Abstract
Background
Unhealthy lifestyles and multimorbidity are major determinants of adverse health outcomes in later life. However, the potential benefits of adhering to a healthy lifestyle among older people with multimorbidity remain unclear. This study aimed to evaluate the independent and joint associations of healthy lifestyle, multimorbidity, and all-cause mortality risk.
Methods
We used data from the 2005–2018 waves of the Chinese Longitudinal Healthy Longevity Survey (CLHLS), including participants aged 60 years and older. Healthy Lifestyle Index (HLI) was constructed based on five modifiable factors: body mass index (BMI), smoking status, alcohol consumption, physical activity, and dietary intake. Multimorbidity was defined as the presence of two or more chronic conditions. Cox proportional hazards regression was employed to assess the associations between healthy lifestyle, multimorbidity, and all-cause mortality, with stratified analyses by age, sex, and urban–rural residence.
Results
A total of 21,418 participants were included, with 15,113 deaths recorded over a median follow-up of 3.44 years (IQR 1.90–6.77). The age- and sex-adjusted mortality rate was 149.19 per 1,000 person-years (95% CI: 147.90–150.49). Among the lifestyle factors, physical activity showed the strongest association with reduced mortality (HRd=0.68, 95% CI 0.65–0.71; p < 0.001). Participants with a healthy lifestyle had significantly lower all-cause mortality risk compared to those with an unhealthy lifestyle (HRd=0.65, 95% CI 0.62–0.69; p < 0.001). Notably, the protective effect was more pronounced among those with multimorbidity (HRc=0.58, 95% CI 0.52–0.65; p < 0.001) than those without (HRd=0.65, 95% CI 0.62–0.69; p < 0.001).
Conclusions
Adherence to a healthy lifestyle is associated with a significantly lower risk of all-cause mortality in older people, especially among those with multimorbidity.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12877-025-06246-4.
Keywords: Healthy lifestyle, Multimorbidity, All-Cause mortality, Cox proportional hazard regression
Introduction
Population aging poses a significant global public health challenge [1], with particularly profound implications for China [2]. According to the Seventh National Population Census, China has officially entered an aging society, with 264.02 million individuals aged 60 years and older, accounting for 18.7% of the total population [3].
China’s rapidly rapidly aging demographic has led to a growing prevalence of chronic diseases, with the coexistence of two or more conditions becoming increasingly widespread [4, 5], thereby exacerbating the national disease burden. Evidence consistently shows that the prevalence of multimorbidity increases with age [6], placing older people at heightened risk [7]. A meta-analysis estimated the global prevalence of multimorbidity to range from 15.3–93.1% [8], with the rate among Chinese older people reaching 49.4% [9]. Multimorbidity is associated with a range of adverse health outcomes, including depression [10, 11], frailty [12], functional decline in activities of daily living [13, 14], and elevated all-cause mortality [15, 16], all of which severely impact both quality of life and healthcare utilization [17–19]. As multimorbidity becomes more common, promoting healthy aging has emerged as a central focus of public health efforts.
Growing evidence from multiple countries indicates that adherence to a healthy lifestyle is linked to improved health outcomes and reduced mortality risk in older populations [20, 21]. However, standardized measures for assessing healthy lifestyle behaviors remain underdeveloped. Currently, most studies adopt one of two approaches to calculate healthy lifestyle scores: (1) using four indicators—smoking, alcohol consumption, physical activity, and dietary intake [20]; (2) including a fifth indicator—body mass index (BMI)—in recognition of obesity as a key public health issue [22–24]. In China, the prevalence of overweight and obesity has increased two- to three-fold since the 1980s. Research has shown that both high and abnormally low BMI are associated with increased all-cause mortality [25, 26]. Therefore, in this study, we construct a comprehensive Healthy Lifestyle Index (HLI) based on five modifiable factors: BMI, smoking, alcohol consumption, physical activity, and dietary intake.
Extensive research has investigated the associations between healthy lifestyle and all-cause mortality, as well as between multimorbidity and all-cause mortality. Numerous studies have also examined the combined effects of individual lifestyle factors—such as physical activity and body mass index (BMI)—with multimorbidity to evaluate their joint influence on mortality risk. For example, Chudasama et al., using data from the UK Biobank, found that moderate physical activity is associated with increased life expectancy even among individuals with multimorbidity [27]. Similarly, a study by Feng et al. among Thai adults demonstrated that engagement in healthy behaviors significantly reduces mortality risk, particularly for those with multimorbidity [28]. However, relatively few studies have focused on the development of a comprehensive Healthy Lifestyle Index (HLI) and its joint impact with multimorbidity on all-cause mortality among older people. Consequently, the present study aims to examine the independent and joint associations of healthy lifestyle and multimorbidity with all-cause mortality among individuals aged 60 years and older, using data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) collected between 2005 and 2018.
Methods
Study design and participants
This study was based on data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS), a nationwide longitudinal study on factors influencing health in older adults, conducted by the Center for Healthy Aging and Development Research at Peking University. The CLHLS employed a multi-stage stratified sampling design, covering 23 provinces, municipalities, and autonomous regions across China. Since its inception in 1998, the survey has primarily targeted adults aged 80 years and older, and since 2002, it has been expanded to include younger older adults (aged 65–79) as well as their middle-aged children (aged 35–64). The CLHLS dataset is distinguished by its comprehensive household and individual-level information, robust sample size, extended follow-up periods, scientific sampling structure, and strong national representativeness.
As height measurements (needed for BMI calculation) and household income data became available beginning in 2005, this study utilized data from the 2005, 2008, 2011, 2014, and 2018 waves to investigate the associations between healthy lifestyle, multimorbidity, and all-cause mortality among older people. A total of 27,585 participants were initially enrolled between 2005 and 2014. We excluded individuals aged under 60 years (n = 151), participants with missing death dates (n = 274), and those lost to follow-up with no record of the last survey date (n = 4,883), resulting in a sample of 22,277 participants. Further exclusions included participants with missing baseline healthy lifestyle data (n = 775), missing survival time (n = 2), or survival time of zero or fewer days (n = 82). The final analytic sample comprised 21,418 participants. The process of data exclusion is presented in Fig. 1.
Fig. 1.
Flow chart of the study population
Healthy lifestyle index (HLI)
Baseline data on lifestyle behaviors among older adults were obtained from the CLHLS. Referring to the World Health Organization’s Decade of Healthy Ageing Baseline Report [29] and previous scholarly research on healthy lifestyle [20, 30], we constructed a Healthy Lifestyle Index (HLI) comprising five modifiable components, including healthy BMI, never smoking, harmless alcohol consumption, ideal physical activity level and ideal dietary intake. Each component was scored as either 0 or 1, with a score of 1 indicating adherence to a healthy behavior.
BMI was calculated as weight in kilograms divided by the square of height in meters (kg/m²). A BMI in the range of 18.5 to 23.9 kg/m² was considered healthy [31] and scored 1, values outside this range were scored 0. Smoking status was categorized as current smoker, former smoker, or never smoker, with never smoking classified as healthy [32] and assigned a score of 1, while other categories were scored 0. Following the World Health Organization’s International Guide for Monitoring Alcohol Consumption and Related Harm, harmless alcohol consumption was defined as intake of less than 41 g of alcohol per day for women and less than 61 g per day for men [33], and was scored as 1. Physical activity was assessed based on the frequency of participation in nine types of activities: regular exercise (aerobic and anaerobic), housework, personal outdoor activities, gardening, keeping domestic pets, reading, playing cards or mahjong, watching television or listening to the radio, and socializing. Responses of “almost every day” or “at least once a week” were scored 2, “at least once a month” scored 1, and “not every month but sometimes” or “never” scored 0 [20]. The total physical activity score was calculated by summing these responses, with the top 40% of the distribution defined as reflecting ideal physical activity and assigned a score of (1) Dietary intake was assessed using self-reported frequency of consumption of ten food items: fruits, fresh vegetables, meat, fish, food made from beans (tofu, etc.), tea, garlic, eggs, sugar, and salt-preserved vegetables. For sugar and salt-preserved vegetables, responses of “almost every day” or “at least once a week” were scored 0, “at least once a month” scored 1, and “not every month but sometimes” or “rarely or never” scored (2) For the remaining eight food items, the scoring was reversed: frequent consumption scored higher [34]. The total dietary score was then computed in a manner analogous to the physical activity score, with ideal dietary intake defined as the top 40% of the population [35] and assigned a score of 1.
The HLI was calculated by summing the five component scores, yielding a total score ranging from 0 to 5, with higher scores indicating a healthier lifestyle. For further analysis, HLI scores were categorized into three groups: unhealthy (0–1), intermediate (2–3), and healthy (4–5).
Multimorbidity
More than 22 chronic diseases, including hypertension, diabetes, heart disease, stroke and cerebrovascular disease, pulmonary tuberculosis, cataracts, glaucoma, cancer, prostate tumour, gastric or duodenal ulcer, Parkinson’s disease, bedsore, arthritis, dementia, epilepsy, cholecystitis, cholelith disease, blood disease, chronic nephritis, galactophore disease, uterine tumour, hepatitis were recorded in the CLHLS. Multimorbidity was defined as the co-occurrence of two or more chronic diseases in a single individual. Participants’ multimorbidity status was assessed using the survey question: “Are you suffering from any of the following chronic diseases?” Participants were divided into “with multimorbidity” and “without multimorbidity” categories based on the number of chronic diseases.
Outcomes
The primary outcome of this study was all-cause mortality. Mortality data were obtained through official death certificates when available, or alternatively reported by the participant’s next of kin, a local physician, or community committees [34, 36]. Survival time was calculated as the duration (in days) from the baseline survey until the occurrence of the outcome. For participants lost to follow-up, survival time was defined as the interval between the baseline survey and the date of the last recorded interview. Survival status was determined based on whether the participant was alive at the time of the 2018 follow-up survey..
Covariates
We identified covariates by reviewing relevant literature and analyzing confounders previously associated with healthy lifestyle, multimorbidity, and all-cause mortality, including age; gender (female/male); area of residence (urban/rural); educational attainment (< 1 year/≥1 year); living pattern (living with family/living alone); ethnicity (Han Chinese/other); marital status (married/unmarried); income.
Statistical analysis
Continuous variables were expressed as mean ± standard deviation (SD) for those following a normal distribution, or as median with interquartile range (IQR) for those not normally distributed. Categorical variables were presented as percentages (%).
We calculated age- and sex-adjusted mortality rates per 1,000 person-years using Poisson regression and estimated hazard ratios (HRs) and 95% CI for multimorbidity and all-cause mortality using Cox proportional hazard regression with follow-up duration as the time scale. First, we estimated associations between five HLI components—healthy BMI, never smoking, harmless alcohol consumption, ideal physical activity level and ideal dietary intake—and all-cause mortality in older people. Second, we assessed the independent associations of HLI, multimorbidity and risk of all-cause mortality. In addition, to assess the impact of a healthy lifestyle on the risk of all-cause mortality among participants with different multimorbidity statuses, we stratified analyses according to whether they were multimorbid or not and analyzed for age, sex, and urban-rural heterogeneity. Five models were constructed to estimate the association of healthy lifestyle and multimorbidity with all-cause mortality. Model 1 was unadjusted; Model 2 was adjusted for age and sex; Model 3 was adjusted for area of residence, educational attainment, living pattern, ethnicity, marital status, and income. To explore the potential causal relationship between HLI, multimorbidity and all-cause mortality, we constructed two additional models. Model 4 was adjusted for area of residence, educational attainment, living pattern, ethnicity, marital status, income and multimorbidity; Model 5 was adjusted for area of residence, educational attainment, living pattern, ethnicity, marital status, income and HLI. The proportional risk hypothesis was examined using Schoenfeld’s residuals. All statistical analyses were done with Stata 17.0, and two-sided P < 0.05 was considered statistically significant.
Sensitivity analysis
To examine the robustness of the results, we performed sensitivity analyses through the following: (1) addressing reverse causation by excluding participants who died within one year of baseline (Appendix Table S3, Figure S1); (2) excluding individuals with poor self-rated health status (Appendix Table S4, Figure S2); (3) since we define multimorbidity as any combinations of 2 or more chronic diseases, a combination of multiple chronic diseases may include “high impact” (e.g., diabetes and heart disease) and “low impact” (e.g., arthritis and cataracts) diseases. To illustrate the severity of the effect, we used the top-10 most common comorbidities and categorized participants into two groups: with top-10 comorbidity and without the top-10 comorbidity (Appendix Table S5, Figure S3). The previous analyses were repeated using three different methods, and no significant bias was found in our results.
Result
Participant characteristics
Table 1 presents the baseline characteristics of participants stratified by Healthy Lifestyle Index (HLI) and multimorbidity status. Of the total sample, 13.28% of participants exhibited an unhealthy lifestyle, 62.52% had an intermediate lifestyle, and 24.20% maintained a healthy lifestyle. Participants with a healthy lifestyle were more likely to be younger, female, urban residents, have ≥ 1 year of education, and have higher incomes compared to participants with an unhealthy lifestyle. Participants with multimorbidity demonstrated a higher likelihood of being female, living with family members, unmarried, having an unhealthy BMI, non-ideal physical activity level, and non-ideal dietary intake.
Table 1.
Baseline characteristics
| Characteristics | All participants (n = 21,418) |
HLI | Multimorbidity | |||
|---|---|---|---|---|---|---|
| Unhealthy (n = 2,844) |
Intermediate (n = 13,391) |
Healthy (n = 5,183) | With multimorbidity (n = 6,137) |
Without multimorbidity (n = 15,281) |
||
| Age, years | 89(78–97) | 90(82–98) | 90(80–99) | 85(73–92) | 87(77–96) | 89(79–97) |
| Gender | ||||||
| Female | 12,315(57.5) | 1,056(37.13) | 7,951(59.38) | 3,308(63.82) | 3,557(57.96) | 8,758(57.31) |
| Male | 9,103(42.5) | 1,788(62.87) | 5,440(40.62) | 1,875(36.18) | 2,580(42.04) | 6,523(42.69) |
| Area of residence | ||||||
| Urban | 7,841(36.61) | 878(30.87) | 4,693(35.05) | 2,270(43.80) | 2,696(43.93) | 5,145(33.67) |
| Rural | 13,577(63.39) | 1,966(69.13) | 8,698(64.95) | 2,913(56.20) | 3,441(56.07) | 10,136(66.33) |
| Educational attainment | ||||||
| < 1 year | 13,663(63.79) | 1,740(61.18) | 8,933(66.71) | 2,990(57.69) | 3,655(59.56) | 10,008(65.49) |
| ≥ 1 year | 7,755(36.21) | 1,104(38.82) | 4,458(33.29) | 2,193(42.31) | 2,482(40.44) | 5,273(34.51) |
| Living pattern | ||||||
| With family members | 18,258(83.35) | 2,422(82.25) | 11,409(85.29) | 4,427(85.58) | 5,292(86.30) | 12,966(84.97) |
| Alone or in nursing home | 3,133(14.65) | 419(14.75) | 1,968(14.71) | 746(14.42) | 840(13.70) | 2,293(15.03) |
| Ethnicity | ||||||
| Han Chinese | 19,831(92.59) | 2,646(93.04) | 12,413(92.70) | 4,772(92.07) | 5,830(95.00) | 14,001(91.62) |
| Others | 1,587(7.41) | 198(6.96) | 978(7.30) | 411(7.93) | 307(5.00) | 1,280(8.38) |
| Marital status | ||||||
| Not married | 14,571 (68.03) | 1,985(69.79) | 9,474(70.75) | 3,111(60.03) | 4,033(65.72) | 10,538(68.96) |
| Married | 6,847 (31.97) | 859(30.21) | 3,917(29.25) | 2,072(39.97) | 2,104(34.28) | 4,743(31.04) |
| Income, Yuan |
4,000 (2,000–10,000) |
3,000 (1,200-7,000) |
4,000 (1,836 − 10,000) |
6,000 (2,800 − 15,000) |
4,000 (1,888 − 10,000) |
4,200 (2,000–10,000) |
| Healthy BMI | ||||||
| No | 12,375(57.78) | 2,467(86.74) | 8,629(64.44) | 1,279(24.68) | 3,759(61.25) | 8,616(56.38) |
| Yes | 9,043(42.22) | 377(13.26) | 4,762(35.56) | 3,904(75.32) | 2,378(38.75) | 6,665(43.62) |
| Never smoker | ||||||
| No | 7,116(33.22) | 2,308(81.15) | 4,317(32.24) | 491(9.47) | 2,155(35.11) | 4,961(32.47) |
| Yes | 14,302(66.78) | 536(18.85) | 9,074(67.76) | 4,692(90.53) | 3,982(64.89) | 10,320(67.53) |
| Harmful alcohol consumption | ||||||
| Yes | 5,472(25.55) | 2,125(74.72) | 3,116(23.27) | 231(4.46) | 1,567(25.53) | 3,905(25.55) |
| No | 15,946(74.45) | 719(25.28) | 10,275(76.73) | 4,952(95.54) | 4,570(74.47) | 11,376(75.45) |
| Ideal physical activity level | ||||||
| No | 11,605(54.18) | 2,435(85.62) | 8,235(61.5) | 935(18.04) | 3,290(53.61) | 8,315(54.41) |
| Yes | 9,813(45.82) | 409(14.38) | 5,156(38.5) | 4,248(81.96) | 2,847(46.39) | 6,966(45.59) |
| Ideal dietary intake | ||||||
| No | 12,709(59.34) | 2,558(89.94) | 8,941(66.77) | 1,210(23.35) | 3,752(61.14) | 8,957(58.62) |
| Yes | 8,709(40.66) | 286(10.06) | 4,450(33.23) | 3,973(76.65) | 2,385(38.86) | 6,324(41.38) |
Values are presented as median (interquartile range [IQR]) or number of participants (%). Continuous variables (e.g., age, income), which were non-normally distributed, were summarized using medians (IQR), whereas categorical variables were expressed as percentages (%). Percentages may not sum to 100% due to rounding
Among 21,418 participants, 31.77% (n = 6,805) had one chronic disease (Appendix Table S1), while 28.65% (n = 6,137) had 2 or more chronic diseases. The five most prevalent chronic diseases were arthritis (18.53%), hypertension (17.97%), cataracts (11.29%), bronchitis, emphysema, asthma and pneumonia (11.19%) and heart disease (8.01%). Since the calibre of chronic disease statistics in CLHLS 2005 was different from CLHLS 2008–2018, the statistics for the most common comorbidity used data from CLHLS 2008–2018. Top-10 comorbidities were hypertension and arthritis (n = 715), hypertension and heart disease (n = 524), cataracts and arthritis (n = 494), bronchitis and arthritis (n = 429), hypertension and cataracts (n = 336), hypertension and stroke (n = 335), heart disease and arthritis (n = 330), hypertension and bronchitis (n = 313), gastric or duodenal ulcer and arthritis (n = 235), heart disease and cataracts (n = 221), Fig. 2.
Fig. 2.
Number of participants with comorbidity. Due to differences in the types of chronic diseases included in CLHLS 2005 compared to the statistical criteria used in CLHLS 2008-2018, to ensure the scientific validity of the results, the analysis of comorbidity patterns and prevalence in this figure utilizes data from CLHLS 2008-2018, with 2008, 2011, and 2014 serving as baseline years. Participants who only participated in the 2005 survey and did not participate in subsequent surveys were excluded, leaving 15,197 participants. The numbers in the figure represent the frequency of corresponding comorbidity among the 15,197 participants
During a median follow-up of 3.44 years (IQR 1.90–6.77 years; 101,300 person-years), a total of 15,113 deaths occurred among 21,418 participants, representing 70.56%, with age- and sex-adjusted mortality per 1,000 person-years was 149.19 (95% CI 147.90-150.49).
Healthy lifestyle factors and all-cause mortality
In unadjusted model (Model 1), three healthy lifestyle factors were significantly associated with decreased all-cause mortality: normal BMI (HRa=0.84, 95% CI 0.82–0.87; p < 0.001), ideal physical activity (HRa=0.39, 95% CI 0.38–0.40; p < 0.001), and healthy dietary intake (HRa=0.81, 95% CI 0.78–0.84; p < 0.001). After adjusting for confounders, Model 2 and Model 3 demonstrated that all healthy lifestyle factors significantly decrease all-cause mortality. Model 4 was further adjusted for multimorbidity, the results remained consistent, Table 2.
Table 2.
Association of healthy lifestyle factors with all-cause mortality
| Healthy Lifestyle factors | Events/participants | Mortality rate (95% CI per 1,000 person-years) |
Model 1 HRa(95% CI) |
Model 2 HRb(95% CI) |
Model 3 HRc(95% CI) |
Model 4 HRd(95% CI) |
|---|---|---|---|---|---|---|
| Healthy BMI (kg/m2) | ||||||
| No | 8,990/12,375 | 160.62(158.84-162.41) | 1 | 1 | 1 | 1 |
| Yes | 6,123/9,043 | 135.08(133.22-136.96) |
0.84*** (0.82–0.87) |
0.93*** (0.90–0.97) |
0.94*** (0.91–0.97) |
0.94*** (0.91–0.98) |
| Never smoker | ||||||
| No | 4,965/7,116 | 138.93(136.66-141.23) | 1 | 1 | 1 | 1 |
| Yes | 10,148/14,302 | 154.78(153.20-156.38) |
1.11*** (1.07–1.15) |
0.87*** (0.83–0.90) |
0.87*** (0.84–0.91) |
0.87*** (0.84–0.91) |
| Harmless alcohol consumption | ||||||
| No | 3,873/5,472 | 142.81(140.19-145.48) | 1 | 1 | 1 | 1 |
| Yes | 11,240/15,946 | 151.52(150.03-153.02) |
1.05** (1.02–1.09) |
0.94** (0.91–0.98) |
0.94** (0.91–0.98) |
0.94** (0.91–0.98) |
| Ideal physical activity level | ||||||
| No | 9,665/11,605 | 232.80(230.06-235.57) | 1 | 1 | 1 | 1 |
| Yes | 5,448/9,813 | 91.13(89.72–92.56) |
0.39*** (0.38–0.40) |
0.67*** (0.65–0.70) |
0.68*** (0.65–0.71) |
0.68*** (0.65–0.71) |
| Ideal dietary intake | ||||||
| No | 9,492/12,709 | 162.22(160.42-164.03) | 1 | 1 | 1 | 1 |
| Yes | 5,621/8,709 | 131.38(129.55-133.22) |
0.81*** (0.78–0.84) |
0.88*** (0.85–0.91) |
0.89*** (0.86–0.92) |
0.89*** (0.86–0.92) |
Age- and sex-adjusted mortality rates per 1,000 person-years were calculated using poisson regression
HRa, Model 1: Unadjusted model
HRb, Model 2: Models adjusted for age and gender
HRc, Model 3: Models adjusted for age, gender, area of residence, educational attainment, living pattern, ethnicity, marital status, and income
HRd, Model 4: Models adjusted for age, gender, area of residence, educational attainment, living pattern, ethnicity, marital status, income, and multimorbidity
*p< 0.05, **p< 0.01, ***p< 0.001
HLI and all-cause mortality
Among the 2884 participants with an unhealthy lifestyle, a total of 2,361 died, with an age- and sex-adjusted mortality rate of 209.81 per 1,000 person-years (95% CI 204.80-214.93), significantly higher than participants with intermediate and healthy lifestyles. Among the 5,183 participants with a healthy lifestyle, a total of 2,908 died, with an all-cause mortality rate of 99.94 per 1,000 person-years (95% CI 98.00-101.91), the lowest among all groups. An increase in healthy lifestyle scores is significantly associated with a reduction in all-cause mortality. In Model 1, the HRa for intermediate and healthy lifestyle were 0.77 (95% CI 0.74–0.81; p < 0.001) and 0.48 (95% CI 0.45–0.51%; p < 0.001). After adjusting for confounders, the HRd for intermediate and healthy lifestyle were 0.83 (95% CI 0.80–0.88; p < 0.001) and 0.65 (95% CI 0.62–0.69; p < 0.001), respectively, Table 3.
Table 3.
Independent association of healthy lifestyle and Multimorbidity with all-cause mortality
| HLI | Multimorbidity | ||||
|---|---|---|---|---|---|
| Unhealthy | Intermediate | Healthy | Without multimorbidity | With multimorbidity | |
| Events/participants | 2,361/2,844 | 9,844/13,391 | 2,908/5,183 | 10,727/15,281 | 4,386/6,137 |
|
Mortality rate (95% CI per 1,000 person-years) |
209.81 (204.80-214.93) |
161.51 (159.73-163.31) |
99.94 (98.00-101.91) |
147.75 (146.22-149.29) |
152.84 (150.44-155.27) |
|
HRa(95% CI), Model 1 |
1 |
0.77*** (0.74–0.81) |
0.48*** (0.45–0.51) |
1 |
1.04 (1.00-1.07) |
|
HRb(95% CI), Model 2 |
1 |
0.82*** (0.79–0.86) |
0.64*** (0.61-0 0.68) |
1 |
1.12*** (1.08–1.16) |
|
HRc(95% CI), Model 3 |
1 |
0.84*** (0.80–0.88) |
0.65*** (0.62–0.69) |
1 |
1.12*** (1.08–1.16) |
|
HRd(95% CI), Model 4 |
1 |
0.83*** (0.80–0.88) |
0.65*** (0.62–0.69) |
- | - |
|
HRe(95% CI), Model 5 |
- | - | - | 1 |
1.11*** (1.07–1.15) |
Age- and sex-adjusted mortality rates per 1,000 person-years were calculated using poisson regression
HRa, Model 1: Unadjusted model
HRb, Model 2: Models adjusted for age and gender
HRc, Model 3: Models adjusted for age, gender, area of residence, educational attainment, living pattern, ethnicity, marital status, and income
HRd, Model 4: Models adjusted for age, gender, area of residence, educational attainment, living pattern, ethnicity, marital status, income, and multimorbidity
HRe, Model 5: Models adjusted for age, gender, area of residence, educational attainment, living pattern, ethnicity, marital status, income, and HLI
*p<0.05, **p<0.01, ***p<0.001
Multimorbidity and all-cause mortality
Among the 6,137 participants with multimorbidity, a total of 4,386 died, with an age- and sex-adjusted mortality rate of 152.84 per 1,000 person-years (95% CI 150.44-155.27), which was significantly higher than those without multimorbidity. Using participants without multimorbidity as a reference, Model 1 showed that multimorbidity increases all-cause mortality (HRa=1.04, 95% CI 1.00-1.07; p = 0.051), but not significantly. After adjusting for confounders, participants with multimorbidity had substantially higher adjusted all-cause mortality than those without multimorbidity, with an HRe of 1.11 (95% CI 1.07–1.15; p < 0.001), Table 3.
HLI and all-cause mortality, stratified by multimorbidity
We found that a healthy lifestyle was significantly associated with decreased multimorbidity risk (HRc=0.60, 95% CI 0.55–0.66; p < 0.001; Appendix Table S2). The interaction between the HLI and multimorbidity on all-cause mortality was significant (p-interaction = 0.006), indicating that the effect of HLI on all-cause mortality varied according to multimorbidity status. As reported in Table 4, the all-cause mortality for different HLI groups stratified according to multimorbidity, and the results indicated that for participants both with multimorbidity and without multimorbidity, the all-cause mortality decreases with lifestyle improvement. Among participants without multimorbidity, the HRc for the intermediate and healthy lifestyle groups were (95% CI 0.83–0.93; p < 0.001) and 0.69 (95% CI 0.65–0.74; p < 0.001), respectively. Among participants with multimorbidity, the corresponding HRc were 0.74 (95% CI 0.68–0.80; p < 0.001) and 0.58 (95% CI 0.52–0.65; p < 0.001). It indicated that a healthy lifestyle is more protective for older people with multimorbidity.
Table 4.
Mortality risk according to healthy lifestyle categories in older people stratified by Multimorbidity
| With multimorbidity(n = 6,137) | Without multimorbidity(n = 15,281) | ||||||
|---|---|---|---|---|---|---|---|
| Unhealthy | Intermediate | Healthy | Unhealthy | Intermediate | Healthy | p-interaction | |
| Events/Participants | 758/882 | 2,844/3,903 | 744/1,352 | 1,603/1,962 | 6,960/9,488 | 2,164/3,831 | - |
|
Mortality rate (95% CI per 1,000 person-years) |
238.42 (228.94-248.29) |
162.77 (159.55-155.05) |
95.39 (91.67–99.26) |
198.54 (192.69-204.57) |
161.00 (158.86-163.16) |
101.60 (99.34-103.92) |
- |
|
HRa(95% CI), Model 1 |
1 |
0.69*** (0.63–0.74) |
0.41*** (0.37-0 0.47) |
1 |
0.81*** (0.77–0.86) |
0.51*** (0.48-0 0.55) |
< 0.001 |
|
HRb(95% CI), Model 2 |
1 |
0.72*** (0.66–0.78) |
0.55*** (0.50-0 0.61) |
1 |
0.87*** (0.83–0.92) |
0.68*** (0.64–0.73) |
0.001 |
|
HRc(95% CI), Model 3 |
1 |
0.74*** (0.68–0.80) |
0.58*** (0.52–0.65) |
1 |
0.88*** (0.83–0.93) |
0.69*** (0.65–0.74) |
0.006 |
Age- and sex-adjusted mortality rates per 1,000 person-years were calculated using poisson regression
HRa, Model 1: Unadjusted model
HRb, Model 2: Models adjusted for age and gender
HRc, Model 3: Models adjusted for age, gender, area of residence, educational attainment, living pattern, ethnicity, marital status, and income
*p< 0.05, **p< 0.01, ***p< 0.001
Heterogeneity analysis
We conducted further analyses of age, sex and urban-rural heterogeneity, Fig. 3. For age heterogeneity, participants were stratified into groups aged 60–80 years and > 80 years. The results indicated that lifestyle improvement was associated with a greater reduction in all-cause mortality in the 60-80-year-old group compared to the > 80-year-old group. Among participants with multimorbidity, the HRc for healthy lifestyle was 0.55 (95% CI 0.43–0.70; p < 0.001) in the 60-80-year age group and 0.59 (95% CI 0.53–0.67; p < 0.001) in the > 80-year age group, Fig. 3. These findings suggest that the older you are, the higher the HLI score needed to achieve significant protective effects.
Fig. 3.
Analysis of age, gender and urban-rural heterogeneity
The protective effect of lifestyle improvement on all-cause mortality was more pronounced in men, particularly among those with multimorbidity. Among participants with multimorbidity, compared to an unhealthy lifestyle, the HRc for intermediate and healthy lifestyle were 0.80 (95% CI 0.71–0.92; p = 0.001) and 0.64 (95% CI 0.54–0.75; p < 0.001) for women, respectively, whereas for men, the corresponding HRc were 0.68 (95% CI 0.61–0.77; p < 0.001) and 0.53 (95% CI 0.45–0.62; p < 0.001).
Urban-rural heterogeneity analyses indicated that a healthy lifestyle conferred greater protection against all-cause mortality among urban residents, particularly those with multimorbidity. Among urban residents with multimorbidity, the HRc for intermediate and healthy lifestyle were 0.72 (95% CI 0.63–0.83; p = 0.002) and 0.54 (95% CI 0.46–0.64; p < 0.001), respectively. However, among rural residents with multimorbidity, the corresponding HRc is 0.75 (95% CI 0.67–0.84; p < 0.001) and 0.63 (95% CI 0.54–0.73; p < 0.001).
Discussion
In this cohort study using data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS, 2005–2018), we found that multimorbidity was significantly associated with increased all-cause mortality. Importantly, adherence to a healthy lifestyle substantially reduced all-cause mortality, regardless of multimorbidity status. This protective effect was especially pronounced among older people with multimorbidity. Heterogeneity analyses revealed that the all-cause mortality-reducing effects of a healthy lifestyle were more evident among three specific subgroups with multimorbidity: adults aged 60–80 years, men, and urban residents.
Among all healthy lifestyle components, ideal physical activity demonstrated the strongest association with reduced mortality (HRe=0.68, 95% CI 0.65–0.71; p < 0.001). This aligns with existing research emphasizing the importance of physical activity in later life [37, 38], especially as age-related functional decline often leads to decreased mobility and elevated the risk of all-cause mortality [39, 40].
Previous research using the China Kadoorie Biobank (CKB) identified cardiometabolic multimorbidity (e.g., diabetes, coronary heart disease, stroke, and hypertension) as the most common comorbidity pattern in China [15], while Han et al.‘s cross-sectional analysis of CLHLS 2018 data found that hypertension combined with diabetes was the most prevalent pattern among those aged 65–79 [41]. In contrast, our study identified arthritis and hypertension as the most common multimorbidity pattern in Chinese adults aged ≥ 60 years, with a relatively low prevalence of diabetes. This discrepancy may be attributed to the specific characteristics of our cohort: over half resided in rural areas with poorer living conditions where arthritis is more prevalent and diabetes is roughly half as common as in urban populations [42]. Additionally, our sample included a higher proportion of females, who are more susceptible to arthritis [43]. These factors may account for the predominance of arthritis and the lower diabetes prevalence observed.
Furthermore, our 13-year retrospective cohort study was based on baseline disease data collected during a period when diabetes prevalence in China was comparatively low, and undiagnosed cases likely existed, introducing potential bias. For instance, Li et al. reported a similarly low diabetes prevalence of 5.9% in a 10-year cohort study of Chinese older people [44]. National surveys in China showed that diabetes prevalence increased from 2.7% in 2002 [45] to 9.7% in 2010 [46], and reached 12.8% by 2018 [44].
The burden of multimorbidity continues to rise and has become a major global public health concern [47, 48]. Numerous studies have demonstrated that multimorbidity increases the risk of dementia, disability, and mortality, while also diminishing quality of life in older people [49–52]. Our findings are consistent with this literature, indicating that multimorbidity significantly elevates all-cause mortality (HRe=1.11, 95% CI 1.07–1.15; p < 0.001).
Healthy lifestyles have been proven to improve health status and decrease the mortality risk, and our study suggested that a healthy lifestyle is associated with lower all-cause mortality (HRd=0.65, 95% CI 0.62–0.69; p < 0.001). While previous studies have shown that individual healthy behaviors can mitigate mortality risk [53, 54], the extent to which such behaviors benefit those with multimorbidity remains less clear. We developed a Healthy Lifestyle Index (HLI) to examine the joint impact of lifestyle and multimorbidity on all-cause mortality. Our results demonstrate that adherence to a healthy lifestyle not only reduces the risk of multimorbidity (HRc=0.60, 95% CI 0.55–0.66; p < 0.001) but also substantially decreases all-cause mortality (HRc=0.65, 95% CI 0.62–0.69; p < 0.001). Stratified analyses revealed that the protective effect of a healthy lifestyle was more pronounced among participants with multimorbidity (HRc=0.58, 95% CI 0.52–0.65; p < 0.001) than those without (HRc=0.69, 95%CI 0.65–0.74; p < 0.001), suggesting that lifestyle interventions may be especially beneficial in mitigating the mortality risk associated with multimorbidity. Effective management of multimorbidity typically requires a combination of interventions [55]. Our findings highlight the vital role of healthy lifestyle behaviors, such as weight control, regular physical activity, and a balanced diet, in managing chronic conditions, reducing the burden of multimorbidity, and improving overall quality of life in older age.
Additionally, we explored heterogeneity by age, sex, and urban-rural residence. The results confirmed that a healthy lifestyle confers all-cause mortality benefits across all subgroups. However, the impact was greatest in multimorbid individuals aged 60–80 years, who experienced a greater reduction in all-cause mortality risk upon transitioning from an unhealthy to a healthy lifestyle compared to their non-morbid counterparts or those aged over 80. Several studies have shown a positive correlation between the age of patients with multimorbidity and their increased risk of all-cause mortality [28, 56]. This may reflect the higher physiological resilience and adaptive capacity in the 60–80 age group, which enables them to derive greater health benefits from behavior change, even in the presence of chronic conditions [57]. Therefore, older people should move into a healthier lifestyle as early as possible, especially those with multimorbidity, so that they can enjoy the benefits of health earlier and with greater benefits.
Our findings are supported by a Japanese cohort study by Sakaniwa et al., which observed stronger lifestyle-related mortality benefits in men compared to women [58]. Consistent with this, we found that multimorbid men adhering to a healthy lifestyle had a notably lower risk of all-cause mortality (HRc=0.53, 95% CI 0.45–0.62; p < 0.001). This may be explained by the higher prevalence of fatal diseases such as cardiovascular conditions and diabetes in men [45]. A prospective cohort study of the UK Biobank showed that adherence to a healthy lifestyle decreased the risk of death associated with cardiometabolic diseases (CMDs) by more than 60% [59]. In contrast, women are more likely to suffer from debilitating but rarely fatal diseases such as depression and arthritis [43]. Additionally, men exhibited a higher prevalence of poorer lifestyle behaviors (e.g., smoking, poor diet) [60] that are linked to elevated mortality risk [61, 62]. For men with multimorbidity, adopting healthier lifestyles is critical to mitigate mortality risk and improve clinical outcomes. Moreover, our study showed that the all-cause mortality-reducing effects of a healthy lifestyle were more significant in urban than rural residents with multimorbidity, echoing findings from the UK Biobank [63]. This may be attributed to better healthcare access, medical resources, and treatment adherence in urban areas [35], which were critical for older people with multimorbidity, particularly those with chronic conditions like hypertension and diabetes [64, 65]. The synergy of healthy lifestyles, prompt medical intervention, and appropriate medication adherence enables effective disease management and improved health outcomes [66]. Consequently, there is a pressing need to improve rural healthcare infrastructure and reduce urban-rural disparities, and providing protection for the health of rural residents.
This study has several strengths. First, to the best of our knowledge, this study is the first to examine the independent and joint associations between healthy lifestyles, multimorbidity, and all-cause mortality in a Chinese population of people aged 60 or older, while accounting for numerous confounding factors. Second, the longitudinal cohort design and an average follow-up of 4.73 years, enhances the reliability of our findings. Third, the CLHLS database is nationally representative, covering 23 provinces and regions, thereby enhancing generalizability. However, several limitations should be acknowledged. First, lifestyle and disease status were self-reported, potentially introducing recall bias. Second, lifestyle changes during the follow-up period were not assessed. Third, due to limitations in the CLHLS mortality data, we were unable to evaluate cause-specific mortality. Fourth, baseline disease data were used without accounting for changes over time. Lastly, we did not examine how specific patterns of multimorbidity may differentially affect the relationship between lifestyle and mortality risk, which warrants further investigation.
Conclusion
Our findings suggested that unhealthy lifestyle and multimorbidity are both significantly associated with increased all-cause mortality among older Chinese people. Adherence to a healthy lifestyle markedly reduces all-cause mortality risk, especially in individuals with multimorbidity. This protective effect is more pronounced among older people aged 60–80 years, men, and urban residents with multimorbidity. These findings provide robust evidence for promoting healthy lifestyle interventions as a public health strategy and highlight the need for targeted efforts to improve healthcare access and outcomes, particularly in vulnerable subgroups.
Supplementary Information
Acknowledgements
We are grateful to all volunteers and staff who participated in China Health and Retirement Longitudinal Study(CLHLS) for collecting and providing data.
Abbreviations
- CLHLS
Chinese Longitudinal Healthy Longevity Survey
- HLI
Healthy Lifestyle Index
- BMI
Body mass index
- HR
Hazard ratio
- CI
Confidence intervals
Authors’ contributions
Tang SL guided the thinking and writing of the whole text. Mao XY processed the data and wrote the full text. Xu JY provided us with the full text of the embellishment. Jiao HL constructed the writing idea of the article. All authors read and approved the final manuscript.
Funding
The research was supported by the National Natural Science Foundation of China (grant number 72074125).
Data availability
Data is provided within the manuscript.
Declarations
Ethics approval and consent to participate
The Chinese Longitudinal Survey of Healthy Longevity was approved by the Ethics Committee of Peking University (reference number IRB00001052-13074). All participants or their legal representatives provided written informed consent during face-to-face interviews.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Xiaoyan Mao and Shaoliang Tang contributed equally to this work and share the first authorship.
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Data Availability Statement
Data is provided within the manuscript.