A Latent Class Analysis of Multimorbidity and the Relationship to Socio-Demographic Factors and Health-Related Quality of Life. A National Population-Based Study of 162,283 Danish Adults.

To identify patterns of multimorbidity in the general population and examine how these patterns are related to socio-demographic factors and health-related quality of life.We used latent class analysis to identify subgroups with statistically distinct and clinically meaningful disease patterns in a nationally representative sample of Danish adults (N = 162,283) aged 16+ years. The analysis was based on 15 chronic diseases.Seven classes with different disease patterns were identified: a class with no or only a single chronic condition (59% of the population) labeled "1) Relatively Healthy" and six classes with a very high prevalence of multimorbidity labeled; "2) Hypertension" (14%); "3) Musculoskeletal Disorders" (10%); "4) Headache-Mental Disorders" (7%); "5) Asthma-Allergy" (6%); "6) Complex Cardiometabolic Disorders" (3%); and "7) Complex Respiratory Disorders" (2%). Female gender was associated with an increased likelihood of belonging to any of the six multimorbidity classes except for class 2 (Hypertension). Low educational attainment predicted membership of all of the multimorbidity classes except for class 5 (Asthma-Allergy). Marked differences in health-related quality of life between the seven latent classes were found. Poor health-related quality of life was highly associated with membership of class 6 (Complex Cardiometabolic Disorders) and class 7 (Complex Respiratory Disorders). Despite different disease patterns, these two classes had nearly identical profiles in relation to health-related quality of life.The results clearly support that diseases tend to compound and interact, which suggests that a differentiated public health and treatment approach towards multimorbidity is needed

Low Health Literacy and Mortality in Individuals with Cardiovascular Disease, Chronic Obstructive Pulmonary Disease, Diabetes, and Mental Illness: A 6-Year Population-Based Follow-Up Study

Background: The objective of the study was to examine the impact of health literacy on mortality in the general population and among individuals with cardiovascular disease (CVD), chronic obstructive pulmonary disease (COPD), diabetes, and mental illness. Methods: Data from a large Danish health survey (n = 29,473) from 2013 were linked with national mortality registry data to permit a 6-year follow-up. Results: Individuals reporting difficulties in understanding information about health, had higher risk of dying during follow-up (hazard rate (HR) 1.38 (95% CI 1.11–1.73)) compared with those without difficulties. Higher risk was also observed among people reporting CVD (HR 1.47 (95% CI 1.01–2.14)), diabetes (HR 1.91 (95% CI 1.13–3.22)) and mental illness (HR 2.18 (95% CI 1.25–3.81)), but not for individuals with COPD. Difficulties in actively engaging with healthcare providers was not associated with an increase in the risk of dying in the general population or in any of the four long-term condition groups. Conclusions: Aspects of health literacy predict a higher risk of dying during a 6-year follow-up period. Our study serves as a reminder to healthcare organizations to consider the health literacy responsiveness of their services in relation to diverse health literacy challenges and needs

Danish validation of the Multimorbidity Treatment Burden Questionnaire (MTBQ) and findings from a population health survey:a mixed-methods study

OBJECTIVE: To validate the Danish Multimorbidity Treatment Burden Questionnaire (MTBQ) and obtain a population-based evaluation of treatment burden. DESIGN: Mixed-methods. SETTING: Danish population-based survey. PARTICIPANTS: Translation by professional translators and an expert group. The scale was tested by 13 407 participants (aged ≥25 years) in treatment. MEASURES: The 10-item MTBQ was translated into Danish using forward-backward translation and used in a large population health survey. A global MTBQ score was calculated and factor analysis and Cronbach’s alpha assessed dimensional structure and internal consistency reliability, respectively. Spearman’s rank correlations between global MTBQ scores and scores of self-rated health, health-related quality of life and the number of long-term conditions, respectively, assessed construct validity. MTBQ scores were grouped into four categories (no, low, medium, high burden) to assess interpretability and population-based evaluation of treatment burden. RESULTS: The scale showed high internal consistency (α=0.87), positive skewness and large floor effects. Factor analysis supported a one-dimensional structure of the scale with a three-dimensional structure as a less parsimonious alternative. The MTBQ score was negatively associated with self-rated health (r(S)−0.45, p<0.0001) and health-related quality of life (r(S)−0.46/−0.51, p<0.0001), and positively associated with the number of long-term conditions (r(S) 0.26, p<0.0001) and perceived stress (r(S) 0.44, p<0.0001). Higher treatment burden was associated with young age, male sex, high educational level, unemployment, being permanently out of work, not living with a spouse/cohabitant, living with child(ren) and long-term conditions (eg, heart attack, stroke, diabetes and mental illness). CONCLUSION: The Danish MTBQ is a valid measure of treatment burden with good construct validity and high internal reliability. This is the first study to explore treatment burden at a population level and provides important evidence to policy makers and clinicians about sociodemographic groups at risk of higher treatment burden

Fit Statistics for Latent Class Analyses.

<p>Fit Statistics for Latent Class Analyses.</p

Self-Reported Health Status Stratified by Class.

<p>Self-Reported Health Status Stratified by Class.</p

Demographics and Multinomial Logistic Regression Results for Covariates by Latent Disease Class.

<p>Demographics and Multinomial Logistic Regression Results for Covariates by Latent Disease Class.</p

Class Proportions and Class-Specific Probabilities from Seven-Latent-Class Model of Chronic Conditions.

<p>Class Proportions and Class-Specific Probabilities from Seven-Latent-Class Model of Chronic Conditions.</p