Characteristics of food environments that influence food acquisition and diets of women in low- and middle-income countries: a scoping review protocol.

OBJECTIVE: This scoping review aims to identify and map characteristics of food environments that influence food acquisition practices and dietary intake of women of reproductive age in low- and middle-income countries. INTRODUCTION: Due to the disproportionate burden of malnutrition on women of reproductive age in low- and middle-income countries, accelerated progress in improving women's nutrition is required to achieve Sustainable Development Goal 2 "Zero hunger" by 2030. Food environments are increasingly recognized as the key interface between consumers and food systems; however, little is known about the characteristics that influence women's food acquisition and diets in low- and middle-income countries, especially during physiological stages of heightened nutritional requirement, such as pre-conception, pregnancy, and breastfeeding. INCLUSION CRITERIA: This review will consider quantitative, qualitative, mixed methods, or review studies that report on the influence of food environment characteristics on food acquisition practices and dietary intake of women aged 15 to 49 years in any low- or middle-income country, as defined by the World Bank in 2021. METHODS: Twenty-one databases across EBSCO, Web of Science Core Collection, and PubMed platforms will be searched. Screening, selection, and data extraction will be performed in duplicate by 2 members of the team, with any discrepancies resolved by group discussion. The patterns of food acquisition and dietary intake in relation to food environment characteristics will be charted, mapped, and summarized in tabular and graphical formats. Findings will inform the refinement of effective food environment conceptual frameworks for this nutritionally vulnerable group.

Automated wearable cameras for improving recall of diet and time use in Uganda: a cross-sectional feasibility study.

BACKGROUND: Traditional recall approaches of data collection for assessing dietary intake and time use are prone to recall bias. Studies in high- and middle-income countries show that automated wearable cameras are a promising method for collecting objective health behavior data and may improve study participants' recall of foods consumed and daily activities performed. This study aimed to evaluate the feasibility of using automated wearable cameras in rural Eastern Ugandan to collect dietary and time use data. METHODS: Mothers of young children (n = 211) wore an automated wearable camera on 2 non-consecutive days while continuing their usual activities. The day after wearing the camera, participants' dietary diversity and time use was assessed using an image-assisted recall. Their experiences of the method were assessed via a questionnaire. RESULTS: Most study participants reported their experiences with the automated wearable camera and image-assisted recall to be good (36%) or very good (56%) and would participate in a similar study in the future (97%). None of the eight study withdrawals could be definitively attributed to the camera. Fifteen percent of data was lost due to device malfunction, and twelve percent of the images were "uncodable" due to insufficient lighting. Processing and analyzing the images were labor-intensive, time-consuming, and prone to human error. Half (53%) of participants had difficulty interpreting the images captured by the camera. CONCLUSIONS: Using an automated wearable camera in rural Eastern Uganda was feasible, although improvements are needed to overcome the challenges common to rural, low-income country contexts and reduce the burdens posed on both participants and researchers. To improve the quality of data obtained, future automated wearable camera-based image assisted recall studies should use a structured data format to reduce image coding time; electronically code the data in the field, as an output of the image review process, to eliminate ex post facto data entry; and, ideally, use computer-assisted personal interviews software to ensure completion and reduce errors. In-depth formative work in partnership with key local stakeholders (e.g., researchers from low-income countries, representatives from government and/or other institutional review boards, and community representatives and local leaders) is also needed to identify practical approaches to ensuring that the ethical rights of automated wearable camera study participants in low-income countries are adequately protected.

Validation of an Automated Wearable Camera-Based Image-Assisted Recall Method and the 24-h Recall Method for Assessing Women's Time Allocation in a Nutritionally Vulnerable Population: The Case of Rural Uganda.

Accurate data are essential for investigating relationships between maternal time-use patterns and nutritional outcomes. The 24 h recall (24HR) has traditionally been used to collect time-use data, however, automated wearable cameras (AWCs) with an image-assisted recall (IAR) may reduce recall bias. This study aimed to evaluate their concurrent criterion validity for assessing women's time use in rural Eastern Ugandan. Women's (n = 211) time allocations estimated via the AWC-IAR and 24HR methods were compared with direct observation (criterion method) using the Bland-Altman limits of agreement (LOA) method of analysis and Cronbach's coefficient alpha (time allocation) or Cohen's κ (concurrent activities). Systematic bias varied from 1 min (domestic chores) to 226 min (caregiving) for 24HR and 1 min (own production) to 109 min (socializing) for AWC-IAR. The LOAs were within 2 h for employment, own production, and self-care for 24HR and AWC-IAR but exceeded 11 h (24HR) and 9 h (AWC-IAR) for caregiving and socializing. The LOAs were within four concurrent activities for 24HR (-1.1 to 3.7) and AWC-IAR (-3.2 to 3.2). Cronbach's alpha for time allocation ranged from 0.1728 (socializing) to 0.8056 (own production) for 24HR and 0.2270 (socializing) to 0.7938 (own production) for AWC-IAR. For assessing women's time allocations at the population level, the 24HR and AWC-IAR methods are accurate and reliable for employment, own production, and domestic chores but poor for caregiving and socializing. The results of this study suggest the need to revisit previously published research investigating the associations between women's time allocations and nutrition outcomes.

A food-based approach could improve dietary adequacy for 12-23-month-old Eastern Ugandan children.

Little is known about dietary adequacy, for young Ugandan children, or context-specific food choices to improve it. This study estimated the percentage of breastfed 12-23-month-old rural Eastern Ugandan children (n = 114) at risk of inadequate intakes of 12 nutrients; and identified realistic food choices for improving it. In this cross-sectional survey, dietary (weighed food records), anthropometric and socioeconomic data were collected. The percentages of children at risk of inadequate nutrient intakes were estimated, assuming 541 g/day of breast milk was consumed. The median nutrient densities of their complementary feeding diets were also compared with desired levels. Linear programming analyses were used to identify 'problem nutrients' (where requirements will be difficult to meet given dietary practices) and model food choices to improve dietary adequacy. Overall, 21.2% of children were stunted and 3.8% were wasted. A high percentage (>45%) of children were at risk of inadequate intakes, for nine of the 12 nutrients assessed, and dietary nutrient densities were below desired levels for seven of the 12 nutrients. Iron, calcium, thiamine and niacin were 'problem nutrients'. Through careful selection of foods, modelling indicates that population level dietary adequacy can be achieved for eight of the 12 nutrients modelled. These choices include cows' milk, legumes, green leafy vegetables, sweet potatoes and fruits. Overall results suggest these high percentages of children at risk of inadequate nutrient intakes can be reduced through behaviour change interventions, although additional interventions may be required to ensure population-level dietary adequacy for iron, thiamine and niacin.

Validation of a life-logging wearable camera method and the 24-h diet recall method for assessing maternal and child dietary diversity.

Accurate and timely data are essential for identifying populations at risk for undernutrition due to poor-quality diets, for implementing appropriate interventions and for evaluating change. Life-logging wearable cameras (LLWC) have been used to prospectively capture food/beverage consumed by adults in high-income countries. This study aimed to evaluate the concurrent criterion validity, for assessing maternal and child dietary diversity scores (DDS), of a LLWC-based image-assisted recall (IAR) and 24-h recall (24HR). Direct observation was the criterion method. Food/beverage consumption of rural Eastern Ugandan mothers and their 12-23-month-old child (n 211) was assessed, for the same day for each method, and the IAR and 24HR DDS were compared with the weighed food record DDS using the Bland-Altman limits of agreement (LOA) method of analysis and Cohen's κ. The relative bias was low for the 24HR (-0·1801 for mothers; -0·1358 for children) and the IAR (0·1227 for mothers; 0·1104 for children), but the LOA were wide (-1·6615 to 1·3012 and -1·6883 to 1·4167 for mothers and children via 24HR, respectively; -2·1322 to 1·8868 and -1·7130 to 1·4921 for mothers and children via IAR, respectively). Cohen's κ, for DDS via 24HR and IAR, was 0·68 and 0·59, respectively, for mothers, and 0·60 and 0·59, respectively, for children. Both the 24HR and IAR provide an accurate estimate of median dietary diversity, for mothers and their young child, but non-differential measurement error would attenuate associations between DDS and outcomes, thereby under-estimating the true associations between DDS - where estimated via 24HR or IAR - and outcomes measured.