Dataset Information

Latent class analysis of multimorbidity patterns and associated outcomes in Spanish older adults: a prospective cohort study.

ABSTRACT: BACKGROUND:This study sought to identify multimorbidity patterns and determine the association between these latent classes with several outcomes, including health, functioning, disability, quality of life and use of services, at baseline and after 3 years of follow-up. METHODS:We analyzed data from a representative Spanish cohort of 3541 non-institutionalized people aged 50 years old and over. Measures were taken at baseline and after 3 years of follow-up. Latent Class Analysis (LCA) was conducted using eleven common chronic conditions. Generalized linear models were conducted to determine the adjusted association of multimorbidity latent classes with several outcomes. RESULTS:63.8% of participants were assigned to the "healthy" class, with minimum disease, 30% were classified under the "metabolic/stroke" class and 6% were assigned to the "cardiorespiratory/mental/arthritis" class. Significant cross-sectional associations were found between membership of both multimorbidity classes and poorer memory, quality of life, greater burden and more use of services. After 3 years of follow-up, the "metabolic/stroke" class was a significant predictor of lower levels of verbal fluency while the two multimorbidity classes predicted poor quality of life, problems in independent living, higher risk of hospitalization and greater use of health services. CONCLUSIONS:Common chronic conditions in older people cluster together in broad categories. These broad clusters are qualitatively distinct and are important predictors of several health and functioning outcomes. Future studies are needed to understand underlying mechanisms and common risk factors for patterns of multimorbidity and to propose more effective treatments.

SUBMITTER: Olaya B

PROVIDER: S-EPMC5563011 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Latent class analysis of multimorbidity patterns and associated outcomes in Spanish older adults: a prospective cohort study.

Olaya Beatriz B Moneta Maria Victoria MV Caballero Francisco Félix FF Tyrovolas Stefanos S Bayes Ivet I Ayuso-Mateos José Luis JL Haro Josep Maria JM

BMC geriatrics 20170818 1

<h4>Background</h4>This study sought to identify multimorbidity patterns and determine the association between these latent classes with several outcomes, including health, functioning, disability, quality of life and use of services, at baseline and after 3 years of follow-up.<h4>Methods</h4>We analyzed data from a representative Spanish cohort of 3541 non-institutionalized people aged 50 years old and over. Measures were taken at baseline and after 3 years of follow-up. Latent Class Analysis ( ...[more]

PMID: 28821233

Similar Datasets

Project description:BackgroundSocial relationships may be the key to successful aging among older adults. However, little is known about the variability of social relationships among community-dwelling older people. This study aimed to describe the patterns of social relationships and examine the differences in sociodemographic characteristics and mental and physical health status among these patterns.MethodsWe obtained the data from a questionnaire survey in 2017 for older adults aged 65 and above who lived in a suburban area in Japan. The Index of Social Interaction (ISI) was used to evaluate social relationships. The final sample comprised 964 people who were independently mobile and answered at least one item of the ISI. To clarify the patterns of social relationships, latent class analysis was performed with five subscales of ISI treated as indicator variables. Multinomial logistic regression was conducted to examine the factors associated with the patterns of social relationships.ResultsThe patterns of social relationships were classified into three classes: "Active" (73.6%), "Socially isolated" (14.7%), and "Less motivated" (11.7%). Persons who had depressive symptoms were more likely to be allocated to the "Socially isolated" (Odds Ratio [OR] 1.80, 95% Confidence Interval [CI] 1.13-2.86) or the "Less motivated" groups (OR 1.69, 95% CI 1.00-2.85) compared to the "Active" group. In addition, men (OR 1.72, 95% CI 1.07-2.76) and those living alone (OR 3.07, 95% CI 1.43-6.61) were more likely to be allocated to the "Socially isolated" group. Moreover, those who were dependent, according to the instrumental activities and daily living functions, were more likely to be assigned to the "Socially isolated" (OR 2.19, 95% CI 1.21-3.97) or "Less motivated" (OR 6.29, 95% CI 3.47-11.39) groups.ConclusionThis study revealed the patterns of social relationships in older adults and suggested that there may be variations of social relationships among community dwellers. The results also indicated the necessity of assessing individual patterns of social relationships and devising strategies for each pattern in public health practice.

Project description:ObjectiveIn the absence of adequate nationally-representative empirical evidence on multimorbidity, the existing healthcare delivery system is not adequately oriented to cater to the growing needs of the older adult population. Therefore, the present study identifies frequently occurring multimorbidity patterns among older adults in India. Further, the study examines the linkages between the identified patterns and socioeconomic, demographic, lifestyle and anthropometric correlates.DesignThe present findings rest on a large nationally-representative sample from a cross-sectional study.Setting and participantsThe study used data on 58 975 older adults (45 years and older) from the Longitudinal Ageing Study in India, 2017-2018.Primary and secondary outcome measuresThe study incorporated a list of 16 non-communicable diseases to identify commonly occurring patterns using latent class analysis. The study employed multinomial logistic regression models to assess the association between identified disease patterns with unit-level socioeconomic, demographic, lifestyle and anthropometric characteristics.ResultsThe present study demonstrates that older adults in the country can be segmented into six patterns: 'relatively healthy', 'hypertension', 'gastrointestinal disorders-hypertension-musculoskeletal disorders', 'musculoskeletal disorders-hypertension-asthma', 'metabolic disorders' and 'complex cardiometabolic disorders'. Additionally, socioeconomic, demographic, lifestyle and anthropometric factors are significantly associated with one or more identified disease patterns.ConclusionsThe identified classes 'hypertension', 'metabolic disorders' and 'complex cardiometabolic disorders' reflect three stages of cardiometabolic morbidity with hypertension as the first and 'complex cardiometabolic disorders' as the last stage of disease progression. This underscores the need for effective prevention strategies for high-risk hypertension group. Also, targeted interventions are essential to reduce the burden on the high-risk population and provide equitable health services at the community level.

Project description:PurposeMultimorbidity is commonly defined and measured using condition counts. The UK National Institute for Health Care Excellence Guidelines for Multimorbidity suggest that a medication-orientated approach could be used to identify those in need of a multimorbidity approach to management.ObjectivesTo compare the accuracy of medication-based and diagnosis-based multimorbidity measures at higher cut-points to identify older community-dwelling patients who are at risk of poorer health outcomes.DesignA secondary analysis of a prospective cohort study with a 2-year follow-up (2010-2012).Setting15 general practices in Ireland.Participants904 older community-dwelling patients.ExposureBaseline multimorbidity measurements based on both medication classes count (MCC) and chronic disease count (CDC).OutcomesMortality, self-reported health related quality of life, mental health and physical functioning at follow-up.AnalysisSensitivity, specificity, positive predictive values (PPV) and negative predictive values (NPV) adjusting for clustering by practice for each outcome using both definitions.ResultsOf the 904 baseline participants, 53 died during follow-up and 673 patients completed the follow-up questionnaire. At baseline, 223 patients had 3 or more chronic conditions and 89 patients were prescribed 10 or more medication classes. Sensitivity was low for both MCC and CDC measures for all outcomes. For specificity, MCC was better for all outcomes with estimates varying from 88.8% (95% CI 85.2% to 91.6%) for physical functioning to 90.9% (95% CI 86.2% to 94.1%) for self-reported health-related quality of life. There were no differences between MCC and CDC in terms of PPV and NPV for any outcomes.ConclusionsNeither measure demonstrated high sensitivity. However, MCC using a definition of 10 or more regular medication classes to define multimorbidity had higher specificity for predicting poorer health outcomes. While having limitations, this definition could be used for proactive identification of patients who may benefit from targeted clinical care.

Dataset Information

Latent class analysis of multimorbidity patterns and associated outcomes in Spanish older adults: a prospective cohort study.

Publications

Latent class analysis of multimorbidity patterns and associated outcomes in Spanish older adults: a prospective cohort study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets