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Lifestyle and Socioeconomic Determinants of Multimorbidity Patterns among Mid-Aged Women: A Longitudinal Study.

ABSTRACT: Little is known about patterns of associative multimorbidity and their aetiology. We aimed to identify patterns of associative multimorbidity among mid-aged women and the lifestyle and socioeconomic factors associated with their development.Participants were from the Australian Longitudinal Study on Women's Health. We included 4896 women born 1946-51, without multimorbidity in 1998. We identified multimorbidity patterns at survey 6 (2010) using factor analysis, and related these patterns to baseline lifestyle and socioeconomic factors using logistic regression. We dichotomised factor scores and determined odds ratios (ORs) with 95% confidence intervals (CIs) for associations between characteristics and odds of a high versus low factor score.We identified five multimorbidity patterns: psychosomatic; musculoskeletal; cardiometabolic; cancer; and respiratory. Overweight and obesity were respectively associated with increased odds of having a high score for the musculoskeletal (adjusted ORs 1.45 [95% CI 1.23, 1.70] and 2.14 [95% CI 1.75, 2.60]) and cardiometabolic (adjusted ORs 1.53 [95% CI 1.31, 1.79] and 2.46 [95% CI 2.02, 2.98]) patterns. Physical inactivity was associated with increased odds of a high score for the psychosomatic, musculoskeletal and cancer patterns (adjusted ORs 1.41 [95% CI 1.13, 1.76]; 1.39 [95% CI 1.11, 1.74]; and 1.35 [95% CI 1.08, 1.69]). Smoking was associated with increased odds of a high score for the respiratory pattern. Education and ability to manage on income were associated with increased odds of a high score for the psychosomatic pattern (adjusted ORs 1.34 [95% CI 1.03, 1.75] and 1.73 [95% CI 1.37, 1.28], respectively) and musculoskeletal pattern (adjusted ORs 1.43 [95% CI 1.10, 1.87] and 1.38 [1.09, 1.75], respectively).Distinct multimorbidity patterns can be identified among mid-aged women. Social inequality, physical activity and BMI are risk factors common to multiple patterns and are appropriate targets for reducing the risk of specific multimorbidity groups in mid-life women.

SUBMITTER: Jackson CA

PROVIDER: S-EPMC4892503 | biostudies-other | 2016

REPOSITORIES: biostudies-other

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Project description:Background: Determining the incidence, progression, and patterns of multimorbidity are important for the prevention, management, and treatment of concurrence of multiple conditions. This study aimed to analyze major multimorbidity patterns and the association of the onset of a primary condition or combinations of a primary and a secondary condition with the progression to subsequent conditions. Methods: We included 53,867 participants aged 45-64 years from the 45 and Up Study who were free of 10 predefined chronic conditions at baseline (2006-2009). The incidence of multimorbidity (coexistence of ≥2, ≥3, and ≥4 conditions) was identified using the claims database until December 31, 2016. The primary, secondary, tertiary, and quaternary condition for each participant was defined according to its temporal order of onset. Results: During a mean 9-years follow-up, the cumulative incidence of primary, secondary, tertiary, and quaternary conditions was 49.6, 23.7, 9.0, and 2.9%, respectively. The time to develop a subsequent condition decreased with the accumulation of conditions (P < 0.0001). Two concurrent cardiometabolic disorders (CMDs, 30.4%) and CMDs clustered with musculoskeletal disorders (15.2%), mental disorders (13.5%), asthma (12.0%), or cancer (8.7%) were the five most common multimorbidity patterns. CMDs tended to occur prior to mental or musculoskeletal disorders but after the onset of cancers or asthma. Compared with all participants who developed cancer as a primary condition, individuals who experienced mental disorders/neurodegenerative disorders and a comorbidity as cardiovascular disease, hypertension, dyslipidemia, diabetes, asthma, or osteoarthritis were 3.36-10.87 times more likely to develop cancer as a tertiary condition. Individuals with neurodegenerative disorders and a comorbidity as hypertension, dyslipidemia, osteoarthritis, or asthma were 5.14-14.15 times more likely to develop mental disorders as a tertiary condition. Conclusions: A high incidence of multimorbidity in middle-aged adults was observed and CMDs were most commonly seen in multimorbidity patterns. There may be accelerated aging after a primary condition occurs. Our findings also reveal a potential preventative window to obviate the development of secondary or tertiary conditions.

Project description:BACKGROUND: Little is known about the patterns and influences of physical activity change in mid-aged adults. This study describes the design, sampling, data collection, and analytical plan of HABITAT, an innovative study of (i) physical activity change over five years (2007-2011) in adults aged 40-65 years at baseline, and (ii) the relative contribution of psychological variables, social support, neighborhood perceptions, area-level factors, and sociodemographic characteristics to physical activity change. METHODS/DESIGN: HABITAT is a longitudinal multi-level study. 1625 Census Collection Districts (CCDs) in Brisbane, Australia were ranked by their index of relative socioeconomic disadvantage score, categorized into deciles, and 20 CCDs from each decile were selected to provide 200 local areas for study inclusion. From each of the 200 CCDs, dwellings with individuals aged between 40-65 years (in 2007) were identified using electoral roll data, and approximately 85 people per CCD were selected to participate (N = 17,000). A comprehensive Geographic Information System (GIS) database has been compiled with area-level information on public transport networks, footpaths, topography, traffic volume, street lights, tree coverage, parks, public services, and recreational facilities Participants are mailed a questionnaire every two years (2007, 2009, 2011), with items assessing physical activity (general walking, moderate activity, vigorous activity, walking for transport, cycling for transport, recreational activities), sitting time, perceptions of neighborhood characteristics (traffic, pleasant surroundings, streets, footpaths, crime and safety, distance to recreational and business facilities), social support, social cohesion, activity-related cognitions (attitudes, efficacy, barriers, motivation), health, and sociodemographic characteristics. Analyses will use binary and multinomial logit regression models, as well as generalized linear latent growth models. DISCUSSION: HABITAT will provide unique information to improve our understanding of the determinants of physical activity, and to help identify "people" and "place" priority targets for public policy and health promotion aimed at increasing physical activity participation among mid-aged men and women.

Project description:BackgroundWhether a healthy lifestyle impacts longevity in the presence of multimorbidity is unclear. We investigated the associations between healthy lifestyle and life expectancy in people with and without multimorbidity.Methods and findingsA total of 480,940 middle-aged adults (median age of 58 years [range 38-73], 46% male, 95% white) were analysed in the UK Biobank; this longitudinal study collected data between 2006 and 2010, and participants were followed up until 2016. We extracted 36 chronic conditions and defined multimorbidity as 2 or more conditions. Four lifestyle factors, based on national guidelines, were used: leisure-time physical activity, smoking, diet, and alcohol consumption. A combined weighted score was developed and grouped participants into 4 categories: very unhealthy, unhealthy, healthy, and very healthy. Survival models were applied to predict life expectancy, adjusting for ethnicity, working status, deprivation, body mass index, and sedentary time. A total of 93,746 (19.5%) participants had multimorbidity. During a mean follow-up of 7 (range 2-9) years, 11,006 deaths occurred. At 45 years, in men with multimorbidity an unhealthy score was associated with a gain of 1.5 (95% confidence interval [CI] -0.3 to 3.3; P = 0.102) additional life years compared to very unhealthy score, though the association was not significant, whilst a healthy score was significantly associated with a gain of 4.5 (3.3 to 5.7; P < 0.001) life years and a very healthy score with 6.3 (5.0 to 7.7; P < 0.001) years. Corresponding estimates in women were 3.5 (95% CI 0.7 to 6.3; P = 0.016), 6.4 (4.8 to 7.9; P < 0.001), and 7.6 (6.0 to 9.2; P < 0.001) years. Results were consistent in those without multimorbidity and in several sensitivity analyses. For individual lifestyle factors, no current smoking was associated with the largest survival benefit. The main limitations were that we could not explore the consistency of our results using a more restrictive definition of multimorbidity including only cardiometabolic conditions, and participants were not representative of the UK as a whole.ConclusionsIn this analysis of data from the UK Biobank, we found that regardless of the presence of multimorbidity, engaging in a healthier lifestyle was associated with up to 6.3 years longer life for men and 7.6 years for women; however, not all lifestyle risk factors equally correlated with life expectancy, with smoking being significantly worse than others.

Project description:BackgroundEvidence on the association between multimorbidity and cognitive impairment in Chinese older population is limited. In addition, whether a healthy lifestyle can protect cognitive function in multimorbid older population remains unknown.MethodsA total of 6116 participants aged ≥ 65 years from the Chinese Longitudinal Healthy Longevity Survey were followed up repeatedly. The number of coexisting chronic diseases was used for assessing multimorbidity and cardiometabolic multimorbidity. Three lifestyle statuses (unhealthy, intermediate, and healthy) were defined based on a lifestyle score covering smoking, alcohol drinking, body mass index, outdoor activities, and dietary pattern. Cognitive impairment was defined as the Mini-Mental State Examination score < 24. A modified Poisson regression model with robust error variance was used to assess the associations between multimorbidity, healthy lifestyle, and cognitive impairment.ResultsDuring a median follow-up period of 5.8 years, 1621 incident cases of cognitive impairment were identified. The relative risk (RR) of cognitive impairment associated with heavy multimorbidity burden (≥ 3 conditions) was 1.39 (95% confidence interval: 1.22-1.59). This association declined with age, with RRs being 3.08 (1.78-5.31), 1.40 (1.04-1.87), and 1.19 (1.01-1.40) in subjects aged < 70 years, ≥ 70 and < 80 years, and ≥ 80 years, respectively (P for interaction = 0.001). Compared to unhealthy lifestyle, a healthy lifestyle was related to an approximately 40% reduced risk of cognitive impairment regardless of multimorbidity burden. Among the 5 lifestyle factors assessed, daily outdoor activities and a healthy dietary pattern showed convincing protective effects on cognitive function.ConclusionsThe relationship between multimorbidity and cognitive impairment is age-dependent but remains significant in the population aged 80 years or older. A healthy lifestyle may protect cognitive function regardless of the multimorbidity burden. These findings highlight the importance of targeting individuals with heavy multimorbidity burden and promoting a heathy lifestyle to prevent cognitive impairment in Chinese older population.

Project description:BackgroundChinese youth have become more sexually active over the years, yet their behaviours of contraceptive use are influenced by socioeconomic and lifestyle factors. This study aimed to investigate the socioeconomic and lifestyle determinants of contraceptive use among Chinese college students, and to investigate quantitatively their reasons for choosing different contraceptive methods.MethodsThe study used the data from a cross-sectional survey, which was conducted in 2015 among 17,517 students from 130 colleges and professional schools in mainland China. Chi-square tests were performed to test the differences in the awareness and uses of contraceptives between male and female students. Multivariable logistic regression models were used to analyse the associations between socioeconomic and lifestyle factors and contraceptive uses.ResultsCondoms (95%), oral contraceptives (91%) and emergency contraceptives (71%) were the most commonly known contraceptive methods among the sample of Chinese youth that were surveyed. Among male participants, high monthly expenditure (OR = 1.37, 95%CI: 1.07-1.75), light alcohol consumption (OR = 1.47, 95%CI: 1.03-2.11), and high sexual knowledge (OR = 1.96, 95%CI: 1.57-2.45) were positively associated with contraceptive uses, while tobacco use (OR = 0.47, 95%CI: 0.23-0.95) showed a negative association with contraceptive uses. Among female students, suburban residency (OR = 1.38, 95%CI: 1.03-1.83), high level of parental education (OR = 1.96, 95%CI: 1.19-3.22), moderate alcohol consumption (OR = 2.66, 95%CI: 1.05-6.77), and high sexual knowledge (OR = 1.50, 95%CI: 1.18-1.91) were positively associated with contraceptive uses, while tobacco use (OR = 0.60, 95%CI: 0.36-0.99) showed a negative association.ConclusionsA series of socioeconomic and lifestyle factors were associated with contraceptive choices among Chinese college students. Targeted sexual education programs are in demand to improve the awareness and the use of contraceptives in this population.

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Lifestyle and Socioeconomic Determinants of Multimorbidity Patterns among Mid-Aged Women: A Longitudinal Study.

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