Associating modifiable lifestyle factors with multimorbidity in community dwelling individuals from mainland China

Abstract

Aims Lifestyle factors have been well-established as essential targets for fighting individual chronic diseases, but little research has concentrated on multimorbidity from the perspective of multiple lifestyle factors in the Chinese population. Thus, this study aimed to explore the associations of lifestyle factors with the occurrence of multimorbidity. Methods and results Cross-sectional data retrieved from the China Health and Retirement Longitudinal Study were used for analysis. Multimorbidity was calculated on a simple count of self-reported chronic conditions. Lifestyle factors included sleep duration, physical activity, alcohol intake, smoking status, and body mass index. Logistic regression analysis was used to examine the independent and accumulating effects of lifestyle factors on multimorbidity. Latent class analysis was performed to explore the lifestyle patterns. Six thousand, five hundred, and ninety-one valid subjects were included for analysis. Overall, the community dweller’s median number of chronic conditions was 1 (range 1–11) and median number of high-risk lifestyle factors was 2 (range 0–5). All lifestyle factors were associated with the occurrence of multimorbidity but varied between genders. We also identified that participants who accumulated more unhealthy lifestyle factors having a higher likelihood of multimorbidity. ‘Physical activity and weight’, ‘smoke and drink’, and ‘sleep and weight’ dominated high-risk lifestyles were the most common lifestyle patterns. Conclusion This study revealed the associations of unhealthy lifestyle factors and their accumulating effect with multimorbidity in Chinese community dwellers. Three common lifestyle patterns indicated that a holistic approach focused on engaging and changing multiple modifiable lifestyle behaviours within an individual might be more effective in managing multimorbidity.

Physical Activity and Multimorbidity Among Community-Dwelling Older Adults: A Systematic Review With Meta-Analysis

“…Table 1 shows the main results and characteristics of the samples. Of the 15 studies included, two were published until 2014, 31,32 and 13 were published from 2014 7,[33][34][35][36][37][38][39][40][41][42][43][44] . Eight studies presented a cross-sectional design, [31][32][33]35,[40][41][42][43] and seven were longitudinal.…”

“…Of the 15 studies included, two were published until 2014, 31,32 and 13 were published from 2014 7,[33][34][35][36][37][38][39][40][41][42][43][44] . Eight studies presented a cross-sectional design, [31][32][33]35,[40][41][42][43] and seven were longitudinal. 7,34,[36][37][38][39]44 Five studies used samples of less than 2000 participants, 31,32,38,39,41 six evaluated from 2001 to 10 000 participants, 33,34,36,37,42,44 and four studies had a sample size of more than 10 000 individuals.…”

“…Eight studies presented a cross-sectional design, [31][32][33]35,[40][41][42][43] and seven were longitudinal. 7,34,[36][37][38][39]44 Five studies used samples of less than 2000 participants, 31,32,38,39,41 six evaluated from 2001 to 10 000 participants, 33,34,36,37,42,44 and four studies had a sample size of more than 10 000 individuals. 7,35,40,43 Of the 15 studies included, two were based on the same study, English Longitudinal Study of Aging (ELSA), with different follow ups.…”

Urban–Rural Differences in Patterns and Associated Factors of Multimorbidity Among Older Adults in China: A Cross-Sectional Study Based on Apriori Algorithm and Multinomial Logistic Regression

“…A previous study showed that the burden of multimorbidity is mainly caused by a series of associated factors (28). Wellestablished factors associated with multimorbidity are age, gender, body mass index (BMI), and education level (29,30). However, the previous studies on the associated factors of multimorbidity among older adults mostly focused on the individual-level factors.…”

Body Constitution and Unhealthy Lifestyles in a Primary Care Population at High Cardiovascular Risk: New Insights for Health Management

“… 29 Personalised support and access to stop smoking, physical activity and alcohol reduction services are actively available in the National Health Service Health Check to support early diagnosis and disease management. 28 Compared to the US National Health Interview Survey (NHIS), 30 the Dutch Monitoring Project on Risk Factors for Chronic Diseases (MORGEN), 31 and the China Health and Retirement Longitudinal Study (CHARLS), 32 our study population reported a relatively lower prevalence of smoking, drinking, and physical inactivity. This, however, implies that the use of body constitutions, when extended to the general population at large, may carry greater public health implications for informing unhealthy lifestyles.…”