Living healthier for longer: comparative effects of three heart-healthy behaviors on life expectancy with and without cardiovascular disease

Association of Life's Simple 7 lifestyle metric with cardiometabolic disease-free life expectancy in older British men

BACKGROUND

Cardiometabolic diseases (CMD), including myocardial infarction, stroke, and type 2 diabetes, are leading causes of disability and mortality globally, particularly for people at an older age. The impact of adhering to the Life's Simple 7 (LS7) on the number of years an individual will live without CMD in older adults remains less studied.

METHODS

This study included a cohort of 2662 British men aged 60-79 years free of CMD at baseline from the British Regional Heart Study (BRHS). Each LS7 factor (BMI, blood pressure, blood glucose, total cholesterol, smoking, physical activity, and diet) was categorized as poor, intermediate, or ideal, and a composite LS7 adherence was determined by summing the number of LS7 ideal levels achieved. Flexible parametric Royston-Parmar proportional-hazards model was applied to estimate CMD-free life expectancy.

RESULTS

Here we show that compared to men with the lowest LS7 adherence [with 18.42 years (95% CI: 16.93, 19.90) of CMD-free life at age 60], men having an ideal LS7 adherence are estimated to gain an additional 4.37 years (95% CI: 2.95, 5.79) of CMD-free life. The CMD-free life gain benefits are consistent across social class groups of manual and non-manual workers. Among LS7 factors, achieving an ideal physical activity provides the largest CMD-free survival benefit: 4.84 years (95% CI: 3.37, 6.32) of additional CMD-free life compared with the physically inactive group.

CONCLUSIONS

Our study quantifies and highlights the benefits of adhering to the LS7 ideal levels for living a longer life without CMD in older adults.

Healthy lifestyle and life expectancy free of major chronic diseases at age 40 in China

Whether a healthy lifestyle helps achieve gains in life expectancy (LE) free of major non-communicable diseases and its share of total LE in Chinese adults remains unknown. We considered five low-risk lifestyle factors: never smoking or quitting for reasons other than illness, no excessive alcohol use, being physically active, healthy eating habits and healthy body fat levels. Here we show that after a median follow-up of 11.1 years for 451,233 Chinese adults, the LE free of cardiovascular diseases, cancer and chronic respiratory diseases (95% confidence interval) at age 40 years for individuals with all five low-risk factors was on average 6.3 (5.1-7.5) years (men) and 4.2 (3.6-5.4) years (women) longer than those with 0-1 low-risk factors. Correspondingly, the proportion of disease-free LE to total LE increased from 73.1% to 76.3% for men and from 67.6% to 68.4% for women. Our findings suggest that promoting healthy lifestyles could be associated with gains in disease-free LE in the Chinese population.

Impact of modifiable healthy lifestyle adoption on lifetime gain from middle to older age

OBJECTIVE

this study explored whether the modification of selected lifestyles is likely to increase life expectancy from middle age onwards, regardless of the presence of major comorbidities.

METHODS

we examined a prospective cohort of 20,373 men and 26,247 women aged 40-80 years. Eight modifiable lifestyle factors were assessed: consumption of fruit, fish and milk, walking and/or sports participation, body-mass index, smoking status, alcohol consumption and sleep duration. Modifiable healthy lifestyle factors scored one point each, for a maximum of eight points. The impact of modifiable healthy lifestyle adoption on lifetime gain during the ages of 40-102 years was analysed.

FINDINGS

during the median 21 years of follow-up, 8,966 individuals (3,683 men and 5,283 women) died. Life expectancy at 40 years (95% confidence intervals) for 7-8 health lifestyle points was 46.8 (45.6-48.1) and 51.3 (50.0-52.6) years for men and women, respectively. The potential impact of modifiable healthy lifestyle adoption on lifetime gain persisted over the age of 80 years or more, in individuals with ≥5 factors (P < 0.001), particularly older men. The benefits were more pronounced among patients with major comorbidities, such as cardiovascular disease, cancer, hypertension, diabetes, kidney disease and those with multimorbidity throughout all age categories.

CONCLUSION

adopting modifiable healthy lifestyles was associated with lifetime gain, even in individuals aged 80 years or more, regardless of the presence of any major comorbidities in each life stage since middle age. The findings imply the importance of improving the one's lifestyle for an increased lifespan, even among older patients and/or those with multimorbidity.

Association Between Living Risk and Healthy Life Years Lost Due to Multimorbidity: Observations From the China Health and Retirement Longitudinal Study

Background

Multimorbidity has an effect on life expectancy, while its effect on healthy life years is unclear. This study aims to investigate the associations between healthy life years lost due to multimorbidity and living risk.

Methods

The participants of The China Health and Retirement Longitudinal Study (CHARLS) were assessed at four visits between 2011 (baseline) and 2018. At baseline, 13,949 individuals were administered surveys. A combined score based on seven health-related factors was calculated, and the participants were classified into 3 groups based on living risk. We used the adjusted Cox regression methods to examine the associations between living risk groups and multimorbidity. We estimated the healthy life years lost due to multimorbidity using the Sullivan method.

Results

A total of 9,091 adults aged 45 years or older (mean age of 59.55 ± 9.50 years with one disease, 52.60% women) were analyzed in the CHARLS. The probability of no multimorbidity over 7 years decreased from 0.9947 to 0.9697 in the low-risk group, whereas the probability of multimorbidity in low living risk was lower than that of high living risk, ranging from HR 1.253 (95% CI.992–1.581; P = 0.058) to 1.431 (1.05–1.949; P = 0.023) in sex, and ranging from HR 1.340 (95% CI 1.106–1.623; P = 0.003) to 2.002 (1.058–3.787; P = 0.033) in area. At 45 years, the healthy life years lost in men was <0.27 years compared to women in the low-risk group. Hypertension increased the risk of multimorbidity with an HR of 1.5 (95% CI 1.21–1.91; P < 0.001) in men. In urban areas, participants with diabetes had 3.2 times (95% CI 1.75–5.94, P < 0.001) higher risk of multimorbidity than participants without diabetes.

Conclusions

These findings indicate that a low-risk lifestyle could decrease the loss of healthy life years under multimorbidity. The probability of multimorbidity in women and in urban areas was high. Hypertension was correlated with the hazard risk of multimorbidity.

The Broken Heart: The Role of Life Events in Takotsubo Syndrome

The onset of Takotsubo syndrome (TTS), also known as stress cardiomyopathy, is thought to be associated with some life events. This study focuses on clarifying life event characteristics and the role of triggers in the onset of TTS. Participants with TTS (n = 54) were compared to those with acute myocardial infarction (AMI; n = 52) and healthy individuals (n = 54). Using a modified version of the Interview for Recent Life Events, information about general life events perceived as stressful and triggers preceding the onset of a cardiac syndrome was collected. The assessment included the impact of these events as indicated by the participants and estimated by the interviewer; finally, the objective impact was considered. Although the number of events and the objective impact did not differ among the groups, patients with TTS reported a more negative perceived impact. Moreover, 61% of these patients objectively and subjectively reported a more stressful trigger before the onset of the disease (in the 24 h preceding the cardiac event) than those reported by patients with AMI. The dynamic between life events and individual responses could help differentiate TTS from other cardiovascular events, such as AMI. This study suggests that patients' perception of some life events (whether triggers or general life events) could represent a possible marker of TTS.

Mixed evidence for the compression of morbidity hypothesis for smoking elimination-a systematic literature review

BACKGROUND

There is debate around the composition of life years gained from smoking elimination. The aim of this study was to conduct a systematic review of the literature to synthesize existing evidence on the effect of smoking status on health expectancy and to examine whether smoking elimination leads to compression of morbidity.

METHODS

Five databases were systematically searched for peer-reviewed articles. Studies that presented quantitative estimates of health expectancy for smokers and non-/never-smokers were eligible for inclusion. Studies were searched, selected and reviewed by two reviewers who extracted the relevant data and assessed the risk of bias of the included articles independently.

RESULTS

The search identified 2491 unique records, whereof 20 articles were eligible for inclusion (including 26 cohorts). The indicators used to measure health included disability/activity limitations (n=9), health-related quality of life (EQ-5D) (n=2), weighted disabilities (n=1), self-rated health (n=9), chronic diseases (n=6), cardiovascular diseases (n=4) and cognitive impairment (n=1). Available evidence showed consistently that non-/never-smokers experience more healthy life years throughout their lives than smokers. Findings were inconsistent on the effect of smoking on the absolute number of unhealthy life years. Findings concerning the time proportionally spent unhealthy were less heterogeneous: nearly all included articles reported that non-/never-smokers experience relatively less unhealthy life years (e.g. relative compression of morbidity).

CONCLUSIONS

Support for the relative compression of morbidity due to smoking elimination was evident. Further research is needed into the absolute compression of morbidity hypothesis since current evidence is mixed, and methodology of studies needs to be harmonized.

Associations of Leisure-Time Physical Activity and Television Viewing with Life Expectancy Cancer-Free at Age 50: The ARIC Study

BACKGROUND

Physical activity has been associated with longer chronic disease-free life expectancy, but specific cancer types have not been investigated. We examined whether leisure-time moderate-to-vigorous physical activity (LTPA) and television (TV) viewing were associated with life expectancy cancer-free.

METHODS

We included 14,508 participants without a cancer history from the Atherosclerosis Risk in Communities (ARIC) study. We used multistate survival models to separately examine associations of LTPA (no LTPA,

RESULTS

Compared with no LTPA, participants who engaged in LTPA ≥median had a greater life expectancy cancer-free from colorectal [men-2.2 years (95% confidence interval (CI), 1.7-2.7), women-2.3 years (95% CI, 1.7-2.8)], lung [men-2.1 years (95% CI, 1.5-2.6), women-2.1 years (95% CI, 1.6-2.7)], prostate [1.5 years (95% CI, 0.8-2.2)], and postmenopausal breast cancer [2.4 years (95% CI, 1.4-3.3)]. Compared with watching TV often/very often, participants who seldom/never watched TV had a greater colorectal, lung, and postmenopausal breast cancer-free life expectancy of ∼1 year.

CONCLUSIONS

Participating in LTPA was associated with longer life expectancy cancer-free from colorectal, lung, prostate, and postmenopausal breast cancer. Viewing less TV was associated with more years lived cancer-free from colorectal, lung, and postmenopausal breast cancer.

IMPACT

Increasing physical activity and reducing TV viewing may extend the number of years lived cancer-free.

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Key Words Collapse

MESH Headings

• Adult
• Aged
• Exercise/physiology
• Female
• Humans
• Life Expectancy/trends
• Male
• Middle Aged
• Neoplasms/epidemiology
• Risk Factors
• Television/trends
• Time Factors

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Grants

• P30 CA016086 NCI NIH HHS
• HHSN268201700002C NHLBI NIH HHS
• HHSN268201700001I NHLBI NIH HHS
• HHSN268201700004I NHLBI NIH HHS
• HHSN268201700004C NHLBI NIH HHS
• HHSN268201700003I NHLBI NIH HHS
• HHSN268201700005C NHLBI NIH HHS
• HHSN268201700001C NHLBI NIH HHS
• HHSN268201700003C NHLBI NIH HHS
• HHSN268201700002I NHLBI NIH HHS
• HHSN268201700005I NHLBI NIH HHS
• T32 HL007055 NHLBI NIH HHS
• U01 CA164975 NCI NIH HHS

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Affiliation(s)

Carmen C Cuthbertson Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.
Hazel B Nichols Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
Xianming Tan Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
Anna Kucharska-Newton Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
Gerardo Heiss Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
Corinne E Joshu Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
Elizabeth A Platz Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
Kelly R Evenson Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina

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Parental cardiovascular health predicts time to onset of cardiovascular disease in offspring

BACKGROUND

Cardiovascular disease (CVD) risk factors are transmitted from parents to children. We prospectively examined the association between parental cardiovascular health (CVH) and time to onset of CVD in the offspring.

METHODS AND RESULTS

The study consisted of a total of 5967 offspring-mother-father trios derived from the Framingham Heart Study. Cardiovascular health score was defined using the seven American Heart Association's CVH metrics attained at ideal levels: poor (0-2), intermediate (3-4), and ideal CVH (5-7). Multivariable-adjusted Cox proportional hazards regression models, Kaplan-Meier plots, and Irwin's restricted mean were used to examine the association and sex-specific differences between parental CVH and offspring's CVD-free survival. In a total of 71 974 person-years of follow-up among the offspring, 718 incident CVD events occurred. The overall CVD incidence rate was 10 per 1000 person-years [95% confidence interval (CI) 9.3-10.7]. Offspring of mothers with ideal CVH lived 9 more years free of CVD than offspring of mothers with poor CVH (P < 0.001). Maternal poor CVH was associated with twice as high hazard of early onset of CVD compared with maternal ideal CVH (adjusted Hazard Ratio 2.09, 95% CI 1.50-2.92). No statistically significant association was observed in the hazards of CVD-free survival by paternal CVH categories.

CONCLUSIONS

We found that offspring of parents with ideal CVH had a greater CVD-free survival. Maternal CVH was a more robust predictor of offspring's CVD-free survival than paternal CVH, underscoring the need for clinical and policy interventions that involve mothers to break the intergenerational cycle of CVD-related morbidity and mortality.

Behavioural risk factors and healthy life expectancy: evidence from two longitudinal studies of ageing in England and the US

We examined whether the co-occurrence of four behavioural risk factors (alcohol consumption, smoking, physical inactivity and obesity) is associated with disability-free and chronic disease-free life expectancy similarly in two longitudinal studies of ageing in England and the United States. Data were from 17,351 individuals aged 50+ from the US Health and Retirement Study (HRS) and, 10,388 from the English Longitudinal Study of Ageing (ELSA), from 2002 to 2013. Disability-free life expectancy was estimated using repeat measures of limitations with instrumental activities and activities of daily living and, chronic disease-free life expectancy was based on chronic health conditions. Multistate life table models were used to estimate sex-specific health expectancy at the ages of 50, 60 and 70. In both countries and at all ages, there was a clear gradient towards shorter health expectancy with increasing number of behavioural risk factors. Compared to people with 2+ behavioural risk factors, in both countries, those with no behavioural risk factors could expect to live up to 11 years longer without disability and, up to 12 years longer without chronic conditions. Individual and co-occurring behavioural risk factors were strongly associated with shorter healthy life expectancy in both countries, attesting to the robustness of the contribution of lifestyle factors on health expectancy.

Healthy lifestyle and life expectancy free of cancer, cardiovascular disease, and type 2 diabetes: prospective cohort study

OBJECTIVE

To examine how a healthy lifestyle is related to life expectancy that is free from major chronic diseases.

DESIGN

Prospective cohort study.

SETTING AND PARTICIPANTS

The Nurses' Health Study (1980-2014; n=73 196) and the Health Professionals Follow-Up Study (1986-2014; n=38 366).

MAIN EXPOSURES

Five low risk lifestyle factors: never smoking, body mass index 18.5-24.9, moderate to vigorous physical activity (≥30 minutes/day), moderate alcohol intake (women: 5-15 g/day; men 5-30 g/day), and a higher diet quality score (upper 40%).

MAIN OUTCOME

Life expectancy free of diabetes, cardiovascular diseases, and cancer.

RESULTS

The life expectancy free of diabetes, cardiovascular diseases, and cancer at age 50 was 23.7 years (95% confidence interval 22.6 to 24.7) for women who adopted no low risk lifestyle factors, in contrast to 34.4 years (33.1 to 35.5) for women who adopted four or five low risk factors. At age 50, the life expectancy free of any of these chronic diseases was 23.5 (22.3 to 24.7) years among men who adopted no low risk lifestyle factors and 31.1 (29.5 to 32.5) years in men who adopted four or five low risk lifestyle factors. For current male smokers who smoked heavily (≥15 cigarettes/day) or obese men and women (body mass index ≥30), their disease-free life expectancies accounted for the lowest proportion (≤75%) of total life expectancy at age 50.

CONCLUSION

Adherence to a healthy lifestyle at mid-life is associated with a longer life expectancy free of major chronic diseases.

Trends across 20 years in multiple indicators of functioning among older adults in the Netherlands

BACKGROUND

Monitoring of trends in functioning of older adults provides indispensable information for health care policy. This study examined trends in multiple indicators of functioning among Dutch older adults across a period of 20 years.

METHODS

Data from the Longitudinal Aging Study Amsterdam were used. We included 10 870 observations of 3803 respondents aged 64-84 years across seven waves (1992-12) and 931 observations of 603 respondents aged 85-94 years across four waves (2001-12). At each wave, 8 indicators of functioning were measured: multimorbidity, severe functional limitations, depression, anxiety, cognitive impairment, physical inactivity, loneliness and social isolation. In addition, a sum score (range: 0-8) of these indicators was calculated, with a score of ≥5 indicating 'multiple problems.' Trends in functioning over time were assessed using Generalized Estimating Equation analyses.

RESULTS

In the 64-84-years-olds, the prevalence of multimorbidity increased over time [OR(year) = 1.06, 95% CI = 1.05-1.06], whereas the prevalence of the other indicators decreased [i.e. cognitive impairment, physical inactivity (in women) and loneliness (in women)] or remained stable [i.e. severe functional limitations, depression, anxiety, physical inactivity (in men), loneliness (in men) and social isolation]. In the 85-94-year-olds, the prevalence of severe functional limitations increased over time [OR(year) = 1.08, 95% CI = 1.02-1.13], whereas the prevalence of the other indicators remained stable. In both age groups, the prevalence of 'multiple problems' remained stable.

CONCLUSION

Unfavorable trends were observed in multimorbidity among 64-84-years-olds and in severe functional limitations among 85-94-year-olds. Favorable trends were found in cognitive impairment, physical inactivity (in women) and loneliness (in women) among 64-84-years-olds.

Associations of Leisure-Time Physical Activity and Television Viewing With Life Expectancy Free of Nonfatal Cardiovascular Disease: The ARIC Study

Background High levels of physical activity have been associated with longer life expectancy free of cardiovascular disease (CVD), but specific types of CVD and sedentary behavior have not been examined. We examined associations of leisure-time moderate-to-vigorous physical activity (LTPA) and television viewing with life expectancy free of 3 types of CVD. Methods and Results We included 13 534 participants from the ARIC (Atherosclerosis Risk in Communities) cohort. We used multistate survival models to estimate associations of LTPA in the past year (no LTPA, less than the median, equal to or greater than the median) and television viewing (often or very often, sometimes, seldom or rarely) with life expectancy at age 50 free of nonfatal coronary heart disease (CHD), stroke, and heart failure (HF). Over 27 years of follow-up, 4519 participants developed one of the 3 nonfatal CVDs and 5475 deaths occurred. Compared with participants who engaged in no LTPA, participants who engaged in LTPA equal to or greater than the median had longer life expectancy free of nonfatal CHD (men: 1.5 years [95% CI, 1.0-2.0]; women: 1.6 years [95% CI, 1.1-2.2]), stroke (men: 1.8 years [95% CI, 1.2-2.3]; women: 1.8 years [95% CI, 1.3-2.3]), and HF (men: 1.6 years [95% CI, 1.1-2.1]; women: 1.7 years [95% CI, 1.2-2.2]). Compared with viewing more television, watching less television was associated with longer life expectancy free of CHD, stroke, and HF (≈0.8 year). Conclusions Higher levels of LTPA and less television viewing were associated with longer life expectancy free of CHD, stroke, and HF. Engaging in LTPA and watching less television may increase the number of years lived free of CHD, stroke, and HF.

Obesity and loss of disease-free years owing to major non-communicable diseases: a multicohort study

BACKGROUND

Obesity increases the risk of several chronic diseases, but the extent to which the obesity-related loss of disease-free years varies by lifestyle category and across socioeconomic groups is unclear. We estimated the number of years free from major non-communicable diseases in adults who are overweight and obese, compared with those who are normal weight.

METHODS

We pooled individual-level data on body-mass index (BMI) and non-communicable diseases from men and women with no initial evidence of these diseases in European cohort studies from the Individual-Participant-Data Meta-Analysis in Working Populations consortium. BMI was assessed at baseline (1991-2008) and non-communicable diseases (incident type 2 diabetes, coronary heart disease, stroke, cancer, asthma, and chronic obstructive pulmonary disease) were ascertained via linkage to records from national health registries, repeated medical examinations, or self-report. Disease-free years from age 40 years to 75 years associated with underweight (BMI <18·5 kg/m2), overweight (≥25 kg/m2 to <30 kg/m2), and obesity (class I [mild] ≥30 kg/m2 to <35 kg/m2; class II-III [severe] ≥35 kg/m2) compared with normal weight (≥18·5 kg/m2 to <25 kg/m2) were estimated.

FINDINGS

Of 137 503 participants from ten studies, we excluded 6973 owing to missing data and 10 349 with prevalent disease at baseline, resulting in an analytic sample of 120 181 participants. Of 47 127 men, 211 (0·4%) were underweight, 21 468 (45·6%) normal weight, 20 738 (44·0%) overweight, 3982 (8·4%) class I obese, and 728 (1·5%) class II-III obese. The corresponding numbers among the 73 054 women were 1493 (2·0%), 44 760 (61·3%), 19 553 (26·8%), 5670 (7·8%), and 1578 (2·2%), respectively. During 1 328 873 person-years at risk (mean follow-up 11·5 years [range 6·3-18·6]), 8159 men and 8100 women developed at least one non-communicable disease. Between 40 years and 75 years, the estimated number of disease-free years was 29·3 (95% CI 28·8-29·8) in normal-weight men and 29·4 (28·7-30·0) in normal-weight women. Compared with normal weight, the loss of disease-free years in men was 1·8 (95% CI -1·3 to 4·9) for underweight, 1·1 (0·7 to 1·5) for overweight, 3·9 (2·9 to 4·9) for class I obese, and 8·5 (7·1 to 9·8) for class II-III obese. The corresponding estimates for women were 0·0 (-1·4 to 1·4) for underweight, 1·1 (0·6 to 1·5) for overweight, 2·7 (1·5 to 3·9) for class I obese, and 7·3 (6·1 to 8·6) for class II-III obese. The loss of disease-free years associated with class II-III obesity varied between 7·1 and 10·0 years in subgroups of participants of different socioeconomic level, physical activity level, and smoking habit.

INTERPRETATION

Mild obesity was associated with the loss of one in ten, and severe obesity the loss of one in four potential disease-free years during middle and later adulthood. This increasing loss of disease-free years as obesity becomes more severe occurred in both sexes, among smokers and non-smokers, the physically active and inactive, and across the socioeconomic hierarchy.

FUNDING

NordForsk, UK Medical Research Council, US National Institute on Aging, Academy of Finland, Helsinki Institute of Life Science, and Cancer Research UK.

Physical activity level as a predictor of healthy and chronic disease-free life expectancy between ages 50 and 75

Background

physical activity promotes healthy aging. However, little is known about the relationship between physical activity levels and healthy and chronic disease-free life expectancy (LE). The study aim was to examine healthy and chronic disease-free LE between ages 50 and 75 and across various levels of physical activity by sex and different occupational statuses.

Methods

overall, 34,379 women (mean age 53.2 (SD 2.9) years) and 8,381 men (53.6 (SD 3.2) years) from the Finnish Public Sector study were categorized into five physical activity levels (inactive to vigorously active) according to self-reported physical activity and into three occupational statuses at the first observation point. Partial LE between ages 50 and 75 based on discrete-time multistate life table models was defined using two health indicators: healthy LE based on self-rated health and chronic disease-free LE based on chronic diseases. The average follow-up time for health indicators was 6.8 (SD 5.2) years.

Results

a clear dose-response relationship between higher physical activity levels and increased healthy and chronic disease-free LE in men and women, and within occupational statuses was found. On average, vigorously active men and women lived 6.3 years longer in good health and 2.9 years longer without chronic diseases between ages 50 and 75 compared to inactive individuals. The difference in years in good health between vigorously active and inactive individuals was the largest in individuals with low occupation status (6.7 years).

Conclusion

higher levels of physical activity increase healthy and chronic disease-free years similarly in men and women, but more among persons with low than with high occupational status.

The modelled impact of increases in physical activity: the effect of both increased survival and reduced incidence of disease

Physical activity can affect ‘need’ for healthcare both by reducing the incidence rate of some diseases and by increasing longevity (increasing the time lived at older ages when disease incidence is higher). However, it is common to consider only the first effect, which may overestimate any reduction in need for healthcare. We developed a hybrid micro-simulation lifetable model, which made allowance for both changes in longevity and risk of disease incidence, to estimate the effects of increases in physical activity (all adults meeting guidelines) on measures of healthcare need for diseases for which physical activity is protective. These were compared with estimates made using comparative risk assessment (CRA) methods, which assumed that longevity was fixed. Using the lifetable model, life expectancy increased by 95 days (95% uncertainty intervals: 68–126 days). Estimates of the healthcare need tended to decrease, but the magnitude of the decreases were noticeably smaller than those estimated using CRA methods (e.g. dementia: change in person-years, −0.6%, 95% uncertainty interval −3.7% to +1.6%; change in incident cases, −0.4%, −3.6% to +1.9%; change in person-years (CRA methods), −4.0%, −7.4% to −1.6%). The pattern of results persisted under different scenarios and sensitivity analyses. For most diseases for which physical activity is protective, increases in physical activity are associated with decreases in indices of healthcare need. However, disease onset may be delayed or time lived with disease may increase, such that the decreases in need may be relatively small and less than is sometimes expected.

Body mass index as a predictor of healthy and disease-free life expectancy between ages 50 and 75: a multicohort study

BACKGROUND

While many studies have shown associations between obesity and increased risk of morbidity and mortality, little comparable information is available on how body mass index (BMI) impacts health expectancy. We examined associations of BMI with healthy and chronic disease-free life expectancy in four European cohort studies.

METHODS

Data were drawn from repeated waves of cohort studies in England, Finland, France and Sweden. BMI was categorized into four groups from normal weight (18.5-24.9 kg m^-2) to obesity class II (⩾35 kg m^-2). Health expectancy was estimated with two health indicators: sub-optimal self-rated health and having a chronic disease (cardiovascular disease, cancer, respiratory disease and diabetes). Multistate life table models were used to estimate sex-specific healthy life expectancy and chronic disease-free life expectancy from ages 50 to 75 years for each BMI category.

RESULTS

The proportion of life spent in good perceived health between ages 50 and 75 progressively decreased with increasing BMI from 81% in normal weight men and women to 53% in men and women with class II obesity which corresponds to an average 7-year difference in absolute terms. The proportion of life between ages 50 and 75 years without chronic diseases decreased from 62 and 65% in normal weight men and women and to 29 and 36% in men and women with class II obesity, respectively. This corresponds to an average 9 more years without chronic diseases in normal weight men and 7 more years in normal weight women between ages 50 and 75 years compared to class II obese men and women. No consistent differences were observed between cohorts.

CONCLUSIONS

Excess BMI is associated with substantially shorter healthy and chronic disease-free life expectancy, suggesting that tackling obesity would increase years lived in good health in populations.

Potential health gains and health losses in eleven EU countries attainable through feasible prevalences of the life-style related risk factors alcohol, BMI, and smoking: a quantitative health impact assessment

BACKGROUND

Influencing the life-style risk-factors alcohol, body mass index (BMI), and smoking is an European Union (EU) wide objective of public health policy. The population-level health effects of these risk-factors depend on population specific characteristics and are difficult to quantify without dynamic population health models.

METHODS

For eleven countries-approx. 80 % of the EU-27 population-we used evidence from the publicly available DYNAMO-HIA data-set. For each country the age- and sex-specific risk-factor prevalence and the incidence, prevalence, and excess mortality of nine chronic diseases are utilized; including the corresponding relative risks linking risk-factor exposure causally to disease incidence and all-cause mortality. Applying the DYNAMO-HIA tool, we dynamically project the country-wise potential health gains and losses using feasible, i.e. observed elsewhere, risk-factor prevalence rates as benchmarks. The effects of the "worst practice", "best practice", and the currently observed risk-factor prevalence on population health are quantified and expected changes in life expectancy, morbidity-free life years, disease cases, and cumulative mortality are reported.

RESULTS

Applying the best practice smoking prevalence yields the largest gains in life expectancy with 0.4 years for males and 0.3 year for females (approx. 332,950 and 274,200 deaths postponed, respectively) while the worst practice smoking prevalence also leads to the largest losses with 0.7 years for males and 0.9 year for females (approx. 609,400 and 710,550 lives lost, respectively). Comparing morbidity-free life years, the best practice smoking prevalence shows the highest gains for males with 0.4 years (342,800 less disease cases), whereas for females the best practice BMI prevalence yields the largest gains with 0.7 years (1,075,200 less disease cases).

CONCLUSION

Smoking is still the risk-factor with the largest potential health gains. BMI, however, has comparatively large effects on morbidity. Future research should aim to improve knowledge of how policies can influence and shape individual and aggregated life-style-related risk-factor behavior.

Effect of major lifestyle risk factors, independent and jointly, on life expectancy with and without cardiovascular disease: results from the Consortium on Health and Ageing Network of Cohorts in Europe and the United States (CHANCES)

Seldom have studies taken account of changes in lifestyle habits in the elderly, or investigated their impact on disease-free life expectancy (LE) and LE with cardiovascular disease (CVD). Using data on subjects aged 50+ years from three European cohorts (RCPH, ESTHER and Tromsø), we used multi-state Markov models to calculate the independent and joint effects of smoking, physical activity, obesity and alcohol consumption on LE with and without CVD. Men and women aged 50 years who have a favourable lifestyle (overweight but not obese, light/moderate drinker, non-smoker and participates in vigorous physical activity) lived between 7.4 (in Tromsø men) and 15.7 (in ESTHER women) years longer than those with an unfavourable lifestyle (overweight but not obese, light/moderate drinker, smoker and does not participate in physical activity). The greater part of the extra life years was in terms of “disease-free” years, though a healthy lifestyle was also associated with extra years lived after a CVD event. There are sizeable benefits to LE without CVD and also for survival after CVD onset when people favour a lifestyle characterized by salutary behaviours. Remaining a non-smoker yielded the greatest extra years in overall LE, when compared to the effects of routinely taking physical activity, being overweight but not obese, and drinking in moderation. The majority of the overall LE benefit is in disease free years. Therefore, it is important for policy makers and the public to know that prevention through maintaining a favourable lifestyle is “never too late”.

Exploring the Life Expectancy Increase in Poland in the Context of CVD Mortality Fall: The Risk Assessment Bottom-Up Approach, From Health Outcome to Policies

Life expectancy at birth is considered the best mortality-based summary indicator of the health status of the population and is useful for measuring long-term health changes. The objective of this article was to present the concept of the bottom-up policy risk assessment approach, developed to identify challenges involved in analyzing risk factor reduction policies and in assessing how the related health indicators have changed over time. This article focuses on the reasons of the significant life expectancy prolongation in Poland over the past 2 decades, thus includes policy context. The methodology details a bottom-up risk assessment approach, a chain of relations between the health outcome, risk factors, and health policy, based on Risk Assessment From Policy to Impact Dimension project guidance. A decline in cardiovascular disease mortality was a key factor that followed life expectancy prolongation. Among basic factors, tobacco and alcohol consumption, diet, physical activity, and new treatment technologies were identified. Poor health outcomes of the Polish population at the beginning of 1990s highlighted the need of the implementation of various health promotion programs, legal acts, and more effective public health policies. Evidence-based public health policy needs translating scientific research into policy and practice. The bottom-up case study template can be one of the focal tools in this process. Accountability for the health impact of policies and programs and legitimization of the decisions of policy makers has become one of the key questions nowadays in European countries' decision-making process and in EU public health strategy.

Ageing in the European Union

The ageing of European populations presents health, long-term care, and welfare systems with new challenges. Although reports of ageing as a fundamental threat to the welfare state seem exaggerated, societies have to embrace various policy options to improve the robustness of health, long-term care, and welfare systems in Europe and to help people to stay healthy and active in old age. These policy options include prevention and health promotion, better self-care, increased coordination of care, improved management of hospital admissions and discharges, improved systems of long-term care, and new work and pension arrangements. Ageing of the health workforce is another challenge, and policies will need to be pursued that meet the particular needs of older workers (ie, those aged 50 years or older) while recruiting young practitioners.

Influence of individual and combined healthy behaviours on successful aging

BACKGROUND

Increases in life expectancy make it important to remain healthy for as long as possible. Our objective was to examine the extent to which healthy behaviours in midlife, separately and in combination, predict successful aging.

METHODS

We used a prospective cohort design involving 5100 men and women aged 42-63 years. Participants were free of cancer, coronary artery disease and stroke when their health behaviours were assessed in 1991-1994 as part of the Whitehall II study. We defined healthy behaviours as never smoking, moderate alcohol consumption, physical activity (≥ 2.5 h/wk moderate physical activity or ≥ 1 h/wk vigorous physical activity), and eating fruits and vegetables daily. We defined successful aging, measured over a median 16.3-year follow-up, as good cognitive, physical, respiratory and cardiovascular functioning, in addition to the absence of disability, mental health problems and chronic disease (coronary artery disease, stroke, cancer and diabetes).

RESULTS

At the end of follow-up, 549 participants had died and 953 qualified as aging successfully. Compared with participants who engaged in no healthy behaviours, participants engaging in all 4 healthy behaviours had 3.3 times greater odds of successful aging (95% confidence interval [CI] 2.1-5.1). The association with successful aging was linear, with the odds ratio (OR) per increment of healthy behaviour being 1.3 (95% CI 1.2-1.4; population-attributable risk for 1-4 v. 0 healthy behaviours 47%). When missing data were considered in the analysis, the results were similar to those of our main analysis.

INTERPRETATION

Although individual healthy behaviours are moderately associated with successful aging, their combined impact is substantial. We did not investigate the mechanisms underlying these associations, but we saw clear evidence of the importance of healthy behaviours for successful aging.

[Physical activity and aging: opposing physiologic effects]

The benefits of physical activity in preventing premature mortality have been established by a large set of epidemiological studies. These benefits have been shown both in middle-aged and elderly individuals. Furthermore, the reduction of acute events such as myocardial infarction observed with higher levels of physical activity together with the increase in disease-free life expectancy among the most active individuals supports physical activity's antiaging effect. This review highlights two models supporting this effect. The first model describes the path to frailty and the second explains that immobilization is a stressor which triggers stress-responses responsible for many chronic diseases. Aging reduces the physiological reserve and can lead to frailty when this reserve cannot allow an appropriate adaptation of the aging body to environmental challenges. The components of this physiological reserve can easily be measured by cardiorespiratory testing. Among them are heart rate reserve and VO(2)max, the maximal body oxygen consumption. The opposite effects of exercise training and aging on the physiological reserve are detailed. Sedentary lifestyle accelerates the effects of aging in susceptible individuals. Sedentary lifestyle induces mechanisms which lead to risk factors of chronic diseases and, eventually, to premature death. These inappropriate mechanisms and their consequences constitute the sedentary lifestyle syndrome.

Does physical activity increase life expectancy? A review of the literature

Physical activity reduces many major mortality risk factors including arterial hypertension, diabetes mellitus type 2, dyslipidemia, coronary heart disease, stroke, and cancer. All-cause mortality is decreased by about 30% to 35% in physically active as compared to inactive subjects. The purpose of this paper was to synthesize the literature on life expectancy in relation to physical activity. A systematic PubMed search on life expectancy in physically active and inactive individuals was performed. In addition, articles comparing life expectancy of athletes compared to that of nonathletes were reviewed. Results of 13 studies describing eight different cohorts suggest that regular physical activity is associated with an increase of life expectancy by 0.4 to 6.9 years. Eleven studies included confounding risk factors for mortality and revealed an increase in life expectancy by 0.4 to 4.2 years with regular physical activity. Eleven case control studies on life expectancy in former athletes revealed consistently greater life expectancy in aerobic endurance athletes but inconsistent results for other athletes. None of these studies considered confounding risk factors for mortality. In conclusion, while regular physical activity increases life expectancy, it remains unclear if high-intensity sports activities further increase life expectancy.

Are sirtuins viable targets for improving healthspan and lifespan?

Although the increased lifespan of our populations illustrates the success of modern medicine, the risk of developing many diseases increases exponentially with old age. Caloric restriction is known to retard ageing and delay functional decline as well as the onset of disease in most organisms. Studies have implicated the sirtuins (SIRT1-SIRT7) as mediators of key effects of caloric restriction during ageing. Two unrelated molecules that have been shown to increase SIRT1 activity in some settings, resveratrol and SRT1720, are excellent protectors against metabolic stress in mammals, making SIRT1 a potentially appealing target for therapeutic interventions. This Review covers the current status and controversies surrounding the potential of sirtuins as novel pharmacological targets, with a focus on SIRT1.

Prolonged sitting: is it a distinct coronary heart disease risk factor?

PURPOSE OF REVIEW

Prolonged sitting (sedentary behavior) has deleterious cardiovascular and metabolic correlates; however, little is known about the associations of too much sitting with all-cause and cardiovascular mortality risk. In addition to the adverse effects of total sitting time, the manner in which it is accumulated has also been postulated to be important for cardiovascular health.

RECENT FINDINGS

We describe recent evidence from several research papers published in the last 12-18 months, showing deleterious relationships of sedentary behavior with mortality outcomes. We also explore emerging findings on breaking up sedentary time and its potential beneficial impact on cardiovascular health.

SUMMARY

Consistent independent associations have been observed between sitting time/sedentary behaviors and elevated all-cause and cardiovascular disease mortality risk. Generally, these associations have persisted following adjustment for physical activity. Furthermore, total sedentary time (measured objectively via accelerometer) is detrimentally associated with several cardiovascular risk factors, whereas breaking up sedentary time (independent of total sedentary time and moderate-to-vigorous intensity activity) is beneficially associated. This evidence provides further support to the importance of avoiding prolonged, uninterrupted periods of sitting time for cardiovascular health. However, further evidence from intervention trials is required to establish the causal pathways.

Theories and mechanisms of aging

This article discusses various theories of aging and their relative plausibility related to the human aging process. Structural and physiologic changes of aging are discussed in detail by organ system. Each of the organ systems is discussed when applicable to the various theories of aging. Normal versus abnormal aging is discussed in the context of specific aging processes, with atypical presentations of disease and general links to life expectancy. Life expectancy and lifespan are discussed in the context of advances in medical science and the potential ultimate link to human life span.

Life expectancy and life expectancy with disability of normal weight, overweight, and obese smokers and nonsmokers in Europe

The goal of this study was to estimate life expectancy (LE) and LE with disability (LwD) among normal weight, overweight, and obese smokers and nonsmokers in Western Europe. Data from four waves (1998-2001) of the European Community Household Panel (ECHP) were used; a standardized multipurpose annual longitudinal survey. Self-reported health and socioeconomic information was collected repeatedly using uniform questionnaires for 66,331 individuals in nine countries. Health status was measured in terms of disability in daily activities. Multistate Markov (MSM) models were applied to obtain hazard ratios (HRs) and age-specific transition rates according to BMI and smoking status. Multistate life tables were computed using the predicted transition probabilities to estimate LE and LwD. Significant associations were observed between disability incidence and BMI (HR = 1.15 for overweight, HR = 1.64 for obese, compared to normal weight). The risk of mortality was negatively associated with overweight status among disabled (HR = 0.77). Overweight people had higher LE than people with normal-weight and obesity. Among women, overweight and obese nonsmokers expect 3.6 and 6.1 more years of LwD than normal weight persons, respectively. In contrast, daily smokers expect lower LE but a similar LwD. The same patterns were observed among people with high education and those with low education. To conclude, daily smoking is associated with mortality more than with disability, whereas obesity is associated with disability more than with mortality. The findings suggest that further tobacco control would contribute to increasing LE, while tackling the obesity epidemic is necessary to prevent an expansion of disability.

[Compression of morbidity: a promising approach to alleviate the societal consequences of population ageing?]

There is an urgent need for strategies that alleviate the societal consequences of population ageing. A possible strategy is aiming for compression of morbidity. Some of the initial conditions for a compression of morbidity have been invalidated. This is, the life expectancy has shown a much stronger increase than was expected and the modal age at death has exceeded the age of 85. Additionally, trend studies have found no consistent evidence for a compression of morbidity. At the department of Public Health, we aim at identifying entry-points for a compression. For example, an analysis was performed on potential contributions of changes in exposure to life style factors (smoking, hypertension, physical inactivity and overweight/obesity) to compression of cardiovascular disease, using multi-state life tables with data from the Framingham Heart Study. It was shown that smoking and physical inactivity increased the incidence of cardiovascular disease, as well as mortality with and without cardiovascular disease. Hypertension and overweight mainly increased the incidence of cardiovascular disease and were associated with a shorter lifespan and more years with cardiovascular disease. Interventions on the latter risk factors will therefore increase the life expectancy, but will also result in a compression of morbidity. For policymakers and researchers it is important to find a mix of interventions that lead to a comparable overall effect.