Browsing by Author "Manerkar K"

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    Development and Evaluation of an Automated Algorithm to Estimate the Nutrient Intake of Infants from an Electronic Complementary Food Frequency Questionnaire
    (Lifescience Global, 2020-11-25) Manerkar K; Harding J; Conlon C; McKinlay C
    Background: We previously validated a four-day complementary food frequency questionnaire (CFFQ) to estimate the nutrient intake in New Zealand infants aged 9-12 months. However, manual entry of the CFFQ data into nutritional analysis software was time-consuming. Therefore, we developed an automated algorithm and evaluated its accuracy by comparing the nutrient estimates with those obtained from the nutritional analysis software. Methods: We analysed 50 CFFQ completed at 9- and 12-months using Food Works nutritional analysis software. The automated algorithm was programmed in SAS by multiplying the average daily consumption of each food item by the nutrient content of the portion size. We considered the most common brands for commercially prepared baby foods. Intakes of energy, macronutrients, and micronutrients were compared between methods using Bland-Altman analysis. Results: The automated algorithm did not have any significant bias for estimates of energy (kJ) (MD 15, 95% CI -27, 58), carbohydrate (g) (MD -0.1, 95% CI -1.2,1.0), and fat (g) (-0.1, 95% CI -0.3,0.1), but slightly underestimated intake of protein (MD -0.4 g, 95% CI -0.7,-0.1), saturated fat, PUFA, dietary fibre, and niacin. The algorithm provided accurate estimates for other micronutrients. The limits of agreement were relatively narrow. Conclusion: This automated algorithm is an efficient tool to estimate the nutrient intakes from CFFQ accurately. The small negative bias observed for few nutrients was clinically insignificant and can be minimised. This algorithm is suitable to use in large clinical trials and cohort studies without the need for proprietary software.
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    Gestational diabetes detection thresholds and infant growth, nutrition, and neurodevelopment at 12-18 months: a prospective cohort study within a randomized trial
    (Springer Nature Limited, 2025-09-05) Amitrano F; Manerkar K; Alsweiler JM; Conlon CA; Crowther CA; Edlin R; Harding JE; McCowan LME; Meyer MP; Rowan JA; Rush EC; McKinlay CJD
    Objective To assess the impact of gestational diabetes(GDM) detection thresholds on infant growth, nutrition, and neurodevelopment at 12-18 months. Design Prospective cohort study within the GEMS trial(ACTRN12615000290594), which randomized pregnant women to detection of GDM using lower or higher glycemic criteria. The main outcomes were overweight/rapid weight gain; food approach appetitive score; energy intake; cognitive z-score. Result Compared to control infants, those exposed to GDM detected and treated by higher criteria or by lower but not higher criteria that was untreated, were less likely to have increased overweight/rapid weight gain, possibly with lower energy intake. There were no important differences in appetite and cognition. Infants exposed to GDM by lower but not higher criteria that was treated were similar to controls. Conclusion Exposure to treated GDM or untreated GDM detected by lower but not higher criteria, was not associated with increased infant risk factors for obesity or adverse cognitive outcomes.