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Associations among Physical Activity, Diet, and Obesity Measures Change during Adolescence.

ABSTRACT: Background. Obesity in youth is highly prevalent. Physical activity and diet are influential in obesity development. However, there is a knowledge gap regarding links between activity and diet quality and their combined influence on obesity during adolescence. Objectives. We used five years of data from 2379 adolescent girls in the National Heart Lung and Blood Institute Growth and Health Study to evaluate the association between physical activity and diet quality during adolescence and to assess both as correlates of obesity. Design. Diet, activity, and body composition measures were evaluated pairwise for correlation. A canonical correlation analysis was used to evaluate relationships within and between variable groups. All statistics were examined for trends over time. Results. We found positive correlations between physical activity and diet quality that became stronger with age. Additionally we discovered an age-related decrease in association between obesity correlates and body composition. Conclusion. These results suggest that while health behaviors, like diet and activity, become more closely linked during growth, obesity becomes less influenced by health behaviors and other factors. This should motivate focus on juvenile obesity prevention capitalizing on the pliable framework for establishing healthy diet and physical activity patterns while impact on body composition is greatest.

SUBMITTER: Maier JH

PROVIDER: S-EPMC4619959 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Associations among Physical Activity, Diet, and Obesity Measures Change during Adolescence.

Maier Janne H JH Barry Ronald R

Journal of nutrition and metabolism 20151011

Background. Obesity in youth is highly prevalent. Physical activity and diet are influential in obesity development. However, there is a knowledge gap regarding links between activity and diet quality and their combined influence on obesity during adolescence. Objectives. We used five years of data from 2379 adolescent girls in the National Heart Lung and Blood Institute Growth and Health Study to evaluate the association between physical activity and diet quality during adolescence and to asses ...[more]

PMID: 26539299

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Project description:BackgroundLongitudinal studies demonstrate an average decline in physical activity (PA) from adolescence to young adulthood. However, while some subgroups of adolescents decrease activity, others increase or maintain high or low activity. Activity domains may differ between subgroups (exhibiting different PA patterns), and they offer valuable information for targeted health promotion. Hence, the aim of this study was to identify PA patterns from adolescence to young adulthood; also to explore the associations of (i) changes in PA domains and in sedentary time, (ii) sociodemographic factors, and (iii) self-rated health with diverging PA patterns.MethodsThe observational cohort study data encompassed 254 adolescents at age 15 and age 19. K-means cluster analysis for longitudinal data was performed to identify participant clusters (patterns) based on their accelerometry-measured moderate-to-vigorous PA (MVPA). Logistic regressions were applied in further analysis.ResultsFive PA patterns were identified: inactivity maintainers (n = 71), activity maintainers (n = 70), decreasers from moderate (to low) PA (n = 61), decreasers from high (to moderate) PA (n = 32), and increasers (n = 20). At age 15, participation in sports clubs (SC, 41-97%) and active commuting (AC, 47-75%) was common in all the patterns. By age 19, clear dropout from these activities was prevalent (SC participation mean 32%, AC 31-63%). Inactivity maintainers reported the lowest amount of weekly school physical education. Dropout from SC - in contrast to non-participation in SC - was associated with higher odds of being a decreaser from high PA, and with lower odds of being an inactivity maintainer. Maintained SC participation was associated with higher odds of belonging to the decreasers from high PA, and to the combined group of activity maintainers and increasers; also with lower odds of being an inactivity maintainer. Maintenance/adoption of AC was associated with decreased odds of being an inactivity maintainer. Self-reported health at age 19 was associated with the patterns of maintained activity and inactivity.ConclusionsPA patterns diverge over the transition to adulthood. Changes in SC participation and AC show different associations with diverging PA patterns. Hence, tailored PA promotion is recommended.

Project description:BACKGROUND:Meta-analysis of genome-wide association studies identified obesity-related genetic variants. Due to the pleiotropic effects of related phenotypes, we tested six of these obesity-related genetic variants for their association with physical activity: fat mass and obesity-associated (FTO)(rs9939609)T>A, potassium channel tetramerization domain containing (KCTD15) (rs11084753)G>A, melanocortin receptor4 (MC4R)(rs17782313)T>C, neuronal growth regulator 1 (NEGR1)(rs2815752)A>G, SH2B adapter protein 1 (SH2B1)(rs7498665)A>G, and transmembrane protein18 (TMEM18)(rs6548238)C>T. METHOD:European-American women (n = 263) and men (n = 229) (23.5 ± 0.3 years, 24.6 ± 0.2 kg/m2) were genotyped and completed the Paffenbarger physical activity Questionnaire. Physical activity volume in metabolic energy equivalents [MET]-hour/week was derived from the summed time spent (hour/week) times the given MET value for vigorous, moderate, and light intensity physical activity, and sitting and sleeping, respectively. Multivariable adjusted [(age, sex, and body mass index (BMI)] linear regression tested associations among genotype (dominant/recessive model) and the log of physical activity volume. RESULT:MC4R (rs17782313)T>C explained 1.1 % (p = 0.02), TMEM18(rs6548238)C>T 1.2 % (p = 0.01), and SH2B1 (rs7498665)A>G 0.6 % (p = 0.08) of the variability in physical activity volume. Subjects with the MC4R C allele spent 3.5 % less MET-hour/week than those with the TT genotype (p = 0.02). Subjects with the TMEM18 T allele spent 4.1 % less MET-hour/week than those with the CC genotype (p = 0.01). Finally, subjects with the SH2B1 GG genotype spent 3.6 % less MET-hour/week than A allele carriers (p = 0.08). CONCLUSION:Our findings suggest a shared genetic influence among some obesity-related gene loci and physical activity phenotypes that should be explored further. Physical activity volume differences by genotype have public health importance equating to 11-13 lb weight difference annually.

Dataset Information

Associations among Physical Activity, Diet, and Obesity Measures Change during Adolescence.

Publications

Associations among Physical Activity, Diet, and Obesity Measures Change during Adolescence.

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