Aging with multimorbidity: a systematic review of the literature

Multimorbidity, the coexistence of 2 or more chronic conditions, has become prevalent among older adults as mortality rates have declined and the population has aged. We examined population-based administrative claims data indicating specific health service delivery to nearly 31 million Medicare fee-for-service beneficiaries for 15 prevalent chronic conditions. A total of 67% had multimorbidity, which increased with age, from 50% for persons under age 65 years to 62% for those aged 65-74 years and 81.5% for those aged ≥85 years. A systematic review identified 16 other prevalence studies conducted in community samples that included older adults, with median prevalence of 63% and a mode of 67%. Prevalence differences between studies are probably due to methodological biases; no studies were comparable. Key methodological issues arise from elements of the case definition, including type and number of chronic conditions included, ascertainment methods, and source population. Standardized methods for measuring multimorbidity are needed to enable public health surveillance and prevention. Multimorbidity is associated with elevated risk of death, disability, poor functional status, poor quality of life, and adverse drug events. Additional research is needed to develop an understanding of causal pathways and to further develop and test potential clinical and population interventions targeting multimorbidity.

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Multimorbidity in Older Adults

PURPOSE We sought to identify and compare studies reporting the prevalence of multimorbidity and to suggest methodologic aspects to be considered in the conduct of such studies. METHODS We searched the literature for English- and French-language articles published between 1980 and September 2010 that described the prevalence of multimorbidity in the general population, in primary care, or both. We assessed quality of included studies with a modified version of the Strengthening the Reporting of Observational Studies in Epidemiology checklist. Results of individual prevalence studies were adjusted so that they could be compared graphically. RESULTS The final sample included 21 articles: 8 described studies conducted in primary care, 12 in the general population, and 1 in both. All articles were of good quality. The largest differences in prevalence of multimorbidity were observed at age 75 in both primary care (with prevalence ranging from 3.5% to 98.5% across studies) and the general population (with prevalence ranging from 13.1% to 71.8% across studies). Apart from differences in geographic settings, we identified differences in recruitment method and sample size (primary care: 980–60,857 patients; general population: 1,099–316,928 individuals), data collection, and the operational definition of multimorbidity used, including the number of diagnoses considered (primary care: 5 to all; general population: 7 to all). This last aspect seemed to be the most important factor in estimating prevalence. CONCLUSIONS Marked variation exists among studies of the prevalence of multimorbidity with respect to both methodology and findings. When undertaking such studies, investigators should carefully consider the specific diagnoses included and their number, as well as the operational definition of multimorbidity.

https://www.annfammed.org/content/annalsfm/10/2/142.full.pdf

A Systematic Review of Prevalence Studies on Multimorbidity: Toward a More Uniform Methodology

Introduction 
Multimorbidity is a major concern in primary care. Nevertheless, evidence of prevalence and patterns of multimorbidity, and their determinants, are scarce. The aim of this study is to systematically review studies of the prevalence, patterns and determinants of multimorbidity in primary care.


Methods 
Systematic review of literature published between 1961 and 2013 and indexed in Ovid (CINAHL, PsychINFO, Medline and Embase) and Web of Knowledge. Studies were selected according to eligibility criteria of addressing prevalence, determinants, and patterns of multimorbidity and using a pretested proforma in primary care. The quality and risk of bias were assessed using STROBE criteria. Two researchers assessed the eligibility of studies for inclusion (Kappa = 0.86).


Results 
We identified 39 eligible publications describing studies that included a total of 70,057,611 patients in 12 countries. The number of health conditions analysed per study ranged from 5 to 335, with multimorbidity prevalence ranging from 12.9% to 95.1%. All studies observed a significant positive association between multimorbidity and age (odds ratio [OR], 1.26 to 227.46), and lower socioeconomic status (OR, 1.20 to 1.91). Positive associations with female gender and mental disorders were also observed. The most frequent patterns of multimorbidity included osteoarthritis together with cardiovascular and/or metabolic conditions.


Conclusions 
Well-established determinants of multimorbidity include age, lower socioeconomic status and gender. The most prevalent conditions shape the patterns of multimorbidity. However, the limitations of the current evidence base means that further and better designed studies are needed to inform policy, research and clinical practice, with the goal of improving health-related quality of life for patients with multimorbidity. Standardization of the definition and assessment of multimorbidity is essential in order to better understand this phenomenon, and is a necessary immediate step.

/pdf/prevalence-determinants-and-patterns-of-multimorbidity-in-4gqa2ewt19.pdf

Prevalence, Determinants and Patterns of Multimorbidity in Primary Care: A Systematic Review of Observational Studies

Background In developed countries, primary health care increasingly involves the care of patients with multiple chronic conditions, referred to as multimorbidity. Aim To describe the epidemiology of multimorbidity and relationships between multimorbidity and primary care consultation rates and continuity of care. Design of study Retrospective cohort study. Setting Random sample of 99 997 people aged 18 years or over registered with 182 general practices in England contributing data to the General Practice Research Database. Method Multimorbidity was defined using two approaches: people with multiple chronic conditions included in the Quality and Outcomes Framework, and people identified using the Johns Hopkins University Adjusted Clinical Groups (ACG®) Case-Mix System. The determinants of multimorbidity (age, sex, area deprivation) and relationships with consultation rate and continuity of care were examined using regression models. Results Sixteen per cent of patients had more than one chronic condition included in the Quality and Outcomes Framework, but these people accounted for 32% of all consultations. Using the wider ACG list of conditions, 58% of people had multimorbidity and they accounted for 78% of consultations. Multimorbidity was strongly related to age and deprivation. People with multimorbidity had higher consultation rates and less continuity of care compared with people without multimorbidity. Conclusion Multimorbidity is common in the population and most consultations in primary care involve people with multimorbidity. These people are less likely to receive continuity of care, although they may be more likely to gain from it.

Epidemiology and impact of multimorbidity in primary care: a retrospective cohort study

Objectives To estimate the prevalence and patterns of multimorbidity in a sample of patients attending general practice, in the population who attended general practice in 2005, and in the Australian population. Design, setting and participants Secondary analyses of data from a study of prevalence of selected conditions (a substudy of the BEACH [Bettering the Evaluation And Care of Health] program); data were provided by 305 general practitioners for 9156 patients seen in July-November 2005, based on knowledge of the patient, patient self-report, and medical records. Listed conditions were classified according to the Cumulative Illness Rating Scale morbidity domains. Main outcome measures Prevalence of morbidity in each domain; prevalence of specific patterns of multimorbidity (defined as presence of morbidity in two or more domains). Results Prevalence of multimorbidity was estimated as 37.1% of surveyed patients, 29.0% of people who attended a GP in 2005, and 25.5% of the Australian population. Prevalence and complexity (number of domains present) increased with age: 83.2% of surveyed patients aged 75 years or older had multimorbidity, 58.2% had morbidity in three or more domains, and 33.4% in four or more. Prevalence of multimorbidity did not differ between the sexes. The most common morbidity combinations were arthritis/chronic back pain + vascular disease (15.0% of sample), a psychological problem + vascular disease (10.6%) and arthritis/chronic back pain + a psychological problem (10.6%). We estimate that 10.6% of people attending a GP in 2005 and 9.3% of the population have arthritis/chronic back pain + vascular disease (+/- other morbidity types studied), and this group accounted for about 15.2 million Medicare-claimed general practice encounters in 2005. Conclusions This study provides the first insight into prevalence and patterns of multimorbidity in Australia. Knowledge of the common combinations of multimorbidity may help in planning the health services needed in the future by an ageing population with an increasing burden of multimorbidity.

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Prevalence and patterns of multimorbidity in Australia.

https://opus.lib.uts.edu.au/bitstream/10453/18834/1/2010001956.pdf

Time Trade-Off Derived EQ-5D Weights for Australia

A case control analysis within an ongoing cohort study was used to examine differences between seroconverters and men who remained HIV-negative. The cases were interviewed within one to 13 months prior to their seroconversion. Their responses to a structured questionnaire were compared with those of HIV-negative controls drawn from the same time period and from the same longitudinal study, Sydney Men and Sexual Health. Data collected from both cases and controls included: demographic and contextual variables, knowledge of HIV transmission, sexual practices, drug and alcohol use and attitudinal factors. The aim was to compare the sexual behaviours, and the social and cultural contexts of such behaviours, of men prior to their HIV seroconversion with men who did not seroconvert. Twenty-three men had seroconverted within the cohort. Cases were identified by a positive HIV antibody test or self-report of positive HIV status following a previous negative HIV test. Three-hundred-and-sixty-nine controls were sel...

Cultures of sexual adventurism as markers of HIV seroconversion: A case control study in a cohort of Sydney gay men

Objectives: To investigate associations between gay men's optimism and sexual behaviour in the context of new HIV treatments. Methods: Cross-sectional surveys (using anonymous, self-completed questionnaires) were conducted in Sydney during February 1998 (n = 2200) and in Melbourne during January 1998 (n = 1891). Gay men were recruited at social and sex-on-premises venues, clinics and fair days/carnivals Results: In a multivariate analysis, unprotected anal intercourse with casual partners (UAIC) was associated with being recruited at a sex-on-premises venue (rather than a clinic or fair day/carnival), HIV positivity, having been tested for HIV less than 6 months ago (rather than over 2 years ago or never having been tested), and not having a regular partner. Over and above these factors, UAIC was associated with agreement with the statements 'An HIV-positive person who is on combination therapy is unlikely to transmit HIV' and 'I'm less worried about HIV infection than I used to be'. Conclusions: The data reveal a significant relationship between UAIC and certain aspects of optimism in the context of new HIV treatments. Whereas the direction of causality cannot be specified, there is a clear need for HIV and sexual health education programmes to clarify issues of viral load, new and drug resistant strains of HIV, and other infectious agents.

HIV treatments optimism and sexual behaviour among gay men in Sydney and Melbourne.

In this article, we describe the gmnl Stata command, which can be used to fit the generalized multinomial logit model and its special cases.

https://journals.sagepub.com/doi/pdf/10.1177/1536867X1301300213

Stephanie Knox

Papers

Prevalence and patterns of multimorbidity in Australia.

Time Trade-Off Derived EQ-5D Weights for Australia

Cultures of sexual adventurism as markers of HIV seroconversion: A case control study in a cohort of Sydney gay men

HIV treatments optimism and sexual behaviour among gay men in Sydney and Melbourne.

Fitting the generalized multinomial logit model in Stata