Dataset Information

Age and gender differences in the prevalence and patterns of multimorbidity in the older population.

ABSTRACT:

Background

The coexistence of several chronic diseases in one same individual, known as multimorbidity, is an important challenge facing health care systems in developed countries. Recent studies have revealed the existence of multimorbidity patterns clustering systematically associated distinct clinical entities. We sought to describe age and gender differences in the prevalence and patterns of multimorbidity in men and women over 65 years.

Methods

Observational retrospective multicentre study based on diagnostic information gathered from electronic medical records of 19 primary care centres in Aragon and Catalonia. Multimorbidity patterns were identified through exploratory factor analysis. We performed a descriptive analysis of previously obtained patterns (i.e. cardiometabolic (CM), mechanical (MEC) and psychogeriatric (PG)) and the diseases included in the patterns stratifying by sex and age group.

Results

67.5% of the aged population suffered two or more chronic diseases. 32.2% of men and 45.3% of women were assigned to at least one specific pattern of multimorbidity, and 4.6% of men and 8% of women presented more than one pattern simultaneously. Among women over 65 years the most frequent pattern was the MEC pattern (33.3%), whereas among men it was the CM pattern (21.2%). While the prevalence of the CM and MEC patterns decreased with age, the PG pattern showed a higher prevalence in the older age groups.

Conclusions

Significant gender differences were observed in the prevalence of multimorbidity patterns, women showing a higher prevalence of the MEC and PG patterns, as well as a higher degree of pattern overlapping, probably due to a higher life expectancy and/or worse health. Future studies on multimorbidity patterns should take into account these differences and, therefore, the study of multimorbidity and its impact should be stratified by age and sex.

SUBMITTER: Abad-Diez JM

PROVIDER: S-EPMC4070347 | biostudies-literature | 2014 Jun

REPOSITORIES: biostudies-literature

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Publications

Age and gender differences in the prevalence and patterns of multimorbidity in the older population.

Abad-Díez José María JM Calderón-Larrañaga Amaia A Poncel-Falcó Antonio A Poblador-Plou Beatriz B Calderón-Meza José Manuel JM Sicras-Mainar Antoni A Clerencia-Sierra Mercedes M Prados-Torres Alexandra A

BMC geriatrics 20140617

<h4>Background</h4>The coexistence of several chronic diseases in one same individual, known as multimorbidity, is an important challenge facing health care systems in developed countries. Recent studies have revealed the existence of multimorbidity patterns clustering systematically associated distinct clinical entities. We sought to describe age and gender differences in the prevalence and patterns of multimorbidity in men and women over 65 years.<h4>Methods</h4>Observational retrospective mul ...[more]

PMID: 24934411

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Project description:BackgroundMultimorbidity among older adults, which is associated with added functional decline and higher health care utilization and mortality, has become increasingly common with the dramatic acceleration of ageing in China. The purpose of this study was to reveal age, sex, residence, and region- specific prevalence and patterns of multimorbidity among older adults in China.MethodsThis study is based on the 2018 Chinese Longitudinal Health Longevity Survey (CLHLS), the most recent edition of this national survey, and involved analysis of 15,275 participants aged 65 years and older. Multimorbidity was defined as an individual who has two or more chronic diseases or conditions and was divided into two types for analysis: ≥2 (MM2+) and ≥ 3 (MM3+). Fourteen chronic diseases or conditions surveyed were used to assess patterns of multimorbidity through association rule mining.ResultsAmong the 15,275 participants, the largest proportion (39.9%) was 90 years old and over, while the distribution of sex and residence is roughly the same. Overall, the prevalence of multimorbidity was 44.1% for MM2+ and 22.9% for MM3+. The most frequently occurring patterns were two or three combinations between hypertension, cardiovascular diseases and affective disorders. Cardiovascular diseases combined with diabetes or dyslipidemia showed the most predominant association in different age groups. Moreover, the prevalence of the hypertension +diabetes pattern decreased with age. The strongest associations were found for the clustering of hypertension + cardiovascular diseases + respiratory diseases in males, however, among females it was the cardiovascular diseases + diabetes cluster. Cardiovascular diseases + rheumatoid arthritis + visual impairment was observed in urban areas and hypertension + cardiovascular diseases + affective disorders in rural areas. The most distinctive association rule in Northern China was {cardiovascular diseases, hypertension, visual impairment} = > {diabetes}. Respiratory disease was more prevalent in combination with other systemic disorders in Western China, and affective disorders in Southern China.ConclusionsThe prevalence of multimorbidity among older Chinese was substantial, and patterns of multimorbidity varied by age, sex, residence, and region. Future efforts are needed to identify possible prevention strategies and guidelines that consider differences in demographic characteristics of multimorbid patients to promote health in older adults.

Project description:BackgroundGeneral practitioners often care for patients with several concurrent chronic medical conditions (multimorbidity). Recent data suggest that multimorbidity might be observed more often than isolated diseases in primary care. We explored the age- and gender-related prevalence of multimorbidity and compared these estimates to the prevalence estimates of other common specific diseases found in Swiss primary care.MethodsWe analyzed data from the Swiss FIRE (Family Medicine ICPC Research using Electronic Medical Record) project database, representing a total of 509,656 primary care encounters in 98,152 adult patients between January 1, 2009 and July 31, 2011. For each encounter, medical problems were encoded using the second version of the International Classification of primary Care (ICPC-2). We defined chronic health conditions using 147 pre-specified ICPC-2 codes and defined multimorbidity as 1) two or more chronic health conditions from different ICPC-2 rubrics, 2) two or more chronic health conditions from different ICPC-2 chapters, and 3) two or more medical specialties involved in patient care. We compared the prevalence estimates of multimorbidity defined by the three methodologies with the prevalence estimates of common diseases encountered in primary care.ResultsOverall, the prevalence estimates of multimorbidity were similar for the three different definitions (15% [95%CI 11-18%], 13% [95%CI 10-16%], and 14% [95%CI 11-17%], respectively), and were higher than the prevalence estimates of any specific chronic health condition (hypertension, uncomplicated 9% [95%CI 7-11%], back syndrome with and without radiating pain 6% [95%CI 5-7%], non-insulin dependent diabetes mellitus 3% [95%CI 3-4%]), and degenerative joint disease 3% [95%CI 2%-4%]). The prevalence estimates of multimorbidity rose more than 20-fold with age, from 2% (95%CI 1-2%) in those aged 20-29 years, to 38% (95%CI 31-44%) in those aged 80 or more years. The prevalence estimates of multimorbidity were similar for men and women (15% vs. 14%, p=0.288).ConclusionsIn primary care, prevalence estimates of multimorbidity are higher than those of isolated diseases. Among the elderly, more than one out of three patients suffer from multimorbidity. Management of multimorbidity is a principal concern in this vulnerable patient population.

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Project description:BackgroundTotal sedentary time varies across population groups with important health consequences. Patterns of sedentary time accumulation may vary and have differential health risks. The purpose of this study is to describe sedentary patterns of older adults living in retirement communities and illustrate gender and age differences in those patterns.MethodsBaseline accelerometer data from 307 men and women (mean age = 84±6 years) who wore ActiGraph GT3X+ accelerometers for ≥ 4 days as part of a physical activity intervention were classified into bouts of sedentary time (<100 counts per minute). Linear mixed models were used to account for intra-person and site-level clustering. Daily and hourly summaries were examined in mutually non-exclusive bouts of sedentary time that were 1+, 5+, 10+, 20+, 30+, 40+, 50+, 60+, 90+ and 120+ minutes in duration. Variations by time of day, age and gender were explored.ResultsMen accumulated more sedentary time than women in 1+, 5+, 10+, 20+, 30+, 40+, 50+ and 60+ minute bouts; the largest gender-differences were observed in 10+ and 20+ minute bouts. Age was positively associated with sedentary time, but only in bouts of 10+, 20+, 30+, and 40+ minutes. Women had more daily 1+ minute sedentary bouts than men (71.8 vs. 65.2), indicating they break up sedentary time more often. For men and women, a greater proportion of time was spent being sedentary during later hours of the day than earlier. Gender differences in intra-day sedentary time were observed during morning hours with women accumulating less sedentary time overall and having more 1+ minute bouts.ConclusionsPatterns identified using bouts of sedentary time revealed gender and age differences in the way in which sedentary time was accumulated by older adults in retirement communities. Awareness of these patterns can help interventionists better target sedentary time and may aid in the identification of health risks associated with sedentary behavior. Future studies should investigate the impact of patterns of sedentary time on healthy aging, disease, and mortality.

Dataset Information

Age and gender differences in the prevalence and patterns of multimorbidity in the older population.

Background

Methods

Results

Conclusions

Publications

Age and gender differences in the prevalence and patterns of multimorbidity in the older population.

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