recently, the development of model-based approaches for producing subnational estimates of HDIs using survey data, particularly cluster-level data, has been an active area of research. This is mostly driven by the increasing demand for estimates at certain administrative levels, for example, districts, at which many development goals are set and evaluated. In this study, we explore spatial modeling approaches for producing district-level estimates of vaccination coverage. Specifically, we compare discrete spatial smoothing models which directly model district-level data with continuous Gaussian process (GP) models that utilize geolocated cluster-level data. We adopt a fully Bayesian framework, implemented using the INLA and SPDE approaches. We compare the predictive performance of the models by analyzing vaccination coverage using data from two Demographic and Health Surveys (DHS), namely the 2014 Kenya DHS and the 2015-16 Malawi DHS. We find that the continuous GP models performed well, offering a credible alternative to traditional discrete spatial smoothing models. Our analysis also revealed that accounting for between-cluster variation in the continuous GP models did not have any real effect on the district-level estimates. Our results provide guidance to practitioners on the reliability of these model-based approaches for producing estimates of vaccination coverage and other HDIs.

Conducting household surveys on reproductive health in urban settings: lessons from Karachi, Pakistan.

BACKGROUND: Data 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. METHODS: The 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. RESULT: This 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. CONCLUSION: This 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.

Electronic data collection in a multi-site population-based survey: EN-INDEPTH study.

BACKGROUND: Electronic data collection is increasingly used for household surveys, but factors influencing design and implementation have not been widely studied. The Every Newborn-INDEPTH (EN-INDEPTH) study was a multi-site survey using electronic data collection in five INDEPTH health and demographic surveillance system sites. METHODS: We described experiences and learning involved in the design and implementation of the EN-INDEPTH survey, and undertook six focus group discussions with field and research team to explore their experiences. Thematic analyses were conducted in NVivo12 using an iterative process guided by a priori themes. RESULTS: Five steps of the process of selecting, adapting and implementing electronic data collection in the EN-INDEPTH study are described. Firstly, we reviewed possible electronic data collection platforms, and selected the World Bank's Survey Solutions® as the most suited for the EN-INDEPTH study. Secondly, the survey questionnaire was coded and translated into local languages, and further context-specific adaptations were made. Thirdly, data collectors were selected and trained using standardised manual. Training varied between 4.5 and 10 days. Fourthly, instruments were piloted in the field and the questionnaires finalised. During data collection, data collectors appreciated the built-in skip patterns and error messages. Internet connection unreliability was a challenge, especially for data synchronisation. For the fifth and final step, data management and analyses, it was considered that data quality was higher and less time was spent on data cleaning. The possibility to use paradata to analyse survey timing and corrections was valued. Synchronisation and data transfer should be given special consideration. CONCLUSION: We synthesised experiences using electronic data collection in a multi-site household survey, including perceived advantages and challenges. Our recommendations for others considering electronic data collection include ensuring adaptations of tools to local context, piloting/refining the questionnaire in one site first, buying power banks to mitigate against power interruption and paying attention to issues such as GPS tracking and synchronisation, particularly in settings with poor internet connectivity.

Estimation of Ethiopia's immunization coverage - 20 years of discrepancies.

BACKGROUND: Coverage with the third dose of diphtheria-pertussis-tetanus-containing vaccine (DPT3) is a widely used measure of the performance of routine immunization systems. Since 2015, data reported by Ethiopia's health facilities have suggested DPT3 coverage to be greater than 95%. Yet, Demographic and Health Surveys in 2016 and 2019 found DPT3 coverage to be 53 and 61% respectively for years during this period. This case study reviews the last 20 years of administrative (based on facility data), survey and United Nations (UN) estimates of Ethiopia's nationwide immunization coverage to document long-standing discrepancies in these statistics. METHODS: Published estimates were compiled of Ethiopia's nationwide DPT3 coverage from 1999 to 2018. These estimates come from the Joint Reporting Form submitted annually to WHO and UNICEF, a series of 8 population-based surveys and the annual reports of the WHO/UNICEF Estimates of National Immunization Coverage (WUENIC). Possible reasons for variation in survey findings were explored through secondary analysis of data from the 2012 immunization coverage survey. In addition, selected health officials involved with management of the immunization program were interviewed to obtain their perspectives on the reliability of various methods for estimation of immunization coverage. FINDINGS: Comparison of Ethiopia's estimates for the same year from different sources shows major and persistent discrepancies between administrative, survey and WUENIC estimates. Moreover, the estimates from each of these sources have repeatedly shown erratic year-to-year fluctuations. Those who were interviewed expressed scepticism of Demographic and Health Survey (DHS) statistics. Officials of the national immunization programme have repeatedly shown a tendency to overlook all survey statistics when reporting on programme performance. CONCLUSIONS: The present case study raises important questions, not only about the estimation methods of national and UN agencies, but about the reliability and comparability of widely trusted coverage surveys. Ethiopia provides an important example of a country where no data source provides a truly robust "gold standard" for estimation of immunization coverage. It is essential to identify and address the reasons for these discrepancies and arrive at a consensus on how to improve the reliability and acceptability of each data source and how best to "triangulate" between them.

Viewpoint: High-frequency phone surveys on COVID-19: Good practices, open questions.

Following the onset of the COVID-19 pandemic, face-to-face survey data collection efforts came to a halt due to lockdowns, limitations on mobility and social distancing requirements. What followed was a surge in phone surveys to fulfill rapidly evolving needs for timely and policy-relevant microdata for understanding the socioeconomic impacts of and responses to the pandemic. Even as the face-to-face survey data collection efforts are resuming in different parts of the world with COVID-19 safety protocols, the rapidly-acquired experience with phone surveys on the part of national statistical offices and survey practitioners in low- and middle-income countries appears to have formed the foundation for phone surveys to be more commonly implemented in the post-pandemic era, in response to other shocks and as complementary efforts to face-to-face surveys. Informed by the practical experience with the high-frequency phone surveys that have been implemented with support from the World Bank Living Standards Measurement Study (LSMS) to monitor the socioeconomic impacts of the COVID-19 pandemic, this paper provides an overview of options for the design and implementation of phone surveys to collect representative data from households and individuals. Further, the discussion identifies the requirements for phone surveys to be a mainstay in the toolkits of national statistical offices and the directions for future research on the design and implementation of phone surveys.

Obtaining district-level health estimates using geographically masked location from Demographic and Health Survey data.

BACKGROUND: Demographic and Health Survey (DHS) data are an important source of maternal, newborn, and child health as well as nutrition information for low- and middle-income countries. However, DHSs are often unavailable at the administrative unit that is most interesting or useful for program planning. In addition, the location of DHS survey clusters are geomasked within 10 km, and prior to 2009, may have crossed district boundaries. We aim to use DHS surveyed information with these geomasked coordinates to estimate district assignments for use in health program planning and evaluation. METHODS: We developed three methods to assign a district to a geomasked survey cluster in two DHS surveys from Malawi: 2000 and 2004. Method A assigns districts of origin in proportion to the likelihood that results from repeated simulated geomasking, allowing more than one possible district of origin. Method B assigns a single district of origin which contains the greatest proportion of simulated geomasked survey clusters. Method C maps the geomasked survey cluster's location to a district polygon. We used these method assignments to estimate a selection of commonly used coverage indicators for each district. We compared the district coverage estimates, confidence intervals, and concordance correlation coefficients, by each of the methods, to those which used validated district assignments in 2004, and we looked at coverage change from 2000 to 2004. RESULTS: The methods we tested each approximated the validated estimates in 2004 by confidence interval comparison and concordance correlation coefficient. Estimated agreement for method A was between .14 and .98, for method B the estimated agreement was between .97 and .99, and for method C the agreement ranged from .93 to .99 when compared with the validated district assignments. Therefore, we recommend the protocol which is the simplest to implement-method C-overlaying geomasked survey cluster within district polygon. CONCLUSIONS: Using geomasked survey clusters from DHSs to assign districts provided district level coverage rates similar to those using the validated surveyed locations. This method may be applied to data sources where survey cluster centroids are available and where district level estimates are needed for program implementation and evaluation in low- and middle-income settings. This method is of special interest to those using DHSs to study spatiotemporal trends as it allows for the utilization of historic DHS data where geomasking hinders the generation of reliable subnational estimates of health in areas smaller than the first-order administrative unit (ADM1).

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

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.

Slowly coming out of COVID-19 restrictions in Australia: Implications for working from home and commuting trips by car and public transport.

With the onset of COVID-19 restrictions and the slow relaxing of many restrictions, it is imperative that we understand what this means for the performance of the transport network. In going from almost no commuting, except for essential workers, to a slow increase in travel activity with working from home (WFH) continuing to be both popular and preferred, this paper draws on two surveys, one in late March at the height of restrictions and one in late May as restrictions are starting to be partially relaxed, to develop models for WFH and weekly one-way commuting travel by car and public transport. We compare the findings as one way to inform us of the extent to which a sample of Australian residents have responded through changes in WFH and commuting. While it is early days to claim any sense of a new stable pattern of commuting activity, this paper sets the context for ongoing monitoring of adjustments in travel activity and WFH, which can inform changes required in the revision of strategic metropolitan transport models as well as more general perspectives on future transport and land use policy and planning.

Insights into the impact of COVID-19 on household travel and activities in Australia - The early days of easing restrictions.

The COVID-19 disease continues to cause unparalleled disruption to life and the economy world over. This paper is the second in what will be an ongoing series of analyses of a longitudinal travel and activity survey. In this paper we examine data collected over a period of late May to early June in Australia, following four-to-six weeks of relatively flat new cases in COVID-19 after the initial nationwide outbreak, as many state jurisdictions have begun to slowly ease restrictions designed to limit the spread of the SARS-CoV-2 virus. We find that during this period, travel activity has started to slowly return, in particular by private car, and in particular for the purposes of shopping and social or recreational activities. Respondents indicate comfort with the idea of meeting friends or returning to shops, so authorities need to be aware of potential erosion of social distancing and appropriate COVID-safe behaviour in this regard. There is still a concern about using public transport, though it has diminished noticeably since the first wave of data collection. We see that working from home continues to be an important strategy in reducing travel and pressure on constrained transport networks, and a policy measure that if carried over to a post-pandemic world, will be an important step towards a more sustainable transport future. We find that work from home has been a generally positive experience with a significant number of respondents liking to work from home moving forward, with varying degrees of employer support, at a level above those seen before COVID-19. Thus, any investment to capitalise on current levels of work from home should be viewed as an investment in transport.

Recent trends in wealth inequality among older Americans in two surveys.

We document changes in wealth inequality across American households with a member aged 55 or older, comparing data in the Health and Retirement Study (HRS) with that in the Survey of Consumer Finances (SCF) between 1998 and 2016. We examine net wealth including housing, financial and nonfinancial assets and debt, without the cash value of insurances, DB pensions or Social Security wealth. We find very similar distributions of net wealth in the two surveys between the 25th and 90th percentiles, but substantially higher wealth in the SCF at the top of the distribution. Both surveys show an increase in wealth inequality between 1998 and 2016, first mostly due to increased wealth at the top, and, after 2012, due to an increase in the share of households with very little wealth as well. Both surveys agree that wealth inequality by education and race, already substantial in 1998, increased further by 2016.

Understanding country-specific determinants of stillbirth using household surveys: The case of Afghanistan.

BACKGROUND: Stillbirth rates in Afghanistan have declined little in the past decade with no data available on key risk factors. Health care utilisation and maternal complications are important factors influencing pregnancy outcomes but rarely captured for stillbirth in national surveys from low- and middle-income countries. The 2010 Afghanistan Mortality Survey (AMS) is one of few surveys with this information. METHODS: We used data from the 2010 AMS that included a full pregnancy history and verbal autopsy. Our sample included the most recent live birth or stillbirth of 13 834 women aged 12-49 years in the three years preceding the survey. Multivariable Poisson regression was used to identify sociodemographic, maternal, and health care utilisation risk factors for stillbirth. RESULTS: The risk of stillbirth was increased among women in the Central Highlands (aRR: 3.01, 95% CI 1.35, 6.70) and of Nuristani ethnicity (aRR: 9.15, 95% CI 2.95, 28.74). Women who did not receive antenatal care had three times increased risk of stillbirth (aRR: 3.03, 95% CI 1.73, 5.30), while high-quality antenatal care was important for reducing the risk of intrapartum stillbirth. Bleeding, infection, headache, and reduced fetal movements were antenatal complications strongly associated with stillbirth. Reduced fetal movements in the delivery period increased stillbirth risk by almost seven (aRR: 6.82, 95% CI 4.20, 11.10). Facility births had a higher risk of stillbirths overall (aRR: 1.55, 95% CI 1.12, 2.16), but not for intrapartum stillbirths. CONCLUSIONS: Targeted interventions are needed to improve access and utilisation of services for high-risk groups. Early detection of complications through improved quality of antenatal and obstetric care is imperative. We demonstrate the potential of household surveys to provide country-specific evidence on stillbirth risk factors for LMICs where data are lacking.

The price elasticity of quantity, and of quality, for tobacco products.

We use household survey data to estimate the price elasticity of quantity, and of quality, for tobacco products. In our data, commonly used estimation methods suggest an own-price elasticity of demand of about -1. These methods add together responses on the quantity margin and the quality margin. Just one third of the response to price is from quantity and two thirds is from quality. The simulated effect of higher excise taxes is to reduce overall quantity by just one third of what is predicted if the quality response is ignored. Higher taxes also shift demand to lower quality tobacco products.

Antenatal care as a means to increase participation in the continuum of maternal and child healthcare: an analysis of the poorest regions of four Mesoamérican countries.

BACKGROUND: Antenatal care (ANC) is a means to identify high-risk pregnancies and educate women so that they might experience a healthier delivery and outcome. There is a lack of evidence about whether receipt of ANC is an effective strategy for keeping women in the system so they partake in other maternal and child interventions, particularly for poor women. The present analysis examines whether ANC uptake is associated with other maternal and child health behaviors in poor mothers in Guatemala, Honduras, Nicaragua, and Mexico (Chiapas). METHODS: We conducted a cross-sectional survey of women regarding their uptake of ANC for their most recent delivery in the last two years and their uptake of selected services and healthy behaviors along a continuity of maternal and child healthcare. We conducted logistic regressions on a sample of 4844 births, controlling for demographic, household, and maternal characteristics to understand the relationship between uptake of ANC and later participation in the continuum of care. RESULTS: Uptake of four ANC visits varied by country from 17.0% uptake in Guatemala to 81.4% in Nicaragua. In all countries but Nicaragua, ANC was significantly associated with in-facility delivery (IFD) (Guatemala odds ratio [OR] = 5.28 [95% confidence interval [CI] 3.62-7.69]; Mexico OR = 5.00 [95% CI: 3.41-7.32]; Honduras OR = 2.60 [95% CI: 1.42-4.78]) and postnatal care (Guatemala OR = 4.82 [95% CI: 3.21-7.23]; Mexico OR = 4.02 [95% CI: 2.77-5.82]; Honduras OR = 2.14 [95% CI: 1.26-3.64]), but did not appear to have any positive relationship with exclusive breastfeeding habits or family planning methods, which may be more strongly determined by cultural influences. CONCLUSIONS: Our results demonstrate that uptake of the WHO-recommended four ANC visits has limited effectiveness on uptake of services in some poor populations in Mesoamérica. Our study highlights the need for continued and varied efforts in these populations to increase both the uptake and the effectiveness of ANC in encouraging positive and lasting effects on women's uptake of health care services.

Sampling design and methodology of the Violence Against Children and Youth Surveys.

INTRODUCTION: Globally 1 billion children are exposed to violence every year. The Violence Against Children Surveys (VACS) are nationally representative surveys of males and females ages 13-24 that are intended to measure the burden of sexual, physical and emotional violence experienced in childhood, adolescence and young adulthood. It is important to document the methodological approach and design of the VACS to better understand the national estimates that are produced in each country, which are used to drive violence prevention efforts. METHODS: This study describes the surveys' target population, sampling design, statistical considerations, data collection process, priority violence indicators and data dissemination. RESULTS: Twenty-four national household surveys have been completed or are being planned in countries across Africa, Asia, the Caribbean, Central and South America, and Eastern Europe. The sample sizes range from 891 to 7912 among females (72%-98% response rate) and 803-2717 among males (66%-98% response rate). Two face-to-face interviews are conducted: a Household and an Individual Questionnaire. A standard set of core priority indicators are generated for each country that range from prevalence of different types of violence, contexts, risk and protective factors, and health consequences. Results are disseminated through various platforms to expand the reach and impact of the survey results. CONCLUSION: Data obtained through VACS can inform development and implementation of effective prevention strategies and improve health service provision for all who experience violence. VACS serves as a standardised tool to inform and drive prevention through high-quality, comprehensive data.

The association between female genital fistula symptoms and gender-based violence: A multicountry secondary analysis of household survey data.

OBJECTIVE: The Demographic and Health Surveys (DHS), which include standardised questions on female genital fistula symptoms, provide a unique opportunity to evaluate the epidemiology of fistula. This study sought to examine associations between self-reported fistula symptoms and experience of gender-based violence (GBV) among women interviewed in DHS surveys. METHODS: This study used data from thirteen DHS surveys with standardised fistula and domestic violence modules. Data from the most recent survey in each country were pooled, weighting each survey equally. Multivariable logistic regressions controlled for maternal and demographic factors. RESULTS: Prevalence of fistula symptoms in this sample of 95 625 women ranges from 0.3% to 1.8% by country. The majority of women reporting fistula symptoms (56%) have ever experienced physical violence, and more than one-quarter have ever experienced sexual violence (27%), compared with 38% and 13% among women with no symptoms, respectively. Similarly, 16% of women with fistula symptoms report recently experiencing sexual violence-twice the percentage among women not reporting symptoms (8%). Women whose first experience of sexual violence was from a non-partner have almost four times the odds of reporting fistula symptoms compared with women who never experienced sexual violence. These associations indicate a need to investigate temporal and causal relationships between violence and fistula. CONCLUSIONS: The increased risk of physical and sexual violence among women with fistula symptoms suggests that fistula programmes should incorporate GBV into provider training and services.

Geographic factors predict wild food and nonfood NTFP collection by households across four African countries.

Wild foods and other nonfood NTFPs are important for improving food security and supplementing incomes in rural peoples' livelihoods. However, studies on the importance of NTFPs to rural communities are often limited to a few select sites and are conducted in areas that are already known to have high rates of NTFP use. To address this, we examined the role of geographic and household level variables in determining whether a household would report collecting wild foods and other nonfood NTFP across 25 agro-ecological landscapes in Tanzania, Rwanda, Uganda and Ghana. The aim of this study was to contribute to the literature on NTFP collection in Africa and to better understand where people depend on these resources by drawing on a broad range of sites that were highly variable in geographic characteristics as well as rates of NTFP collection to provide a better understanding of the determinants of NTFP collection. We found that geographic factors, such as the presence of forests, non-forest natural areas like grasslands and shrublands, and lower population density significantly predict whether a household will report collecting NTFP, and that these factors have greater explanatory power than household characteristics.

How can we better capture food away from Home? Lessons from India's linking person-level meal and household-level food data.

Despite acknowledged shortcomings, household consumption and expenditure surveys (HCES) are increasingly being used to proxy food consumption because they are relatively more available and affordable than surveys using more precise dietary assessment methods. One of the most common, significant sources of HCES measurement error is their under-estimation of food away from home (FAFH). In 2011, India's National Survey Sample Organization introduced revisions in its HCES questionnaire that included replacing "cooked meals"-the single item in the food consumption module designed to capture FAFH at the household level-with five more detailed and explicitly FAFH sub-categories. The survey also contained a section with seven, household member-specific questions about meal patterns during the reference period and included three sources of meals away from home (MAFH) that overlapped three of the new FAFH categories. By providing a conceptual framework with which to organize and consider each household member's meal pattern throughout the reference period, and breaking down the recalling (or estimating) process into household member-specific responses, we assume the MAFH approach makes the key respondent's task less memory- and arithmetically-demanding, and thus more accurate than the FAFH household level approach. We use the MAFH estimates as a reference point, and approximate one portion of FAFH measurement error as the differences in MAFH and FAFH estimates. The MAFH estimates reveal marked heterogeneity in intra-household meal patterns, reflecting the complexity of the HCES's key informant task of reporting household level data, and underscoring its importance as a source of measurement error. We find the household level-based estimates of FAFH increase from just 60.4% of the individual-based estimates in the round prior to the questionnaire modifications to 96.7% after the changes. We conclude that the MFAH-FAFH linked approach substantially reduced FAFH measurement error in India. The approach has wider applicability in global efforts to improve HCES.

A composite likelihood approach in testing for Hardy Weinberg Equilibrium using family-based genetic survey data.

In population-based household surveys, for example, the National Health and Nutrition Examination Survey, households are often sampled by stratified multistage cluster sampling, and multiple individuals related by blood are often sampled within households. Therefore, genetic data collected from these population-based household surveys, called National Genetic Household Surveys, can be correlated because of two levels of correlation. One level of correlation is caused by the multistage geographical cluster sampling and the other is caused by biological inheritance among participants within the same sampled family. In this paper, we develop an efficient Hardy Weinberg Equilibrium (HWE) test utilizing pairwise composite likelihood methods that incorporate the sample weighting effect induced by the differential selection probabilities in complex sample designs, as well as the two-level clustering (correlation) effects described above. Monte Carlo simulation studies show that the proposed HWE test maintains the nominal levels, and is more powerful than existing methods (Li et al. 2011) under various (non)informative sample designs that depend on genotypes (explicitly or implicitly), family relationships or both, especially when within-household sampling depends on the genotypes. The developed tests are further evaluated using simulated genetic data based on the Hispanic Health and Nutrition Survey. Copyright © 2016 John Wiley & Sons, Ltd.