Risk Factors Explaining Military Deaths From Suicide, 2008–2017: A Latent Class Analysis

2021 ◽  
pp. 0095327X2110469
Author(s):  
Scott D. Landes ◽  
Janet M. Wilmoth ◽  
Andrew S. London ◽  
Ann T. Landes
Keyword(s):  
Mental Health ◽  
Risk Factors ◽  
Latent Class Analysis ◽  
Military Service ◽  
Latent Class ◽  
Service Providers ◽  
Service Members ◽  
Latent Classes ◽  
Class Analysis ◽  
Military Service Members

Military suicide prevention efforts would benefit from population-based research documenting patterns in risk factors among service members who die from suicide. We use latent class analysis to analyze patterns in identified risk factors among the population of 2660 active-duty military service members that the Department of Defense Suicide Event Report (DoDSER) system indicates died by suicide between 2008 and 2017. The largest of five empirically derived latent classes was primarily characterized by the dissolution of an intimate relationship in the past year. Relationship dissolution was common in the other four latent classes, but those classes were also characterized by job, administrative, or legal problems, or mental health factors. Distinct demographic and military-status differences were apparent across the latent classes. Results point to the need to increase awareness among mental health service providers and others that suicide among military service members often involves a constellation of potentially interrelated risk factors.

Subtypes of Mental Health Stigma and Barriers to Care Among National Guard Personnel: Results of a Latent Class Analysis

2019 ◽  
Vol 46 (3) ◽  
pp. 424-437
Author(s):  
Craig J. Bryan ◽  
David Wood ◽  
Michael Applegarth ◽  
AnnaBelle O. Bryan
Keyword(s):  
Mental Health ◽  
Health Care ◽  
Latent Class Analysis ◽  
Access To Health Care ◽  
Latent Class ◽  
Barriers To Care ◽  
Service Providers ◽  
National Guard ◽  
Class Analysis ◽  
Suicidal Thoughts And Behaviors

U.S. National Guard (NG) military personnel experience many barriers to care such as limited access to health-care services and geographic separation from service providers. Although stigma and barriers to mental health care have been examined in the military, little is known about how different facets of stigma and barriers to care might impact different military subgroups. In a sample of 965 NG personnel, latent class analysis was used to identify distinct subgroups of stigma and barriers to care. Four groups were identified: no stigma or barriers (31%), mild stigma and barriers (30%), high stigma and career concerns (20%), and moderate stigma and barriers (20%). Classes significantly differed with respect to several demographic characteristics, rates of mental health conditions, and rates of previous suicidal thoughts and behaviors. Results suggest that different subgroups of NG personnel vary with respect to levels of perceived stigma, barriers to care, and mental health needs.

scholarly journals The whole is greater than the sum of its parts: profiles of multiple mental health risk factors using Latent class analysis

2021 ◽  
Vol 15 (1) ◽  
Author(s):  
Kristin Göbel ◽  
Caroline Cohrdes
Keyword(s):  
Mental Health ◽  
Risk Factors ◽  
Health Outcomes ◽  
Latent Class Analysis ◽  
Latent Class ◽  
Mental Health Outcomes ◽  
Class Analysis ◽  
Late Adolescent ◽  
Risk Profiles ◽  
Multiple Risk

Abstract Background The exposure to an accumulation of various risk factors during childhood and adolescence relative to a single risk is associated with poorer mental health. Identification of distinct constellations of risk factors is an essential step towards the development of effective prevention strategies of mental disorders. A Latent class analysis (LCA) extracts different combinations of risk factors or subgroups and examines the association between profiles of multiple risk and mental health outcomes. Methods The current study used longitudinal survey data (KiGGS) of 10,853 German children, adolescents and young adults. The LCA included 27 robust risk and protective factors across multiple domains for mental health. Results The LCA identified four subgroups of individuals with different risk profiles: a basic-risk (51.4%), high-risk (23.4%), parental-risk (11.8%) and social-risk class (13.4%). Multiple risk factors of the family domain, in particular family instability were associated with negative mental health outcomes (e.g. mental health problems, depression, ADHD) and predominately comprised late adolescent girls. The social environment represented a more common risk domain for young males. Conclusion The understanding of multiple risk and different risk “profiles” helps to understand and adjust targeted interventions with a focus on vulnerable groups.

Examining Associations Between Race, Gender, Alcohol Use, School Performance, and Patterns of Bullying in the School Context: A Latent Class Analysis

2021 ◽  
pp. 088626052199912
Author(s):  
Valdemir Ferreira-Junior ◽  
Juliana Y. Valente ◽  
Zila M. Sanchez
Keyword(s):  
Alcohol Use ◽  
Latent Class Analysis ◽  
School Performance ◽  
Latent Class ◽  
School Context ◽  
Bullying Victimization ◽  
Latent Classes ◽  
Class Analysis ◽  
Seventh Grade ◽  
Sociodemographic Variables

Although many studies addressed bullying occurrence and its associations, they often use individual variables constructed from few items that probably are inadequate to evaluate bullying severity and type. We aimed to identify involvement patterns in bullying victimization and perpetration, and its association with alcohol use, school performance, and sociodemographic variables. Baseline assessment of a randomized controlled trial were used and a latent class analysis was conducted to identify bullying patterns among 1,742 fifth-grade and 2,316 seventh-grade students from 30 public schools in São Paulo, Brazil. Data were collected using an anonymous self-reported, audio-guided questionnaire completed by the participants on smartphones. Multinomial logistic regressions were performed to verify how covariant variables affected bullying latent classes. Both grades presented the same four latent classes: low bullying, moderate bullying victimization, high bullying victimization, and high bullying victimization and perpetration. Alcohol use was associated with all bullying classes in both grades, with odds ratio up to 5.36 (95% CI 3.05; 10.38) among fifth graders from the high bullying victimization and perpetration class. Poor school performance was also strongly associated with this class (aOR = 10.12, 95%CI = 4.19; 24.41). Black/brown 5th graders were 3.35 times more likely to fit into the high bullying victimization class (95% CI 1.34; 8.37). Lack of evidence for association of sociodemographic variables and bullying latent class among seventh-grade students was found. Bullying and alcohol use are highly harmful behaviors that must be prevented. However, prevention programs should consider how racial and gender issues are influencing the way students experience violence.

Identifying individuals with multiple non-communicable disease risk factors in Kenya: a latent class analysis

Public Health ◽  
2021 ◽  
Vol 198 ◽  
pp. 180-186
Author(s):  
R.S. Mkuu ◽  
T.D. Gilreath ◽  
A.E. Barry ◽  
F.M. Nafukho ◽  
J. Rahman ◽  
...  
Keyword(s):  
Risk Factors ◽  
Latent Class Analysis ◽  
Latent Class ◽  
Disease Risk ◽  
Communicable Disease ◽  
Class Analysis ◽  
Non Communicable Disease

Prevalence, risk factors and multi-group latent class analysis of lifetime anxiety disorders comorbid depressive symptoms

2019 ◽  
Vol 243 ◽  
pp. 360-365 ◽  
Author(s):  
Hongguang Chen ◽  
Xiao Wang ◽  
Yueqin Huang ◽  
Guohua Li ◽  
Zhaorui Liu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Depressive Symptoms ◽  
Anxiety Disorders ◽  
Latent Class Analysis ◽  
Latent Class ◽  
Class Analysis

scholarly journals Clusters of the Risk Markers and the Pattern of Premature Coronary Heart Disease: An Application of the Latent Class Analysis

2021 ◽  
Vol 8 ◽  
Author(s):  
Leila Jahangiry ◽  
Mahdieh Abbasalizad Farhangi ◽  
Mahdi Najafi ◽  
Parvin Sarbakhsh
Keyword(s):  
Risk Factors ◽  
Coronary Heart Disease ◽  
Latent Class Analysis ◽  
High Probability ◽  
Latent Class ◽  
Class Analysis ◽  
Risk Markers ◽  
History Of ◽  
Opium Addiction ◽  
The Mean

Background: Coronary heart disease (CHD) is the major cause of mortality in the world with a significant impact on the younger population. The aim of this study was to identify prematurity among patients with coronary artery bypass graft surgery (CABG) based on the clustering of CHD risk factors.Methods: Patients were recruited from an existing cohort of candidates for CABG surgery named Tehran Heart Center Coronary Outcome Measurement (THC-COM). A latent class analysis (LCA) model was formed using 11 potential risk factors as binary variables: cigarette smoking, obesity, diabetes, family history of CHD, alcohol use, opium addiction, hypertension, history of stroke, history of myocardial infarction (MI), peripheral vascular disease (PVD), and hyperlipidemia (HLP). We analyzed our data to figure out how the patients are going to be clustered based on their risk factors.Results: For 566 patients who were studied, the mean age (SD) and BMI of patients were 59.1 (8.9) and 27.3 (4.1), respectively. The LCA model fit with two latent classes was statistically significant (G2 = 824.87, df = 21, p < 0.0001). The mean (SD) age of patients for Class I and Class II was 55.66 (8.55) and 60.87 (8.66), respectively. Class I (premature) was characterized by a high probability of smoking, alcohol consumption, opium addiction, and a history of MI (P < 0.05), and class II by a high probability of obesity, diabetes, and hypertension.Conclusion: Latent class analysis calculated two groups of severe CHD with distinct risk markers. The younger group, which is characterized by smoking, addiction, and the history of MI, can be regarded as representative of premature CHD.

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.

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