Is There a Spillover Effect of Targeted Dietary Change on Untargeted Health Behaviors? Evidence From a Dietary Modification Trial

2019 ◽  
Vol 46 (4) ◽  
pp. 569-581 ◽  
Author(s):  
Elizabeth A. Sarma ◽  
Anne Moyer ◽  
Catherine R. Messina ◽  
Helena H. Laroche ◽  
Linda Snetselaar ◽  
...  
Keyword(s):  
Physical Activity ◽  
Alcohol Consumption ◽  
Health Behavior ◽  
Health Behaviors ◽  
Latent Class Analysis ◽  
Repeated Measures ◽  
Latent Class ◽  
Dietary Change ◽  
Dietary Modification ◽  
First Year

Background. The gateway behavior hypothesis posits that change in a health behavior targeted for modification may promote positive changes in other untargeted health behaviors; however, previous studies have shown inconsistent results. Aims. To examine the patterns and predictors of change in untargeted health behaviors in a large health behavior change trial. Method. Using repeated-measures latent class analysis, this study explored patterns of change in untargeted physical activity, alcohol consumption, and smoking behavior during the first year of the Women’s Health Initiative dietary modification trial that targeted total fat reduction to 20% kcal and targeted increased fruit and vegetable intake. Participants were healthy postmenopausal women who were randomly assigned to either the low-fat dietary change intervention ( n = 8,193) or a control ( n = 12,187) arm. Results. Although there were increases in untargeted physical activity and decreases in alcohol consumption and smoking in the first year, these changes were not consistently associated with study arm. Moreover, although the results of the repeated-measures latent class analysis identified three unique subgroups of participants with similar patterns of untargeted health behaviors, none of the subgroups showed substantial change in the probability of engagement in any of the behaviors over 1 year, and the study arms had nearly identical latent class solutions. Discussion and Conclusion. These findings suggest that the dietary intervention did not act as a gateway behavior for change in the untargeted behaviors and that researchers interested in changing multiple health behaviors may need to deliberately target additional behaviors.

scholarly journals Clustering of Modifiable Behavioral Risk Factors and Their Association with All-Cause Mortality in Taiwan’s Adult Population: a Latent Class Analysis

2021 ◽  
Author(s):  
Shikha Kukreti ◽  
Tsung Yu ◽  
Po Wei Chiu ◽  
Carol Strong
Keyword(s):  
Physical Activity ◽  
Alcohol Consumption ◽  
Health Behavior ◽  
Latent Class Analysis ◽  
Risk Behaviors ◽  
Latent Class ◽  
Latent Classes ◽  
Class Analysis ◽  
Unhealthy Behavior ◽  
All Cause Mortality

Abstract Background Modifiable risk behaviors, such as smoking, diet, alcohol consumption, physical activity, and sleep, are known to impact health. This study aims toward identifying latent classes of unhealthy lifestyle behavior, exploring the correlations between sociodemographic factors, identifying classes, and further assessing the associations between identified latent classes and all-cause mortality. Methods For this study, the data were obtained from a prospective cohort study in Taiwan. The participants’ self-reported demographic and behavioral characteristics (smoking, physical activity, alcohol consumption, fruit and vegetable intake, and sleep) were used. Latent class analysis was used to identify health-behavior patterns, and Cox proportional hazard regression analysis was used to find the association between the latent class of health-behavior and all-cause mortality. Results A complete dataset was obtained from 290,279 participants with a mean age of 40 (12.4). Seven latent classes were identified, characterized as having a 100% likelihood of at least one unhealthy behavior coupled with the probability of having the other four unhealthy risk behaviors. This study also shows that latent health-behavior classes are associated with mortality, suggesting that they are representative of a healthy lifestyle. Finally, it appeared that multiple risk behaviors were more prevalent in younger men and individuals with low socioeconomic status. Conclusions There was a clear clustering pattern of modifiable risk behaviors among the adults under consideration, where the risk of mortality increased with increases in unhealthy behavior. Our findings can be used to design customized disease prevention programs targeting specific populations and corresponding profiles identified in the latent class analysis.

scholarly journals Can Health-Promoting Schools Contribute to Better Health Behaviors? Physical Activity, Sedentary Behavior, and Dietary Habits among Israeli Adolescents

2021 ◽  
Vol 18 (3) ◽  
pp. 1183
Author(s):  
Hila Beck ◽  
Riki Tesler ◽  
Sharon Barak ◽  
Daniel Sender Moran ◽  
Adilson Marques ◽  
...  
Keyword(s):  
Physical Activity ◽  
Health Behavior ◽  
Confidence Interval ◽  
Health Behaviors ◽  
Sedentary Behavior ◽  
Dietary Habits ◽  
Group Differences ◽  
Time Behavior ◽  
Health Promoting ◽  
The Mean

Schools with health-promoting school (HPS) frameworks are actively committed to enhancing healthy lifestyles. This study explored the contribution of school participation in HPS on students’ health behaviors, namely, physical activity (PA), sedentary behavior, and dieting. Data from the 2018/2019 Health Behavior in School-aged Children study on Israeli adolescents aged 11–17 years were used. Schools were selected from a sample of HPSs and non-HPSs. Between-group differences and predictions of health behavior were analyzed. No between-group differences were observed in mean number of days/week with at least 60 min of PA (HPS: 3.84 ± 2.19 days/week, 95% confidence interval of the mean = 3.02–3.34; non-HPS: 3.93 ± 2.17 days/week, 95% confidence interval of the mean = 3.13–3.38). Most children engaged in screen time behavior for >2 h/day (HPS: 60.83%; non-HPS: 63.91%). The odds of being on a diet were higher among more active children (odds ratio [OR] = 1.20), higher socio-economic status (OR = 1.23), and female (OR = 2.29). HPS did not predict any health behavior. These findings suggest that HPSs did not contribute to health behaviors more than non-HPSs. Therefore, health-promoting activities in HPSs need to be improved in order to justify their recognition as members of the HPS network and to fulfill their mission.

Brief Report: A Latent Class Analysis of Guideline Compliance Across Nine Health Behaviors

2021 ◽  
Author(s):  
Simone Pettigrew ◽  
Liyuwork M. Dana ◽  
Alison McAleese ◽  
Alice Bastable ◽  
Catherine Drane ◽  
...  
Keyword(s):  
Health Behaviors ◽  
Latent Class Analysis ◽  
Latent Class ◽  
Class Analysis ◽  
Guideline Compliance

scholarly journals Eating behaviour, physical activity, TV exposure and sleeping habits in five year olds: a latent class analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Molly Mattsson ◽  
Deirdre M. Murray ◽  
Mairead Kiely ◽  
Fergus P. McCarthy ◽  
Elaine McCarthy ◽  
...  
Keyword(s):  
Physical Activity ◽  
Latent Class Analysis ◽  
Latent Class ◽  
Eating Behaviour ◽  
Overweight And Obesity ◽  
Class Analysis ◽  
Class Membership ◽  
Active Play ◽  
Food Avoidance ◽  
Cluster Membership

Abstract Background Diet, physical activity, sedentary behaviours, and sleep time are considered major contributory factors of the increased prevalence of childhood overweight and obesity. The aims of this study were to (1) identify behavioural clusters of 5 year old children based on lifestyle behaviours, (2) explore potential determinants of class membership, and (3) to determine if class membership was associated with body measure outcomes at 5 years of age. Methods Data on eating behaviour, engagement in active play, TV watching, and sleep duration in 1229 5 year old children from the Cork BASELINE birth cohort study was obtained through in-person interviews with parent. Latent class analysis was used to identify behavioural clusters. Potential determinants of cluster membership were investigated using multinomial logistic regression. Associations between the identified classes and cardio metabolic body measures were examined using multivariate logistic and linear regression, with cluster membership used as the independent variable. Results 51% of children belonged to a normative class, while 28% of children were in a class characterised by high scores on food avoidance scales in combination with low enjoyment of food, and 20% experienced high scores on the food approach scales. Children in both these classes had lower conditional probabilities of engaging in active play for at least 1 hour per day and sleeping for a minimum of 10 h, and higher probability of watching TV for 2 hours or more, compared to the normative class. Low socioeconomic index (SEI) and no breastfeeding at 2 months were found to be associated with membership of the class associated with high scores on the food avoidance scale, while lower maternal education was associated with the class defined by high food approach scores. Children in the class with high scores on the food approach scales had higher fat mass index (FMI), lean mass index (LMI), and waist-to-height ratio (WtHR) compared to the normative class, and were at greater risk of overweight and obesity. Conclusion Findings suggest that eating behaviour appeared to influence overweight and obesity risk to a greater degree than activity levels at 5 years old. Further research of how potentially obesogenic behaviours in early life track over time and influence adiposity and other cardio metabolic outcomes is crucial to inform the timing of interventions.

scholarly journals Utilizing Participatory Research to Engage Underserved Populations to Improve Health-Related Outcomes in Delaware

Nutrients ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 2353
Author(s):  
Shannon M. Robson ◽  
Samantha M. Rex ◽  
Katie Greenawalt ◽  
P. Michael Peterson ◽  
Elizabeth Orsega-Smith
Keyword(s):  
Physical Activity ◽  
Health Behavior ◽  
Health Behaviors ◽  
Participatory Research ◽  
Cooperative Extension ◽  
Underserved Populations ◽  
Community Outreach ◽  
Outreach Program ◽  
Health Related ◽  
Improve Health

Cooperative Extension is a community outreach program. Despite its large reach, there is a need for the evaluation of changes in health-related outcomes for individuals engaged with Cooperative Extension. A team-based challenge was developed using community-engaged participatory research integrated with Cooperative Extension to encourage healthy eating and physical activity behaviors through Cooperative Extension programming. Thus, the primary purpose of this secondary analysis was to (1) evaluate changes in anthropometric outcomes and (2) evaluate changes in health behavior outcomes. Associations of anthropometric changes and health behavior changes with engagement in the three-month team-based challenge were explored. Anthropometrics were measured using standard procedures, and intake of fruits and vegetables and physical activity were self-reported. Of the 145 participants in the community-engaged participatory research portion of the study, 52.4% (n = 76) had complete anthropometrics before and after the team-based challenge and were included in this study. At 3 months, there was a significant reduction in body mass index (−0.3 kg/m2, p = 0.024) and no significant change in waist circumference (p = 0.781). Fruit and vegetable intake significantly increased (+0.44 servings/day, p = 0.018). Physical activity did not significantly change based on (1) the number of days 30 or more minutes of physical activity was conducted (p = 0.765) and (2) Godin Leisure-Time Exercise Questionnaire scores (p = 0.612). Changes in anthropometrics and health behaviors were not associated with engagement in the team-based challenge. Using community-engaged participatory research with community outreach programs, such as Cooperative Extension, can improve health-related outcomes in underserved populations. However, despite a participatory approach, changes in anthropometrics and health behaviors were not associated with engagement in the developed team-based challenge.

Abstract 04: Racial Disparities in Cardiovascular Health Behaviors are Partially Explained by Socioeconomic, Psychosocial and Environmental Factors: the Coronary Artery Risk Development in Young Adults (CARDIA) Study

Circulation ◽  
2017 ◽  
Vol 135 (suppl_1) ◽  
Author(s):  
Kara M Whitaker ◽  
David R Jacobs ◽  
Kiarri N Kershaw ◽  
John N Booth ◽  
David C Goff ◽  
...  
Keyword(s):  
Physical Activity ◽  
Environmental Factors ◽  
Health Behavior ◽  
Health Behaviors ◽  
Socioeconomic Factors ◽  
Racial Differences ◽  
Fast Food ◽  
Cardiovascular Health ◽  
Race Difference ◽  
Explanatory Role

Introduction: There are known racial differences in cardiovascular health behaviors, including smoking, physical activity, and diet quality. A better understanding of factors that explain these differences may suggest novel intervention targets for reducing disparities in cardiovascular disease. Objective: To examine whether socioeconomic, psychosocial and environmental factors mediate racial differences in health behaviors. Methods: We studied 3,028 Black or White CARDIA participants who were enrolled at age 18-30 years in 1985-86 and completed the 30 year follow-up visit in 2015-2016. Health behaviors included smoking (current, former ≤ 12 months, never smoker/quit >12 months), physical activity (inactive, active but not meeting guidelines, meeting guidelines), and a surrogate for healthy eating using fast food and sugar-sweetened beverage consumption (frequency per week ≥ 2, some but < 2, none). Each behavior was assigned a value of 0 for poor, 1 for intermediate or 2 for ideal and summed to calculate an overall health behavior score for each participant (range 0-6). The race difference (β) in health behavior score was estimated using linear regression. Formal mediation analyses computed the proportion of the total effect of race on health behavior score explained by socioeconomic, psychosocial, and environmental factors (see Table footnote). Results: Blacks had a lower health behavior score than Whites in crude analyses (mean difference: -1.04, p<0.001). After adjustment for sex, age and field center, socioeconomic factors mediated 50.5% of the association between race and the health behavior score, psychosocial factors 26.8% and environmental factors 9.0% (p<0.05 for all). Joint associations mediated 58.1% of the race-health behavior score association. Conclusions: Observed racial differences in the health behavior score are predominately mediated by socioeconomic factors, which appear to play a stronger explanatory role than psychosocial and environmental factors.

scholarly journals Physical Activity and Sedentary Activity Patterns Among Children and Adolescents: A Latent Class Analysis Approach

2011 ◽  
Vol 8 (4) ◽  
pp. 457-467 ◽  
Author(s):  
Carrie D. Patnode ◽  
Leslie A. Lytle ◽  
Darin J. Erickson ◽  
John R. Sirard ◽  
Daheia J. Barr-Anderson ◽  
...  
Keyword(s):  
Physical Activity ◽  
Latent Class Analysis ◽  
Children And Adolescents ◽  
Latent Class ◽  
Multinomial Logistic Regression ◽  
Activity Patterns ◽  
Moderate Activity ◽  
Class Analysis ◽  
Sedentary Behaviors ◽  
Sedentary Activity

Background:While much is known about the overall levels of physical activity and sedentary activity among youth, few studies have attempted to define clusters of such behaviors. The purpose of this study was to identify and describe unique classes of youth based on their participation in a variety of physical activity and sedentary behaviors.Methods:Latent class analysis was used to characterize segments of youth based on patterns of self-reported and accelerometer-measured participation in 12 behaviors. Children and adolescents (N = 720) from 6th-11th grade were included in the analysis. Differences in class membership were examined using multinomial logistic regression.Results:Three distinct classes emerged for boys and girls. Among boys, the 3 classes were characterized as “Active” (42.1%), “Sedentary” (24.9%), and “Low Media/Moderate Activity” (33.0%). For girls, classes were “Active” (18.7%), “Sedentary” (47.6%), and “Low Media/Functional Activity” (33.7%). Significant differences were found between the classes for a number of demographic indicators including the proportion in each class who were classified as overweight or obese.Conclusions:The behavioral profiles of the classes identified in this study can be used to suggest possible audience segments for intervention and to tailor strategies appropriately.

scholarly journals Differences in park characteristic preferences for visitation and physical activity among adolescents: A latent class analysis

PLoS ONE ◽  
2019 ◽  
Vol 14 (3) ◽  
pp. e0212920 ◽  
Author(s):  
Lieze Mertens ◽  
Jelle Van Cauwenberg ◽  
Jenny Veitch ◽  
Benedicte Deforche ◽  
Delfien Van Dyck
Keyword(s):  
Physical Activity ◽  
Latent Class Analysis ◽  
Latent Class ◽  
Class Analysis
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