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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.

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BACKGROUND: Anthropometric data quality in large multicentre nutrition surveys is seldom adequately assessed. In preparation for the South African National Dietary Intake Survey (NDIS-2022), this study assessed site leads' and fieldworkers' intra- and inter-rater reliability for measuring weight, length/height, mid-upper arm circumference (MUAC), waist circumference (WC) and calf circumference (CC). METHODS: Standardised training materials and measurement protocols were developed, and new anthropometric equipment was procured. Following two training rounds (12 site lead teams, 46 fieldworker teams), measurement reliability was assessed for both groups, using repeated measurements of volunteers similar to the survey target population. Reliability was statistically assessed using the technical error of measurement (TEM), relative TEM (%TEM), intra-class correlation coefficient (ICC) and coefficient of reliability (R). Agreement was visualised with Bland-Altman analysis. RESULTS: By %TEM, the best reliability was achieved for weight (%TEM = 0.260-0.923) and length/height (%TEM = 0.434-0.855), and the poorest for MUAC by fieldworkers (%TEM = 2.592-3.199) and WC (%TEM = 2.353-2.945). Whole-sample ICC and R were excellent ( > 0.90) for all parameters except site leads' CC inter-rater reliability (ICC = 0.896, R = 0.889) and fieldworkers' inter-rater reliability for MUAC in children under two (ICC = 0.851, R = 0.881). Bland-Altman analysis revealed no significant bias except in fieldworkers' intra-rater reliability of length/height measurement in adolescents/adults ( + 0.220 (0.042, 0.400) cm). Reliability was higher for site leads vs. fieldworkers, for intra-rater vs. inter-rater assessment, and for weight and length/height vs. circumference measurements. CONCLUSION: NDIS-2022 site leads and fieldworkers displayed acceptable reliability in performing anthropometric measurements, highlighting the importance of intensive training and standardised measurement protocols. Ongoing reliability assessment during data collection is recommended.

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Post-natal growth influences short- and long-term preterm infant outcomes. Different growth charts, such as the Fenton Growth Chart (FGC) and INTERGROWTH-21st Preterm Post-natal Growth Standards (IG-PPGS), describe different growth curves and targets. This study compares FGC- and IG-PPGS-derived weight-for-postmenstrual age z-score (WZ) up to 50 weeks postmenstrual age (PMA50) for predicting 1-year anthropometry in 321 South African preterm infants. The change in WZ from birth to PMA50 (ΔWZ, calculated using FGC and IG-PPGS) was correlated to age-corrected 1-year anthropometric z-scores for weight-for-age (WAZ), length-for-age (LAZ), weight-for-length (WLZ) and BMI-for-age (BMIZ), and categorically compared with rates of underweight (WAZ < -2), stunting (LAZ < -2), wasting (WLZ < -2) and overweight (BMIZ > + 2). Multivariable analyses explored the effects of other early-life exposures on malnutrition risk. At PMA50, mean WZ was significantly higher on IG-PPGS (-0.56 ± 1.52) than FGC (-0.90 ± 1.52; p < 0.001), but ΔWZ was similar (IG-PPGS -0.26 ± 1.23, FGC -0.11 ± 1.14; p = 0.153). Statistically significant ΔWZ differences emerged among small-for-gestational age infants (FGC -0.38 ± 1.22 vs. IG-PPGS -0.01 ± 1.30; p < 0.001) and appropriate-for-gestational age infants (FGC + 0.02 ± 1.08, IG-PPGS -0.39 ± 1.18; p < 0.001). Correlation coefficients of ΔWZ with WAZ, LAZ, WLZ and BMIZ were low (r < 0.45), though higher for FGC than IG-PPGS. Compared with IG-PPGS, ΔWZ < -1 on FGC predicted larger percentages of underweight (42% vs. 36%) and wasting (43% vs. 39%) and equal percentages of stunting (33%), while ΔWZ > + 1 predicted larger percentages overweight (57% vs. 38%). Both charts performed similarly in multivariable analysis. Differences between FGC and IG-PPGS are less apparent when considering ΔWZ, highlighting the importance of assessing growth as change over time, irrespective of growth chart.

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AIM: Macronutrient and energy content of human milk are largely assumed for fortification practices. The aim was to explore macronutrient and energy content of transition and mature human milk from South African mothers of preterm infants with a birth weight <1800 g. Secondary objectives compared day to night milk; and explored associations with selected innate factors. METHODS: In this single-centre, observational study macronutrient and energy content of day, night and mixed samples of transition (first 14 days of life) and mature (from Day 15 of life) human milk were analysed with mid-infrared spectroscopy. RESULTS: In total, 116 samples (38 days; 37 night; 41 mixed) from 47 mothers were retained for statistical analysis. Mean true protein, carbohydrate, fat and energy content of mixed samples per 100 mL were 1.5 ± 0.4 g, 7.2 ± 0.7 g, 3.5 ± 0.9 g and 69.4 ± 9.9 kcal, respectively. Mixed transition milk (n = 9) had 1.9 ± 0.3 g protein and 67.4 ± 9.6 kcal and mixed mature milk (n = 32) 1.4 ± 0.4 g protein and 70.0 ± 10.1 kcal, per 100 mL.The protein content of transition (p = 0.004) and mature (p = 0.004) milk were significantly higher than published data. Transition milk: 1.5 g protein, 65 kcal; mature milk: 1.2 g protein, 72 kcal per 100 mL. Night samples had less fat (p = 0.014) and energy (p = 0.033) than day samples. With increasing day of life protein content declined (p = 0.003). CONCLUSION: The protein content of human milk from South African mothers of preterm babies differs from published data and has implications for human milk fortification practises.

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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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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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Lower resting energy expenditure (REE) may partially explain the disproportionate prevalence of overweight/obesity among black African women. As no previous studies have investigated the REE of Southern African (South. Afr.) children, we aimed to determine, by sex and population group, the REE of 6- to 9-year-old urban school children. In a cross-sectional study with quota sampling, REE was measured with indirect calorimetry (IC). Confounders considered were: body composition (BC) (fat-free mass (FFM), FFM index, fat mass (FM), FM index), assessed using multifrequency bioelectrical impedance analysis, and physical activity (PA) measured with a pedometer. Multivariate regression was used to calculate REE adjusted for phenotypes (BC, z-scores of weight-for-age, height-for-age, body mass index-for-age) and PA. Sex and population differences in REE were determined with two-way ANOVA. Ninety-four healthy children (59.6% girls; 52.1% black) with similar socioeconomic status and PA opportunities participated. Despite BC variations, sex differences in REE were not significant (41 kcal/day; P = 0.375). The REE of black participants was lower than of white (146 kcal/day; P = 0.002). When adjusted for FFM and HFA z-score, the differences in REE declined but remained clinically meaningful at 91 kcal/day (P = 0.039) and 82 kcal/day (P = 0.108), respectively. We recommend the development of population-specific REE prediction equations for South. Afr. children.

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OBJECTIVE: Amidst a high prevalence of prematurity, limited research on the growth of very low birth weight (VLBW) preterm infants and the availability of a reformulated fortifier c(RF), the study aimed to compare in-hospital growth of such infants receiving exclusively human milk fortified with either of 2 different formulations in a tertiary South African hospital. METHODS: In a prospective comparative effectiveness design, intakes and growth of VLBW infants on the Original Fortifier (OF; 2016-2017) were compared with those receiving RF (2017-2018). Daily intake was calculated using published composition of preterm and mature milk with fortifier (OF: 0.2 g protein, 3.5kcal/g powder; RF: 0.4 g protein, 4.4 kcal/g powder). Change in z scores from start to end of fortification for weight (WFAZ), length (LFAZ), and head circumference (HCFAZ) for age was the primary outcome. Additionally, weight gain velocity (g ·â€Škg-1 ·â€Šday-1) and gain in length and head circumference (HC) (cm/week) were calculated. RESULTS: Fifty-eight infants (52% girls; gestational age: 30 ±â€Š2 weeks; birth weight: 1215 ±â€Š187 g) received OF for 16 days and 59 infants (56% girls; gestational age: 29 ±â€Š2 weeks; birth weight 1202 ±â€Š167 g) received RF for 15 days. Protein intake of RF (3.7 ±â€Š0.4 g ·â€Škg-1 ·â€Šday-1) was significantly higher (P < 0.001) than of OF (3.4 ±â€Š0.2 g ·â€Škg-1 ·â€Šday-1). Protein-to-energy ratio of RF (2.6 ±â€Š0.2 g/100 kcal) was significantly higher (P < 0.001) than of OF (2.3 ±â€Š0.1 g/100 kcal). In both groups, WFAZ and LFAZ decreased; HCFAZ improved slightly. No significant differences (P > 0.05) were noted between the 2 groups for change in z scores, weight gain velocity, length or HC gain. CONCLUSIONS: Despite a modest increase in protein intake and protein-to-energy ratio, the growth of VLBW infants on RF was not better than on OF during their hospital stay.

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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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BACKGROUND: In South Africa, noncommunicable diseases and obesity are increasing and also affect children. No validated assessment tools for fat intake are available. OBJECTIVE: To determine test-retest reliability and relative validity of a pictorial modified meats, eggs, dairy, fried foods, fats in baked goods, convenience foods, table fats, and snacks (MEDFICTS) dietary fat screener. DESIGN: We determined test-retest reliability and diagnostic accuracy with the modified MEDFICTS as the index test and a 3-day weighed food record and parental completion of the screener as primary and secondary reference methods, respectively. PARTICIPANTS/SETTING: Grade-six learners (aged 12 years, 4 months) in an urban, middle-class school (n=93) and their parents (n=72). OUTCOME MEASURES: Portion size, frequency of intake, final score, and classification of fat intake of the modified MEDFICTS, and percent energy from fat, saturated fatty acids, and cholesterol of the food record. STATISTICAL ANALYSES: For categorical data agreement was based on kappa statistics, McNemar's test for symmetry, and diagnostic performance parameters. Continuous data were analyzed with correlations, mean differences, the Bland-Altman method, and receiver operating characteristics. RESULTS: The classification of fat intake by the modified MEDFICTS was test-retest reliable. Final scores of the group did not differ between administrations (P=0.86). The correlation of final scores between administrations was significant for girls only (r=0.58; P=0.01). Reliability of portion size and frequency of intake scores depended on the food category. For girls the screener final score was significantly (P<0.5) correlated to total, saturated fat, and cholesterol intakes (but not to percent energy from fat and saturated fatty acids intakes). The sensitivity of the modified MEDFICTS was very high (>90%), but chance corrected agreement between the classifications was poor. Parents did not agree with their children. CONCLUSIONS: Test-retest reliability and relative validity of a modified MEDFICTS dietary fat screener in South African schoolchildren depended on the use and outcome measures applied.

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