Differences in Clinical Outcomes of Adults Referred to a Homeless Transitional Care Program Based on Multimorbid Health Profiles: A Latent Class Analysis

Profiles of Permanent Supportive Housing Residents Related to Their Housing Conditions, Service Use, and Associated Sociodemographic and Clinical Characteristics

As permanent supportive housing (PSH) is the main strategy promoted to reduce homelessness, understanding how PSH resident profiles may be differentiated is crucial to the optimization of PSH implementation - and a subject that hasn't been studied yet. This study identified PSH resident profiles based on their housing conditions and service use, associated with their sociodemographic and clinical characteristics. In 2020-2021, 308 PSH residents from Quebec (Canada) were interviewed, with K-means cluster analysis produced to identify profiles and subsequent analyses to compare profiles and PSH resident characteristics. Of the three profiles identified, Profiles 1 and 2 (70% of sample) showed moderate or poor housing, neighborhood, and health conditions, and moderate or high unmet care needs and service use. Besides their "moderate" conditions, Profile 1 residents (52%) reported being in PSH for more than two years and being less educated. With the "worst" conditions and high service use, Profile 2 (18%) included younger individuals, while Profile 3 (30%) showed the "best" conditions and integrated individuals with more protective determinants (e.g., few in foster care, homelessness at older age, more self-esteem), with a majority living in single-site PSH and reporting higher satisfaction with support and community-based services. Profiles 1 and 2 may be provided with more psychosocial, crisis, harm reduction, and empowerment interventions, and peer helper support. Profile 2 may benefit from more intensive and integrated care, and better housing conditions. Continuous PSH may be sustained for Profile 3, with regular monitoring of service satisfaction and met needs.

Opportunities for Nurses to Decrease the Stigma Associated with Housing Instability and Homelessness

The number of people experiencing homelessness (PEH) in the United States has increased in the past 5 years. PEH have a higher disease burden and early mortality compared to people who are housed. Stigma adds to the burden of disease and disease management for PEH. In this article the authors review stigma, define housing and homelessness, describe the health and health care disparities PEH experience, and using the socio-ecological model as a framework, offer opportunities for nurses to intervene in efforts to decrease the stigma that PEH and housing instability encounter to improve health outcomes.

Risk profiles of adults with heavy alcohol use: Drinking patterns, behavioral and metabolic factors, health problems, and racial and ethnic disparities

BACKGROUND

Heavy alcohol use is a growing risk factor for chronic disease, yet little is known about its co-occurrence with other risk factors and health problems. This study aimed to identify risk profiles of adults with heavy alcohol use and examined potential disparities by race and ethnicity.

METHODS

This cross-sectional study included 211,333 adults with heavy alcohol use (in excess of daily or weekly limits recommended by National Institute on Alcohol Abuse and Alcoholism) between June 1, 2013 and December 31, 2014 in Kaiser Permanente Northern California. Latent class analysis was used to examine how heavy drinking patterns clustered with other behavioral and metabolic risk factors and health problems to form risk profiles. Multinomial logistic regression models were fit to examine associations between race, ethnicity, and risk profiles.

RESULTS

A 5-class model was selected as best fitting the data and representing clinically meaningful risk profiles: (1) "heavy daily drinking and lower health risks" (DAILY, 44.3%); (2) "substance use disorder and mental health disorder" (SUD/MH, 2.3%); (3) "heavy weekly drinking and lower health risks" (WEEKLY, 19.6%); (4) "heavy daily drinking and more health risks" (DAILY-R, 18.5%); (5) "heavy weekly drinking and more health risks" (WEEKLY-R, 15.3%). American Indian or Alaska Native (AIAN) and Black patients had higher odds than White patients of being in the SUD/MH, DAILY-R, and WEEKLY-R profiles than the DAILY profile. AIAN, Black, and Latino/Hispanic patients had higher odds than White patients of being in the SUD/MH, DAILY-R, and WEEKLY-R profiles rather than the WEEKLY profile.

CONCLUSIONS

AIAN, Black, and Latino/Hispanic patients with self-reported heavy drinking were more likely to be in risk profiles with greater alcohol consumption, more health risks, and higher morbidity. Targeted, culturally appropriate interventions for heavy alcohol use that may address other modifiable risk factors are needed to work towards health equity.

Social determinants of multimorbidity patterns: A systematic review

Social determinants of multimorbidity are poorly understood in clinical practice. This review aims to characterize the different multimorbidity patterns described in the literature while identifying the social and behavioral determinants that may affect their emergence and subsequent evolution. We searched PubMed, Embase, Scopus, Web of Science, Ovid MEDLINE, CINAHL Complete, PsycINFO and Google Scholar. In total, 97 studies were chosen from the 48,044 identified. Cardiometabolic, musculoskeletal, mental, and respiratory patterns were the most prevalent. Cardiometabolic multimorbidity profiles were common among men with low socioeconomic status, while musculoskeletal, mental and complex patterns were found to be more prevalent among women. Alcohol consumption and smoking increased the risk of multimorbidity, especially in men. While the association of multimorbidity with lower socioeconomic status is evident, patterns of mild multimorbidity, mental and respiratory related to middle and high socioeconomic status are also observed. The findings of the present review point to the need for further studies addressing the impact of multimorbidity and its social determinants in population groups where this problem remains invisible (e.g., women, children, adolescents and young adults, ethnic groups, disabled population, older people living alone and/or with few social relations), as well as further work with more heterogeneous samples (i.e., not only focusing on older people) and using more robust methodologies for better classification and subsequent understanding of multimorbidity patterns. Besides, more studies focusing on the social determinants of multimorbidity and its inequalities are urgently needed in low- and middle-income countries, where this problem is currently understudied.