Literature DB >> 26850309

Structural equation modeling of the associations between the home environment and obesity-related cardiovascular fitness and insulin resistance among Hispanic children.

Margarita Santiago-Torres1, Yuchen Cui2, Alexandra K Adams3, David B Allen4, Aaron L Carrel4, Jessica Y Guo5, Tara L LaRowe6, Dale A Schoeller7.   

Abstract

Hispanic children are disproportionally affected by obesity-related risk of metabolic disease. We used the structural equation modeling to examine the associations between specific diet and physical activity (PA) behaviors at home and Hispanic children's metabolic health. A total of 187 Hispanic children and their parents from an urban community in Wisconsin participated in the study. Exposure variables included, children's daily intake of sugar-sweetened beverages (SSB) and PA; home availability of SSB and PA areas/equipment; and parents' intake of SSB and PA, assessed through self-administered questionnaires. Outcome variables for children's metabolic health included, measured anthropometrics; cardiovascular fitness assessed using the Progressive Aerobic Cardiovascular Endurance Run (PACER); and insulin resistance determined with the homeostasis model assessment of insulin resistance (HOMAIR). We found that children's daily intake of SSB was positively associated with BMI z-score, which in turn, was positively associated with HOMAIR (P < 0.05). Specific diet behaviors at home associated with children's intake of SSB, included home availability of SSB, which mediated the association between parents' and children's intake of SSB (P < 0.05). Children's PA was positively associated with PACER z-score, which in turn, was inversely associated with HOMAIR (P < 0.05). Specific PA behaviors at home associated with children's PA, included home availability of PA areas/equipment, which mediated the association between parents' and children's PA (P < 0.05). The structural equation model indices suggested a satisfactory model fit (Chi-square, X(2) = 53.1, comparative fix index = 0.92, root-mean-squared error associated = 0.04). The findings confirm the need for interventions at the family level that promotes healthier home environments by targeting poor diet and low levels of PA in all family members. Published by Elsevier Ltd.

Entities:  

Keywords:  Cardiovascular fitness; Hispanic children; Home environment; Insulin resistance; Structural equation modeling

Mesh:

Substances:

Year:  2016        PMID: 26850309      PMCID: PMC5912911          DOI: 10.1016/j.appet.2016.02.003

Source DB:  PubMed          Journal:  Appetite        ISSN: 0195-6663            Impact factor:   3.868


  37 in total

1.  The longitudinal influence of home and neighbourhood environments on children's body mass index and physical activity over 5 years: the CLAN study.

Authors:  D Crawford; V Cleland; A Timperio; J Salmon; N Andrianopoulos; R Roberts; B Giles-Corti; L Baur; K Ball
Journal:  Int J Obes (Lond)       Date:  2010-03-30       Impact factor: 5.095

2.  Defining the complexity of childhood obesity and related behaviours within the family environment using structural equation modelling.

Authors:  Gilly A Hendrie; John Coveney; David N Cox
Journal:  Public Health Nutr       Date:  2011-08-02       Impact factor: 4.022

3.  Prevalence of obesity and trends in body mass index among US children and adolescents, 1999-2010.

Authors:  Cynthia L Ogden; Margaret D Carroll; Brian K Kit; Katherine M Flegal
Journal:  JAMA       Date:  2012-01-17       Impact factor: 56.272

4.  Effect of the volume and intensity of exercise training on insulin sensitivity.

Authors:  Joseph A Houmard; Charles J Tanner; Cris A Slentz; Brian D Duscha; Jennifer S McCartney; William E Kraus
Journal:  J Appl Physiol (1985)       Date:  2003-09-12

5.  Adolescent physical activity and screen time: associations with the physical home environment.

Authors:  John R Sirard; Melissa N Laska; Carrie D Patnode; Kian Farbakhsh; Leslie A Lytle
Journal:  Int J Behav Nutr Phys Act       Date:  2010-11-15       Impact factor: 6.457

6.  The obesity epidemic and changes in self-report biases in BMI.

Authors:  Aiko Hattori; Roland Sturm
Journal:  Obesity (Silver Spring)       Date:  2013-04       Impact factor: 5.002

7.  Television watching and soft drink consumption: associations with obesity in 11- to 13-year-old schoolchildren.

Authors:  Joyce Giammattei; Glen Blix; Helen Hopp Marshak; Alison Okada Wollitzer; David J Pettitt
Journal:  Arch Pediatr Adolesc Med       Date:  2003-09

8.  Family food environment and dietary behaviors likely to promote fatness in 5-6 year-old children.

Authors:  K J Campbell; D A Crawford; K Ball
Journal:  Int J Obes (Lond)       Date:  2006-02-21       Impact factor: 5.095

9.  Change in the family food environment is associated with positive dietary change in children.

Authors:  Gilly Hendrie; Gundeep Sohonpal; Kylie Lange; Rebecca Golley
Journal:  Int J Behav Nutr Phys Act       Date:  2013-01-07       Impact factor: 6.457

10.  Clustering of diet- and activity-related parenting practices: cross-sectional findings of the INPACT study.

Authors:  Gerda Rodenburg; Anke Oenema; Stef P J Kremers; Dike van de Mheen
Journal:  Int J Behav Nutr Phys Act       Date:  2013-03-25       Impact factor: 6.457

View more
  5 in total

1.  Analysis of risk factors of metabolic syndrome using a structural equation model: a cohort study.

Authors:  Zhimin Ma; Ditian Li; Siyan Zhan; Feng Sun; Chaonan Xu; Yunfeng Wang; Xinghua Yang
Journal:  Endocrine       Date:  2018-08-21       Impact factor: 3.633

2.  Methods and rationale to assess the efficacy of a parenting intervention targeting diet improvement and substance use prevention among Latinx adolescents.

Authors:  Sonia Vega-López; Flavio F Marsiglia; Stephanie Ayers; Lela Rankin Williams; Meg Bruening; Anaid Gonzalvez; Beatriz Vega-Luna; Alex Perilla; Mary Harthun; Gabriel Q Shaibi; Freddy Delgado; Christian Rosario; Leopoldo Hartmann
Journal:  Contemp Clin Trials       Date:  2019-12-13       Impact factor: 2.226

Review 3.  Perspective: Chaos in a Bottle-A Critical Evaluation of Beverage Categorization in Nutrition Research.

Authors:  Patrick E Merkel; Emma K Ditto; Kim Robien; Allison C Sylvetsky
Journal:  Adv Nutr       Date:  2020-11-16       Impact factor: 8.701

4.  Measuring beverage consumption in US children and adolescents: a systematic review.

Authors:  A H Grummon; R L Sokol; C A Hecht; A I Patel
Journal:  Obes Rev       Date:  2018-06-25       Impact factor: 9.213

5.  Factor Analysis Reduces Complex Measures of Nutrition Environments in US Elementary and Middle Schools into Cohesive Dimensions in the Healthy Communities Study.

Authors:  Marisa M Tsai; Edward A Frongillo; Lorrene D Ritchie; Gail Woodward-Lopez; Lauren E Au
Journal:  J Nutr       Date:  2021-05-11       Impact factor: 4.798

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.