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An investigation is conducted into whether trip generation models, estimated on travel survey data collected in the 1998 Nashville household travel behavior survey, can be enhanced in forecast performance by combining the 1998 Nashville survey data with data collected in metropolitan regions in either the 2009 National Household Travel Survey (NHTS) or in the 2009 State of Tennessee Add-On NHTS. Data for assessing the forecast performance of the alternative developed models were collected in the 2012 Nashville transportation and health survey. Linear regression analysis and Bayesian statistics were used to develop alternative trip generation models whose performances in forecasting travel were assessed. Major findings of the study include the following: (a) metropolitan trip generation models for the mandatory purposes of work and school did not benefit from update with national or state-level data for these trip purposes; (b) metropolitan trip generation models for nonwork nonschool purposes (discretionary purposes) and for trips across all travel purposes improved in forecast performance with update with national-level data collected in the 2009 NHTS only. This finding suggests that metro-level data collected in the regular NHTS rather than data collected in a specific US state's Add-on Survey should be the data source for updating metropolitan models of discretionary travel in medium-range forecasting; and (c) development of updated models by Bayesian updating, though relatively simple, had the best forecast performance of the tested models and hence is recommended as the preferred method for model updating in planning practice in the state. [ABSTRACT FROM AUTHOR]

Background: Low birth weight (LBW) is associated with infant mortality and postpartum health complications. In previous studies, overall LBW has been found to be significantly associated with several sociodemographic factors, including ethnicity, maternal age, and family income. Few studies have evaluated the association between environmental risk factors and LBW rates. This study investigated the effect of pre-birth water, sanitation, and hygiene (WASH) and housing conditions on self-reported low birth weight. Methods: The Ethiopian Demographic and Health Survey, which covered all administrative regions of Ethiopia from January to June 2016, provided data for this study. STATA version 16 was used to analyze 12,125 participants across weighted samples. Multivariable multilevel mixed-effect logistic regression analysis was conducted to determine the effects of each factor on the outcome while accounting for data clustering. The adjusted odds ratios and corresponding 95% confidence intervals were used to determine the statistical significance of the independent variables. Results: One thousand five hundred and seventeen newborns, or 12.59% [95% CI (10.2- 15.3)], had low birth weights. When other factors were taken into account, the following factors were significantly associated with low birth weight: not using small-scale water treatment technology before using water [AOR (95% CI) 1.36 (1.08–2.23)], burning solid fuels for energy [AOR (95% CI) 1.99 (1.60–2.21)], living in homes with natural wall coverings [AOR (95% CI) 1.81 (1.47–2.21)], using a shared latrine within a woman's housing complex or compound [AOR (95% CI) 1.63(1.06–2.25)], and living in peripheral, isolated regions [AOR (95% CI) 1.38 (1.06–2.21)]. Conclusion: A little more than one out of every ten deliveries in Ethiopia was under normal (recommended) weight. This study shows that poor housing conditions and lack of household WASH infrastructure are independent predictors of poor birth outcomes among Ethiopian women, adding to the limited evidence that environmental factors within the domicile contribute to low birth weight. Interventions to address these issues may help lower the prevalence of LBW. [ABSTRACT FROM AUTHOR]

The Demographic and Health Surveys (DHS) have been carried out in over 90 countries since 1984, as interviewer administered household surveys conducted initially by paper and pencil interviews (PAPI). Computer assisted personal interviews (CAPI) were introduced in the 2004 Peru DHS, and since then numerous countries have also switched. However, DHS randomized mode comparisons have been limited. The 2018 Sixth Turkey DHS was conducted using CAPI but allocated one household from 21 in each of 754 clusters to PAPI. This analysis examines a wide range of potential differences between modes: interviewer attitudes toward modes; response rates, underreporting and misreporting of persons or events, number of selections to "check all that applies" questions, respondents' attitudes towards modes reflected by responses to sensitive questions, satisficing behavior such as age heaping, straight-line response patterns, and use of don't know options; and some operational aspects of modes such as retrospective monthly contraceptive prevalence rates, presence of others during interview, and interview length. Findings show that, despite strong interviewer CAPI preference, CAPI and PAPI were on average almost identical in terms of responses. CAPI took 11 min less (total duration of 33 min). Analysis of retrospective monthly contraception use indicated potential underreporting by CAPI for past use, an issue highlighted before in DHS literature. Overall, the switch to computer technology in DHS surveys does not appear to change estimates or levels of nonsampling errors, although some differences with respect to PAPI mode may need DHS designer attention. [ABSTRACT FROM AUTHOR]

Our objective was to examine the prevalence and predictors of delayed medical care due to transportation barriers among children with atopic dermatitis (AD) living in the United States (US). We analyzed data from the 1998–2018 National Health Interview Survey, a nationally representative survey of US households. In 2018, transport‐delayed care was reported for 3.4% of US children with AD, representing approximately 279,000 children annually given the National Health Interview Survey's weighted survey design, and was more common among patients of lower socioeconomic status. Targeted interventions aimed at reducing transportation barriers to healthcare among at‐risk AD patients may reduce health disparities related to AD. [ABSTRACT FROM AUTHOR]

Objective: To assess whether an adapted Demographic and Health Survey (DHS) like cross-sectional household survey with full pregnancy histories can demonstrate the validity of health and demographic surveillance (HDSS) data by producing similar population structural characteristics and childhood mortality indicators at two HDSS sites in The Gambia–Farafenni and Basse. Methods: A DHS-type survey was conducted of 2,580 households in the Farafenni HDSS, and 2,907 in the Basse HDSS. Household members were listed and pregnancy histories obtained for all women aged 15–49. HDSS datasets were extracted for the same households including residency episodes for all current and former members and compared with the survey data. Neonatal (0–28 days), infant (<1 year), child (1–4 years) and under-5 (< 5 years) mortality rates were derived from each source by site and five-year periods from 2001–2015 and by calendar year between 2011 and 2015 using Kaplan–Meier failure probabilities. Survey-HDSS rate ratios were determined using the Mantel-Haenszel method. Results: The selected households in Farafenni comprised a total population of 27,646 in the HDSS, compared to 26,109 captured in the household survey, implying higher coverage of 94.4% (95% CI: 94.1–94.7; p<0.0001) against a hypothesised proportion of 90% in the HDSS. All population subgroups were equally covered by the HDSS except for the Wollof ethnic group. In Basse, the total HDSS population was 49,287, compared to 43,538 enumerated in the survey, representing an undercount of the HDSS by the survey with a coverage of 88.3% (95% CI: 88.0–88.6; p = 1). All sub-population groups were also under-represented by the survey. Except for the neonatal mortality rate for Farafenni, the childhood mortality indicators derived from pregnancy histories and HDSS data compare reasonably well by 5-year periods from 2001–2015. Annual estimates from the two data sources for the most recent quinquennium, 2011–2015, were similar in both sites, except for an excessively high neonatal mortality rate for Farafenni in 2015. Conclusion: Overall, the adapted DHS-type survey has reasonably represented the Farafenni HDSS database using population size and structure; and both databases using childhood mortality indicators. If the hypothetical proportion is lowered to 85%, the survey would adequately validate both HDSS databases in all considered aspects. The adapted DHS-type sample household survey therefore has potential for validation of HDSS data. [ABSTRACT FROM AUTHOR]

Background: Tobacco use is an established preventable risk factor for many noncommunicable diseases and is considered as an important indicator for monitoring progress towards Universal Health Coverage (UHC) and Sustainable Development Goals (SDGs). This study aimed to determine the situation of tobacco use among Iranian adults using 2016 household survey. Methods: This is a secondary analysis of the data from 2016 nationally representative STEPwise approach to Surveillance (STEPs) survey with a sample size of 31,050. The data on tobacco consumption was gathered using questions incorporated in the survey questionnaire. Results: The prevalence of current tobacco use in Iran was 25.2 % (24.4-25.9) in men versus 4% (3.7-4.3) in women. The prevalence was higher in rural areas and among second wealth group. The prevalence of current daily cigarette smoking was 20.1% (19.4-20.7) in men versus 0.9% (0.8-1.1) in women). Average number of cigarettes per day among current cigarette smokers was 14.5% (14.1-14.9), mean age at start smoking among daily cigarette smokers was 21.6% (21.1-22), and 95.2% (94.4-96) of daily current daily cigarette smokers attempted for cessation during past 12 months. Prevalences of exposure to secondhand cigarette smoke among nonsmokers at homes and workplaces were 23.21% (22.65-23.76) and 18.04% (17.2-18.87), respectively. Conclusions: There was a large difference between the prevalence of tobacco use between men and women (25.2% vs. 4%). Higher prevalences of tobacco use in rural areas and among lower wealth quintiles require more equity-based approaches in tobacco combatting actions. [ABSTRACT FROM AUTHOR]

This study analyzes the factors associated with eye care service utilization among Peruvians 50 years of age and older, measured as self-reporting of having undergone examination of visual acuity during the last 12 months. A secondary analysis of the 2019 Demographic and Family Health Survey (ENDES, for its acronym in Spanish) database was carried out. We estimated the weighted proportion of adults 50 years of age and older that reported having undergone a visual acuity examination in the previous 12 months and the frequency according to the variables of interest. Crude (PR) and adjusted prevalence ratios (aPR) of eye care service utilization were constructed using generalized linear models. Approximately 28.8% of Peruvians 50 years of age and older underwent a visual acuity examination in the previous 12 months. Having a higher education (aPR = 1.79; 95% CI: 1.33–2.40), health insurance such as EsSalud (aPR = 1.54; 95% CI: 1.28–1.87), a previous diagnosis of cataracts (aPR = 1.86; 95% CI: 1.67–2.09) and being part of the richest wealth quintile (aPR = 2.36; 95% CI: 1.74–3.20) were associated with greater utilization of eye care services, while living in the jungle was associated with a lower likelihood of utilization of these services. The unequal distribution of health resources within the territory and socioeconomic gaps among the population could explain our findings. Further efforts are needed to fulfill the eye health needs of the Peruvian population. [ABSTRACT FROM AUTHOR]

Background: Much applied research on the consequences of conflicts for health suffers from data limitations, particularly the absence of longitudinal data spanning pre-, during- and post-conflict periods for affected individuals. Such limitations often hinder reliable measurement of the causal effects of conflict and their pathways, hampering also the design of effective post-conflict health policies. Researchers have sought to overcome these data limitations by conducting ex-post surveys, asking participants to recall their health and living standards before (or during) conflict. These questions may introduce important analytical biases due to recall error and misreporting. Methods: We investigate how to implement ex-post health surveys that collect recall data, for conflict-affected populations, which is reliable for empirical analysis via standard quantitative methods. We propose two complementary strategies based on methods developed in the psychology and psychometric literatures—the Flashbulb and test-retest approaches—to identify and address recall bias in ex-post health survey data. We apply these strategies to the case study of a large-scale health survey which we implemented in Colombia in the post-peace agreement period, but that included recall questions referring to the conflict period. Results: We demonstrate how adapted versions of the Flashbulb and test-retest strategies can be used to test for recall bias in (post-)conflict survey responses. We also show how these test strategies can be incorporated into post-conflict health surveys in their design phase, accompanied by further ex-ante mitigation strategies for recall bias, to increase the reliability of survey data analysis—including by identifying the survey modules, and sub-populations, for which empirical analysis is likely to yield more reliable causal inference about the health consequences of conflict. Conclusions: Our study makes a novel contribution to the field of applied health research in humanitarian settings, by providing practical methodological guidance for the implementation of data collection efforts in humanitarian contexts where recall information, collected from primary surveys, is required to allow assessments of changes in health and wellbeing. Key lessons include the importance of embedding appropriate strategies to test and address recall bias into the design of any relevant data collection tools in post-conflict or humanitarian contexts. [ABSTRACT FROM AUTHOR]

Background The Brazilian Household Food Insecurity Measurement Scale (EBIA) is the main tool for assessing household food insecurity (FI) in Brazil and facilitates the monitoring and improvement of national public policies to promote food security. Since 2004, the Brazilian government has conducted National Household Sample Surveys, and in 2018, the government carried out the last national evaluation of FI. Objectives To describe trends in severe FI in Brazil from 2004 to 2018. Methods Data from 3 cross-sectional Brazilian National Household Sample Surveys (sample sizes: 2004 = 112,530; 2009 = 120,910; 2013 = 116,196) and from the last Household Budget Survey (sample size = 57,920) that assessed the status of FI using the EBIA were analyzed. Changes in severe FI during 2 periods (2004–2013; 2013–2018) were estimated while considering sociodemographic factors. Results The period between 2004 and 2013 was marked by a significant decrease in severe FI (–53.6%), but this trend reversed in 2013–2018 (+43.8%). The greatest decrease in severe FI occurred in the Northeast (–57.6%) among households where the reference person was a man (–57.6%) and self-identified as white (–58.1%) (2004–2013). In 2013–2018, households with children aged ≤4 y (+6.3%) and members aged ≥65 y (+12.5%) experienced the lowest increases in severe FI. Conclusions After a significant reduction from 2004 to 2013, severe FI increased sharply from 2013 to 2018, likely due to disruptions in public policies aimed at reducing hunger and unemployment rates. [ABSTRACT FROM AUTHOR]

The need for rigorous and timely health and demographic summaries has provided the impetus for an explosion in geographic studies in low- and middle-income countries. Many of these studies present fine-scale pixel-level maps in an attempt to answer the needs of the current era of precision public health. However, even though household surveys with a two-stage cluster design stratified by region and urbanicity are a major source of data, cavalier approaches are taken to acknowledging the survey design. We investigate the extent to which accounting for the sample design affects the predictive performance at the aggregate level of interest for health policy decisions. We consider various commonly used models and introduce a new Bayesian cluster-level model with a discrete spatial smoothing prior. The investigation is performed through a simulation study in which realistic sampling frames are created for Kenya, based on the population and demographic information, with a survey design that mimics a Demographic Health Survey (DHS). We find that including stratification and cluster-level random effects can improve predictive performance. Spatially smoothed direct (weighted) estimates and area-level models accounting for stratification were robust to the underlying population and survey design. Continuous spatial models showed some promise in the presence of fine-scale variation; however, these models require the most "hand holding." Subsequently, we examine how the models perform on real data, estimating the prevalence of secondary education for women aged 20–29 and neonatal mortality rates, using data from the 2014 Kenya DHS. [ABSTRACT FROM AUTHOR]

Objective. To describe the design of the Mexican 2021 National Health and Nutrition Survey (Ensanut 2021). Materials and methods. The Ensanut 2021 is a probabilistic household survey that is part of the continuous Ensanut 2020-2024; survey outreach, sampling, measurement and logistic organization are described. Results. It is planned to obtain at least 12 060 complete household interviews and 9 837 samples to determine SARS-CoV-2 seropositivity at the national level. Conclusions. Ensanut 2021 will allow to estimate the seroprevalence of SARS-CoV-2 antibodies at regional and national level; also, it will accumulate information to make state inferences for the year 2024. [ABSTRACT FROM AUTHOR]