RESUMO
PURPOSE: To describe adherence to sustainable healthy diets among a sample of 958 Chilean pre-schoolers (3-6 years) and explore associations between adherence and child and maternal sociodemographic and anthropometric characteristics. METHODS: Children's adherence to sustainable healthy diets was calculated from single multiple-pass 24-h dietary recalls using the Planetary Health Diet Index for children and adolescents (PHDI-C). Higher PHDI-C scores (max score = 150 points) represent greater adherence. Adjusted linear regression models were fitted to explore associations between PHDI-C scores and child and maternal characteristics. RESULTS: Children obtained low total PHDI-C scores (median 50.0 [IQR 39.5-59.8] points). This resulted from low consumption of nuts & peanuts, legumes, vegetables, whole cereals, and vegetable oils; a lack of balance between dark green and red & orange vegetables, inadequate consumption of tubers & potatoes and eggs & white meats, and excess consumption of dairy products, palm oil, red meats, and added sugars. Mean PHDI-C total score was significantly higher (50.6 [95%CI 49.6, 51.7] vs 47.3 [95%CI 45.0, 49.5]) among children whose mothers were ≥ 25 years compared to those with younger mothers. Positive associations were observed between scores for fruits and maternal education, vegetables and maternal age, added sugars and child weight status, while negative associations were observed between fruits and child age, and vegetable oils and maternal education. Scores for dairy products PHDI-C component were lower among girls. CONCLUSION: Adherence to sustainable healthy diets was low among this sample of Chilean children and was significantly associated with maternal age, being lower among children whose mothers were younger.
Assuntos
Antropometria , Dieta Saudável , Fatores Socioeconômicos , Humanos , Estudos Transversais , Feminino , Masculino , Dieta Saudável/estatística & dados numéricos , Dieta Saudável/métodos , Pré-Escolar , Chile , Criança , Antropometria/métodos , Adulto , Fatores Sociodemográficos , Mães/estatística & dados numéricos , Cooperação do Paciente/estatística & dados numéricosRESUMO
BACKGROUND: Although urban residence is consistently identified as one of the primary correlates of non-communicable disease in low- and middle-income countries, it is not clear why or how urban settings predispose individuals and populations to non-communicable disease (NCD), or how this relationship could be modified to slow the spread of NCD. The urban-rural dichotomy used in most population health research lacks the nuance and specificity necessary to understand the complex relationship between urbanicity and NCD risk. Previous studies have developed and validated quantitative tools to measure urbanicity continuously along several dimensions but all have been isolated to a single country. The purposes of this study were 1) To assess the feasibility and validity of a multi-country urbanicity scale; 2) To report some of the considerations that arise in applying such a scale in different countries; and, 3) To assess how this scale compares with previously validated scales of urbanicity. METHODS: Household and community-level data from the Young Lives longitudinal study of childhood poverty in 59 communities in Ethiopia, India and Peru collected in 2006/2007 were used. Household-level data include parents' occupations and education level, household possessions and access to resources. Community-level data include population size, availability of health facilities and types of roads. Variables were selected for inclusion in the urbanicity scale based on inspection of the data and a review of literature on urbanicity and health. Seven domains were constructed within the scale: Population Size, Economic Activity, Built Environment, Communication, Education, Diversity and Health Services. RESULTS: The scale ranged from 11 to 61 (mean 35) with significant between country differences in mean urbanicity; Ethiopia (30.7), India (33.2), Peru (39.4). Construct validity was supported by factor analysis and high corrected item-scale correlations suggest good internal consistency. High agreement was observed between this scale and a dichotomized version of the urbanicity scale (Kappa 0.76; Spearman's rank-correlation coefficient 0.84 (p < 0.0001). Linear regression of socioeconomic indicators on the urbanicity scale supported construct validity in all three countries (p < 0.05). CONCLUSIONS: This study demonstrates and validates a robust multidimensional, multi-country urbanicity scale. It is an important step on the path to creating a tool to assess complex processes like urbanization. This scale provides the means to understand which elements of urbanization have the greatest impact on health.