scholarly journals Health lifestyles and Chinese oldest-old’s subjective well-being—evidence from a latent class analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Li Zhang ◽  
Xiangyang Bi ◽  
Zhihong Ding
Keyword(s):  
Mental Health ◽  
Latent Class Analysis ◽  
Latent Class ◽  
Healthy Lifestyle ◽  
Well Being ◽  
Class Analysis ◽  
Lifestyle Behaviors ◽  
Subjective Well Being ◽  
Health Lifestyles ◽  
Healthy Lifestyle Behaviors

Abstract Background Previous research on the associations between lifestyle behaviors and health has largely focused on morbidity, mortality and disease prevention. More attention should be paid to examining relationships between lifestyle behaviors and positive health outcomes such as well-being. The aim of the study was to classify Chinese oldest-old’s health lifestyles and evaluate the manner in which health lifestyles have impacted Chinese oldest-old’s subjective well-being. Methods Analyzing the 2014 Chinese Longitudinal Healthy Longevity Survey (CLHLS), latent class analysis was applied to identify predominant health lifestyles among Chinese oldest-old aged 85 to 105. Ordinary Least Square (OLS) regression models were used to assess the effects of health lifestyles on Chinese oldest-old’s subjective well-being, adjusting for socio-demographic characteristics. Results Four distinct classes representing health lifestyles emerged. Health lifestyles were found to be strongly associated with Chinese oldest-old’s subjective well-being, even after controlling for demographic features as well as individual and parental socioeconomic disadvantage. Findings showed that healthy lifestyle behaviors stimulated Chinese oldest-old’s positive feelings and led to better evaluative subjective well-being. In contrast, less healthy lifestyle behaviors can be a predictor of negative feelings. Conclusions The regression results highlighted the importance of integrating health lifestyle choices in promoting oldest-old’s psychological well-being. Elders can tackle healthier lifestyle behaviors in their daily lives to reduce the risk of mental health problems. Practicing healthy lifestyles should be integrated in programs for mental health promotion.

scholarly journals Latent Class Analysis of Mental Health in Middle Childhood: Evidence for the Dual-Factor Model

2020 ◽  
Vol 12 (4) ◽  
pp. 786-800
Author(s):  
Kimberly J. Petersen ◽  
Neil Humphrey ◽  
Pamela Qualter
Keyword(s):  
Mental Health ◽  
Latent Class Analysis ◽  
Conduct Problems ◽  
Middle Childhood ◽  
Mental Distress ◽  
Latent Class ◽  
Factor Model ◽  
Well Being ◽  
Subjective Well Being ◽  
Emotional Symptoms

Abstract Mental health is complex, comprising both mental distress and well-being. This study used latent class analysis to identify common combinations of mental distress and well-being (‘mental health classes’) among schoolchildren aged 8–9 years (N = 3340). Thirteen items, measuring a range of conduct problems, emotional symptoms, and subjective well-being, were included in the analysis. Four mental health classes were identified: (1) complete mental health (n = 1895, 57%), (2) vulnerable (n = 434, 13%), (3) emotional symptoms but content (n = 606, 18%), and (4) conduct problems but content (n = 404, 12%). The classes were reliably identified across different datasets, and for males and females. Differential relations with covariates indicated that mental health classes were distinct and externally valid. The results supported the dual-factor model of mental health, suggesting that mental distress and subjective well-being are separate continua. Three of the four possible combinations of high and low distress and subjective well-being posited by the dual-factor model were found using this inductive statistical method. Importantly, our analysis also revealed two ‘symptomatic but content’ groups, differentiated by symptom domain (internalising/externalising). The covariate analyses between mental health classes and sociodemographic factors, prior academic attainment, school connectedness, and peer support, indicated that there are nuanced relations between those variables and particular constellations of mental distress and well-being. As one of the few dual-factor studies to focus on middle childhood, the current study adds important new evidence that contributes to our understanding of the complexities of mental health among schoolchildren.

scholarly journals Lifestyle Clusters and Cardiometabolic Risks in Adolescents: A Chinese School-Based Study Using a Latent Class Analysis Approach

2021 ◽  
Vol 9 ◽  
Author(s):  
Weiying Zhao ◽  
Danyan Su ◽  
Luxia Mo ◽  
Cheng Chen ◽  
Bingbing Ye ◽  
...  
Keyword(s):  
Physical Activity ◽  
Latent Class Analysis ◽  
Latent Class ◽  
Healthy Lifestyle ◽  
Class Analysis ◽  
Lifestyle Behaviors ◽  
School Based ◽  
Significant Difference ◽  
Cardiometabolic Risks ◽  
Lifestyle Pattern

Background: Unhealthy dietary and lifestyle behaviors are associated with a higher prevalence of non-communicable chronic diseases and higher mortality in adults. However, there remains some uncertainty about the magnitude of the associations between lifestyle behaviors and cardiovascular factors in adolescents.Methods: We conducted a school-based cross-sectional study of 895 Chinese adolescents aged 15–19 years. They participated in a questionnaire survey, physical examination, and blood sample collection. Latent class analysis (LCA) was used to identify heterogeneous subgroups of lifestyle behaviors. A set of 12 latent class indicators, which reflected lifestyle behaviors including dietary habits, physical activity, sleep duration, screen time, and pressure perception, were included in the analysis. Logistic regression analysis was performed to determine whether the derived classes were related to a cardiometabolic risk.Results: In total, 13.7 and 5.6% of the participants were overweight and obese, respectively, and 8.4 and 14.1% reported having pre-hypertension and hypertension, respectively. A two-class model provided the best fit with a healthy lifestyle pattern (65.8%) and a sub-healthy lifestyle pattern (34.2%). There were more female participants with a healthy lifestyle (56.2 vs. 43.8%), whereas there were more males with a sub-healthy lifestyle (45.4 vs. 54.6%), (all P = 0.002). Increased risk of cardiometabolic abnormality (BMI categories, blood pressure and lipids) was not significant across lifestyle patterns, except for waist circumference (70.5 vs 69.1 cm, P = 0.044). There was no significant difference in physical activity and intake of fruit and vegetable between the two patterns.Conclusion: Primary prevention based on lifestyle modification should target patterns of behaviors at high risk in adolescents. Due to the complex effect of lifestyle clusters on cardiometabolic risks, well-designed and prospective studies in adolescents are needed in the future.

scholarly journals Suicidal Behavior in Adolescents: A Latent Class Analysis

2020 ◽  
Vol 17 (8) ◽  
pp. 2820
Author(s):  
Adriana Díez-Gómez ◽  
Alicia Pérez-Albéniz ◽  
Carla Sebastián-Enesco ◽  
Eduardo Fonseca-Pedrero
Keyword(s):  
Negative Affect ◽  
Latent Class Analysis ◽  
Suicidal Behavior ◽  
Behavioral Problems ◽  
Latent Class ◽  
Emotional Adjustment ◽  
Well Being ◽  
Emotional And Behavioral Problems ◽  
Class Analysis ◽  
Subjective Well Being

The main goal of the present study was to identify and validate latent classes of suicidal behavior in a representative sample of adolescents. The sample comprised a total of 1506 students, including 667 males (44.3%), selected through a sample stratified by clusters. The mean age was 16.15 years (SD = 1.36). The instruments used evaluated suicidal behavior, positive and negative affect, emotional and behavioral problems, prosocial behavior, and subjective well-being. Using the Paykel Suicide Scale, the latent class analysis identified four homogeneous subgroups: “low risk”, “suicidal act”, “suicidal ideation”, and “high risk for suicide”. These subgroups presented a differential pattern in terms of their social-emotional adjustment. The subgroups with the highest theoretical risk showed lower scores on subjective well-being and positive affect as well as higher scores on emotional and behavioral problems and negative affect compared to the non-risk subgroups. This study contributes to an understanding of the typologies of suicidal behavior among adolescents and the relationship with psychopathological adjustment. Ultimately, these findings may promote the development or improvement of early detection and prevention strategies in the suicidal behavior field in order to reduce the socio-economic burdens associated with suicide in young populations.

A Latent Class Analysis of Mental Health Beliefs Related to Military Sexual Trauma

2020 ◽  
Author(s):  
Christine K. Hahn ◽  
Jessica Turchik ◽  
Rachel Kimerling
Keyword(s):  
Mental Health ◽  
Latent Class Analysis ◽  
Health Beliefs ◽  
Sexual Trauma ◽  
Latent Class ◽  
Military Sexual Trauma ◽  
Class Analysis ◽  
Mental Health Beliefs

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

2018 ◽  
Vol 53 (1) ◽  
pp. 53-64 ◽  
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

A national study of the availability of law enforcement agency wellness programming for officers: A latent class analysis

2021 ◽  
pp. 146135572110640
Author(s):  
Bruce G Taylor ◽  
Weiwei Liu ◽  
Elizabeth A. Mumford
Keyword(s):  
Mental Health ◽  
United States ◽  
Substance Use ◽  
Law Enforcement ◽  
Latent Class Analysis ◽  
Latent Class ◽  
Wellness Programs ◽  
The United States ◽  
Substance Use Treatment ◽  
Class Analysis

The purpose of this study is to understand the availability of employee wellness programs within law enforcement agencies (LEAs) across the United States, including physical fitness, resilience/wellness, coping skills, nutrition, mental health treatment, and substance use treatment. The research team investigated whether patterns of LEA wellness programming are identifiable and, if so, what characteristics describe these patterns. We assess using latent class analysis whether there are distinct profiles of agencies with similar patterns offering different types of wellness programs and explore what characteristics distinguish agencies with certain profiles of wellness programming. Data were from a nationally representative sample of 1135 LEAs: 80.1% municipal, 18.6% county and 1.3% other agencies (state-level and Bureau of Indian Affairs LEAs). We found that many agencies (62%) offer no wellness programming. We also found that 23% have comprehensive wellness programming, and that another group of agencies specialize in specific wellness programming. About 14% of the agencies have a high probability of providing resilience coping skill education, mental health and/or substance use treatment services programming. About 1% of the agencies in the United States limit their programming to fitness and nutrition, indicating that fitness and nutrition programs are more likely to be offered in concert with other types of wellness programs. The analyses revealed that agencies offering broad program support are more likely to be large, municipal LEAs located in either the West, Midwest or Northeast (compared with the southern United States), and not experiencing a recent budget cut that impacted wellness programming.

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

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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