RESUMEN

The "Dairy Diary" is a user-friendly web-based dairy intake screener. The reliability and validity are unknown. We aimed to evaluate the screener in terms of test-retest reliability and comparative validity. In a diagnostic accuracy study, a purposefully recruited sample of 79 (age: 21.6 ± 3.8 years) undergraduate dietetics/nutrition students from three South African universities completed 3 non-consecutive days of weighed food records (reference standard) within a seven-day period (comparative validity), followed by two administrations, 2 weeks apart, of the screener (index test) (reliability). For the four dairy product serving scores (PSSs) and the summative dairy serving scores (DSSs) of the screener and the food records, t-tests, correlations, Bland-Altman, Kappa, McNemar's, and diagnostic accuracy were determined. For reliability, mean PSSs and DSSs did not differ significantly (p > .05) between the screener administrations. The mean PSSs were strongly correlated: milk (r = .69; p < .001), maas (fermented milk) (r = .72; p < .001), yoghurt (r = .71; p < .001), cheese (r = .74; p < .001). For DSSs, Kappa was moderate (k = 0.45; p < .001). Non-agreeing responses suggest symmetry (p = .334). For validity, the PSSs of the screener and food records were moderately correlated [milk (r = .30; p = .0129), yoghurt (r = .38; p < .001), cheese (r = .38; p < .001)], with k = 0.31 (p = .006) for DSS. Bland-Altman analyses showed acceptable agreement for DSSs (bias: -0.49; 95% CI: -0.7 to -0.3). Categorized DSSs had high sensitivity (81.4%) and positive predictive value (93.4%), yet low specificity (55.6%) and negative predictive value (27.8%). The area under the receiver operating characteristic curve (0.7) was acceptable. The "Dairy Diary" is test-retest reliable with moderate comparative validity to screen for dairy intake of nutrition-literate consumers.

RESUMEN

Weight-for-age (WFA) growth faltering often precedes severe acute malnutrition (SAM) in children, yet it is often missed during routine growth monitoring. Automated interpretation of WFA growth within electronic health records could expedite the identification of children at risk of SAM. This study aimed to develop an automated screening tool to predict SAM risk from WFA growth, and to determine its predictive ability compared with simple changes in weight or WFA z-score. To develop the screening tool, South African child growth experts (n = 30) rated SAM risk on 100 WFA growth curves, which were then used to train an artificial neural network (ANN) to assess SAM risk from consecutive WFA z-scores. The ANN was validated in 185 children under five (63 SAM cases; 122 controls) using diagnostic accuracy methodology. The ANN's performance was compared with that of changes in weight or WFA z-score. Even though experts' SAM risk ratings of the WFA growth curves differed considerably, the ANN achieved a sensitivity of 73.0% (95% confidence interval [CI]: 60.3; 83.4), specificity of 86.1% (95% CI: 78.6; 91.7) and receiver-operating characteristic curve area of 0.795 (95% CI: 0.732; 0.859) during validation with real cases, outperforming changes in weight or WFA z-scores. The ANN, as an automated screening tool, could markedly improve the identification of children at risk of SAM using routinely collected WFA growth information.

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RESUMEN

Paper-based dietary assessment tools such as food frequency questionnaires (FFQ) and especially dietary screeners are making way for versions that use technology. Amidst low intakes of dairy and dairy-related nutrients in South Africa, and to increase public awareness thereof, we aimed to develop and evaluate the usability of an application (app) to screen for dairy intake in higher income South African adults. In a consultative process, a dairy intake screener ('Dairy Diary') was developed as an eight-item quantitative FFQ with four types of commonly consumed local dairy products: milk, maas (fermented milk), yoghurt, and cheese. For each dairy product, usual frequency of consumption and portion size per eating occasion were scored resulting in three risk classes: <1 serving daily; 1≤2 servings daily; ≥2 servings daily. Digitalisation included product- and portion-specific graphics with linkage to risk class-relevant preliminary dairy-related guidance as part of a web-based mobile app. For the evaluation of the usability, the 26-item end-user version of the Mobile Application Rating Scale (uMARS) was used in an online cross-sectional survey (Qualtrics; April 2020). Items were scored on a 5-point Likert-type scale, resulting in three final app scores. From a conveniently recruited sample of 1102, 703 (64%; 81% female; mean age 29.8 ± 11.0 years) were retained for analysis. uMARS-informed descriptive statistics summarise the findings. The uMARS app mean objective quality score (3.9 ± 0.85), app subjective quality score (3.5 ± 0.77), app-specific score (3.6 ± 0.94), and additional question on e-portion (4.3 ± 0.78) met the minimum acceptability score of ≥3.0. For the subscales, the mean score for aesthetics was the highest (4.4 ± 0.82), followed by information (4.3 ± 0.90) and functionality (4.0 ± 1.33). Engagement scored lowest (3.0 ± 1.55). The 'Dairy Diary' is a user-friendly screener for dairy intake.

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Bioelectrical impedance analysis (BIA) is a practical alternative to dual-energy X-ray absorptiometry (DXA) for determining body composition in children. Currently, there are no population specific equations available for predicting fat-free mass (FFM) in South African populations. We determined agreement between fat-free mass measured by DXA (FFMDXA) and FFM calculated from published multi-frequency bioelectrical impedance prediction equations (FFMBIA); and developed a new equation for predicting FFM for preadolescent black South African children. Cross-sectional data on a convenience sample of 84 children (mean age 8.5 ± 1.4 years; 44 {52%} girls) included body composition assessed using Dual X-ray Absorptiometry (FFMDXA) and impedance values obtained from the Seca mBCA 514 Medical Body Composition analyzer used to calculate FFM using 17 published prediction equations (FFMBIA). Only two equations yielded FFM estimates that were similar to the DXA readings (p > 0.05). According to the Bland-Altman analysis, the mean differences in FFM (kg) were 0.15 (LOA: -2.68; 2.37) and 0.01 (LOA: -2.68; 2.66). Our new prediction equation, F F M = 105.20 + 0.807 × S e x + 0.174 × W e i g h t + 0.01 × R e a c t a n c e + 15.71 × log ( R I ) , yielded an adjusted R2 = 0.9544. No statistical shrinkage was observed during cross-validation. A new equation enables the BIA-based prediction of FFM in the assessment of preadolescent black South African children.

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BACKGROUND: Overweight affects 65% of black South African women. Effective weight management requires accurate measurement or estimation of energy expenditure. AIMS: The study aimed to determine, among overweight women, whether measured resting energy expenditure (REE) differs between black and white participants, and the performance of REE estimation equations. METHODS: The REE of 44 black (age 39.6 ± 9.7 years, body mass index (BMI) 35.1 ± 6.2 kg/m2) and 41 white (age 38.0 ± 11.6 years, BMI 33.9 ± 7.6 kg/m2) women was measured with indirect calorimetry and estimated with equations. Body composition was assessed with multi-frequency bioelectrical impedance analysis. Differences in REE were determined with t tests (Welch), and included adjustment for fat free mass (FFM) and BMI, and for FFM index (FFMI). RESULTS: Measured REE was 585 kJ/day (95% CI 264-905; p = 0.0005) and 861 kJ/day (95% CI 499-1,221; p < 0.0001) lower in black than in white women when adjusted for FFM and BMI, and FFMI, respectively. Out of 14 equations, 13 underestimated REE (error range 2,261 ± 727 kJ/day (Bernstein equation, white women) to 8 ± 782 kJ/day (BMI equation, black women)). CONCLUSIONS: Black overweight women have significantly lower REE than their white counterparts. No tested estimation equation provided satisfactory results across race/ethnicity. REE measurements or development of overweight- or race/ethnicity-specific estimation equations are recommended.

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