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Objective: Artisanal and small-scale mining (ASM) is a widespread livelihood in low- and middle-income countries; however, many in ASM communities face high levels of poverty and malnutrition. The food environments in ASM communities have non-agricultural rural characteristics that differ from those in urban and agricultural rural areas examined in much existing food environment literature. Design: We examine these complex external and personal food environments in ASM communities via a study using qualitative and quantitative methods. Market surveys and a cross-sectional household survey, plus qualitative mining site non-participant observations and in-depth structured interviews, were conducted in three waves. Setting: Eighteen study sites in ASM communities in northern Guinea. Participants: Surveys covered mothers in mining households with young children (n 613); in-depth interviews engaged caregivers of young children (n 45), food vendors (n 40) and young single miners (n 15); observations focused on mothers of young children (n 25). Results: The external food environment in these ASM communities combines widespread availability of commercially processed and staple-heavy foods with lower availability and higher prices for more nutritious, non-staple foods. Within the personal food environment, miners are constrained in their food choices by considerable variability in daily cash income and limited time for acquisition and preparation. Conclusions: We demonstrate that ASM communities have characteristics of both urban and rural populations and argue for greater nuance and appreciation of complexity in food environment research and resultant policy and programming.
Research was conducted in Kouroussa and Siguiri prefectures, Kankan region, Guinea. Study sites were selected purposively to cover four different strata: temporary mining camps, villages far from towns, villages close to towns and towns. Stratification was driven by expectations that proximity to a village/town influenced food access. Eighteen sites were included; specific sites studied changed over time, as mines are regularly closing and being started. The focus population was mothers of children under age 5 in mining households due to the importance of maternal and young child nutrition in development. Young single miners, primarily male, were also included to understand how experiences might vary across groups. Data were collected iteratively from May 2018 to December 2019. First, structured non-participant observations at ten mining sites were used to understand the setting, food availability, actors involved and work roles. Stakeholders (government, civil society and local ASM leaders) were consulted via key informant interviews. A cross-sectional household survey was carried out in two waves, with no overlap in respondents between waves. Households were chosen randomly, with sample size proportional to site population. Survey sample size was determined based on an ability to calculate the proportion of women with a minimally diverse diet, conservatively assuming a level of 50 %, alpha of 0·05, power of 0·8, beta of 0·2 and design effect of 1·5, yielding a minimum sample size of 291 per wave. Households were eligible to participate if at least one member was active in mining and a child under 5 lived in the household. The mother/guardian of the youngest child was the primary respondent. In addition, two waves of in-depth interviews were conducted, covering mothers of young children, food vendors and young single miners. Twenty-five interviews with mothers also included extended periods of non-participant observation. Four market surveys were conducted, aiming to cover all major seasons. In each, 4–7 markets that served the mining sites targeted by the household survey were selected; the number of markets surveyed varied by wave, depending on how many sites had associated markets. In-depth non-participant observations were carried out at eight markets. Data collection instruments were developed based on standard questions (e.g. from Demographic and Health Surveys) and validated tools used by other studies within the Drivers of Food Choice project portfolio, where relevant. Instruments were pilot-tested in a comparable community not targeted by the research and revised accordingly, primarily to shorten interview length. The survey and interview questionnaires were developed in French and translated orally into Malinké; an agreed-upon translation was developed and validated with interviewers during training. Household and market surveys used structured, mainly closed-ended questionnaires. Market surveys collected price and quantity data and covered all foods at least occasionally present in local markets aside from the ‘basic ingredients and snacks’ categories (see Table Table5),5), wherein there was more diversity and indicative products were chosen to represent broader groups. Household survey questions on food acquisition measured the more frequently consumed foods (Table (Table6).6). Commercially processed drinks and snacks (e.g. cookies, candies, pasta and sardines), following a definition previously used for research in Guinea(67), were also noted in observations. For the household and market observations, semi-structured paper-based guides were used, including both categorical/closed-ended questions (e.g. distance to closest village) and open-ended ones (e.g. miners’ working conditions). Availability and prices of foods in open-air markets*,† Avg, average. Main foods consumed and consumption from home production* Field research was conducted by up to nine data collectors, supervised by 2–5 supervisors (depending on the data collection wave). Data collectors were competitively selected from recent graduates of Université Julius Nyerere de Kankan’s sociology department. All knew the local context well and were fluent in Malinké and French. Data collectors were trained in research ethics, interview methods and data-entry and note-taking methods in addition to the data-collection instruments. Each data collector specialised in either qualitative (in-depth interviews, observations) or quantitative (household and market survey) methods. Supervisors oversaw data collection progress and verified data quality daily. Data from market and household surveys were entered via smartphones into a cloud-based data storage platform. Interview data were recorded via detailed interview notes and post-interview debriefings. During the non-participant observations, notes were taken on paper and later scanned/transcribed into electronic versions. All data were entered and analysed in French. Interview notes were coded using deductive coding in ATLAS.ti(68). An initial deductive coding scheme was created based on the thematic modules covered in the interview guides and applied to all collected data; similar codes were grouped into thematic categories (e.g. food preparation practices) and code summaries created. Quantitative data were cleaned and analysed using Stata SE15(69) via frequency tabulations and/or calculation of means. Dietary diversity was assessed via a list-based 24-h-recall using ten standard categories(70). We also calculated the Household Food Insecurity Access Score(71). For food price data, there was considerable variation across seasons and markets; as such, we calculated median price across all data points and the seasonal range in the across-market median price, to indicate seasonal price variability. Table Table11 summarises data collection methods, sample sizes and topics, while Table Table22 indicates how these were used to measure different food environment dimensions, showing the diversity in evidence brought by the mix of methods used. Summary of methods Methods and main indicators used by food environment dimension Dimensions are classified as per(39). To clarify the type of evidence presented on each food environment dimension, we note whether data are objective (via direct observation) (O); objective fact as reported by participants (R) or participants’ personal perceptions (P).
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