Household-level Information Research Articles

Bayesian belief network modelling approach for predicting and ranking risk factors for malaria infections among children under 5 years in refugee settlements in Uganda

BackgroundMalaria risk factors at household level are known to be complex, uncertain, stochastic, nonlinear, and multidimensional. The interplay among these factors, makes targeted interventions, and resource allocation for malaria control challenging. However, few studies have demonstrated malaria’s transmission complexity, control, and integrated modelling, with no available evidence on Uganda’s refugee settlements. Using the 2018–2019 Uganda’s Malaria Indicator Survey (UMIS) data, an alternative Bayesian belief network (BBN) modelling approach was used to analyse, predict, rank and illustrate the conceptual reasoning, and complex causal relationships among the risk factors for malaria infections among children under-five in refugee settlements of Uganda.MethodsIn the UMIS, household level information was obtained using standardized questionnaires, and a total of 675 children under 5 years were tested for malaria. From the dataset, a casefile containing malaria test results, demographic, social-economic and environmental information was created. The casefile was divided into a training (80%, n = 540) and testing (20%, n = 135) datasets. The training dataset was used to develop the BBN model following well established guidelines. The testing dataset was used to evaluate model performance.ResultsModel accuracy was 91.11% with an area under the receiver-operating characteristic curve of 0.95. The model’s spherical payoff was 0.91, with the logarithmic, and quadratic losses of 0.36, and 0.16 respectively, indicating a strong predictive, and classification ability of the model. The probability of refugee children testing positive, and negative for malaria was 48.1% and 51.9% respectively. The top ranked malaria risk factors based on the sensitivity analysis included: (1) age of child; (2) roof materials (i.e., thatch roofs); (3) wall materials (i.e., poles with mud and thatch walls); (4) whether children sleep under insecticide-treated nets; 5) type of toilet facility used (i.e., no toilet facility, and pit latrines with slabs); (6) walk time distance to water sources (between 0 and 10 min); (7) drinking water sources (i.e., open water sources, and piped water on premises).ConclusionRanking, rather than the statistical significance of the malaria risk factors, is crucial as an approach to applied research, as it helps stakeholders determine how to allocate resources for targeted malaria interventions within the constraints of limited funding in the refugee settlements.

The Prevalence of Self-Reported Tuberculosis in the Andaman and Nicobar Islands, India: Evidence from the NFHS-IV and V.

Since 1992, many rounds of the National Family Health Surveys have produced a significant quantity of data in India. The magnitude of the tuberculosis (TB) burden in Andaman and Nicobar Island can be better understood with this data. The household-level information on self-reported TB may provide useful information on the prevalence and distribution of TB as well as care-seeking behaviour. The primary objective is to analyse the data from the NFHS-IV and NFHS-V to understand the prevalence of self-reported TB as well as healthcare-seeking patterns for TB in the Andaman and Nicobar Islands. We performed secondary data analysis of NFHS-IV and NFHS-V data. After taking into consideration the survey's cluster design and sampling weights, the prevalence was estimated. The association of identified factors with self-reported TB was investigated using the chi-square and logistic regression models. The point prevalence of self-reported TB was 615 (418, 873) and 221 (122, 367) in the NFHS-IV and NFHS-V, respectively (p = 0.012). The elderly, those from rural areas, those belonging to a tribe, and those with a poor wealth index were more likely to report TB. Self-reported TB prevalence was higher in the Nicobar district. There is an increase in a significant proportion of individuals not seeking care. The NFHS-IV and NFHS-V show a decline in self-reported TB, which is consistent with national estimates. However, the enhanced TB case detection in individuals at high risk of TB among the Nicobar districts and tribal communities could significantly contribute to the fight against tuberculosis. Improved awareness of TB could improve care seeking for TB.

Assessing household fine particulate matter (PM2.5) through measurement and modeling in the Bangladesh cook stove pregnancy cohort study (CSPCS)

Biomass fuel burning is a significant contributor of household fine particulate matter (PM2.5) in the low to middle income countries (LMIC) and assessing PM2.5 levels is essential to investigate exposure-related health effects such as pregnancy outcomes and acute lower respiratory infection in infants. However, measuring household PM2.5 requires significant investments of labor, resources, and time, which limits the ability to conduct health effects studies. It is therefore imperative to leverage lower-cost measurement techniques to develop exposure models coupled with survey information about housing characteristics. Between April 2017 and March 2018, we continuously sampled PM2.5 in three seasonal waves for approximately 48-h (range 46 to 52-h) in 74 rural and semi-urban households among the participants of the Bangladesh Cook Stove Pregnancy Cohort Study (CSPCS). Measurements were taken simultaneously in the kitchen, bedroom, and open space within the household. Structured questionnaires captured household-level information related to the sources of air pollution. With data from two waves, we fit multivariate mixed effect models to estimate 24-h average, cooking time average, daytime and nighttime average PM2.5 in each of the household locations. Households using biomass cookstoves had significantly higher PM2.5 concentrations than those using electricity/liquefied petroleum gas (626 μg/m3 vs. 213 μg/m3). Exposure model performances showed 10-fold cross validated R2 ranging from 0.52 to 0.76 with excellent agreement in independent tests against measured PM2.5 from the third wave of monitoring and ambient PM2.5 from a separate satellite-based model (correlation coefficient, r = 0.82). Significant predictors of household PM2.5 included ambient PM2.5, season, and types of fuel used for cooking. This study demonstrates that we can predict household PM2.5 with moderate to high confidence using ambient PM2.5 and household characteristics. Our results present a framework for estimating household PM2.5 exposures in LMICs, which are often understudied and underrepresented due to resource limitations.

Till taxes keep us apart? The impact of the marriage tax on the marriage rate

Married couples can face a higher or lower tax burden than cohabitating couples with the same income when the former are taxed as one unit. I study the effect of such joint income taxation on the marriage rate in Switzerland, where tax differentials between married and cohabitating couples vary considerably across cantons. For this purpose, I construct a dataset containing sociodemographic and -economic variables on every individual living in Switzerland and use household-level information to identify cohabitating couples. Using a simulated instrumental variable approach, I find a negative impact of joint income taxation on the marriage rate for couples married between 2012 and 2019. The effect is driven by households without children and from the lower end of the income distribution.

Post-cyclonic migration in coastal areas: An assessment of who, where, why migrates, and barriers to migration

As cyclones increase in frequency and severity, more people experience their adverse impacts. However, little is known about post-cyclonic migration patterns in coastal southern Bangladesh, a cyclone-prone area. This paper compares post-cyclonic migration patterns with non-cyclonic migration in terms of who migrates, where they migrate to, why they migrate, and the barriers to migration. 472 households across 16 blocks (moujas) were selected by stratified sampling. A survey collected individual and household-level information regarding demographics, socioeconomy, and migration patterns in non-cyclonic and post-cyclonic situations. The analysis demonstrated that, in non-cyclonic situations, secure employment represented the migrants’ main livelihood while, following a cyclone, non-secure professions such as day-labouring were the most prevalent. The post-cyclonic migrants were, overall, less educated and less wealthy landless and marginal farm holders compared to those who migrated in the non-cyclonic period. Most people migrated to nearby districts following a cyclone, whereas long-distance migrations were found in non-cyclonic periods. We thus argue that, in a non-cyclonic period, people migrate for employment and are in a stronger position, socioeconomically, than post-cyclonic migrants, while, in a post-cyclonic period, it is mainly socioeconomically distressed people with non-secured day-labouring jobs who migrate a short distance area.

Determinants of malaria infections among children in refugee settlements in Uganda during 2018–2019

BackgroundWhile 5% of 247 million global malaria cases are reported in Uganda, it is also a top refugee hosting country in Africa, with over 1.36 million refugees. Despite malaria being an emerging challenge for humanitarian response in refugee settlements, little is known about its risk factors. This study aimed to investigate the risk factors for malaria infections among children under 5 years of age in refugee settlements in Uganda.MethodsWe utilized data from Uganda’s Malaria Indicator Survey which was conducted between December 2018 and February 2019 at the peak of malaria season. In this national survey, household level information was obtained using standardized questionnaires and a total of 7787 children under 5 years of age were tested for malaria using mainly the rapid diagnostic test. We focused on 675 malaria tested children under five in refugee settlements located in Yumbe, Arua, Adjumani, Moyo, Lamwo, Kiryadongo, Kyegegwa, Kamwenge and Isingiro districts. The extracted variables included prevalence of malaria, demographic, social-economic and environmental information. Multivariable logistic regression was used to identify and define the malaria associated risk factors.ResultsOverall, malaria prevalence in all refugee settlements across the nine hosting districts was 36.6%. Malaria infections were higher in refugee settlements located in Isingiro (98.7%), Kyegegwa (58.6%) and Arua (57.4%) districts. Several risk factors were significantly associated with acquisition of malaria including fetching water from open water sources [adjusted odds ratio (aOR) = 1.22, 95% CI: 0.08–0.59, P = 0.002], boreholes (aOR = 2.11, 95% CI: 0.91–4.89, P = 0.018) and water tanks (aOR = 4.47, 95% CI: 1.67–11.9, P = 0.002). Other factors included pit-latrines (aOR = 1.48, 95% CI: 1.03–2.13, P = 0.033), open defecation (aOR = 3.29, 95% CI: 1.54–7.05, P = 0.002), lack of insecticide treated bed nets (aOR = 1.15, 95% CI: 0.43–3.13, P = 0.003) and knowledge on the causes of malaria (aOR = 1.09, 95% CI: 0.79–1.51, P = 0.005).ConclusionsThe persistence of the malaria infections were mainly due to open water sources, poor hygiene, and lack of preventive measures that enhanced mosquito survival and infection. Malaria elimination in refugee settlements requires an integrated control approach that combines environmental management with other complementary measures like insecticide treated bed nets, indoor residual spraying and awareness.Graphical

Household catastrophic health expenditure for COVID-19 during March-August 2021, in South India: a cross-sectional study

BackgroundThe Coronavirus disease 2019 (COVID-19) pandemic increased the utilisation of healthcare services. Such utilization could lead to higher out-of-pocket expenditure (OOPE) and catastrophic health expenditures (CHE). We estimated OOPE and the proportion of households that experienced CHE by conducting a cross-sectional survey of 1200 randomly selected confirmed COVID-19 cases.MethodsA cross-sectional survey was conducted by telephonic interviews of 1200 randomly selected COVID-19 patients who tested positive between 1 March and 31 August 2021. We collected household-level information on demographics, income, expenditure, insurance coverage, direct medical and non-medical costs incurred toward COVID-19 management. We estimated the proportion of CHE with a 95% confidence interval. We examined the association of household characteristics; COVID-19 cases, severity, and hospitalisation status with CHE. A multivariable logistic regression analysis was conducted to ascertain the effects of variables of interest on the likelihood that households face CHE due to COVID-19.ResultsThe mean (95%CI) OOPE per household was INR 122,221 (92,744–1,51,698) [US$1,643 (1,247–2,040)]. Among households, 61.7% faced OOPE, and 25.8% experienced CHE due to COVID-19. The odds of facing CHE were high among the households; with a family member over 65 years [OR = 2.89 (2.03–4.12)], with a comorbid individual [OR = 3.38 (2.41–4.75)], in the lowest income quintile [OR = 1.82 (1.12–2.95)], any member visited private hospital [OR = 11.85 (7.68–18.27)]. The odds of having CHE in a household who have received insurance claims [OR = 5.8 (2.81- 11.97)] were high. Households with one and more than one severe COVID-19 increased the risk of CHE by more than two-times and three-times respectively [AOR = 2.67 (1.27–5.58); AOR = 3.18 (1.49–6.81)].ConclusionCOVID-19 severity increases household OOPE and CHE. Strengthening the public healthcare and health insurance with higher health financing is indispensable for financial risk protection of households with severe COVID-19 from CHE.

Can North American animal poison control center call data provide early warning of outbreaks associated with contaminated pet food? Using the 2007 melamine pet food contamination incident as a case study.

The 2007 melamine pet food contamination incident highlighted the need for enhanced reporting of toxicological exposures and development of a national quantitative disease surveillance system for companion animals. Data from poison control centers, such as the Animal Poison Control Center (APCC), may be useful for conducting real-time surveillance in this population. In this study, we explored the suitability of APCC call data for early warning of toxicological incidents in companion animal populations by using a-priori knowledge of the melamine-related nephrotoxicosis outbreak. Patient and household-level information regarding possible toxicological exposures in dogs and cats reported to the APCC from 2005 to 2007, inclusive, were extracted from the APCC's AnTox database. These data were used to examine the impact of surveillance outcome, statistical methodology, analysis level, and call source on the ability to detect the outbreak prior to the voluntary recall issued by the pet food manufacturer. Retrospective Poisson temporal scan tests were applied for each combination of outcome, method, level, and call source. The results showed that month-adjusted scans using syndromic data may have been able to help detect the outbreak up to two months prior to the voluntary recall although the success of these methods varied across call sources. We also demonstrated covariate month-adjustment can lead to vastly different results based on the surveillance outcome and call source to which it is applied. This illustrates care should be taken prior to arbitrarily selecting a surveillance outcome and statistical model for surveillance efforts and warns against ignoring the impacts of call source or key covariates when applying quantitative surveillance methods to APCC call data since these factors can lead to very different results. This study provides further evidence that APCC call data may be useful for conducting surveillance in the US companion animal population and further exploratory analyses and validation studies are warranted.

Measuring the poverty reduction effects of adopting agricultural technologies in rural Ethiopia: findings from an endogenous switching regression approach

The purpose of this study is to understand how the adoption of different agricultural technologies can reduce poverty in rural regions of Ethiopia. To attain this objective, this paper uses a comprehensive socio-economic survey of Ethiopia, which allows us to securitize the household level information. The paper uses a multinomial endogenous switching regression model to estimate the impact of alternative technologies adoption on poverty reduction on a sample of 2316 farm households, and a multinomial logit model to estimate the determinants of alternative agricultural technologies adoption. The results showed that the decision to adopt alternative agricultural technologies depends on several variables such as education, regional heterogeneity, remittance income, extension visit, credit access, off-farm activity, soil quality, farm size, tropical livestock unit, distance, plot's potential wetness, and ownership certification. The impact results of the study show that household consumption increases when households adopt alternative agricultural technologies, thereby reducing their poverty. Furthermore, adoption of a package of technologies can result in higher food and total consumption per adult than single technology adoption. The paper recommends strategies for further disseminating and scaling up these technologies to help reduce poverty in Ethiopia.

Evaluation of Household Preparedness and Risk Factors for Cutaneous Leishmaniasis (CL) Using the Community Assessment for Public Health Emergency Response (CASPER) Method in Pakistan.

(1) Background: In endemic areas of Pakistan, local community knowledge and attitudes towards cutaneous leishmaniasis (CL) are critical elements in the effective control and management of the disease. A cross-sectional epidemiologic design was used to assess the disease concern, preparedness, practices, and preventive behavior of the households and to assist the personnel and health care professionals in strengthening their planning efforts and awareness of CL. (2) Methods: A two-stage cluster sampling process, i.e., Community Assessment for Public Health Emergency Response (CASPER) was conducted from September 2020 to March 2021 on present household-level information about community needs and health status regarding CL in a cost-effective, timely, and representative manner. (3) Results: In the current study, 67% of the respondents were aware of CL and its causative agent and showed a low level of pandemic preparedness. The majority (74%) of the respondents mentioned that they did not avoid sandfly exposure areas. The majority (84%) of respondents had unsatisfactory behavior towards using bed nets, sprays, or repellents. (4) Conclusion: In endemic areas of Pakistan, the inadequate concern and low preparedness of the local community toward CL are critical aspects in efficient control and management of the disease.

Inflation expectations and consumer spending: the role of household balance sheets

Research interest in the reaction of consumption to expected inflation has increased in recent years due to efforts by central banks to kick-start demand by steering inflation expectations. We contribute to this literature by analysing whether various components of households’ balance sheets determine how consumption reacts to expected inflation. Two channels in particular are conceivable: an increase in inflation expectations can raise consumption through direct increases in expected real wealth, e.g. for households with nominal financial liabilities. By affecting the real interest rate, expected inflation can interact with wealth if only those households can adapt their consumption to current real interest rates that are not budget-constrained or sufficiently liquid to shift funds between consumption and savings. We investigate these channels empirically using household-level information on balance sheets, durable consumption and inflation expectations from the Dutch Central Bank’s Household Survey. We find that investments in risky assets as well as net worth moderates the relation between expected inflation and durable spending decisions. The net worth effect is most pronounced for households with fixed interest rate mortgages.

Urbanization of energy poverty? The case of Mozambique

What is the impact of the unprecedented scale and pace of urbanization in the global South on the evolution of energy poverty incidence? Remarkably enough, urban population growth and energy poverty are mainly studied separately from each other in different strands of the literature. We argue that there is much to be gained in studying these phenomena in their interdependence. To illustrate this, we analyze for the case of Mozambique the relationship between spatial variation in population density and three commonly used indicators of energy poverty over time. We think that the case of Mozambique exemplifies the future development of Africa's energy poverty situation in many respects. Our analysis makes use of two newly constructed datasets with household level information that originate from national household welfare surveys as well as an own survey for Mozambique's capital city Maputo. The data show that over time, and especially in urban areas, energy poverty is decreasing in terms of consumption quantities and access to modern energy fuels, but increasing in terms of energy expenditure shares. Also, we show that by largely ignoring transport energy use, the national welfare surveys typically overestimate energy consumption poverty while underestimating energy expenditure poverty to a substantial degree. Finally, based on a multiple non-linear regression analysis we find, after controlling for spatial sorting of households, that if population densities rise, energy poverty levels in terms of modern fuel use first fall and then increase – thus following a U-shaped pattern. In contrast, the relationship between population density and energy expenditure poverty follows an inverted N-shaped curve. This suggests that urbanization processes in poor countries like Mozambique may not lead to an unequivocal reduction of energy poverty rates, in line with existing evidence on urbanization of poverty in Africa.

AN EXPLORATORY STUDY OF DETERMINANTS OF THE QUALITY OF MUNICIPAL SERVICE DELIVERY IN EKURHULENI

The City of Ekurhuleni is a major metropolitan municipality that provides essential municipal services 3, 178, 470 residents and ratepayers. The purpose of research was to determine the level of satisfaction of people who live and work in the City of Ekurhuleni with the quality of municipal services they are provided with routinely. The survey was conducted by gathering household-level information from 544 residents of Ekurhuleni. The level of satisfaction of respondents with the quality of municipal services was measured by using a matrix of indicators developed by Das, Das and Barman (2021:885-913) for conducting a similar assessment. A composite index developed by D’Inverno and De Witte (2020:1129-1141) was used as a benchmark for measuring the level of services rendered to people who live in the City. The main result of the survey was that 63.05% of people who took part in the survey expressed satisfaction with the quality of services that were rendered to people living in the City. The results showed that 36.95% of people in the survey were not happy with the quality of services rendered to people who live in the City. The survey revealed that satisfaction with services was influenced by the ability of employees of the City to resolve service-related queries promptly, a lengthy duration of residence in Ekurhuleni (11 years or longer), and being provided with accurate financial statements.

Coping with climate shocks: The complex role of livestock portfolios

• Livestock portfolios play a significant role, as an income and consumption buffering strategy during severe droughts. • The buffering potential of livestock varies by income quintile, length of the climate shock, animal species, and region. • Households face trade-offs between using livestock assets to smooth the effect of the shock or protect future income generation. • Livestock oriented resilience interventions should carefully consider the relationships among species, droughts, and socioeconomic groups. • This study employs a unique dataset combining socioeconomic and livestock asset data from 150 000 households with a multi-scalar drought index. The effects of climate change are alarming, with projections suggesting that weather events will become more extreme and frequent, affecting households in regions that are already highly vulnerable. This study explores the role of livestock as a household coping strategy against climate shocks. Using quantile regression analysis, we examine the potential of different animal species to buffer the effects of drought on income and consumption. We assemble a unique global dataset that combines household-level socioeconomic information with a multi-scalar climatic drought index. Our study confirms the significant, yet context-dependent, role of livestock portfolios as a buffering mechanism against the effects of drought on household income and consumption. The effect is driven by the specific type of animal species, length of the shock, and socioeconomic features. These findings could assist the design of livestock-oriented policy interventions. The novel contributions of this study include the first cross-country analysis of the buffering effect of livestock against drought; use of the standardized precipitation-evapotranspiration index as a multi-scalar drought indicator -; and a uniquely extensive dataset allowing for the analysis of interactions.

Community Assessment for Public Health Emergency Response (CASPER) Following Hurricane Michael, Bay and Gulf Counties, Florida, 2019.

On October 10, 2018, Hurricane Michael made landfall near Mexico Beach, Florida, as one of the strongest storms on record to hit the US mainland. Hurricane Michael brought strong winds, heavy rain, and life-threatening storm surge, causing extensive damage across the Florida Panhandle. To assess community preparedness and effects experienced by Panhandle residents, including structural and economic losses, injury and illness, health care access, and suicide risk and ideation in the counties most severely impacted by Hurricane Michael. The Florida Department of Health conducted a Community Assessment for Public Health Emergency Response (CASPER) in October and November 2019, a year after Hurricane Michael made landfall. CASPER is a 2-stage cluster sampling method designed to provide household-level information about a community's needs in a timely, inexpensive, and representative manner. A total of 30 clusters were randomly selected from Bay and Gulf Counties, Florida. In total, 178 face-to-face interviews were completed with adult residents 18 years or older. Hurricane-related impacts, including structural and economic losses, injury and illness, health care access; and mental health. Almost half of respondents did not evacuate despite mandatory evacuation orders. Most houses (78.1%) received some damage, with more than half still not repaired 1 year later. Access to emergency supply kits, water, nonperishable foods, medications, and health care was common, though many reported needing supplies not included in their kit. Less than half reported having working household carbon monoxide detectors. Injuries and illnesses associated with the hurricane were uncommon; however, anxiety, depression, and insomnia were reported as occurring or worsening by more than one-third of respondents posthurricane. Increased education and communication regarding hurricane preparedness and recovery, which include clearer messaging on evacuation, improving emergency supply kits, importance of carbon monoxide detectors, and proper generator use, could enhance the safety of the community.

No ordinary leaders - Analysing female-headed households in Palestine refugee camps

Abstract We explore the potential impacts of being a female head of household (FH) or a family member in a female-headed household (MFH) in terms of budget expenditures and socio-economic determinants. Female household leaders in Palestine Refugee Camps find themselves with more barriers to provide the basic needs to their families. However, there is yet no analysis on the different household typologies, nor whether these translate into differences in healthcare spending and well-being outcomes. We perform a cross section analysis using two-part models (probit and glm) to understand correlations between household composition and spending decisions, as well as healthcare indicators. The data are from AUB Socioeconomic Surveys from 2010 and 2015 with household and individual level information. Our preliminary results follow the evidence in the literature and show that expenditure in healthcare as a percentage of total spending is 2.3%*** higher in 2010 and 3.3%*** in 2015 in female headed households. This difference is higher in families headed by widows or single women. Comparing 2010 to 2015 female-headed households are better off financially and belonging to these families is a significant determinant of receiving remittances from family abroad or in Lebanon and being self-employed. Our results suggest that family remittances for female-headed households, heads of households having their own business and better budget management may be helping these families to cope with financial distress. These families are also target of special social support, but further research is needed to understand whether this support should target the gender of the household head or a more specific issue, that might be common to most of these households, but not the female leadership itself. Key messages Female-headed households are related to higher household budget spending on healthcare, are more likely to receive remittances from abroad and most of female heads of households are self-employed. We contribute to the discussion on whether special social support should target specifically female headed households or other specific poverty related issues.

Agroforestry diversity, indigenous food consumption and nutritional outcomes in Sauria Paharia tribal women of Jharkhand, India.

Like several indigenous populations, Sauria Paharias, a vulnerable indigenous tribal group residing in a biodiverse environment of Jharkhand, India, have high levels of undernutrition. We assessed agroforestry and dietary diversity, food consumption especially indigenous food (IF) intake and nutritional status of Sauria Paharia women through a cross‐sectional study conducted in 18 villages of Godda district, Jharkhand. Household level information was elicited through household surveys including a dietary survey and a food frequency questionnaire. Twenty‐four‐hour dietary recalls (24 HDR) and anthropometric assessments were taken on one randomly selected woman per household. An index, Food Accessed Diversity Index (FADI) created to measure agroforestry diversity, showed a low mean score of 0.21 ± 0.15 and range: 0, 0.85. Fifty‐nine percent of women consumed any IF during 24 HDR. Median minimum dietary diversity score for women (MDD‐W) was 3 (acceptable score ≥5). More than 96% of women had intakes below estimated average requirements for all nutrients studied (energy; vitamins A, C, thiamine, riboflavin, niacin, pyridoxine; folate; iron; calcium and zinc) except protein; 41% women were underweight. IF consumption was independently associated with calcium and vitamin A intake. Decision trees developed for micronutrient consumption at different levels of MDD‐W score and IF consumption scenarios revealed 1.3 to 2.9 times higher consumption of micronutrients among women with MDD‐W ≥ 3 or 4. Strategies like agricultural extension programmes promoting indigenous varieties and nutrition education for increasing dietary diversity with IFs have potential to address undernutrition in Sauria Paharia women.

Mobilizing Knowledge: A Comprehensive Toolkit for Quality Assured Nutrition Data and Piloting Gender Indicators

Abstract Objectives Nutrition International (NI) sought to standardize and add novel indicators to the multiple coverage surveys conducted each year on maternal, newborn, infant and child nutrition programs to assure quality and timely, gender-related data that meets next-generation monitoring needs. Methods In collaboration with Campbell Collaboration (CC) and University of Toronto (UT), NI developed a comprehensive step-wise survey toolkit with multiple intervention modules using a systematic process for selecting and contextualizing indicators (NI), validating data quality (NI-UT) and piloting gender indicators derived based on statistical modelling results using Demographic and Health Survey gender and nutrition related data (CC-NI). The resulting Nutrition Information Monitoring Systems (NIMS) toolkit now includes ODK formatted questionnaire templates, quality control and assurance checklists and ready-to-use SPSS syntax for data analysis and interpretation purposes. NIMS derives its results from household-level information through the following modules: zinc and Oral Rehydration Salts coverage for diarrhea treatment, maternal-newborn nutrition, weekly iron-folic acid supplementation among adolescent girls, and infant and young child nutrition – each with selected knowledge components and newly-devised gender-related questions to inform NI's nutrition-sensitive programs. Selected modules were implemented in NI's ten intervention countries 2019–20. Results Application of these procedures and quality metrics allowed NI program officers to: 1) systematically assess quality during data collection – identifying and correcting surveyor errors and potential sampling bias in a timely fashion, 2) validate and visually demonstrate data quality to relevant stakeholders, and 3) produce quality assured data within 1–3 weeks, compared to 1–3 months for previous surveys that did not use the NIMS procedures and tools. Conclusions This systematic approach facilitated reporting timely, quality assured nutrition program data to inform how NI interventions and gender-related analyses will identify how NI's programming can be more gender-responsive. Funding Sources CanWaCH, Global Affairs Canada and Nutrition International.

Modeling and comparing central and room air conditioning ownership and cold-season in-home thermal comfort using the American Housing Survey.

Household-level information on central (cenAC) and room (rmAC) air conditioning and cold-weather thermal comfort are often missing from publicly available housing databases hindering research and action on climate adaptation and air pollution exposure reduction. We modeled these using information from the American Housing Survey for 2003–2013 and 140 U.S. core-based statistical areas employing variables that would be present in publicly available parcel records. We present random-intercept logistic regression models with either cenAC, rmAC or “home was uncomfortably cold for 24 hours or more” (tooCold) as outcome variables and housing value, rented vs. owned, age, and multi- vs. single-family, each interacted with cooling- or heating-degree days as predictors. The out-of-sample predicted probabilities for years 2015–2017 were compared to corresponding American Housing Survey values (0 or 1). Using a 0.5 probability threshold, the model had 63% specificity (true negative rate), and 91% sensitivity (true positive rate) for cenAC, while specificity and sensitivity for rmAC were 94% and 34%, respectively. Area-specific sensitivities and specificities varied widely. For tooCold, the overall sensitivity was effectively 0%. Future epidemiologic studies, heat vulnerability maps, and intervention screenings may reliably use these or similar AC models with parcel-level data to improve understanding of health risk and the spatial patterning of homes without AC.

Climate Change and Migration: Adapting to Crisis

The present study is attempted to identify the determinants of migration in India. The National Sample Survey data of 64th round (July 2007-June 2008) was used and decoded to elicit household-level information. A multi-criteria approach was adapted to the analysis of the data. The study’s findings revealed that about 70% of migrated people are illiterate, while 57% of migrated people were agricultural laborers. The multi-criteria analysis results for permanent migration revealed that farmers belong to the rural area, having a land size less than two hectares, belonging to the Hindu religion, are likely to migrate permanently. Also, illiteracy, marital status, low consumption expenditure in rural areas, rainfall, and minimum temperature motivate farmer’s decision to adopt migration as an ultimate coping strategy against climate change. As far as grass-root policy interventions are concern, it is suggested that in rural areas, where unemployment has the main driver for migration, a proactive social protection programme, i.e., MGNREGA can be part of a proactive approach to managing climate-induced migration. Climate change as a cause of migration is uncertain and contextual. This necessitates the inclusivity of local populations in decision-making wherein their perceptions and responses are democratically represented and not merely channeled into participatory processes.