BACKGROUND: Little is known about factors contributing to physical activity (PA) in American Indian (AI) populations. Addressing this gap is paramount as sedentary activity and obesity continue to increase in this population. The purpose of this study was to determine factors associated with PA among AI families with young children. METHODS: Height and weight of both adult (n = 423) and child (n = 390) were measured, and surveys assessed demographics, PA, stress (adult only), sleep, and screen time. Separate multivariate logistic regression models were constructed for adults and children (reported as adjusted odds ratios, aORs). RESULTS: For adults, age (aOR = 0.952; P ≤ .001), television viewing (aOR = 0.997; P = .01), and computer use (aOR = 0.996; P = .003) decreased the odds of being active. For children, high adult activity (aOR = 1.795; P ≤ .01), longer weekday sleep (aOR = 1.004; P = .01), and family income >$35,000 (aOR = 2.772; P = .01) increased the odds of being active. We found no association between adult PA with stress or adult sleep or between child PA with body mass index and screen time. CONCLUSIONS: Given the complexity of the factors contributing to obesity among AI families, multigenerational interventions focused on healthy lifestyle change such as decreasing adult screen time and increasing child sleep time may be needed to increase PA within AI families.
BACKGROUND: Little is known about factors contributing to physical activity (PA) in American Indian (AI) populations. Addressing this gap is paramount as sedentary activity and obesity continue to increase in this population. The purpose of this study was to determine factors associated with PA among AI families with young children. METHODS: Height and weight of both adult (n = 423) and child (n = 390) were measured, and surveys assessed demographics, PA, stress (adult only), sleep, and screen time. Separate multivariate logistic regression models were constructed for adults and children (reported as adjusted odds ratios, aORs). RESULTS: For adults, age (aOR = 0.952; P ≤ .001), television viewing (aOR = 0.997; P = .01), and computer use (aOR = 0.996; P = .003) decreased the odds of being active. For children, high adult activity (aOR = 1.795; P ≤ .01), longer weekday sleep (aOR = 1.004; P = .01), and family income >$35,000 (aOR = 2.772; P = .01) increased the odds of being active. We found no association between adult PA with stress or adult sleep or between child PA with body mass index and screen time. CONCLUSIONS: Given the complexity of the factors contributing to obesity among AI families, multigenerational interventions focused on healthy lifestyle change such as decreasing adult screen time and increasing child sleep time may be needed to increase PA within AI families.
Authors: Gary G Bennett; Kathleen Y Wolin; K Viswanath; Sandy Askew; Elaine Puleo; Karen M Emmons Journal: Am J Public Health Date: 2006-07-27 Impact factor: 9.308
Authors: Andrea Bersamin; Christopher Wolsko; Bret R Luick; Bert B Boyer; Cecile Lardon; Scarlett E Hopkins; Judith S Stern; Sheri Zidenberg-Cherr Journal: Ethn Health Date: 2013-01-09 Impact factor: 2.772
Authors: Lori A J Scott-Sheldon; Larry V Hedges; Chris Cyr; Deborah Young-Hyman; Laura Kettel Khan; Mackenzie Magnus; Heather King; Sonia Arteaga; John Cawley; Christina D Economos; Debra Haire-Joshu; Christine M Hunter; Bruce Y Lee; Shiriki K Kumanyika; Lorrene D Ritchie; Thomas N Robinson; Marlene B Schwartz Journal: Child Obes Date: 2020-09 Impact factor: 2.992