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McNeish, Daniel; Peña, Armando; Vander Wyst, Kiley B.; Ayers, Stephanie L.; Olson, Micha L.; Shaibi, Gabriel Q. – Prevention Science, 2023
Growth mixture models (GMMs) are applied to intervention studies with repeated measures to explore heterogeneity in the intervention effect. However, traditional GMMs are known to be difficult to estimate, especially at sample sizes common in single-center interventions. Common strategies to coerce GMMs to converge involve post hoc adjustments to…
Descriptors: Prevention, Intervention, Growth Models, Program Effectiveness
Tanja Plasil; Ellen Margrete Iveland Ersfjord; Kim Berge; Line M. Oldervoll – Journal of Applied Research in Intellectual Disabilities, 2024
Background: Research suggests that people with intellectual disabilities have a higher risk for cardiovascular disease than the general population. The aim of this study was to identify barriers for the prevention, diagnosis, and treatment of cardiovascular disease for people with intellectual disabilities. Method: We conducted individual…
Descriptors: Barriers, Prevention, Clinical Diagnosis, Medical Services
McNeish, Daniel; Peña, Armando; Vander Wyst, Kiley B.; Ayers, Stephanie L.; Olson, Micha L.; Shaibi, Gabriel Q. – Grantee Submission, 2021
Growth mixture models (GMMs) are applied to intervention studies with repeated measures to explore heterogeneity in the intervention effect. However, traditional GMMs are known to be difficult to estimate, especially at sample sizes common in single-center interventions. Common strategies to coerce GMMs to converge involve post-hoc adjustments to…
Descriptors: Prevention, Intervention, Growth Models, Program Effectiveness
Peña, Armando; McNeish, Daniel; Ayers, Stephanie L.; Olson, Micah L.; Vander Wyst, Kiley B.; Williams, Allison N.; Shaibi, Gabriel Q. – Grantee Submission, 2020
Objective: To characterize the heterogeneity in response to lifestyle intervention among Latino adolescents with obesity. Methods: We conducted secondary data analysis of 90 Latino adolescents (age 15.4 ± 0.9 y, female 56.7%) with obesity (BMI% 98.1 ± 1.5%) that were enrolled in a 3 month lifestyle intervention and were followed for a year.…
Descriptors: Life Style, Intervention, Hispanic Americans, Adolescents
Peart, Tasha; de Leon Siantz, MaryLou – American Journal of Health Education, 2017
Though many studies have examined the level of physician obesity prevention counseling among the general population, little is known about how homeless patients are advised about healthy eating and physical activity by their health care provider. The homeless are an at-risk population with whom physicians and other health professionals can play a…
Descriptors: Obesity, Prevention, Physicians, Role
Cook, Jessica A.; McCormick, Emily V.; Mickiewicz, Theresa E.; Davidson, Arthur J.; Main, Deborah S. – Journal of School Health, 2017
Background: Adolescent overweight and obesity are serious health risks, with prevalence varying by sociodemographic group. Studies link children's weight status and sex/race-ethnic differences with meeting recommendations for physical activity and diet. But, research examining the intersection of sociodemographic characteristics, behavior, and…
Descriptors: Correlation, Obesity, Risk, Incidence
Beal, Sarah J.; Nause, Katie; Crosby, Imani; Greiner, Mary V. – Journal of Applied Research on Children, 2018
Children in child welfare protective custody (e.g., foster care) are known to have increased health concerns compared to children not in protective custody. The poor health documented for children in protective custody persists well into adulthood; young adults who emancipate from protective custody report poorer health, lower quality of life, and…
Descriptors: Child Welfare, Foster Care, Child Health, At Risk Persons
Alker, Heather J.; Wang, Monica L.; Pbert, Lori; Thorsen, Nancy; Lemon, Stephenie C. – Journal of School Health, 2015
Background: Healthy, productive employees are an integral part of school health programs. There have been few assessments of work productivity among secondary school staff. This study describes the frequency of 3 common health risk factors--obesity, depressive symptoms, and smoking--and their impact on work productivity in secondary school…
Descriptors: Productivity, School Personnel, At Risk Persons, Obesity
Skouteris, Helen; Hill, Briony; McCabe, Marita; Swinburn, Boyd; Sacher, Paul; Chadwick, Paul – Early Child Development and Care, 2014
The aim of this paper was to compare the recruitment strategies of two recent studies that focused on the parental influences on childhood obesity during the preschool years. The first study was a randomised controlled trial (RCT) of the Mind, Exercise, Nutrition?…?Do It! 2-4 obesity prevention programme and the second was a longitudinal cohort…
Descriptors: Parent Participation, Obesity, Prevention, At Risk Persons
Castro, Yessenia; Fernández, Maria E.; Strong, Larkin L.; Stewart, Diana W.; Krasny, Sarah; Hernandez Robles, Eden; Heredia, Natalia; Spears, Claire A.; Correa-Fernández, Virmarie; Eakin, Elizabeth; Resnicow, Ken; Basen-Engquist, Karen; Wetter, David W. – Health Education & Behavior, 2015
More than 60% of cancer-related deaths in the United States are attributable to tobacco use, poor nutrition, and physical inactivity, and these risk factors tend to cluster together. Thus, strategies for cancer risk reduction would benefit from addressing multiple health risk behaviors. We adapted an evidence-based intervention grounded in social…
Descriptors: Cancer, Health Behavior, Obesity, Hispanic Americans
Glied, Sherry; Oellerich, Don – Future of Children, 2014
Parents' health and children's health are closely intertwined--healthier parents have healthier children, and vice versa. Genetics accounts for some of this relationship, but much of it can be traced to environment and behavior, and the environmental and behavioral risk factors for poor health disproportionately affect families living in…
Descriptors: Health Programs, Family Programs, Child Health, Barriers
Dera de Bie, Eveliene; Jansen, Maria; Gerver, Willem Jan – Child Care in Practice, 2012
The aim of this study was to explore inhibiting factors in the prevention of overweight in infants younger than one year, among practitioners working for municipal child healthcare organisations in the Netherlands. Twelve in-depth interviews with child healthcare physicians and nurses were conducted. All interviews were tape-recorded, after which…
Descriptors: Obesity, Prevention, Physicians, Identification
Kann, Laura; McManus, Tim; Harris, William A.; Shanklin, Shari L.; Flint, Katherine H.; Hawkins, Joseph; Queen, Barbara; Lowry, Richard; Olsen, Emily O'Malley; Chyen, David; Whittle, Lisa; Thornton, Jemekia; Lim, Connie; Yamakawa, Yoshimi; Brener, Nancy; Zaza, Stephanie – Centers for Disease Control and Prevention, 2016
Problem: Priority health-risk behaviors contribute to the leading causes of morbidity and mortality among youth and adults. Population-based data on these behaviors at the national, state, and local levels can help monitor the effectiveness of public health interventions designed to protect and promote the health of youth nationwide. Reporting…
Descriptors: Health Behavior, High School Students, National Surveys, At Risk Persons
Summers, Amber; Confair, Amy R.; Flamm, Laura; Goheer, Attia; Graham, Karlene; Muindi, Mwende; Gittelsohn, Joel – American Journal of Health Education, 2013
Background: The Healthy Bodies, Healthy Souls (HBHS) program aims to reduce diabetes risk among urban African Americans by creating healthy food and physical activity environments within churches. Participant engagement supports the development of applicable intervention strategies by identifying priority concerns, resources, and opportunities.…
Descriptors: Diabetes, Health Promotion, Program Development, Prevention
Hohensee, Caroline W.; Nies, Mary A. – Journal of School Health, 2012
Background: This study assessed the association between amount of physical activity and body mass index (BMI) percentile among middle and high school children. Total daily physical activity needs to include both in and out of school physical activity. Methods: A secondary data analysis was performed on 1306 children drawn from the Panel Study of…
Descriptors: Body Composition, Body Weight, Physical Activity Level, Middle School Students