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 Eating Behaviour, Physical Activity, TV Exposure and Sleeping Habits in Five Year Olds: A Latent Class Analysis

2020 ◽  
Author(s):  
Molly Mattsson ◽  
Deirdre Murray ◽  
Mairead Kiely ◽  
Fergus McCarthy ◽  
Elaine McCarthy ◽  
...  
Keyword(s):  
Physical Activity ◽  
Latent Class Analysis ◽  
Latent Class ◽  
Multinomial Logistic Regression ◽  
Eating Behaviour ◽  
Overweight And Obesity ◽  
Class Analysis ◽  
Active Play ◽  
Cluster Membership ◽  
Metabolic Outcomes

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 aim of this study was to identify behavioural clusters of five year old children based on lifestyle behaviours, their association with sociodemographic and maternal characteristics and early feeding practices, and to determine if class membership was associated with cardio metabolic outcomes. Methods Latent class analysis of eating behaviour, engagement in active play, TV watching, and sleep duration in 1,229 five year old children from the Cork BASELINE birth cohort study was used to identify behavioral clusters. Determinants of cluster membership were investigated using multinomial logistic regression. Associations between the identified classes and cardio 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 one hour per day and sleeping for a minimum of 10 hours, and higher probability of watching TV for two hours or more, compared to the normative class. Children in the class with high scores on 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 five 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 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 Mental disorders pattern in staff of a military unit in Iran: the role of metabolic syndrome on latent class membership

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Abbas Abbasi-Ghahramanloo ◽  
Mohammadkarim Bahadori ◽  
Esfandiar Azad ◽  
Nooredin Dopeykar ◽  
Parisa Mahdizadeh ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Mental Disorders ◽  
Latent Class Analysis ◽  
Latent Class ◽  
Adult Population ◽  
Class Analysis ◽  
Class Membership ◽  
Anthropometric Measures ◽  
Military Unit

Abstract Introduction Mental disorders are among the most prevalent health problems of the adult population in the world. This study aimed to identify the subgroups of staff based on mental disorders and assess the independent role of metabolic syndrome (MetS) on the membership of participants in each latent class. Methods This cross-sectional study was conducted among 694 staff of a military unit in Tehran in 2017. All staff of this military unit was invited to participate in this study. The collected data included demographic characteristics, anthropometric measures, blood pressure, biochemical parameters, and mental disorders. We performed latent class analysis using a procedure for latent class analysis (PROC LCA) in SAS to identify class membership of mental disorders using Symptom Checklist-90. Results Three latent classes were identified as healthy (92.7%), mild (4.9%), and severe (2.4%) mental disorders. Having higher age significantly decreased the odds of belonging to the mild class (adjusted OR (aOR = 0.21; 95% confidence interval (CI): 0.05–0.83) compared to the healthy class. Also, obesity decreased the odds of membership in mild class (aOR = 0.10, 95% CI: 0.01–0.92) compared to healthy class. On the other hand, being female increased the odds of being in severe class (aOR = 9.76; 95% CI: 1.35–70.65) class in comparison to healthy class. Conclusion This study revealed that 7.3% of staff fell under mild and severe classes. Considering educational workshops in the workplace about mental disorders could be effective in enhancing staff’s knowledge of these disorders. Also, treatment of comorbid mental disorders may help reduce their prevalence and comorbidity.

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

Patterns of physical activity, sitting time and sleep in Australian adults: a latent class analysis

2019 ◽  
Vol 22 ◽  
pp. S56
Author(s):  
M. Duncan ◽  
S. Oftedal ◽  
A. Rebar ◽  
B. Murawski ◽  
C. Short ◽  
...  
Keyword(s):  
Physical Activity ◽  
Latent Class Analysis ◽  
Latent Class ◽  
Sitting Time ◽  
Class Analysis

scholarly journals A primer to latent profile and latent class analysis

2021 ◽  
Author(s):  
Johannes Bauer
Keyword(s):  
Individual Differences ◽  
Latent Class Analysis ◽  
Latent Class ◽  
Class Analysis ◽  
Class Membership ◽  
External Variables ◽  
Response Profiles ◽  
Person Centered Approach ◽  
Conceptual Overview ◽  
Latent Profile

This chapter gives an applied introduction to latent profile and latent class analysis (LPA/LCA). LPA/LCA are model-based methods for clustering individuals in unobserved groups. Their primary goals are probing whether and, if so, how many latent classes can be identified in the data, and to estimate the proportional size and response profiles of these classes in the population. Moreover, latent class membership can serve as predictor or outcome for external variables. Substantively, LPA/LCA adopt a person-centered approach that is useful for analyzing individual differences in prerequisites, processes, or outcomes of learning. The chapter provides a conceptual overview of LPA/LCA, a nuts-and-bolts discussion of the steps and decisions involved in their application, and illustrative examples using freely available data and the R statistical environment.

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