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

Day Scholars Food Insecurity Experience Scale-Survey Module (DSFIES-SM):Psychometric Analysis

Background: School feeding programs’ evaluation requires the measurement of food insecurity, a more objective indicator, within schools in low-income countries. The Global Child Nutrition Foundation (GCNF) uses subjective indicators to report school feeding coverage rates across many countries that participate in the global survey of school meal programs all year round. Aim: To test the methodological feasibility of measuring a school food insecurity construct as a direct indicator of the effectiveness and efficiency of school feeding programs. Methods: Two-stage sampling was used during the selection of schools and 128 schoolchildren with a mean (SD) age of 10.5(1.58) were recruited. Item Response Theory (IRT) and Classical Test Theory (CTT) approaches were utilized during DSFIES-SM development. Psychometric analysis was utilized to assess the psychometric properties of the measure of school food insecurity and to establish the construct-level reliability, convergent and discriminant validity of the DSFIES-SM. Results: DSFIES-SM generated acceptable item-level reliabilities, ranging from.75 to.78. The construct-level reliability of the DSFIES-SM was indicated by Cronbach’s α of.78. Composite reliability was at.77. Fit measures and tests of model fitness for confirmatory factor analysis (CFA) (RMSEA &lt; 0.0001; TLI = 1.06; SRMR = 0.043; CFI = 1.00, p =.85) confirmed that the data fitted the model perfectly. Conclusion: DSFIES-SM consists of twelve questions with dichotomous yes/no responses. DSFIES-SM has good convergent and discriminant validity. Findings suggest that the items compose a statistical scale designed to cover a range of severity of school food insecurity. Future replications to establish other forms of validity across different cultural contexts in low-income countries can be of benefit to the present research.</p

Differential COVID-19 Vaccination Uptake and Associated Factors among the Slum and Estate Communities in Uganda: A Cross-Sectional Population-Based Survey

Vaccination against COVID-19 remains one of the ultimate solutions to the ongoing pandemic. This study examined and compared the completion of primary COVID-19 vaccination series and associated factors in the slum and estate communities of Uganda. This was a cross-sectional survey conducted among 1025 slum and estate residents. Logistic regression models were fitted. Of the 1025 participants, 511 were slum residents and 514 were estate residents. Completion of COVID-19 vaccination was 43.8% in the slum community and 39.9% in the estate community (p = 0.03). Having more knowledge about COVID-19 was positively associated with completing COVID-19 vaccination in both communities. Perceived benefits and cues to action also had a positive association, but only among the slum residents. However, perceiving people infected with COVID-19 as having a high death rate, perceived barriers such as serious side effects and long distances, and depressive symptoms had negative associations with vaccine uptake among the slum community, but not in the estate community. Addressing barriers to vaccination, strengthening and utilizing the various cues to action, engagement of religious and cultural leaders, and continued community education and sensitization tailored to the needs of each community are potentially vital strategies in raising vaccination rates. Consideration of socioeconomic impact-alleviation strategies, especially among the urban poor, would also be beneficial

Validation of an automated wearable camera-based image-assisted recall method and the 24-Hour 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

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

Abstract 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