Addressing unintentional exclusion of vulnerable and mobile households in traditional surveys in Kathmandu, Dhaka and Hanoi : a mixed methods feasibility study

The methods used in low- and middle-income countries’ (LMICs) household surveys have not changed in four decades; however, LMIC societies have changed substantially and now face unprecedented rates of urbanization and urbanization of poverty. This mismatch may result in unintentional exclusion of vulnerable and mobile urban populations. We compare three survey method innovations with standard survey methods in Kathmandu, Dhaka, and Hanoi and summarize feasibility of our innovative methods in terms of time, cost, skill requirements, and experiences. We used descriptive statistics and regression techniques to compare respondent characteristics in samples drawn with innovative versus standard survey designs and household definitions, adjusting for sample probability weights and clustering. Feasibility of innovative methods was evaluated using a thematic framework analysis of focus group discussions with survey field staff, and via survey planner budgets. We found that a common household definition excluded single adults (46.9%) and migrant-headed households (6.7%), as well as non-married (8.5%), unemployed (10.5%), disabled (9.3%), and studying adults (14.3%). Further, standard two-stage sampling resulted in fewer single adult and non-family households than an innovative area-microcensus design; however, two-stage sampling resulted in more tent and shack dwellers. Our survey innovations provided good value for money, and field staff experiences were neutral or positive. Staff recommended streamlining field tools and pairing technical and survey content experts during fieldwork. This evidence of exclusion of vulnerable and mobile urban populations in LMIC household surveys is deeply concerning and underscores the need to modernize survey methods and practices

Prevalence and socio-economic determinants of inadequate dietary diversity among adolescent girls and boys in Bangladesh: findings from a nationwide cross-sectional survey.

Malnutrition among adolescents is often associated with inadequate dietary diversity (DD). We aimed to explore the prevalence of inadequate DD and its socio-economic determinants among adolescent girls and boys in Bangladesh. A cross-sectional survey was conducted during the 2018-19 round of national nutrition surveillance in Bangladesh. Univariate and multivariable logistic regression was performed to identify the determinants of inadequate DD among adolescent girls and boys separately. This population-based survey covered eighty-two rural, non-slum urban and slum clusters from all divisions of Bangladesh. A total of 4865 adolescent girls and 4907 adolescent boys were interviewed. The overall prevalence of inadequate DD was higher among girls (55⋅4 %) than the boys (50⋅6 %). Moreover, compared to boys, the prevalence of inadequate DD was higher among the girls for almost all socio-economic categories. Poor educational attainment, poor maternal education, female-headed household, household food insecurity and poor household wealth were associated with increased chances of having inadequate DD in both sexes. In conclusion, more than half of the Bangladeshi adolescent girls and boys consumed an inadequately diversified diet. The socio-economic determinants of inadequate DD should be addressed through context-specific multisectoral interventions

Surveys for Urban Equity

This dataset contains results and documentation from three cross-sectional urban household surveys done in Kathmandu (Nepal), Dhaka (Bangladesh) and Hanoi (Vietnam) in 2017 and 2018. The surveys primarily aimed to test the feasibility of using new urban household survey methods that try to better cover/capture informal/slum settlements using sampling frame data generated from random forest models that incorporate census data (which is often outdated and inaccurate) with multiple remotely-sensed covariates, such as urbanisation and infrastructure data. Additionally, the surveys also aimed to gather data on a range of topics including many that are not commonly collected in household surveys, particularly of urban areas: A) basic socio-demographic details of household members, B) household characteristics, assets, income and expenses, C) household migration and social capital, D) household member injury and injury related death, and, for one individual per household, E) migration, social capital and depression/mental health. See the "Readme - dataset file descriptions.docx” file for a description of all files and datasets available, plus additional relevant references