Dataset Information

A Multidimensional Latent Class Analysis of Harmful Alcohol Use Among Older Adults: Subtypes Within the Swedish Addiction Severity Index Registry.

ABSTRACT: OBJECTIVES:The present study aimed to identify multidimensional typologies of harmful alcohol use based on the Swedish Addiction Severity Index (ASI) assessment data on individuals aged 50 years and above. METHODS:Latent class analysis examined 11 indicators from ASI data on 1747 individuals (men?=?1255, women?=?492) who reported they were troubled by alcohol problem at least one day in the past 30 days before their assessment. The discriminative validity of the classes was assessed by comparing other measures of individual characteristics and problem severity of other ASI dimensions. RESULTS:Five subtypes of harmful alcohol use were identified. Two classes with alcohol problems varying in psychosocial functioning, age composition and ages of onset of both regular and heavy drinking. Two with psychiatric comorbidity but varying in violence, criminality, gender composition and ages of onset of regular and heavy drinking. One with high prevalence of concurrent use of other substances, psychiatric, legal, and employment problems. CONCLUSIONS:The analysis identified, in a national sample, heterogeneous risk groups of older adults with harmful alcohol use. These findings suggest a need for healthcare providers to assess older adults not only for their substance use but also for associated problems and needs. Given these findings, the Addiction Severity Index is a valuable assessment tool for older adults with harmful alcohol use.

SUBMITTER: Jemberie WB

PROVIDER: S-EPMC7413671 | biostudies-literature | 2020 Jul/Aug

REPOSITORIES: biostudies-literature

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A Multidimensional Latent Class Analysis of Harmful Alcohol Use Among Older Adults: Subtypes Within the Swedish Addiction Severity Index Registry.

Jemberie Wossenseged Birhane WB Padyab Mojgan M Snellman Fredrik F Lundgren Lena L

Journal of addiction medicine 20200701 4

<h4>Objectives</h4>The present study aimed to identify multidimensional typologies of harmful alcohol use based on the Swedish Addiction Severity Index (ASI) assessment data on individuals aged 50 years and above.<h4>Methods</h4>Latent class analysis examined 11 indicators from ASI data on 1747 individuals (men = 1255, women = 492) who reported they were troubled by alcohol problem at least one day in the past 30 days before their assessment. The discriminative validity of the classes was assess ...[more]

PMID: 32097236

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Project description:BackgroundStructural racism is a complex system of inequities working in tandem to cause poor health for communities of color, especially for Black people. However, the multidimensional nature of structural racism is not captured by existing measures used by population health scholars to study health inequities. Multidimensional measures can be made using complex analytical techniques. Whether or not the multidimensional measure of structural racism provides more insight than the existing unidimensional measures is unknown.MethodsWe derived measures of Black-White residential segregation, inequities in education, employment, income, and homeownership, evaluated for 2,338 Public Use Microdata Areas (PUMAs) in the United States (US), and consolidated them into a multidimensional measure of structural racism using a latent class model. We compared the median COVID-19 vaccination rates observed across 54 New York City (NYC) PUMAs by levels (high/low) of structural racism and the multidimensional class using the Kruskal-Wallis test. This study was conducted in March 2021.FindingsOur latent class model identified three structural racism classes in the US, all of which can be found in NYC. We observed intricate interactions between the five dimensions of structural racism of interest that cannot be simply classified as "high" (i.e., high on all dimensions of structural racism), "medium," or "low." Compared to Class A PUMAs with the median rate of two-dose completion of 6·9%, significantly lower rates were observed for Class B PUMAs (5·5%, p = 0·04) and Class C PUMAs (5·2%, p = 0·01). When the vaccination rates were evaluated based on each dimension of structural racism, significant differences were observed between PUMAs with high and low Black-White income inequity only (7·2% vs. 5·3%, p = 0·001).InterpretationOur analysis suggests that measuring structural racism as a multidimensional determinant of health provides additional insight into the mechanisms underlying population health inequity vis-à-vis using multiple unidimensional measures without capturing their joint effects.FundingThis project is funded by the Robert J. Jones Urban Research and Outreach-Engagement Center, University of Minnesota. Additional support is provided by the Minnesota Population Center, which is funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (Grant P2C HD041023).

Project description:Heterogeneity of injury severity among children with traumatic brain injury (TBI) classified by the Glasgow Coma Scale (GCS) makes comparisons across research cohorts, enrollment in clinical trials, and clinical predictions of outcomes difficult. The present study uses latent class analysis (LCA) to distinguish severity subgroups from a prospective cohort of 433 children 2.5-15 years of age with TBI who were recruited from two level 1 pediatric trauma centers. Indicator variables available within 48 h post-injury including emergency department (ED) GCS, hospital motor GCS, Abbreviated Injury Score (AIS), Rotterdam Score, hypotension in the ED, and pre-hospital loss of consciousness, intubation, seizures, and sedation were evaluated to define subgroups. To understand whether latent class subgroups were predictive of clinically meaningful outcomes, the Pediatric Injury Functional Outcome Scale (PIFOS) at 6 and 12 months, and the Behavior Rating Inventory of Executive Function at 12 months, were compared across subgroups. Then, outcomes were examined by GCS (primary) and AIS (secondary) classification alone to assess whether LCA provided improved outcome prediction. LCA identified four distinct increasing severity subgroups (1-4). Unlike GCS classification, mean outcome differences on PIFOS at 6 months showed decreasing function across classes. PIFOS differences relative to the lowest latent class (LC1) were: LC2 2.27 (0.83, 3.72), LC3 3.99 (1.88, 6.10), and LC4 11.2 (7.04, 15.4). Differences in 12 month outcomes were seen between the most and least severely injured groups. Differences in outcomes in relation to AIS were restricted to the most and less severely injured at both time points. This study distinguished four latent classes that are clinically meaningful, distinguished a more homogenous severe injury group, and separated children by 6-month functional outcomes better than GCS alone. Systematic reporting of these variables would allow comparisons across research cohorts, potentially improve clinical predictions, and increase sensitivity to treatment effects in clinical trials.

Dataset Information

A Multidimensional Latent Class Analysis of Harmful Alcohol Use Among Older Adults: Subtypes Within the Swedish Addiction Severity Index Registry.

Publications

A Multidimensional Latent Class Analysis of Harmful Alcohol Use Among Older Adults: Subtypes Within the Swedish Addiction Severity Index Registry.

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