Socioeconomic status and dietary patterns in children from around the world : different associations by levels of country human development?

Background: Although 'unhealthy' diet is a well-known risk factor for non-communicable diseases, its relationship with socio-economic status (SES) has not been fully investigated. Moreover, the available research has largely been conducted in countries at high levels of human development. This is the first study to examine relationships among dietary patterns and SES of children from countries spanning a wide range of human development. Methods: This was a multinational cross-sectional study among 9-11 year-old children (n = 6808) from urban/peri-urban sites across 12 countries. Self-reported food frequency questionnaires were used to determine the children's dietary patterns. Principal Components Analysis was employed to create two component scores representing 'unhealthy' and 'healthy' dietary patterns. Multilevel models accounting for clustering at the school and site level were used to examine the relationships among dietary patterns and SES. Results: The mean age of participants in this study (53.7% girls) was 10.4 years. Largest proportions of total variance in dietary patterns occurred at the individual, site, and school levels (individual, school, site: 62.8%; 10.8%; 26.4% for unhealthy diet pattern (UDP) and 88.9%; 3.7%; 7.4%) for healthy diet pattern (HDP) respectively. There were significant negative 'unhealthy' diet-SES gradients in 7 countries and positive 'healthy' diet-SES gradients in 5. Within country diet-SES gradients did not significantly differ by HDI. Compared to participants in the highest SES groups, unhealthy diet pattern scores were significantly higher among those in the lowest within-country SES groups in 8 countries: odds ratios for Australia (2.69; 95% CI: 1.33-5.42), Canada (4.09; 95% CI: 2.02-8.27), Finland (2.82; 95% CI: 1.27-6.22), USA (4.31; 95% CI: 2.20-8.45), Portugal (2.09; 95% CI: 1.06-4.11), South Africa (2.77; 95% CI: 1.22-6.28), India (1.88; 95% CI: 1.12-3.15) and Kenya (3.35; 95% CI: 1.91-5.87). Conclusions: This study provides evidence of diet-SES gradients across all levels of human development and that lower within-country SES is strongly related to unhealthy dietary patterns. Consistency in within-country diet-SES gradients suggest that interventions and public health strategies aimed at improving dietary patterns among children may be similarly employed globally. However, future studies should seek to replicate these findings in more representative samples extended to more rural representation.Peer reviewe

Cardiometabolic risk factor response to a lifestyle intervention: a randomized trial

BACKGROUND: Strategies to increase adherence to national dietary and physical activity (PA) guidelines to improve the health in regions such as the Lower Mississippi Delta (LMD) of the United States are needed. Here we explore the cardiometabolic responses to an education and behavior change intervention among overweight and obese adults that adapted the 2010 Dietary Guidelines (DG), with and without a PA component. METHODS: White and African American overweight and obese adults were randomized to a DG group (n=61) or a DG+PA group (n=60). Both groups received a 12-week dietary education and behavior change intervention, and the DG+PA group also received a PA education and behavior change intervention with a pedometer. Changes in individual risk factors (blood pressure, fasting glucose, triglycerides, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol) and a continuous cardiometabolic risk score were determined. General linear models compared mean changes between groups, adjusting for covariates. RESULTS: No main effect of intervention group was found in completers (n=99) and those who engaged with ≥80% of the intervention (n=83) for individual risk factors or the continuous risk score. Pooling both groups, those with higher baseline risk factor values realized greater improvements in individual risk factors. CONCLUSIONS: Adapting DG did not produce any cardiometabolic benefits, even with a PA component. Although the sample was ostensibly healthy, they were all overweight to mildly obese (body mass index of 25-34.9 kg/m[superscript: 2]) and participants with higher baseline risk factor values showed more improvements. Adherence to longer-term behavior change may elicit changes in risk profile, so this should be explored

A model for presenting accelerometer paradata in large studies: ISCOLE

Background: We present a model for reporting accelerometer paradata (process-related data produced from survey administration) collected in the International Study of Childhood Obesity Lifestyle and the Environment (ISCOLE), a multi-national investigation of >7000 children (averaging 10.5 years of age) sampled from 12 different developed and developing countries and five continents. Methods: ISCOLE employed a 24-hr waist worn 7-day protocol using the ActiGraph GT3X+. Checklists, flow charts, and systematic data queries documented accelerometer paradata from enrollment to data collection and treatment. Paradata included counts of consented and eligible participants, accelerometers distributed for initial and additional monitoring (site specific decisions in the face of initial monitoring failure), inadequate data (e.g., lost/malfunction, insufficient wear time), and averages for waking wear time, valid days of data, participants with valid data (>4 valid days of data, including 1 weekend day), and minutes with implausibly high values (>20,000 activity counts/min). Results: Of 7806 consented participants, 7372 were deemed eligible to participate, 7314 accelerometers were distributed for initial monitoring and another 106 for additional monitoring. 414 accelerometer data files were inadequate (primarily due to insufficient wear time). Only 29 accelerometers were lost during the implementation of ISCOLE worldwide. The final locked data file consisted of 6553 participant files (90.0% relative to number of participants who completed monitoring) with valid waking wear time, averaging 6.5 valid days and 888.4 minutes/day (14.8 hours). We documented 4762 minutes with implausibly high activity count values from 695 unique participants (9.4% of eligible participants and <0.01% of all minutes). Conclusions: Detailed accelerometer paradata is useful for standardizing communication, facilitating study management, improving the representative qualities of surveys, tracking study endpoint attainment, comparing studies, and ultimately anticipating and controlling costs