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

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.

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Variations in adolescents’ motivational characteristics across gender and physical activity patterns: A latent class analysis approach

BMC Public Health ◽

10.1186/s12889-017-4677-x ◽

2017 ◽

Vol 17 (1) ◽

Cited By ~ 13

Author(s):

Margaret Lawler ◽

Caroline Heary ◽

Elizabeth Nixon

Keyword(s):

Physical Activity ◽

Latent Class Analysis ◽

Latent Class ◽

Activity Patterns ◽

Analysis Approach ◽

Class Analysis ◽

Physical Activity Patterns

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

10.21203/rs.3.rs-115069/v1 ◽

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.

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

BMC Pediatrics ◽

10.1186/s12887-021-02640-0 ◽

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.

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Well-being and Long-term Physical Activity Participation in Midlife Adults: A Latent Class Analysis

Annals of Behavioral Medicine ◽

10.1093/abm/kay016 ◽

2018 ◽

Vol 53 (1) ◽

pp. 53-64 ◽

Cited By ~ 4

Author(s):

Jerrald L Rector ◽

Sharon L Christ ◽

Elliot M Friedman

Keyword(s):

Physical Activity ◽

Latent Class Analysis ◽

Latent Class ◽

Well Being ◽

Physical Activity Participation ◽

Activity Participation ◽

Class Analysis ◽

Midlife Adults

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Application of latent class analysis in assessing the mental health of medical students during the COVID-19 Epidemic (Preprint)

10.2196/preprints.26804 ◽

2020 ◽

Author(s):

Fei Wang

Keyword(s):

Mental Health ◽

Medical Students ◽

High Risk ◽

Latent Class Analysis ◽

Latent Class ◽

Risk Group ◽

Multinomial Logistic Regression ◽

High Risk Group ◽

Class Analysis ◽

Related Factors

BACKGROUND The novel coronavirus disease 2019 (COVID-19) is a global public health emergency that has caused worldwide concern. The mental health of medical students under the COVID-19 epidemic has attracted much attention. OBJECTIVE This study aims to identify subgroups of medical students based on mental health status and explore the influencing factors during the COVID-19 epidemic in China. METHODS A total of 29,663 medical students were recruited during the epidemic of COVID-19 in China. Latent class analysis of the mental health of medical students was performed using M-plus software to identify subtypes of medical students. The latent class subtypes were compared using the chi-square test. Multinomial logistic regression was used to examine associations between identified classes and related factors. RESULTS In this study, three distinct subgroups were identified, namely, the high-risk group, the low-risk group and the normal group. Therefore, medical students can be divided into three latent classes, and the number of students in each class is 4325, 9321 and 16,017. The multinomial logistic regression results showed that compared with the normal group, the factors influencing mental health in the high-risk group were insomnia, perceived stress, family psychiatric disorders, fear of being infected, drinking, individual psychiatric disorders, sex, educational level and knowledge of COVID-19, according to the intensity of influence from high to low. CONCLUSIONS Our findings suggested that latent class analysis can be used to categorize different medical students according to their mental health subgroup during the outbreak of COVID-19. The main factors influencing the high-risk group and low-risk group are basic demographic characteristics, disease history, COVID-19 related factors and behavioral lifestyle, among which insomnia and perceived stress have the greatest impact. School administrative departments could utilize more specific measures on the basis of different subgroups, and provide targeted measures.

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

PLoS ONE ◽

10.1371/journal.pone.0212920 ◽

2019 ◽

Vol 14 (3) ◽

pp. e0212920 ◽

Cited By ~ 3

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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Associative stigma among mental health professionals in Singapore: a cross-sectional study

BMJ Open ◽

10.1136/bmjopen-2018-028179 ◽

2019 ◽

Vol 9 (7) ◽

pp. e028179 ◽

Cited By ~ 2

Author(s):

Louisa Picco ◽

Sherilyn Chang ◽

Edimansyah Abdin ◽

Boon Yiang Chua ◽

Qi Yuan ◽

...

Keyword(s):

Mental Health ◽

Job Satisfaction ◽

Latent Class Analysis ◽

Mental Health Professionals ◽

Health Professionals ◽

Online Survey ◽

Latent Class ◽

Multinomial Logistic Regression ◽

Class Analysis ◽

Associative Stigma

Objectives(1) Investigate and explore whether different classes of associative stigma (the process by which a person experiences stigmatisation as a result of an association with another stigmatised person) could be identified using latent class analysis; (2) determine the sociodemographic and employment-related correlates of associative stigma and (3) examine the relationship between associative stigma and job satisfaction, among mental health professionals.DesignCross-sectional online survey.ParticipantsDoctors, nurses and allied health staff, working in Singapore.MethodsStaff (n=462) completed an online survey, which comprised 11 associative stigma items and also captured sociodemographic and job satisfaction-related information. Latent class analysis was used to classify associative stigma on patterns of observed categorical variables. Multinomial logistic regression was used to examine associations between sociodemographic and employment-related factors and the different classes, while multiple linear regression analyses were used to examine the relationship between associative stigma and job satisfaction.ResultsThe latent class analysis revealed that items formed a three-class model where the classes were classified as ‘no/low associative stigma’, ‘moderate associative stigma’ and ‘high associative stigma’. 48.7%, 40.5% and 10.8% of the population comprised no/low, moderate and high associative stigma classes, respectively. Multinomial logistic regression showed that years of service and occupation were significantly associated with moderate associative stigma, while factors associated with high associative stigma were education, ethnicity and occupation. Multiple linear regression analyses revealed that high associative stigma was significantly associated with lower job satisfaction scores.ConclusionAssociative stigma was not uncommon among mental health professionals and was associated with sociodemographic factors and poorer job satisfaction. Associative stigma has received comparatively little attention from empirical researchers and continued efforts to address this understudied yet important construct in conjunction with future efforts to dispel misconceptions related to mental illnesses are needed.

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It’s A-bout Time: Detailed Patterns of Physical Activity in Obese Adolescents Participating in a Lifestyle Intervention

Journal of Physical Activity and Health ◽

10.1123/jpah.2014-0480 ◽

2015 ◽

Vol 12 (11) ◽

pp. 1453-1460 ◽

Cited By ~ 3

Author(s):

Erin Kaye Howie ◽

Timothy Olds ◽

Joanne A. McVeigh ◽

Rebecca A. Abbott ◽

Leon Straker

Keyword(s):

Physical Activity ◽

Lifestyle Intervention ◽

Sedentary Time ◽

Activity Patterns ◽

Lower Percentage ◽

Moderate Activity ◽

Variation Analysis ◽

Sedentary Behaviors ◽

Obese Adolescents ◽

Exposure Variation Analysis

Background:The detailed patterns of physical activity and sedentary behaviors of overweight and obese adolescents are unknown, but may be important for health outcomes and targeted intervention design.Methods:Participants completed Curtin University’s Activity, Food and Attitudes Program (CAFAP), an 8-week intervention with 12 months of maintenance intervention. Physical activity and sedentary time were assessed at 6 time periods with accelerometers and were analyzed by 1) time and type of day, 2) intensity bout patterns using exposure variation analysis, and 3) individual case analysis.Results:Participants (n = 56) spent a lower percentage of time at baseline in light activity during school days compared with weekend days (24.4% vs 29.0%, P = .004). The majority of time was in long uninterrupted sedentary bouts of greater than 30 minutes (26.7% of total time, 36.8% of sedentary time at baseline). Moderate activity was accumulated in short bouts of less than 5 minutes (3.1% of total time, 76.0% moderate time). Changes varied by individuals.Conclusions:Exposure variation analysis revealed specific changes in activity patterns in overweight and obese adolescents who participated in a lifestyle intervention. A better understanding of these patterns can help to design interventions that meaningfully affect specific behaviors, with unique health consequences.

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Trajectories of Depressive Symptoms among Multicultural Adolescents in Korea: Longitudinal Analysis Using Latent Class Growth Model

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17218217 ◽

2020 ◽

Vol 17 (21) ◽

pp. 8217

Author(s):

Min Kyung Song ◽

Ju Young Yoon ◽

Eunjoo Kim

Keyword(s):

Depressive Symptoms ◽

Latent Class Analysis ◽

Predictive Factors ◽

Latent Class ◽

Multinomial Logistic Regression ◽

Panel Study ◽

Class Analysis ◽

Early Screening ◽

Care Plans ◽

Latent Class Growth

The purpose of this study was to investigate the trajectory of depressive symptoms in multicultural adolescents using longitudinal data, and to identify predictive factors related to depressive symptoms of multicultural adolescents using latent class analysis. We used six time-point data derived from the 2012 to 2017 Multicultural Adolescents Panel Study (MAPS). Latent growth curve modeling was used to assess the overall features of depressive symptom trajectories in multicultural adolescents, and latent class growth modeling was used to determine the number and shape of trajectories. We applied multinomial logistic regression analysis to each class to explore predictive factors. We found that the overall slope of depressive symptoms in multicultural adolescents increased. Latent class analysis demonstrated three classes: (1) high-increasing class (i.e., high intercept, significantly increasing slope), (2) moderate-increasing class (i.e., moderate intercept, significantly increasing slope), and (3) low-stable class (i.e., low intercept, no significant slope). In particular, we found that the difference in the initial intercept of depressive symptoms determined the subsequent trajectory. There is a need for early screening for depressive symptoms in multicultural adolescents and preparing individual mental health care plans.

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