A Latent Class Analysis of Risk Factors for Acquiring HIV Among Men Who Have Sex with Men: Implications for Implementing Pre-Exposure Prophylaxis Programs

Background New innovative technologies, such as mobile apps, have been developed to increase pre-exposure prophylaxis (PrEP) adherence and the use of log sex diaries. The contiguity of mobile apps reduces the recall bias that generally affects reported condom and PrEP use. However, none of the currently used mobile apps were designed for event-driven PrEP users, and few studies have demonstrated the potential usage of sex diary data to facilitate the understanding of the different HIV risks among heterogeneous profiles of sex diaries and PrEP use. Objective We aim to discriminate the heterogeneous profiles of sex events and PrEP use and examine the risk of condomless anal sex among different types of sex events. Methods We recruited 35 adult men who have sex with men from two medical centers in Taiwan since May 2020 and followed up for four months. Participants were on PrEP or willing to take PrEP. They were asked to log their sex events, PrEP use, and dosing regimens on a mobile app to improve their PrEP adherence. Latent class analysis was used to distinguish profiles of sex events and PrEP use. Indicators included correct intake of PrEP for each sex event, participants’ sexual positioning, partner’s HIV status, and age. Results A total of 551 sex events were classified into three classes by latent class analysis: PrEP nonadherent flip-flopping (234/551, 42%), PrEP imperfect-adherent power bottoming (284/551, 52%), and PrEP adherent serodiscordant topping (33/551, 6%). “PrEP nonadherent flip-flopping” sex events were more likely to involve condomless anal sex than “PrEP imperfect-adherent power bottoming” (OR 1.83, 95% CI 1.03-3.25) after considering random intercepts for individuals, and this class needed to increase their PrEP adherence and use of condoms. “PrEP imperfect-adherent power bottoming” realized their own risk and packaged PrEP with condoms to protect themselves. Up to 99% (32/33) of sex events in “PrEP adherent serodiscordant topping” were protected by PrEP, but all of the sex events in this group were condomless. Conclusions Using the sex diary data could advance the capacity to identify high-risk groups. HIV prevention strategy should be more flexible and combine PrEP with condom use for future HIV prevention.

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Condomless Anal Sex Associated With Heterogeneous Profiles Of HIV Pre-Exposure Prophylaxis Use and Sexual Activities Among Men Who Have Sex With Men: A Latent Class Analysis Using Sex Diary Data on a Mobile App (Preprint)

10.2196/preprints.33877 ◽

2021 ◽

Author(s):

Yi-Fang Yu ◽

Huei-Jiuan Wu ◽

Stephane Wen-Wei Ku ◽

Po-Hsien Huang ◽

Chia-Wen Li ◽

...

Keyword(s):

Latent Class Analysis ◽

Latent Class ◽

Mobile Apps ◽

Mobile App ◽

Class Analysis ◽

Anal Sex ◽

Condomless Anal Sex ◽

Diary Data ◽

Sex With Men ◽

Exposure Prophylaxis

BACKGROUND New innovative technologies, such as mobile apps, have been developed to increase pre-exposure prophylaxis (PrEP) adherence and the use of log sex diaries. The contiguity of mobile apps reduces the recall bias that generally affects reported condom and PrEP use. However, none of the currently used mobile apps were designed for event-driven PrEP users, and few studies have demonstrated the potential usage of sex diary data to facilitate the understanding of the different HIV risks among heterogeneous profiles of sex diaries and PrEP use. OBJECTIVE We aim to discriminate the heterogeneous profiles of sex events and PrEP use and examine the risk of condomless anal sex among different types of sex events. METHODS We recruited 35 adult men who have sex with men from two medical centers in Taiwan since May 2020 and followed up for four months. Participants were on PrEP or willing to take PrEP. They were asked to log their sex events, PrEP use, and dosing regimens on a mobile app to improve their PrEP adherence. Latent class analysis was used to distinguish profiles of sex events and PrEP use. Indicators included correct intake of PrEP for each sex event, participants’ sexual positioning, partner’s HIV status, and age. RESULTS A total of 551 sex events were classified into three classes by latent class analysis: PrEP nonadherent flip-flopping (234/551, 42%), PrEP imperfect-adherent power bottoming (284/551, 52%), and PrEP adherent serodiscordant topping (33/551, 6%). “PrEP nonadherent flip-flopping” sex events were more likely to involve condomless anal sex than “PrEP imperfect-adherent power bottoming” (OR 1.83, 95% CI 1.03-3.25) after considering random intercepts for individuals, and this class needed to increase their PrEP adherence and use of condoms. “PrEP imperfect-adherent power bottoming” realized their own risk and packaged PrEP with condoms to protect themselves. Up to 99% (32/33) of sex events in “PrEP adherent serodiscordant topping” were protected by PrEP, but all of the sex events in this group were condomless. CONCLUSIONS Using the sex diary data could advance the capacity to identify high-risk groups. HIV prevention strategy should be more flexible and combine PrEP with condom use for future HIV prevention.

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Association between childhood sexual abuse and patterns of HIV risky sexual behaviors among men who have sex with men in China: A latent class analysis

Child Abuse & Neglect ◽

10.1016/j.chiabu.2021.105164 ◽

2021 ◽

Vol 120 ◽

pp. 105164

Author(s):

Xiaoyan Li ◽

Menglan Guo ◽

Wei Wang ◽

Liqing Wei ◽

Chenchang Xiao ◽

...

Keyword(s):

Sexual Abuse ◽

Childhood Sexual Abuse ◽

Latent Class Analysis ◽

Sexual Behaviors ◽

Latent Class ◽

Risky Sexual Behaviors ◽

Class Analysis ◽

Sex With Men

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

Public Health ◽

10.1016/j.puhe.2021.07.031 ◽

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

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

Journal of Affective Disorders ◽

10.1016/j.jad.2018.09.053 ◽

2019 ◽

Vol 243 ◽

pp. 360-365 ◽

Cited By ~ 1

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

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

Frontiers in Cardiovascular Medicine ◽

10.3389/fcvm.2021.707070 ◽

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.

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

Armed Forces & Society ◽

10.1177/0095327x211046976 ◽

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.

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Patterns of comorbidities in hospitalised cancer survivors for palliative care and associated in-hospital mortality risk: A latent class analysis of a statewide all-inclusive inpatient data

Palliative Medicine ◽

10.1177/0269216319860705 ◽

2019 ◽

Vol 33 (10) ◽

pp. 1272-1281 ◽

Cited By ~ 2

Author(s):

Lan Luo ◽

Wei Du ◽

Shanley Chong ◽

Huibo Ji ◽

Nicholas Glasgow

Keyword(s):

Risk Factors ◽

Palliative Care ◽

Hospital Mortality ◽

Cancer Survivors ◽

Latent Class Analysis ◽

Cancer Patients ◽

Mortality Risk ◽

Latent Class ◽

Class Analysis ◽

Hospital Deaths

Background: At the end of life, cancer survivors often experience exacerbations of complex comorbidities requiring acute hospital care. Few studies consider comorbidity patterns in cancer survivors receiving palliative care. Aim: To identify patterns of comorbidities in cancer patients receiving palliative care and factors associated with in-hospital mortality risk. Design, Setting/Participants: New South Wales Admitted Patient Data Collection data were used for this retrospective cohort study with 47,265 cancer patients receiving palliative care during the period financial year 2001–2013. A latent class analysis was used to identify complex comorbidity patterns. A regression mixture model was used to identify risk factors in relation to in-hospital mortality in different latent classes. Results: Five comorbidity patterns were identified: ‘multiple comorbidities and symptoms’ (comprising 9.1% of the study population), ‘more symptoms’ (27.1%), ‘few comorbidities’ (39.4%), ‘genitourinary and infection’ (8.7%), and ‘circulatory and endocrine’ (15.6%). In-hospital mortality was the highest for ‘few comorbidities’ group and the lowest for ‘more symptoms’ group. Severe comorbidities were associated with elevated mortality in patients from ‘multiple comorbidities and symptoms’, ‘more symptoms’, and ‘genitourinary and infection’ groups. Intensive care was associated with a 37% increased risk of in-hospital deaths in those presenting with more ‘multiple comorbidities and symptoms’, but with a 22% risk reduction in those presenting with ‘more symptoms’. Conclusion: Identification of comorbidity patterns and risk factors for in-hospital deaths in cancer patients provides an avenue to further develop appropriate palliative care strategies aimed at improving outcomes in cancer survivors.

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