☆ 4.5 Article

Diet quality across early childhood and adiposity at 6 years: the Southampton Women's Survey

INTERNATIONAL JOURNAL OF OBESITY (2015)

期刊

INTERNATIONAL JOURNAL OF OBESITY

卷 39, 期 10, 页码 1456-1462

出版社

NATURE PUBLISHING GROUP

DOI: 10.1038/ijo.2015.97

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类别

Endocrinology & Metabolism Nutrition & Dietetics

资金

Medical Research Council
British Heart Foundation
Arthritis Research UK
National Osteoporosis Society
International Osteoporosis Foundation
Cohen Trust
National Institute for Health Research Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton National Health Service Foundation Trust
National Institute for Health Research Musculoskeletal Biomedical Research Unit, University of Oxford
Dunhill Medical Trust
European Union's Seventh Framework Programme, EarlyNutrition [289346]
British Heart Foundation [RG/07/009/23120] Funding Source: researchfish
Medical Research Council [MC_UU_12011/4, MC_U147585819, MC_UP_A620_1015, MC_U147585827, MC_UP_A620_1017, MC_UP_A620_1014, U1475000002, MC_UU_12011/1, U1475000001] Funding Source: researchfish
National Institute for Health Research [NF-SI-0513-10085, NF-SI-0508-10082] Funding Source: researchfish
MRC [MC_U147585827, MC_UP_A620_1017, MC_UP_A620_1015, MC_UU_12011/4, MC_U147585819] Funding Source: UKRI

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摘要

BACKGROUND: Poor diet quality in early childhood is inconsistently linked to obesity risk. Understanding may be limited by the use of cross-sectional data and the use of body mass index (BMI) to define adiposity in childhood. OBJECTIVE: The objective of this study is to examine the effects of continued exposure to diets of varying quality across early childhood in relation to adiposity at 6 years. METHODS: One thousand and eighteen children from a prospective UK birth cohort were studied. Diet was assessed using food frequency questionnaires when the children were aged 6 and 12 months, and 3 and 6 years; diet quality was determined according to scores for a principal component analysis-defined dietary pattern at each age (characterized by frequent consumption of fruits, vegetables and fish). At each age, children were allocated a value of 0/1/2 according to third of the distribution (bottom/middle/top) their diet quality score was in; values were summed to calculate an overall diet quality index (DQI) for early childhood (range 0-8). Obesity outcomes considered at 6 years were dual-energy X-ray absorptiometry-assessed fat mass and BMI. RESULTS: One hundred and seven (11%) children had a DQI = 0, indicating a consistently low diet quality, 339 (33%) had a DQI = 1-3, 378 (37%) had a DQI = 4-6 and 194 (19%) had a DQI = 7-8. There was a strong association between lower DQI and higher fat mass z-score at 6 years that was robust to adjustment for confounders (fat mass s.d. per 1-unit DQI increase: beta = -0.05 (95% confidence interval (CI): -0.09, -0.01), P = 0.01). In comparison with children who had the highest diet quality (DQI = 7-8), this amounted to a difference in fat mass of 14% (95% CI: 2%, 28%) at 6 years for children with the poorest diets (DQI = 0). In contrast, no independent associations were observed between DQI and BMI. CONCLUSIONS: Continued exposure to diets of low quality across early childhood is linked to adiposity at the age of 6 years.

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Evaluation and interpretation of latent class modelling strategies to characterise dietary trajectories across early life: a longitudinal study from the Southampton Women's Survey

Kathryn V. Dalrymple, Christina Vogel, Keith M. Godfrey, Janis Baird, Mark A. Hanson, Cyrus Cooper, Hazel M. Inskip, Sarah R. Crozier

Summary: There is a growing interest in modeling longitudinal dietary data to identify subgroups with similar trajectories. This paper compares two latent class methods, group-based trajectory modeling (GBTM) and growth mixture modeling (GMM), to analyze dietary data from a longitudinal study. Both methods suggest that five classes are optimal, with strong correlation between class assignments. Results show stable dietary trajectories with varying levels of quality. GBTM is recommended as it is less computationally intensive, but results can be confirmed using GMM.

BRITISH JOURNAL OF NUTRITION (2023)