Sanaz Mehranfar1, Yahya Jalilpiran1,2, Pamela J Surkan3, Leila Azadbakht1,4,5. 1. Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences, Tehran, Iran. 2. Students' Scientific Research Center (SSRC), Tehran University of Medical Sciences (TUMS), Tehran, Iran. 3. Department of International Health, John Hopkins Bloomberg School of Public Health, Baltimore, Maryland. 4. Diabetes Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran. 5. Department of Community Nutrition, School of Nutrition and Food Science, Isfahan University of Medical Science, Isfahan, Iran.
Abstract
AIM: The associations between types of dietary protein intake and child anthropometric measurements have not been fully studied. Therefore, we examined dietary protein pattern in relation to anthropometric indicators among 6-year-old children. METHODS: We carried out a cross-sectional study of 788 randomly selected children from health centres in Tehran, Iran. Dietary intake was assessed using a food frequency questionnaire completed by the mothers. Anthropometric measurements were based on standard protocols. Principle component analysis was performed to identify different dietary protein patterns. We used multivariate logistic regression to evaluate how these patterns were associated with child anthropometry. RESULTS: Three dietary protein patterns were identified: pattern 1 (rich in red and processed meats, dairy products and eggs), pattern 2 (rich in fish and poultry) and pattern 3 (rich in soy and legumes). After adjusting for potential confounders (energy intake, socioeconomic status and physical activity), being in the third compared to the first tertiles of pattern 2 was associated with increased (OR = 1.57; 95% CI: 1.09-2.27; P = .01) and decreased (OR = 0.54; 95% CI: 0.32-0.92; P = .02) risk of overweight/obesity and underweight/wasting, respectively. There was no association between other dietary patterns and risk of overweight/obesity or underweight/wasting. CONCLUSIONS: The present study showed inverse association between the fish/white meat pattern and underweight/wasting and also a positive association between higher fish/white meat protein intake and higher risk of overweight/obesity. Further studies are needed to confirm these results.
AIM: The associations between types of dietary protein intake and child anthropometric measurements have not been fully studied. Therefore, we examined dietary protein pattern in relation to anthropometric indicators among 6-year-old children. METHODS: We carried out a cross-sectional study of 788 randomly selected children from health centres in Tehran, Iran. Dietary intake was assessed using a food frequency questionnaire completed by the mothers. Anthropometric measurements were based on standard protocols. Principle component analysis was performed to identify different dietary protein patterns. We used multivariate logistic regression to evaluate how these patterns were associated with child anthropometry. RESULTS: Three dietary protein patterns were identified: pattern 1 (rich in red and processed meats, dairy products and eggs), pattern 2 (rich in fish and poultry) and pattern 3 (rich in soy and legumes). After adjusting for potential confounders (energy intake, socioeconomic status and physical activity), being in the third compared to the first tertiles of pattern 2 was associated with increased (OR = 1.57; 95% CI: 1.09-2.27; P = .01) and decreased (OR = 0.54; 95% CI: 0.32-0.92; P = .02) risk of overweight/obesity and underweight/wasting, respectively. There was no association between other dietary patterns and risk of overweight/obesity or underweight/wasting. CONCLUSIONS: The present study showed inverse association between the fish/white meat pattern and underweight/wasting and also a positive association between higher fish/white meat protein intake and higher risk of overweight/obesity. Further studies are needed to confirm these results.
Authors: Karolien Van De Maele; Charlotte De Geyter; Yvan Vandenplas; Inge Gies; Roland Devlieger Journal: Nutrients Date: 2020-08-25 Impact factor: 5.717