Impact of Combined Lifestyle Factors on All-Cause and Cause-Specific Mortality and Life Expectancy in Chinese: The Singapore Chinese Health Study

Risk factors for cardiometabolic health in Ghana: Cardiometabolic Risks Study Protocol-APTI Project

Introduction

Cardiometabolic diseases are rapidly becoming primary causes of death in developing countries, including Ghana. However, risk factors for these diseases, including obesity phenotype, and availability of cost-effective diagnostic criteria are poorly documented in an African-ancestry populations in their native locations. The extent to which the environment, occupation, geography, stress, and sleep habits contribute to the development of Cardiometabolic disorders should be examined.

Purpose

The overall goal of this study is to determine the prevalence of undiagnosed diabetes, prediabetes, and associated cardiovascular risks using a multi-sampled oral glucose tolerance test. The study will also investigate the phenotype and ocular characteristics of diabetes and prediabetes subgroups, as well as determine if lifestyle changes over a one-year period will impact the progression of diabetes and prediabetes.

Methods and analysis

The study employs a community-based quasi-experimental design, making use of pre- and post-intervention data, as well as a questionnaire survey of 1200 individuals residing in the Cape Coast metropolis to ascertain the prevalence and risk factors for undiagnosed diabetes and prediabetes. Physical activity, dietary habits, stress levels, sleep patterns, body image perception, and demographic characteristics will be assessed. Glucose dysregulation will be detected using oral glucose tolerance test, fasting plasma glucose, and glycated hemoglobin. Liver and kidney function will also be assessed. Diabetes and prediabetes will be classified using the American Diabetes Association criteria. Descriptive statistics, including percentages, will be used to determine the prevalence of undiagnosed diabetes and cardiovascular risks. Inferential statistics, including ANOVA, t-tests, chi-square tests, ROC curves, logistic regression, and linear mixed model regression will be used to analyze the phenotypic variations in the population, ocular characteristics, glycemic levels, sensitivity levels of diagnostic tests, etiological cause of diabetes in the population, and effects of lifestyle modifications, respectively. Additionally, t-tests will be used to assess changes in glucose regulation biomarkers after lifestyle modifications.

Ethics and dissemination

Ethics approval was granted by the Institutional Review Board of the University of Cape Coast, Ghana (UCCIRB/EXT/2022/27). The findings will be disseminated in community workshops, online learning platforms, academic conferences and submitted to peer-reviewed journals for publication.

Impact of Healthy Lifestyle Factors on Life Expectancy and Lifetime Health Care Expenditure: Nationwide Cohort Study

BACKGROUND

The association between lifestyle risk factors and the risk of mortality and chronic diseases has been established, while limited research has explored the impact of healthy lifestyle factors on lifetime health care expenditure using longitudinal individual data.

OBJECTIVE

We aimed to determine the individual and combined effects of 5 healthy lifestyle factors on life expectancy and lifetime health care expenditure in Taiwan.

METHODS

Using data from the National Health Interview Survey cohort, 5 healthy lifestyle behaviors were defined and analyzed: nonsmoking, avoiding excessive alcohol consumption, engaging in sufficient physical activity, ensuring sufficient fruit and vegetable intake, and maintaining a normal weight. We used a rolling extrapolation algorithm that incorporated inverse probability of treatment weighting to estimate the life expectancy and lifetime health care expenditure of the study populations with and without healthy lifestyle factors.

RESULTS

A total of 19,893 participants aged ≥30 (mean age 48.8, SD 13.4) years were included, with 3815 deaths recorded during a median follow-up period of 15.6 years. The life expectancy and per capita estimated lifetime health care expenditures for the overall study population were 35.32 years and US $58,560, respectively. Multivariable-adjusted hazard ratios for all-cause mortality in participants adhering to all 5 healthy lifestyle factors, compared with those adhering to none, were 0.37 (95% CI 0.27-0.49). We found significant increases in life expectancy for nonsmokers (2.31 years; 95% CI 0.04-5.13; P=.03), those with sufficient physical activity (1.85 years; 95% CI 0.25-4.34; P=.02), and those with adequate fruit and vegetable intake (3.25 years; 95% CI 1.29-6.81; P=.01). In addition, nonsmokers experienced a significant reduction in annual health care expenditure (-9.78%; 95% CI -46.53% to -1.45%; P=.03), as did individuals maintaining optimal body weight (-18.36%; 95% CI -29.66% to -8.57%; P=.01). Overall, participants adhering to all 5 healthy lifestyle behaviors exhibited a life gain of 7.13 years (95% CI 1.33-11.11; P=.02) compared with those adhering to one or none, with a life expectancy of 29.19 years (95% CI 25.45-33.62). Furthermore, individuals adopting all 5 healthy lifestyle factors experienced an average annual health care expenditure reduction of 28.12% (95% CI 4.43%-57.61%; P=.02) compared with those adopting one or none.

CONCLUSIONS

Adopting a healthy lifestyle is associated with a longer life expectancy and a reduction of health care expenditure in Taiwanese adults. This contributes to a more comprehensive understanding of the impact of healthy lifestyle factors on the overall health and economic burden.

Impact of 8 lifestyle factors on mortality and life expectancy among United States veterans: The Million Veteran Program

BACKGROUND

Lifestyle medicine has been proposed as a way to address the root causes of chronic disease and their associated health care costs.

OBJECTIVE

This study aimed to estimate mortality risk and longevity associated with individual lifestyle factors and comprehensive lifestyle therapy.

METHODS

Age- and sex-specific mortality rates were calculated on the basis of 719,147 veterans aged 40-99 y enrolled in the Veteran Affairs Million Veteran Program (2011-2019). Hazard ratios and estimated increase in life expectancy were examined among a subgroup of 276,132 veterans with complete data on 8 lifestyle factors at baseline. The 8 lifestyle factors included never smoking, physical activity, no excessive alcohol consumption, restorative sleep, nutrition, stress management, social connections, and no opioid use disorder.

RESULTS

On the basis of 1.12 million person-years of follow-up, 34,247 deaths were recorded. Among veterans who adopted 1, 2, 3, 4, 5, 6, 7, and 8 lifestyle factors, the adjusted hazard ratios for mortality were 0.74 (0.60-0.90), 0.60 (95% CI: 0.49, 0.73), 0.50 (95% CI: 0.41, 0.61), 0.43 (95% CI: 0.35, 0.52), 0.35 (95% CI: 0.29, 0.43), 0.27 (95% CI: 0.22, 0.33), 0.21 (95% CI: 0.17, 0.26), and 0.13 (95% CI: 0.10, 0.16), respectively, as compared with veterans with no adopted lifestyle factors. The estimated life expectancy at age 40 y was 23.0, 26.5, 28.8, 30.8, 32.7, 35.1, 38.3, 41.3, and 47.0 y among males and 27.0, 28.8, 33.1, 38.0, 39.2, 41.4, 43.8, 46.3, and 47.5 y for females who adopted 0, 1, 2, 3, 4, 5, 6, 7, and 8 lifestyle factors, respectively. The difference in life expectancy at age 40 y was 24.0 y for male veterans and 20.5 y for female veterans when comparing adoption of 8-9 lifestyle factors.

CONCLUSIONS

A combination of 8 lifestyle factors is associated with a significantly lower risk of premature mortality and an estimated prolonged life expectancy.

Cardiovascular health and life expectancy with and without cardiovascular disease in the middle-aged and elderly Chinese population

BACKGROUND

High cardiovascular health (CVH) was associated with lower risk of cardiovascular disease (CVD) and longer life expectancy. However, whether life years lived without CVD could increase faster than or at least at the same pace as total lifespan remains unknown. We aimed to explore the associations of CVH status with total life expectancy and life years lived with and without CVD among middle-aged and elderly men and women.

METHODS

We included 65,587 participants aged ≥ 45 years from Kailuan study, who were recruited during June 2006 to October 2007. CVH was scored and classified (low [0-49 points], moderate [50-79 points] and high [80-100 points]) with Life's Essential 8, incorporating evaluations of health behaviors and factors. All-cause mortality and incident non-fatal CVD were recorded from baseline to December 31, 2020. The multi-state life table was adopted to explore the associations of CVH status with total life expectancy and life years lived with and without CVD.

RESULTS

Six thousand fifty eight cases of incident non-fatal CVD and 10,580 cases of deaths were identified. Men aged 45 years with low, moderate, and high CVH had a life expectancy of 33.0, 36.5 and 38.5 years, of which 7.8 (23.6%), 6.0 (16.3%) and 3.7 years (9.6%) were spent with CVD. For women, the corresponding life expectancy was 36.6, 43.6 and 48.6 years, and the remaining life years lived with CVD were 7.8 (21.3%), 6.0 (13.7%) and 4.5 years (9.3%), respectively. The benefits of high CVH were persistent across lifespan from age 45 to 85 years and consistent when CVH was evaluated with health behaviors and factors alone.

CONCLUSIONS

High CVH compared with low CVH was associated with longer total life expectancy and fewer years spent with CVD, indicating that promoting CVH is of great importance for CVD prevention and healthy ageing in China.

Ideal cardiovascular health metrics and life expectancy free of cardiovascular diseases: a prospective cohort study

Objectives

Whether cardiovascular health (CVH) metrics impact longevity with and without cardiovascular diseases (CVDs) has not been well established. This study aimed to investigate the association between CVH metrics and life expectancy in participants free of CVD events. We hypothesized that ideal CVH status was associated with increased life expectancy and assessed the effect of CVH status as a prevention target of longevity in the framework of predictive, preventive, and personalized medicine (PPPM/3PM).

Methods

A total of 92,795 participants in the Kailuan study were examined and thereafter followed up until 2020. We considered three transitions (from non-CVD events to incident CVD events, from non-CVD events to mortality, and from CVD events to mortality). The multistate lifetable method was applied to estimate the life expectancy.

Results

During a median follow-up of 13 years, 12,541 (13.51%) deaths occurred. Compared with poor CVH, ideal CVH attenuated the risk of incident CVD events and mortality without CVD events by approximately 58% and 27%, respectively. Women with ideal CVH at age 35 had a 5.00 (3.23-6.77) year longer life expectancy free of CVD events than did women with poor CVH metrics. Among men, ideal CVH was associated with a 6.74 (5.55-7.93) year longer life expectancy free of CVD events.

Conclusion

An ideal CVH status is associated with a lower risk of premature mortality and a longer life expectancy, either in the general population or in CVD patients, which are cost-effective ways for personalized medicine of potential CVD patients. Our findings suggest that the promotion of a higher CVH score or ideal CVH status would result in reduced burdens of CVD events and extended disease-free life expectancy, which offered an accurate prediction for primary care following the concept of PPPM/3PM.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-023-00322-8.

Life expectancy and healthy life expectancy of patients with advanced schistosomiasis in Hunan Province, China

BACKGROUND

Few studies have investigated the change in life expectancy (LE) and the healthy lifespan among patients with advanced schistosomiasis. This study was to evaluate the LE and healthy life expectancy (HLE) for patients and assess the mechanism responsible for the LE inequality.

METHODS

We utilized data from a dynamic advanced schistosomiasis cohort (10,362 patients) for the period from January 2008 to December 2019 in Hunan Province, China, to calculate the LEs of patients, and made a comparison with that of general population (19,642 schistosomiasis-free individuals) in the schistosomiasis endemic areas. LEs were estimated from 15 years of age by constructing period life tables. Arriaga's decomposition method was applied to quantify the influence of the age structure on the difference in LE. HLE for advanced schistosomiasis patients was calculated by using Sullivan method with age-specific disability weight. The LE and HLE were calculated for both males and females to perform further analyses on gender gap.

RESULTS

The estimated LE for advanced schistosomiasis patients aged 15-19 was 49.51 years (48.86 years for males and 51.07 years for females), which was 20.14 years lower compared with general population (69.65 years), and the LE gap between patients and general population decreased with age. The largest age-specific mortality contribution to the gap (32.06%) occurred at age 80-84 years. Women had a lower LE and HLE than men at age ≥ 60 years (both gender gaps in LE and HLE < 0). For advanced schistosomiasis patients, the gender gap in LE was largely attributed to the difference in mortality among those under the age of 55; the age-specific mortality in women exerted positive influence on the gap at age 25-64 and 75-79 years, with the contribution rate ranging from 0.59% to 57.02%, and made the negative contribution at other age groups.

CONCLUSIONS

The LE of advanced schistosomiasis patients was still much lower compared with general population. Strengthened prevention strategies and targeted treatments are needed to reduce morbidity and mortality due to advanced schistosomiasis, especially for younger population and elderly female patients.

Association of Combined Healthy Lifestyles With Cardiovascular Disease and Mortality of Patients With Diabetes: An International Multicohort Study

OBJECTIVE

To prospectively examine the associations of combined lifestyle factors with incident cardiovascular disease (CVD) and mortality in patients with diabetes.

PATIENTS AND METHODS

Patients with prevalent diabetes were included from 5 prospective, population-based cohorts in China (Dongfeng-Tongji cohort and Kailuan study), the United Kingdom (UK Biobank study), and the United States (National Health and Nutrition Examination Survey and National Institutes of Health-AARP Diet and Health Study). Healthy lifestyle scores were constructed according to non-current smoking, low to moderate alcohol drinking, regular physical activity, healthy diet, and optimal body weight; the healthy level of each lifestyle factor was assigned 1 point, or 0 for otherwise, and the range of the score was 0 to 5. Cox proportional hazards models were used to estimate hazard ratios for incident CVD, CVD mortality, and all-cause mortality adjusting for sociodemographic, medical, and diabetes-related factors, and outcomes were obtained by linkage to medical records and death registries. Data were collected from October 18, 1988, to September 30, 2020.

RESULTS

A total of 6945 incident CVD cases were documented in 41,350 participants without CVD at baseline from the 2 Chinese cohorts and the UK Biobank during 389,330 person-years of follow-up, and 40,353 deaths were documented in 101,219 participants from all 5 cohorts during 1,238,391 person-years of follow-up. Adjusted hazard ratios (95% CIs) comparing patients with 4 or 5 vs 0 or 1 healthy lifestyle factors were 0.67 (0.60 to 0.74) for incident CVD, 0.58 (0.50 to 0.68) for CVD mortality, and 0.60 (0.53 to 0.68) for all-cause mortality. Findings remained consistent across different cohorts, subgroups, and sensitivity analyses.

CONCLUSION

The international analyses document that adherence to multicomponent healthy lifestyles is associated with lower risk of CVD and premature death of patients with diabetes.

Associations of combined healthy lifestyles with cancer morbidity and mortality among individuals with diabetes: results from five cohort studies in the USA, the UK and China

AIMS/HYPOTHESIS

Cancer has contributed to an increasing proportion of diabetes-related deaths, while lifestyle management is the cornerstone of both diabetes care and cancer prevention. We aimed to evaluate the associations of combined healthy lifestyles with total and site-specific cancer risks among individuals with diabetes.

METHODS

We included 92,239 individuals with diabetes but without cancer at baseline from five population-based cohorts in the USA (National Health and Nutrition Examination Survey and National Institutes of Health [NIH]-AARP Diet and Health Study), the UK (UK Biobank study) and China (Dongfeng-Tongji cohort and Kailuan study). Healthy lifestyle scores (range 0-5) were constructed based on current nonsmoking, low-to-moderate alcohol drinking, adequate physical activity, healthy diet and optimal bodyweight. Cox regressions were used to calculate HRs for cancer morbidity and mortality, adjusting for sociodemographic, medical and diabetes-related factors.

RESULTS

During 376,354 person-years of follow-up from UK Biobank and the two Chinese cohorts, 3229 incident cancer cases were documented, and 6682 cancer deaths were documented during 1,089,987 person-years of follow-up in the five cohorts. The pooled multivariable-adjusted HRs (95% CIs) comparing participants with 4-5 vs 0-1 healthy lifestyle factors were 0.73 (0.61, 0.88) for incident cancer and 0.55 (0.46, 0.67) for cancer mortality, and ranged between 0.41 and 0.63 for oesophagus, lung, liver, colorectum, breast and kidney cancers. Findings remained consistent across different cohorts and subgroups.

CONCLUSIONS/INTERPRETATION

This international cohort study found that adherence to combined healthy lifestyles was associated with lower risks of total cancer morbidity and mortality as well as several subtypes (oesophagus, lung, liver, colorectum, breast and kidney cancers) among individuals with diabetes.

Healthy lifestyle and life expectancy at age 30 years in the Chinese population: an observational study

BACKGROUND

The improvement of life expectancy is one of the aims of the Healthy China 2030 blueprint. We aimed to investigate the extent to which healthy lifestyles are associated with life expectancy in Chinese adults.

METHODS

We used the prospective China Kadoorie Biobank (CKB) study to examine the relative risk of mortality associated with individual and combined lifestyle factors (never smoking or quitting not for illness, no excessive alcohol use, being physically active, healthy eating habits, and healthy body shape). Participants with coronary heart disease, stroke, cancer, or missing values for body-mass index were excluded. For analysis of chronic respiratory diseases, participants with chronic obstructive pulmonary disease or asthma were excluded. We estimated the national prevalence of lifestyle factors using data from the China Nutrition and Health Surveillance (CNHS; 2015) and derived mortality rates from the Global Burden of Diseases, Injuries, and Risk Factors Study (2015). All three data sources were combined to estimate the life expectancy of individuals at age 30 years following different levels of lifestyle factors by using the life table method. The cause-specific decomposition of the life expectancy differences was analysed using Arriaga's method.

FINDINGS

After the exclusion of CKB participants with coronary heart disease, stroke, cancer, or missing BMI data at baseline, 487 209 were included in the primary analysis. Participants with COPD or asthma at baseline were additionally excluded for chronic respiratory disease-related analysis, leaving 451 233 participants with data available for analysis. Data from 171 127 adults aged 30-84 years from the CNHS 2015 were used to estimate the sex-specific and age-specific prevalence of lifestyle-related factors. There were 42 496 deaths documented over a median follow-up of 11·1 years (IQR 10·2-12·1) in CKB. The adjusted hazard ratios (aHRs) of participants adopting five versus 0-1 low-risk factors was 0·38 (95% CI 0·34-0·43) for all-cause mortality, aHR 0·37 (0·30-0·46) for cardiovascular disease mortality, aHR 0·47 (0·39-0·56) for cancer mortality, and aHR 0·30 (0·14-0·64) for chronic respiratory disease mortality. The life expectancy at age 30 years for individuals with 0-1 low-risk factors was on average 41·7 years (95% CI 41·5-42·0) for men and 47·3 years (46·6-48·0) for women. For individuals with all five low-risk factors, the life expectancy at age 30 was 50·5 years (95% CI 48·5-52·4) for men and 55·4 years (53·5-57·4) for women; meaning a difference of 8·8 years (95% CI 6·8-10·7) for men and 8·1 years (6·5-9·9) for women. The estimated extended life expectancy for men and women was mainly attributable to reduced death from cardiovascular disease (2·4 years [27% of the total extended life expectancy] for men and 3·7 years [46%] for women), cancer (2·6 years [30%] for men and 0·9 years [11%] for women), and chronic respiratory disease (0·6 years [7%] for men and 1·2 years [15%] for women).

INTERPRETATION

Our findings suggest that increasing the adoption of these five healthy lifestyle factors through public health interventions could be associated with substantial gains in life expectancy in the Chinese population.

FUNDING

National Natural Science Foundation of China, National Key Research and Development Program of China, Kadoorie Charitable Foundation, UK Wellcome Trust.

Associations of combined lifestyle behaviors with all-cause and cardiovascular mortality in adults: A population-based cohort study in Jiangxi Province of China

Background

Data are limited on the impact of combined lifestyle behaviors on mortality in Jiangxi Province, China.

Objective

The study examined the association between combined lifestyle behaviors and all-cause and cardiovascular disease (CVD) mortality in Jiangxi province.

Methods

The baseline survey was completed in Jiangxi Province from November 2013 to August 2014. We conducted a follow-up on 12,608 participants of 35 years of age or older from July 2019 to October 2020. Four known lifestyle behaviors were evaluated: alcohol consumption, smoking, diet (AHEI scores), and physical activity. Cox regression analysis was performed to determine the association of combined lifestyle behaviors with all-cause and CVD mortality.

Results

During 65,083 person-years of follow-up, among the 11,622 participants (mean age 59.1 years; 40.1% men) 794 deaths occurred, including 375 deaths from CVD disease in this study. Compared to the favorable lifestyle group, the adjusted HR of all-cause mortality was 1.25 (95% CI, 1.03-1.53) for the intermediate lifestyle group and 1.37 (95% CI, 1.11-1.71) for the unfavorable lifestyle group. Compared to the favorable lifestyle group, the adjusted HR of CVD mortality was 1.50 (95% CI, 1.11-2.03) for the intermediate lifestyle group and 1.58 (95% CI, 1.14-2.20) for the unfavorable lifestyle group. Significant interactions of lifestyle and BMI (P for interaction <0.05) with the risk of all-cause mortality and CVD mortality were observed.

Conclusion

In the current study, we reaffirm the associations of combined lifestyle factors with total and CVD mortality in Jiangxi Province, our data suggest that an unfavorable lifestyle was associated with a substantially increased risk of all-cause and CVD mortality.

Effect of healthy lifestyle index and lifestyle patterns on the risk of mortality: A community-based cohort study

Background

Limited evidence was available on the association of the integrated effect of multidimensional lifestyle factors with mortality among Chinese populations. This cohort study was to examine the effect of combined lifestyle factors on the risk of mortality by highlighting the number of healthy lifestyles and their overall effects.

Methods

A total of 11,395 participants from the Guangzhou Heart Study (GZHS) were followed up until 1 January 2020. Individual causes of death were obtained from the platform of the National Death Registry of China. The healthy lifestyle index (HLI) was established from seven dimensions of lifestyle, and lifestyle patterns were extracted from eight dimensions of lifestyle using principal component analysis (PCA). Hazard ratios (HRs) and 95% confidence intervals (95% CIs) were estimated using the Cox proportional hazard regression model.

Results

During 35,837 person-years of follow-up, 184 deaths (1.61%) were observed, including 64 from cardiovascular disease. After adjustment for confounders, HLI was associated with a 50% (HR: 0.50, 95% CI: 0.25–0.99) reduced risk of all-cause mortality when comparing the high (6–7 lifestyle factors) with low (0–2 lifestyle factors) categories. Three lifestyle patterns were defined and labeled as pattern I, II, and III. Lifestyle pattern II with higher factor loadings of non-smoking and low-level alcohol drinking was associated with a decreased risk of all-cause mortality (HR: 0.63, 95% CI: 0.43–0.92, P_–trend = 0.023) when comparing the high with low tertiles of pattern score, after adjustment for confounders. Every 1-unit increment of pattern II score was associated with a decreased risk (HR: 0.97, 95% CI: 0.95–0.99) of all-cause mortality. The other two patterns were not associated with all-cause mortality, and the association of cardiovascular mortality risk was observed with neither HLI nor any lifestyle pattern.

Conclusion

The results suggest that the more dimensions of the healthy lifestyle the lower the risk of death, and adherence to the lifestyle pattern characterized with heavier loading of non-smoking and low-level alcohol drinking reduces the risk of all-cause mortality. The findings highlight the need to consider multi-dimensional lifestyles rather than one when developing health promotion strategies.

Cardiometabolic diseases, total mortality, and benefits of adherence to a healthy lifestyle: a 13-year prospective UK Biobank study

Background

Cardiometabolic disease (CMD) increases the risk of mortality, but the extent to which this can be offset by adherence to a healthy lifestyle is unknown. We aimed to investigate whether and to what extent a combination of healthy lifestyle is associated with lower risk of total mortality that related to CMD.

Methods

Data for this prospective analysis was sourced from the UK Biobank with 356,967 participants aged 37 to 73 years between 2006 and 2010. Adherence to a healthy lifestyle was determined on the basis of four factors: no smoking, healthy diet, body mass index < 30 kg/m², and regular physical activity. CMD was defined as any of incidence of diabetes, coronary heart disease and stroke at baseline. Cox proportional hazards models were used to calculate hazard ratios (HRs) and confidence intervals (CIs) of the associations of CMDs and lifestyle factors with total mortality.

Results

During a median follow-up of 13 years, a total of 21,473 death events occurred. The multivariable-adjusted HRs of mortality were 1.49 (95% CI 1.53–1.56) for one, 2.17 (95% CI 2.01–2.34) for two, and 3.75 (95% CI 3.04–4.61) for three CMDs. In joint exposure analysis, compared with CMDs-free and a favorable lifestyle, the HRs of mortality were 2.57 (95% CI 2.38–2.78) for patients with CMDs plus an unfavorable lifestyle and 1.58 (95% CI 1.50–1.66) for those with CMDs plus a favorable lifestyle. A favorable lifestyle attenuates the CMDs-related risk of mortality by approximately 63%. The mortality risk of CMDs-free people but have unfavorable lifestyle was higher than those who have over one CMDs but have favorable lifestyle.

Conclusion

The potential effect of an increasing number of CMDs on total mortality appears additive, adherence to a healthy lifestyle may attenuate the CMDs-related mortality risk by more than 60%. These findings highlight the potential importance of lifestyle interventions to reduce risk of mortality across entire populations, even in patients with CMDs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03439-y.

Cardiovascular health and healthy longevity in people with and without cardiometabolic disease: A prospective cohort study

BACKGROUND

Existing evidence suggest an association of cardiovascular health (CVH) level with cardiometabolic disease (CMD) and mortality, but the effect of CVH on life expectancy, particularly survival years in CMD patients, has not been well-established. This study aimed to investigate the association of CVH defined using the 7-item tool from the American Heart Association (AHA) with life expectancy in people with and without CMD.

METHODS

Between 2006 and 2010, a total of 341,331 participants (age 37-73 years) in the UK Biobank were examined and thereafter followed up to 2020. The CVH raised by the AHA included 4 behavioral (smoking, diet, physical activity, body mass index) and 3 biological (fasting glucose, blood cholesterol, blood pressure) metrics, coded on a three-point scale (0, 1, 2). The CVH score was the sum of 7 metrics (score range 0-14) and was then categorized into poor (scores 0-6), intermediate (7-11), and ideal (12-14) CVH. The flexible parametric survival models were applied to estimate life expectancy.

FINDINGS

During a median follow-up of 11.4 years, 18,420 (5.4%) deaths occurred. The multivariable-adjusted hazard ratio (HRs) of all-cause mortality were 2.21 (95% CI: 1.77 to 2.75) for male and 2.63 (95% CI: 2.22 to 3.12) for female with prevalent CMD and a poor CVH compared with CMD-free and ideal CVH group, an ideal CVH attenuated the CMD-related risk of mortality by approximately 62% for male and 53% for female. In CMD patients, an ideal CVH compared to poor CVH was associated with additional life years gain of 5.50 (95% CI: 3.94-7.05) for male 4.20 (95% CI: 2.77-5.62) for female at the age of 45 years. Corresponding estimates in those without CMD were 4.55 (95% CI: 3.62-5.48) and 4.89 (95% CI: 3.99-5.79), respectively. Ideal smoking status, fasting glucose and physical activity for male and ideal smoking status, cholesterol level and physical activity for female contributed to the greatest survival benefit.

INTERPRETATION

An ideal CVH is associated with a lower risk of premature mortality and longer life expectancy whether in general population or CMD patients. Our study highlights the benefits of maintaining better CVH across the life course and calls attention to the need for comprehensive strategies (healthy behavioral lifestyle and biological phenotypes) to preserve and restore a higher CVH level.

FUNDING

Scientific Research Foundation for Scholars of HZNU (Grant No. 4265C50221204119).

Association Between Functional Limitations and Incident Cardiovascular Diseases and All-Cause Mortality Among the Middle-Aged and Older Adults in China: A Population-Based Prospective Cohort Study

Background

The prevalence of functional limitations is relatively high among the middle-aged and older adults. However, the contribution of functional limitations to subsequent incident cardiovascular diseases (CVD) and death is unclear. This study aims to examine the association between functional limitations and incident CVD and all-cause mortality among the middle-aged and older adults.

Methods

This is a nationally representative prospective cohort study. Participants were middle-aged and older Chinese adults from The China Health and Retirement Longitudinal Study. Functional limitations were measured using activities of daily living (ADL) scale and instrumental activities of daily living (IADL) scale. Incident CVD and death were recorded at followed-up from June 1, 2011, up until August 31, 2018. Cox proportional hazards model was used to assess the association between functional limitations and incident CVD and all-cause mortality.

Results

A total of 11,013 participants were included in this study. During the 7 years of follow-up, 1,914 incident CVD and 1,182 incident deaths were identified. Participants with functional limitations were associated with a 23% increased risk of incident CVD (HR, 1.23, 95% CI:1.08,1.39) after adjusting for age, gender, residential area, marital status, education, smoking, alcohol drinking, sleep duration, nap duration, depression symptoms, social participation, history of hypertension, diabetes, dyslipidemia, use of hypertension medications, diabetes medications, and lipid-lowering therapy. Moreover, participants with functional limitations were associated with a 63% increased risk of all-cause mortality (HR,1.63, 95%CI: 1.41,1.89) after adjusting for potential confounders.

Conclusions

Functional limitations were significantly associated with subsequent incident CVD and death among the middle-aged and older Chinese adults.

Serum markers of biological ageing provide long-term prediction of life expectancy-a longitudinal analysis in middle-aged and older German adults

BACKGROUND

lifestyle behaviours and chronic co-morbidities are leading risk factors for premature mortality and collectively predict wide variability in individual life expectancy (LE). We investigated whether a pre-selected panel of five serum markers of biological ageing could improve predicting the long-term mortality risk and LE in middle-aged and older women and men.

METHODS

we conducted a case-cohort study (n = 5,789 among which there were 2,571 deaths) within the European Prospective Investigation into Cancer-Heidelberg cohort, a population cohort of middle-aged and older individuals, followed over a median duration of 18 years. Gompertz models were used to compute multi-adjusted associations of growth differentiation factor-15, N-terminal pro-brain natriuretic peptide, glycated haemoglobin A1c, C-reactive protein and cystatin-C with mortality risk. Areas under estimated Gompertz survival curves were used to estimate the LE of individuals using a model with lifestyle-related risk factors only (smoking history, body mass index, waist circumference, alcohol, physical inactivity, diabetes and hypertension), or with lifestyle factors plus the ageing-related markers.

RESULTS

a model including only lifestyle-related factors predicted a LE difference of 16.8 [95% confidence interval: 15.9; 19.1] years in men and 9.87 [9.20; 13.1] years in women aged ≥60 years by comparing individuals in the highest versus the lowest quintiles of estimated mortality risk. Including the ageing-related biomarkers in the model increased these differences up to 22.7 [22.3; 26.9] years in men and 14.00 [12.9; 18.2] years in women.

CONCLUSIONS

serum markers of ageing are potentially strong predictors for long-term mortality risk in a general population sample of older and middle-aged individuals and may help to identify individuals at higher risk of premature death, who could benefit from interventions to prevent further ageing-related health declines.

Healthy lifestyle in older adults and life expectancy with and without heart failure

Several lifestyle factors have been linked to risk for heart failure (HF) and premature mortality. The aim of this study was to estimate the impact of a healthy lifestyle on life expectancy with and without HF among men and women from a general population. This study was performed among 6113 participants (mean age 65.8 ± 9.7 years; 58.9% women) from the Rotterdam Study, a large prospective population-based cohort study. A continuous lifestyle score was created based on five lifestyle factors: smoking status, alcohol consumption, diet quality, physical activity and weight status (assessed 1995–2008). The lifestyle score was categorized into three levels: unhealthy (reference), intermediate and healthy. Gompertz regression and multistate life tables were used to estimate the effects of lifestyle on life expectancy with and without HF in men and women separately at ages 45, 65 and 85 years (follow-up until 2016). During an average follow-up of 11.3 years, 699 incident HF events and 2146 deaths occurred. At the age of 45 years, men in the healthy lifestyle category had a 4.4 (95% CI: 4.1–4.7) years longer total life expectancy than men in the unhealthy lifestyle category, and a 4.8 (95% CI: 4.4–5.1) years longer life expectancy free of HF. Among women, the difference in total life-expectancy at the age of 45 years was 3.4 (95% CI: 3.2–3.5) years and was 3.4 (95% CI: 3.3–3.6) years longer for life expectancy without HF. This effect persisted also at older ages. An overall healthy lifestyle can have a positive impact on total life expectancy and life expectancy free of HF.

Joint association of modifiable lifestyle and metabolic health status with incidence of cardiovascular disease and all-cause mortality: a prospective cohort study

PURPOSE

We aimed to identify the joint associations of modifiable lifestyle and metabolic factors with the incidences of cardiovascular disease and all-cause mortality.

METHODS

We recruited 94,831 participants (men, 79.76%; median age, 51.60 [43.47-58.87]) without a history of cardiovascular disease from the Kailuan study during 2006 and 2007 and followed them until a cardiovascular disease event, or death occurred, or until December 31, 2017. Baseline metabolic health status was assessed using Adult Treatment Panel III criteria, and details of the lifestyles of the participants were recorded using a self-reported questionnaire. We used Cox proportional hazards models to evaluate the joint associations.

RESULTS

During a median follow-up of 11.03 years, we recorded 6590 cardiovascular disease events and 9218 all-cause mortality. Participants with the most metabolic risk components and the least healthy lifestyle had higher risk of cardiovascular disease (hazard ratio 2.06 [95% confidence interval (CI) 1.77-2.39]) and mortality (HR 1.53 [95% CI 1.31-1.78]), than participants with fewer metabolic risk components and the healthiest lifestyle. Compared with those in participants with the healthiest lifestyle, the HRs for cardiovascular disease in participants with the least healthy lifestyle were 1.26 (95% CI 1.17-1.37), 1.16 (95% CI 1.03-1.31), and 1.07 (95% CI 0.90-1.27) for those with low, medium, and high metabolic risk, respectively.

CONCLUSION

Healthy lifestyle is associated with a lower risk of cardiovascular disease and there is no significant interaction between metabolic risk and a healthy lifestyle. Therefore, a healthy lifestyle should be promoted, even for people with high metabolic risk.

Association Between Combined Lifestyle Factors and Healthy Ageing in Chinese Adults: The Singapore Chinese Health Study

BACKGROUND

The aim of the study was to examine the relations of individual lifestyle factors and its composite score with healthy ageing among Chinese adults.

METHOD

We included 14 159 participants aged 45-74 years at baseline from the Singapore Chinese Health Study, a population-based prospective cohort. A protective lifestyle score (0-5 scale) was calculated at baseline (1993-1998) and updated at the second follow-up visit (2006-2010) on the basis of optimal body mass index (18.5-22.9 kg/m2), healthy diet (upper 40% of the Alternative Healthy Eating Index score), being physically active (≥2 h/wk of moderate activity or ≥0.5 h/wk of strenuous activity), nonsmoking (never smoking), and low-to-moderate alcohol drinking (>0 to ≤14 drinks/wk for men and >0 to ≤7 drinks/wk for women). Healthy ageing was assessed at the third follow-up visit (2014-2016) and was defined as absence of specific chronic diseases, absence of cognitive impairment and limitations in instrumental activities of daily living, good mental and overall self-perceived health, good physical functioning, and no function-limiting pain.

RESULTS

About 20.0% (2834) of the participants met the criteria of healthy ageing after a median follow-up of 20 years. Each 1-point increase in the protective lifestyle score computed at baseline and second follow-up visits was associated with higher likelihood of healthy ageing by 25% (95% CI: 20%-30%) and 24% (18%-29%), respectively. The population-attributable risk percent of adherence to 4-5 protective lifestyle factors was 34.3% (95% CI: 25.3%-42.3%) at baseline and 31.3% (23.0%-38.7%) at second follow-up visits for healthy ageing. In addition, positive increase in lifestyle scores from baseline to second follow-up visits was also significantly associated with a higher likelihood of healthy ageing with an odds ratio of 1.18 (95% CI: 1.12%-1.24%) for each increment in protective lifestyle score.

CONCLUSIONS

Our findings confirmed that adopting healthy lifestyle factors, even after midlife, was associated with healthy ageing at old age.

Association of healthy lifestyle score with all-cause mortality and life expectancy: a city-wide prospective cohort study of cancer survivors

BACKGROUND

Adherence to a healthy lifestyle could reduce the cancer mortality in the western population. We conducted a city-wide prospective study in China investigating the association of a healthy lifestyle score with all-cause mortality and the life expectancy in cancer survivors.

METHODS

This prospective cohort study included 46,120 surviving patients who were firstly diagnosed with cancer in Guangzhou. Five low-risk lifestyle factors including never smoking, never alcohol use, regular physical activity (≥ 2 h/week), sufficient sleep (≥ 6 h/day), and normal or high BMI (≥ 18.5 kg/m²) were assessed and a lifestyle score (0-5, a higher score indicates healthier lifestyle) was generated. Hazard ratios (HRs) of all-cause mortality and the life expectancy by levels of the lifestyle scores were estimated.

RESULTS

Of 46,120 cancer survivors registered from 2010 to 2017, during an average follow-up of 4.3 years (200,285 person-years), 15,209 deaths were recorded. Adjusted HRs for mortality in cancer survivors with lifestyle score of 0-2, versus 5, were 2.59 (95% confidence interval (CI): 2.03-3.30) in women, 1.91 (95%CI 1.77-2.05) in men, 2.28 (95%CI 2.03-2.55) in those aged <65 years, and 1.90 (95%CI 1.75, 2.05) in those aged ≥ 65 years. Life expectancy at age 55 for those with a score of 0-2 and 5 was 53.4 and 57.1 months, respectively. We also found that cancer survivors with healthy lifestyle scores of 5 showed 59.9 months of life expectancy on average, which was longer than those with a score of 0-2.

CONCLUSION

Adopting a healthy lifestyle was associated with a substantially lower risk of all-cause mortality and longer life expectancy in cancer survivors. Our findings should be useful for health education and health promotion in primary care and clinical practice.

Associations Between Healthy Lifestyle Trajectories and the Incidence of Cardiovascular Disease With All-Cause Mortality: A Large, Prospective, Chinese Cohort Study

Background: Lifestyles generally change across the life course yet no prospective study has examined direct associations between healthy lifestyle trajectories and subsequent cardiovascular disease (CVD) or all-cause mortality risk. Methods: Healthy lifestyle score trajectories during 2006-2007, 2008-2009, and 2010-2011 were collated through latent mixture modeling. An age-scale based Cox proportional hazard regression model was implemented to calculate hazard ratios (HR) with corresponding 95% confidence intervals (CI) for developing CVD or all-cause mortality across healthy lifestyle trajectories. Results: 52,248 participants were included with four distinct trajectories identified according to healthy lifestyle scores over 6 years i.e., low-stable (n = 11,248), high-decreasing (n = 7,374), low-increasing (n = 7,828), and high-stable (n = 25,799). Compared with the low-stable trajectory, the high-stable trajectory negatively correlated with lower subsequent risk of developing CVD (HR, 0.73; 95% CI, 0.65-0.81), especially stroke (HR, 0.70; 95% CI, 0.62-0.79), and all-cause mortality (HR, 0.89; 95% CI, 0.80-0.99) under a multivariable-adjusted model. A protective effect for CVD events was observed only in men and in those without diabetes, while a reduced risk of all-cause mortality was observed only in those older than 60 years, though interactions were not statistically significant. Marginally significant interactions were observed between the changing body mass index (BMI) group, healthy lifestyle score trajectories and stratified analysis. This highlighted an inverse correlation between the high-stable trajectory and CVD in BMI decreased and stable participants as well as all-cause mortality in the stable BMI group. The low-increasing trajectory also had reduced risk of CVD only when BMI decreased and in all-cause mortality only when BMI was stable. Conclusions: Maintaining a healthy lifestyle over 6 years corresponds with a 27% lower risk of CVD and an 11% lower risk in all-cause mortality, compared with those engaging in a consistently unhealthy lifestyle. The benefit of improving lifestyle could be gained only after BMI change is considered further. This study provides further evidence from China around maintaining/improving healthy lifestyles to prevent CVD and early death.

Healthy lifestyle and life expectancy in people with multimorbidity in the UK Biobank: A longitudinal cohort study

BACKGROUND

Whether 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 FINDINGS

A 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.

CONCLUSIONS

In 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.