Baseline survey dataset on household characteristics and dietary intake among women of reproductive age and children 6-23 months in Kisumu’s Urban Informal settlements (2022)

This data was collected through the HealthyFoodAfrica Project (https://healthyfoodafrica.eu/), a research and innovation project which aims at improving nutrition in Africa by strengthening the diversity, sustainability, resilience, and connectivity of food systems by reconnecting food production and food consumption in effective ways. The project was implemented in 10 cities in 6 African Countries. The objective was to assess the food consumption patterns and their determinants among households in the context of Kisumu informal settlements, providing an understanding of the types of foods consumed in the households (focusing on the consumption of women and children) to inform interventions aimed at improving diet quality in vulnerable urban populations. Methodology:The data was collected as part of HealthyFoodAfrica Project’s baseline conducted in February 2022 in 4 urban informal settlements in Kisumu, Kenya. The 4 informal settlements were Manyatta A, Manyatta B, Obunga and Bandani. We conducted a cross-sectional survey of randomly selected households. The study focused on women of reproductive age (WRA, 15–49 years) and children (6–23 months), the population groups most vulnerable to malnutrition. To determine the number of villages (clusters) to be included in the survey, we first applied a proportionate-to-population-size (PPS) approach based on population estimates for each settlement. Community health promoters provided village names and household lists, which we filtered to retain only households that included our eligible sampling frame of WRA and children aged 6–23 months. Using the PPS method, a total of 42 villages were sampled, distributed across the four settlements as follows: 17 villages each in Manyatta A and Manyatta B, and four villages each in Obunga and Bandani. These were randomly selected from the full list of villages available in each settlement. We determined a minimum sample size of 372 households based on the Charan and Biswas (2013) method. The sample size was increased to 504 households to account for potential non-response attrition (such as refusals or unavailable participants), ensure balanced representation across all four settlements, and improve precision in subgroup analyses. Households were then randomly selected from the eligible list. Because population size had already been considered, we uniformly selected 12 households per village for the survey. In the end, 510 households were surveyed. The slight increase beyond the planned sample size was due to the inclusion of additional eligible woman-child pairs encountered during data collection. We used a semi-structured questionnaire developed in English and uploaded in the KoboToolbox platform to capture a range of household data, including socio-demographic characteristics; nutrition knowledge, attitudes, and practices (KAP); main sources of food; distance to the main food market, and food shopping behavior (frequency of shopping and preferred time of shopping). We assessed individual dietary intakes for both mothers and children using a multiple pass 24-hour quantitative dietary intake recall on two non-consecutive days for at least half of the participants. The tool adhered to Food and Agriculture Organization (FAO) and World Health Organization (WHO) guidelines for measuring dietary diversity in women of reproductive age, and infants and young children, respectively (FAO, 2021; WHO and UNICEF, 2021). Participants reported all foods and beverages consumed in the 24 hours preceding the interview.