Association of physical activity with all-cause and cardiovascular mortality: a systematic review and meta-analysis (original) (raw)

Journal Article

,

Institute for Social Medicine

, Epidemiology and Health Economics, Charité University Medical Center, Berlin, Germany

Correspondence to Dr Marc Nocon, Institute for Social Medicine, Epidemiology and Health Economics, Charité University Medical Center, Berlin, 10098, Germany Tel: +49 30 450 529 122; fax: +49 30 450 529 902; e-mail: marc.nocon@charite.de

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,

Institute for Social Medicine

, Epidemiology and Health Economics, Charité University Medical Center, Berlin, Germany

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,

Falk Müller-Riemenschneider

Institute for Social Medicine

, Epidemiology and Health Economics, Charité University Medical Center, Berlin, Germany

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,

Institute for Social Medicine

, Epidemiology and Health Economics, Charité University Medical Center, Berlin, Germany

Search for other works by this author on:

,

Institute for Social Medicine

, Epidemiology and Health Economics, Charité University Medical Center, Berlin, Germany

Search for other works by this author on:

Institute for Social Medicine

, Epidemiology and Health Economics, Charité University Medical Center, Berlin, Germany

Search for other works by this author on:

Accepted:

07 December 2007

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Marc Nocon, Theresa Hiemann, Falk Müller-Riemenschneider, Frank Thalau, Stephanie Roll, Stefan N Willich, Association of physical activity with all-cause and cardiovascular mortality: a systematic review and meta-analysis, European journal of cardiovascular prevention and rehabilitation, Volume 15, Issue 3, 1 June 2008, Pages 239–246, https://doi.org/10.1097/HJR.0b013e3282f55e09
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Abstract

Background

Over the past several decades, numerous large cohort studies have attempted to quantify the protective effect of physical activity on cardiovascular and all-cause mortality. The aim of the authors’ review was to provide an up-to-date overview of the study results.

Methods

In a systematic MEDLINE search conducted in May 2007, the authors included cohort studies that assessed the primary preventive impact of physical activity on all-cause and cardiovascular mortality. The authors reported risk reductions on the basis of comparison between the least active and the most active population subgroups, with the least active population subgroup as the reference group. Random-effect models were used for meta-analysis.

Results

A total of 33 studies with 883372 participants were included. Follow-up ranged from 4 years to over 20 years. The majority of studies reported significant risk reductions for physically active participants. Concerning cardiovascular mortality, physical activity was associated with a risk reduction of 35% (95% confidence interval, 30–40%). All-cause mortality was reduced by 33% (95% confidence interval, 28–37%). Studies that used patient questionnaires to assess physical activity reported lower risk reductions than studies that used more objective measures of fitness.

Conclusions

Physical activity is associated with a marked decrease in cardiovascular and all-cause mortality in both men and women, even after adjusting for other relevant risk factors.

Introduction

Physical inactivity increases the risk of developing a variety of diseases, including overweight, diabetes, hypertension, osteoporosis, and depression. Moreover, inactivity has been associated with higher all-cause and cardiovascular mortality [1,2]. Numerous large cohort studies assessed self-reported physical activity, objective measures of physical fitness, activities of daily living, and systematic exercise training to determine the risks associated with a sedentary lifestyle in men and women [1]. According to a study by Mokdad et al. [3], physical inactivity, along with smoking and malnutrition, is one of the most important lifestyle-related risk factors.

Although most studies have reported a significant relative reduction in mortality for physically active participants, the range of benefit has varied considerably. For example, Myers et al. [4] reported a reduction in all-cause mortality of 72% between their most and least fit male participants during 6 years of follow-up, whereas Lee et al. [5] found a risk reduction of only 13%. Risk reduction may also vary depending on adjustment for important covariables such as blood pressure or diabetes. However the extent to which the risk reduction achieved through physical activity is attenuated by adjusting for other important risk factors remains unclear [6,7].

Table 1

Study characteristics

Study Population Sex Age Physical activity assessed by Follow-up in years (mean) Results adjusted for
Arraiz et al. [8] 9792 Men and women 30–69 Fitness test 7 Age, sex, BMI, smoking
Barengo et al. [9] 32677 15853 men; 16824 women 30–59 Self-report 20 Age, study year, BMI, systolic blood pressure, cholesterol, education, smoking, other physical activity
Blair et al. [10]a 9777 Men 20–82 Fitness test 5 Age
Blair et al. [11] 32421 25341 men; 7080 women 20–88 Fitness test 8 Age, smoking, cholesterol, blood pressure, health status
Bucksch [12] 7187 3742 men; 3445 women 30–69 Self-report 16 Age, smoking, BMI, cardiovascular risk factors, alcohol use, diet, chronic disease index, social status
Carlsson et al. [13] 27734 Women 51–83 Self-report 5 Age, smoking, education, number of children, hormone replacement, fruit/vegetable intake, BMI, blood pressure, comorbidity
Church et al. [14] 22167 Men Mean 43 Fitness test 14 Age, examination year, alcohol use, smoking, family history of CVD, cholesterol, BMI, fasting glucose
Davey et al. [15] 6702 Men 40–64 Self-report 25 Age, employment, smoking, BMI, forced expiratory volume
Evenson et al. 2004 [16] 5712 3000 men, 2712 women ≥ 30 Fitness test 24, 26 Age, smoking, education, alcohol use, BMI, race, cholesterol
Fang et al. [17] 9790 3730 men, 6060 women 25–74 Self-report 17 Age, sex, race, family income, education, diabetes, smoking, systolic blood pressure, cholesterol, illnesses affecting eating
Gregg et al. [18] 7553 Women ≥ 65 Self-report 7 Age, smoking, BMI, stroke, diabetes, hypertension, self-rated health status
Hillsdon et al. [19] 10522 Men and women 35–64 Self-report 10 Age, sex, smoking, alcohol use, health status, social class
Hu et al. [20] 80921 Women 30–55 Self-report 24 Age, smoking, family history of CVD, menopausal status, hormone use
Hu et al. [7] 47212 22528 men; 24684 women 25–64 Self-report 18 Age, study year, smoking, systolic blood pressure, cholesterol, BMI, diabetes, education
Kaplan et al. [21] 6131 Men and women 16–94, mean 43 Self-report 28 Age, sex, race, education, health status, social isolation
Katzmarzyk et al. [22] 19223 Men 20–83, mean 43 Fitness test 10 Age, year of examination, alcohol use, smoking, family history of CVD, BMI
Katzmarzyk et al. [23] 5421 Women 20–69 Self-report 12 Age, smoking, alcohol use, waist circumference
Khaw et al. [24] 22191 9984 men; 12207 women 45–79 Self-report 8 Age, BMI, systolic blood pressure, cholesterol, smoking, alcohol use, diabetes, social status
Kohl et al. [25] 8108 Men 20–84, mean 42 Fitness test 8 Age, glycemic status, systolic blood pressure, cholesterol, BMI, family history of CVD, smoking
Kushi et al. [26] 33154 Women 55–69 Self-report 7 Age, age at menarche/menopause/first live birth, parity, smoking, alcohol use, BMI, waist-to-hip ratio, energy intake, oestrogen use, hypertension, diabetes, education, marital status
Lee et al. [5] 17231 Men Mean 46 Self-report 22, 26 Age, smoking, hypertension, diabetes, early parental death
Leon et al. [27] 12138 Men 35–57, mean 46 Self-report 16 Age, education, smoking, cholesterol, diastolic blood pressure, BMI
Matthews et al. [28] 67143 Women 40–70, mean 52 Self-report 6 Age, marital status, education, income, smoking, alcohol use, number of pregnancies, oral contraceptive use, menopausal status, diabetes, hypertension, respiratory disease, chronic hepatitis
Richardson et al. [29] 9611 Men and women 51–61 Self-report 8 Age, sex, race, self-rated health, history of cancer, obesity, CVD risk
Rockhill et al. [30] 80348 Women 30–55 Self-report 14 Age, smoking, alcohol use, height, BMI, hormone use
Schooling et al. [31] 56167 18759 men; 37417 women ≥ 65 Self-report 4 Age, sex, education, alcohol use, smoking, income, BMI
Stevens et al. [32] 5366 2860 men; 2506 women Mean 46 Fitness test 22, 26 Age, education, smoking, alcohol use, diet
Trolle-Lagerros et al. [33] 99099 Women 30–49 Self-report 11 Age, education, BMI, alcohol use, smoking
Vatten et al. [34] 54248 26515 men; 27769 women ≥ 20 Self-report 16 Age, BMI, marital status, education, alcohol use, smoking, blood pressure, blood pressure medication
Wannamethee et al. [35]b 4311 Men 40–59 Self-report 4 Age, smoking, BMI, social class, self-rated health, other physical activity
Wei et al. [36] 25714 normal weight Men Mean 44 Fitness test 10 Age, examination year, BMI, family history of CVD, CVD, diabetes, cholesterol, hypertension, smoking
Weller and Corey [37] 6620 Women ≥ 30 Self-report 7 Age
Wisloff et al. [38] 56072 27143 men; 28929 women Mean 47 Self-report 16 Age, BMI, marital status, education, alcohol use, smoking, blood pressure
Study Population Sex Age Physical activity assessed by Follow-up in years (mean) Results adjusted for
Arraiz et al. [8] 9792 Men and women 30–69 Fitness test 7 Age, sex, BMI, smoking
Barengo et al. [9] 32677 15853 men; 16824 women 30–59 Self-report 20 Age, study year, BMI, systolic blood pressure, cholesterol, education, smoking, other physical activity
Blair et al. [10]a 9777 Men 20–82 Fitness test 5 Age
Blair et al. [11] 32421 25341 men; 7080 women 20–88 Fitness test 8 Age, smoking, cholesterol, blood pressure, health status
Bucksch [12] 7187 3742 men; 3445 women 30–69 Self-report 16 Age, smoking, BMI, cardiovascular risk factors, alcohol use, diet, chronic disease index, social status
Carlsson et al. [13] 27734 Women 51–83 Self-report 5 Age, smoking, education, number of children, hormone replacement, fruit/vegetable intake, BMI, blood pressure, comorbidity
Church et al. [14] 22167 Men Mean 43 Fitness test 14 Age, examination year, alcohol use, smoking, family history of CVD, cholesterol, BMI, fasting glucose
Davey et al. [15] 6702 Men 40–64 Self-report 25 Age, employment, smoking, BMI, forced expiratory volume
Evenson et al. 2004 [16] 5712 3000 men, 2712 women ≥ 30 Fitness test 24, 26 Age, smoking, education, alcohol use, BMI, race, cholesterol
Fang et al. [17] 9790 3730 men, 6060 women 25–74 Self-report 17 Age, sex, race, family income, education, diabetes, smoking, systolic blood pressure, cholesterol, illnesses affecting eating
Gregg et al. [18] 7553 Women ≥ 65 Self-report 7 Age, smoking, BMI, stroke, diabetes, hypertension, self-rated health status
Hillsdon et al. [19] 10522 Men and women 35–64 Self-report 10 Age, sex, smoking, alcohol use, health status, social class
Hu et al. [20] 80921 Women 30–55 Self-report 24 Age, smoking, family history of CVD, menopausal status, hormone use
Hu et al. [7] 47212 22528 men; 24684 women 25–64 Self-report 18 Age, study year, smoking, systolic blood pressure, cholesterol, BMI, diabetes, education
Kaplan et al. [21] 6131 Men and women 16–94, mean 43 Self-report 28 Age, sex, race, education, health status, social isolation
Katzmarzyk et al. [22] 19223 Men 20–83, mean 43 Fitness test 10 Age, year of examination, alcohol use, smoking, family history of CVD, BMI
Katzmarzyk et al. [23] 5421 Women 20–69 Self-report 12 Age, smoking, alcohol use, waist circumference
Khaw et al. [24] 22191 9984 men; 12207 women 45–79 Self-report 8 Age, BMI, systolic blood pressure, cholesterol, smoking, alcohol use, diabetes, social status
Kohl et al. [25] 8108 Men 20–84, mean 42 Fitness test 8 Age, glycemic status, systolic blood pressure, cholesterol, BMI, family history of CVD, smoking
Kushi et al. [26] 33154 Women 55–69 Self-report 7 Age, age at menarche/menopause/first live birth, parity, smoking, alcohol use, BMI, waist-to-hip ratio, energy intake, oestrogen use, hypertension, diabetes, education, marital status
Lee et al. [5] 17231 Men Mean 46 Self-report 22, 26 Age, smoking, hypertension, diabetes, early parental death
Leon et al. [27] 12138 Men 35–57, mean 46 Self-report 16 Age, education, smoking, cholesterol, diastolic blood pressure, BMI
Matthews et al. [28] 67143 Women 40–70, mean 52 Self-report 6 Age, marital status, education, income, smoking, alcohol use, number of pregnancies, oral contraceptive use, menopausal status, diabetes, hypertension, respiratory disease, chronic hepatitis
Richardson et al. [29] 9611 Men and women 51–61 Self-report 8 Age, sex, race, self-rated health, history of cancer, obesity, CVD risk
Rockhill et al. [30] 80348 Women 30–55 Self-report 14 Age, smoking, alcohol use, height, BMI, hormone use
Schooling et al. [31] 56167 18759 men; 37417 women ≥ 65 Self-report 4 Age, sex, education, alcohol use, smoking, income, BMI
Stevens et al. [32] 5366 2860 men; 2506 women Mean 46 Fitness test 22, 26 Age, education, smoking, alcohol use, diet
Trolle-Lagerros et al. [33] 99099 Women 30–49 Self-report 11 Age, education, BMI, alcohol use, smoking
Vatten et al. [34] 54248 26515 men; 27769 women ≥ 20 Self-report 16 Age, BMI, marital status, education, alcohol use, smoking, blood pressure, blood pressure medication
Wannamethee et al. [35]b 4311 Men 40–59 Self-report 4 Age, smoking, BMI, social class, self-rated health, other physical activity
Wei et al. [36] 25714 normal weight Men Mean 44 Fitness test 10 Age, examination year, BMI, family history of CVD, CVD, diabetes, cholesterol, hypertension, smoking
Weller and Corey [37] 6620 Women ≥ 30 Self-report 7 Age
Wisloff et al. [38] 56072 27143 men; 28929 women Mean 47 Self-report 16 Age, BMI, marital status, education, alcohol use, smoking, blood pressure

aOutcome cardiovascular mortality; all-cause mortality was extracted from the larger 1996 study by Blair. b _N_=4311 men with no history of coronary heart disease. BMI, body mass index; CVD, cardiovascular disease.

Table 1

Study characteristics

Study Population Sex Age Physical activity assessed by Follow-up in years (mean) Results adjusted for
Arraiz et al. [8] 9792 Men and women 30–69 Fitness test 7 Age, sex, BMI, smoking
Barengo et al. [9] 32677 15853 men; 16824 women 30–59 Self-report 20 Age, study year, BMI, systolic blood pressure, cholesterol, education, smoking, other physical activity
Blair et al. [10]a 9777 Men 20–82 Fitness test 5 Age
Blair et al. [11] 32421 25341 men; 7080 women 20–88 Fitness test 8 Age, smoking, cholesterol, blood pressure, health status
Bucksch [12] 7187 3742 men; 3445 women 30–69 Self-report 16 Age, smoking, BMI, cardiovascular risk factors, alcohol use, diet, chronic disease index, social status
Carlsson et al. [13] 27734 Women 51–83 Self-report 5 Age, smoking, education, number of children, hormone replacement, fruit/vegetable intake, BMI, blood pressure, comorbidity
Church et al. [14] 22167 Men Mean 43 Fitness test 14 Age, examination year, alcohol use, smoking, family history of CVD, cholesterol, BMI, fasting glucose
Davey et al. [15] 6702 Men 40–64 Self-report 25 Age, employment, smoking, BMI, forced expiratory volume
Evenson et al. 2004 [16] 5712 3000 men, 2712 women ≥ 30 Fitness test 24, 26 Age, smoking, education, alcohol use, BMI, race, cholesterol
Fang et al. [17] 9790 3730 men, 6060 women 25–74 Self-report 17 Age, sex, race, family income, education, diabetes, smoking, systolic blood pressure, cholesterol, illnesses affecting eating
Gregg et al. [18] 7553 Women ≥ 65 Self-report 7 Age, smoking, BMI, stroke, diabetes, hypertension, self-rated health status
Hillsdon et al. [19] 10522 Men and women 35–64 Self-report 10 Age, sex, smoking, alcohol use, health status, social class
Hu et al. [20] 80921 Women 30–55 Self-report 24 Age, smoking, family history of CVD, menopausal status, hormone use
Hu et al. [7] 47212 22528 men; 24684 women 25–64 Self-report 18 Age, study year, smoking, systolic blood pressure, cholesterol, BMI, diabetes, education
Kaplan et al. [21] 6131 Men and women 16–94, mean 43 Self-report 28 Age, sex, race, education, health status, social isolation
Katzmarzyk et al. [22] 19223 Men 20–83, mean 43 Fitness test 10 Age, year of examination, alcohol use, smoking, family history of CVD, BMI
Katzmarzyk et al. [23] 5421 Women 20–69 Self-report 12 Age, smoking, alcohol use, waist circumference
Khaw et al. [24] 22191 9984 men; 12207 women 45–79 Self-report 8 Age, BMI, systolic blood pressure, cholesterol, smoking, alcohol use, diabetes, social status
Kohl et al. [25] 8108 Men 20–84, mean 42 Fitness test 8 Age, glycemic status, systolic blood pressure, cholesterol, BMI, family history of CVD, smoking
Kushi et al. [26] 33154 Women 55–69 Self-report 7 Age, age at menarche/menopause/first live birth, parity, smoking, alcohol use, BMI, waist-to-hip ratio, energy intake, oestrogen use, hypertension, diabetes, education, marital status
Lee et al. [5] 17231 Men Mean 46 Self-report 22, 26 Age, smoking, hypertension, diabetes, early parental death
Leon et al. [27] 12138 Men 35–57, mean 46 Self-report 16 Age, education, smoking, cholesterol, diastolic blood pressure, BMI
Matthews et al. [28] 67143 Women 40–70, mean 52 Self-report 6 Age, marital status, education, income, smoking, alcohol use, number of pregnancies, oral contraceptive use, menopausal status, diabetes, hypertension, respiratory disease, chronic hepatitis
Richardson et al. [29] 9611 Men and women 51–61 Self-report 8 Age, sex, race, self-rated health, history of cancer, obesity, CVD risk
Rockhill et al. [30] 80348 Women 30–55 Self-report 14 Age, smoking, alcohol use, height, BMI, hormone use
Schooling et al. [31] 56167 18759 men; 37417 women ≥ 65 Self-report 4 Age, sex, education, alcohol use, smoking, income, BMI
Stevens et al. [32] 5366 2860 men; 2506 women Mean 46 Fitness test 22, 26 Age, education, smoking, alcohol use, diet
Trolle-Lagerros et al. [33] 99099 Women 30–49 Self-report 11 Age, education, BMI, alcohol use, smoking
Vatten et al. [34] 54248 26515 men; 27769 women ≥ 20 Self-report 16 Age, BMI, marital status, education, alcohol use, smoking, blood pressure, blood pressure medication
Wannamethee et al. [35]b 4311 Men 40–59 Self-report 4 Age, smoking, BMI, social class, self-rated health, other physical activity
Wei et al. [36] 25714 normal weight Men Mean 44 Fitness test 10 Age, examination year, BMI, family history of CVD, CVD, diabetes, cholesterol, hypertension, smoking
Weller and Corey [37] 6620 Women ≥ 30 Self-report 7 Age
Wisloff et al. [38] 56072 27143 men; 28929 women Mean 47 Self-report 16 Age, BMI, marital status, education, alcohol use, smoking, blood pressure
Study Population Sex Age Physical activity assessed by Follow-up in years (mean) Results adjusted for
Arraiz et al. [8] 9792 Men and women 30–69 Fitness test 7 Age, sex, BMI, smoking
Barengo et al. [9] 32677 15853 men; 16824 women 30–59 Self-report 20 Age, study year, BMI, systolic blood pressure, cholesterol, education, smoking, other physical activity
Blair et al. [10]a 9777 Men 20–82 Fitness test 5 Age
Blair et al. [11] 32421 25341 men; 7080 women 20–88 Fitness test 8 Age, smoking, cholesterol, blood pressure, health status
Bucksch [12] 7187 3742 men; 3445 women 30–69 Self-report 16 Age, smoking, BMI, cardiovascular risk factors, alcohol use, diet, chronic disease index, social status
Carlsson et al. [13] 27734 Women 51–83 Self-report 5 Age, smoking, education, number of children, hormone replacement, fruit/vegetable intake, BMI, blood pressure, comorbidity
Church et al. [14] 22167 Men Mean 43 Fitness test 14 Age, examination year, alcohol use, smoking, family history of CVD, cholesterol, BMI, fasting glucose
Davey et al. [15] 6702 Men 40–64 Self-report 25 Age, employment, smoking, BMI, forced expiratory volume
Evenson et al. 2004 [16] 5712 3000 men, 2712 women ≥ 30 Fitness test 24, 26 Age, smoking, education, alcohol use, BMI, race, cholesterol
Fang et al. [17] 9790 3730 men, 6060 women 25–74 Self-report 17 Age, sex, race, family income, education, diabetes, smoking, systolic blood pressure, cholesterol, illnesses affecting eating
Gregg et al. [18] 7553 Women ≥ 65 Self-report 7 Age, smoking, BMI, stroke, diabetes, hypertension, self-rated health status
Hillsdon et al. [19] 10522 Men and women 35–64 Self-report 10 Age, sex, smoking, alcohol use, health status, social class
Hu et al. [20] 80921 Women 30–55 Self-report 24 Age, smoking, family history of CVD, menopausal status, hormone use
Hu et al. [7] 47212 22528 men; 24684 women 25–64 Self-report 18 Age, study year, smoking, systolic blood pressure, cholesterol, BMI, diabetes, education
Kaplan et al. [21] 6131 Men and women 16–94, mean 43 Self-report 28 Age, sex, race, education, health status, social isolation
Katzmarzyk et al. [22] 19223 Men 20–83, mean 43 Fitness test 10 Age, year of examination, alcohol use, smoking, family history of CVD, BMI
Katzmarzyk et al. [23] 5421 Women 20–69 Self-report 12 Age, smoking, alcohol use, waist circumference
Khaw et al. [24] 22191 9984 men; 12207 women 45–79 Self-report 8 Age, BMI, systolic blood pressure, cholesterol, smoking, alcohol use, diabetes, social status
Kohl et al. [25] 8108 Men 20–84, mean 42 Fitness test 8 Age, glycemic status, systolic blood pressure, cholesterol, BMI, family history of CVD, smoking
Kushi et al. [26] 33154 Women 55–69 Self-report 7 Age, age at menarche/menopause/first live birth, parity, smoking, alcohol use, BMI, waist-to-hip ratio, energy intake, oestrogen use, hypertension, diabetes, education, marital status
Lee et al. [5] 17231 Men Mean 46 Self-report 22, 26 Age, smoking, hypertension, diabetes, early parental death
Leon et al. [27] 12138 Men 35–57, mean 46 Self-report 16 Age, education, smoking, cholesterol, diastolic blood pressure, BMI
Matthews et al. [28] 67143 Women 40–70, mean 52 Self-report 6 Age, marital status, education, income, smoking, alcohol use, number of pregnancies, oral contraceptive use, menopausal status, diabetes, hypertension, respiratory disease, chronic hepatitis
Richardson et al. [29] 9611 Men and women 51–61 Self-report 8 Age, sex, race, self-rated health, history of cancer, obesity, CVD risk
Rockhill et al. [30] 80348 Women 30–55 Self-report 14 Age, smoking, alcohol use, height, BMI, hormone use
Schooling et al. [31] 56167 18759 men; 37417 women ≥ 65 Self-report 4 Age, sex, education, alcohol use, smoking, income, BMI
Stevens et al. [32] 5366 2860 men; 2506 women Mean 46 Fitness test 22, 26 Age, education, smoking, alcohol use, diet
Trolle-Lagerros et al. [33] 99099 Women 30–49 Self-report 11 Age, education, BMI, alcohol use, smoking
Vatten et al. [34] 54248 26515 men; 27769 women ≥ 20 Self-report 16 Age, BMI, marital status, education, alcohol use, smoking, blood pressure, blood pressure medication
Wannamethee et al. [35]b 4311 Men 40–59 Self-report 4 Age, smoking, BMI, social class, self-rated health, other physical activity
Wei et al. [36] 25714 normal weight Men Mean 44 Fitness test 10 Age, examination year, BMI, family history of CVD, CVD, diabetes, cholesterol, hypertension, smoking
Weller and Corey [37] 6620 Women ≥ 30 Self-report 7 Age
Wisloff et al. [38] 56072 27143 men; 28929 women Mean 47 Self-report 16 Age, BMI, marital status, education, alcohol use, smoking, blood pressure

aOutcome cardiovascular mortality; all-cause mortality was extracted from the larger 1996 study by Blair. b _N_=4311 men with no history of coronary heart disease. BMI, body mass index; CVD, cardiovascular disease.

The aim of this systematic review was therefore to summarise the results of the largest cohort studies that examine the effects of physical activity on cardiovascular and all-cause mortality.

Methods

In a systematic MEDLINE search conducted in May 2007, the authors identified prospective cohort studies that assessed the impact of physical activity on all-cause and cardiovascular mortality. Studies analysing populations with a history of cardiovascular or other serious diseases were excluded. To be included in the authors’ review, studies needed to be published in English or German and have a minimum population size of 5000 and a minimum follow-up of 3 years. The authors reported risk reductions on the basis of comparison between the least active and the most active population subgroups, with the least active population subgroup as the reference group. In cases where results were adjusted for relevant variables in addition to age, the authors selected the results of the most extensively adjusted models.

Meta-analyses were performed using a generic inverse variance approach with RevMan version 4.2 (The Cochrane Collaboration, Copenhagen, Denmark). Funnel plots were used to assess publication bias. The results of the meta-analysis were presented using forest plots stratified according to the mean by which physical activity had been assessed (i.e. self-reported or objectively measured). Random-effect models were used to pool study results. Heterogeneity was assessed using χ2 and I methods. The authors performed sensitivity and subgroup analyses to determine the impact of sex, the number of variables in the final model, and the number of physical activity categories.

Results

The authors’ MEDLINE search yielded 1768 articles, 1469 of which were excluded on the basis of a review of the title and the abstract. The remaining 299 studies were analysed in greater detail, and 33 studies fulfilled all inclusion criteria. The main study characteristics are presented in Table 1. The studies ultimately included in the authors’ analysis published between 1992 and 2007, had a total of 883372 participants, and included a roughly equal number of men and women (not all studies provided information on the number of men and women in their samples). The follow-up period in the included studies ranged from 4 years to more than 20 years. A total of nine studies used a fitness test (usually a treadmill test) to assess physical activity, and 24 studies used patient questionnaires. Most studies reported results adjusted for other known risk factors such as hypertension, high cholesterol, and obesity, and 15 studies also reported results for parsimonious models (usually adjusted only for age).

Funnel plots for cardiovascular and all-cause mortality are presented in Figs 1 and 2. For cardiovascular mortality, the distribution of studies is not symmetrical. Although the majority of studies is grouped around the pooled effect, some studies reported larger risk reductions, which is an indicator of publication bias. All studies reporting larger risk reductions were, however, based on objective fitness tests and had less precise effect estimates. The funnel plot for all-cause mortality shows similar nonsymmetrical distributions, though outliers are closer to the pooled estimate than in Fig. 1. Here, too, studies based on objective fitness tests tended to report larger risk reductions.

Associations between physical activity and cardiovascular mortality are presented in Fig. 3. Of all the studies included in the authors’ analysis, five reported nonsignificant results and 26 reported statistically significant risk reductions. Reductions in risk ranged from 11 to 81%. Most studies reported a risk reduction of 30–50%. Risk reductions were found for both men and women.

Funnel plot for physical activity and cardiovascular mortality.

Fig. 1

Funnel plot for physical activity and cardiovascular mortality.

Funnel plot for physical activity and all-cause mortality.

Fig. 2

Funnel plot for physical activity and all-cause mortality.

Relative risk of cardiovascular mortality in physically active versus physically inactive participants (fully adjusted models).

Fig. 3

Relative risk of cardiovascular mortality in physically active versus physically inactive participants (fully adjusted models).

The overall pooled risk reduction was 35%. Studies that used a fitness test to assess physical activity reported larger risk reductions than studies based on self-reported activity (57 vs. 30%).

The results were similar for the association between physical activity and all-cause mortality (Fig. 4). Here, the reductions in risk ranged from 2 to 61%, with 33 of the 35 results being significant. The overall pooled risk reduction was 33%. Again, the largest reductions were found in studies that used a fitness test to assess physical activity (41 vs. 29%).

Sensitivity and subgroup analyses are presented in Table 2. Overall, 15 studies reported age-adjusted results in addition to fully adjusted models. The age-adjusted risk reductions were always larger than the fully adjusted reductions. Stratifying the fitness status of the study populations into more categories (e.g., five instead of three fitness categories) increased the risk reductions moderately. The overall results were similar in men and women. After stratifying the data according to the method that had been used to assess physical activity (i.e. by self-reported or objectively measured data), the risk reductions associated with physical activity were larger for women than for men (Table 2).

Relative risk of all-cause mortality in physically active versus physically inactive participants (fully adjusted models).

Fig. 4

Relative risk of all-cause mortality in physically active versus physically inactive participants (fully adjusted models).

Table 2

Sensitivity/subgroup analyses for physical activity and cardiovascular/all-cause mortality

Fitness test Self-report Total
Cardiovascular mortality
Only age adjusted
Relative risk (95% CI) 0.27 (0.20–0.36) 0.59 (0.53–0.66) 0.53 (0.46–0.61)
Number of studies _N_=3 _N_=10 _N_=13
Fitness categories compared < =3
Relative risk (95% CI) 0.49 (0.36–0.68) 0.69 (0.61–0.78) 0.66 (0.59–0.74)
Number of studies _N_=4 _N_=9 _N_=13
Fitness categories compared >3
Relative risk (95% CI) 0.37 (0.23–0.60) 0.70 (0.63–0.79) 0.65 (0.59–0.72)
Number of studies _N_=6 _N_=12 _N_=18
Men
Relative risk (95% CI) 0.48 (0.36–0.64) 0.74 (0.70–0.79) 0.65 (0.57–0.72)
Number of studies _N_=7 _N_=8 _N_=15
Women
Relative risk (95% CI) 0.31 (0.17–0.56) 0.65 (0.58–0.72) 0.63 (0.56–0.71)
Number of studies _N_=2 _N_=10 _N_=12
All-cause mortality
Only age-adjusted
Relative risk (95% CI) 0.46 (0.38–0.55) 0.60 (0.54–0.67) 0.59 (0.53–0.65)
Number of studies _N_=3 _N_=16 _N_=19
Fitness categories compared <=3
Relative risk (95% CI) 0.60 (0.52–0.69) 0.73 (0.67–0.80) 0.69 (0.64–0.75)
Number of studies _N_=6 _N_=12 _N_=18
Fitness categories compared >3
Relative risk (95% CI) 0.55 (0.46–0.66) 0.67 (0.60–0.76) 0.65 (0.58–0.72)
Number of studies _N_=4 _N_=13 _N_=17
Men
Relative risk (95% CI) 0.61 (0.55–0.68) 0.78 (0.70–0.68) 0.70 (0.64–0.77)
Number of studies _N_=7 _N_=8 _N_=15
Women
Relative risk (95% CI) 0.49 (0.38–0.62) 0.65 (0.59–0.73) 0.63 (0.57–0.70)
Number of studies _N_=3 _N_=13 _N_=16
Fitness test Self-report Total
Cardiovascular mortality
Only age adjusted
Relative risk (95% CI) 0.27 (0.20–0.36) 0.59 (0.53–0.66) 0.53 (0.46–0.61)
Number of studies _N_=3 _N_=10 _N_=13
Fitness categories compared < =3
Relative risk (95% CI) 0.49 (0.36–0.68) 0.69 (0.61–0.78) 0.66 (0.59–0.74)
Number of studies _N_=4 _N_=9 _N_=13
Fitness categories compared >3
Relative risk (95% CI) 0.37 (0.23–0.60) 0.70 (0.63–0.79) 0.65 (0.59–0.72)
Number of studies _N_=6 _N_=12 _N_=18
Men
Relative risk (95% CI) 0.48 (0.36–0.64) 0.74 (0.70–0.79) 0.65 (0.57–0.72)
Number of studies _N_=7 _N_=8 _N_=15
Women
Relative risk (95% CI) 0.31 (0.17–0.56) 0.65 (0.58–0.72) 0.63 (0.56–0.71)
Number of studies _N_=2 _N_=10 _N_=12
All-cause mortality
Only age-adjusted
Relative risk (95% CI) 0.46 (0.38–0.55) 0.60 (0.54–0.67) 0.59 (0.53–0.65)
Number of studies _N_=3 _N_=16 _N_=19
Fitness categories compared <=3
Relative risk (95% CI) 0.60 (0.52–0.69) 0.73 (0.67–0.80) 0.69 (0.64–0.75)
Number of studies _N_=6 _N_=12 _N_=18
Fitness categories compared >3
Relative risk (95% CI) 0.55 (0.46–0.66) 0.67 (0.60–0.76) 0.65 (0.58–0.72)
Number of studies _N_=4 _N_=13 _N_=17
Men
Relative risk (95% CI) 0.61 (0.55–0.68) 0.78 (0.70–0.68) 0.70 (0.64–0.77)
Number of studies _N_=7 _N_=8 _N_=15
Women
Relative risk (95% CI) 0.49 (0.38–0.62) 0.65 (0.59–0.73) 0.63 (0.57–0.70)
Number of studies _N_=3 _N_=13 _N_=16

Table 2

Sensitivity/subgroup analyses for physical activity and cardiovascular/all-cause mortality

Fitness test Self-report Total
Cardiovascular mortality
Only age adjusted
Relative risk (95% CI) 0.27 (0.20–0.36) 0.59 (0.53–0.66) 0.53 (0.46–0.61)
Number of studies _N_=3 _N_=10 _N_=13
Fitness categories compared < =3
Relative risk (95% CI) 0.49 (0.36–0.68) 0.69 (0.61–0.78) 0.66 (0.59–0.74)
Number of studies _N_=4 _N_=9 _N_=13
Fitness categories compared >3
Relative risk (95% CI) 0.37 (0.23–0.60) 0.70 (0.63–0.79) 0.65 (0.59–0.72)
Number of studies _N_=6 _N_=12 _N_=18
Men
Relative risk (95% CI) 0.48 (0.36–0.64) 0.74 (0.70–0.79) 0.65 (0.57–0.72)
Number of studies _N_=7 _N_=8 _N_=15
Women
Relative risk (95% CI) 0.31 (0.17–0.56) 0.65 (0.58–0.72) 0.63 (0.56–0.71)
Number of studies _N_=2 _N_=10 _N_=12
All-cause mortality
Only age-adjusted
Relative risk (95% CI) 0.46 (0.38–0.55) 0.60 (0.54–0.67) 0.59 (0.53–0.65)
Number of studies _N_=3 _N_=16 _N_=19
Fitness categories compared <=3
Relative risk (95% CI) 0.60 (0.52–0.69) 0.73 (0.67–0.80) 0.69 (0.64–0.75)
Number of studies _N_=6 _N_=12 _N_=18
Fitness categories compared >3
Relative risk (95% CI) 0.55 (0.46–0.66) 0.67 (0.60–0.76) 0.65 (0.58–0.72)
Number of studies _N_=4 _N_=13 _N_=17
Men
Relative risk (95% CI) 0.61 (0.55–0.68) 0.78 (0.70–0.68) 0.70 (0.64–0.77)
Number of studies _N_=7 _N_=8 _N_=15
Women
Relative risk (95% CI) 0.49 (0.38–0.62) 0.65 (0.59–0.73) 0.63 (0.57–0.70)
Number of studies _N_=3 _N_=13 _N_=16
Fitness test Self-report Total
Cardiovascular mortality
Only age adjusted
Relative risk (95% CI) 0.27 (0.20–0.36) 0.59 (0.53–0.66) 0.53 (0.46–0.61)
Number of studies _N_=3 _N_=10 _N_=13
Fitness categories compared < =3
Relative risk (95% CI) 0.49 (0.36–0.68) 0.69 (0.61–0.78) 0.66 (0.59–0.74)
Number of studies _N_=4 _N_=9 _N_=13
Fitness categories compared >3
Relative risk (95% CI) 0.37 (0.23–0.60) 0.70 (0.63–0.79) 0.65 (0.59–0.72)
Number of studies _N_=6 _N_=12 _N_=18
Men
Relative risk (95% CI) 0.48 (0.36–0.64) 0.74 (0.70–0.79) 0.65 (0.57–0.72)
Number of studies _N_=7 _N_=8 _N_=15
Women
Relative risk (95% CI) 0.31 (0.17–0.56) 0.65 (0.58–0.72) 0.63 (0.56–0.71)
Number of studies _N_=2 _N_=10 _N_=12
All-cause mortality
Only age-adjusted
Relative risk (95% CI) 0.46 (0.38–0.55) 0.60 (0.54–0.67) 0.59 (0.53–0.65)
Number of studies _N_=3 _N_=16 _N_=19
Fitness categories compared <=3
Relative risk (95% CI) 0.60 (0.52–0.69) 0.73 (0.67–0.80) 0.69 (0.64–0.75)
Number of studies _N_=6 _N_=12 _N_=18
Fitness categories compared >3
Relative risk (95% CI) 0.55 (0.46–0.66) 0.67 (0.60–0.76) 0.65 (0.58–0.72)
Number of studies _N_=4 _N_=13 _N_=17
Men
Relative risk (95% CI) 0.61 (0.55–0.68) 0.78 (0.70–0.68) 0.70 (0.64–0.77)
Number of studies _N_=7 _N_=8 _N_=15
Women
Relative risk (95% CI) 0.49 (0.38–0.62) 0.65 (0.59–0.73) 0.63 (0.57–0.70)
Number of studies _N_=3 _N_=13 _N_=16

Discussion

Physical activity is associated with a marked decrease in cardiovascular and all-cause mortality. Most studies included in the authors’ meta-analysis reported risk reductions of 30–50% for cardiovascular mortality and of 20–50% for all-cause mortality, with pooled risk reductions of 35% for the former and 33% for the latter. These results are based on studies including a total of nearly 900000 participants.

Most of these findings were based on regression models adjusted for important risk factors such as hypertension, hypercholesterolemia, and diabetes, which themselves are associated with physical inactivity. As a result, the risk reductions reported were rather conservative. Adjusting only for age, increased the already large risk reductions for cardiovascular mortality from 35 to 47% and for all-cause mortality from 33 to 41%. Accordingly, the largest reductions in the risk of cardiovascular mortality were reported by the two studies that did not adjust for important confounding variables [8,10]. In one study [7], including these variables attenuated the risk reduction for all-cause mortality compared to a model adjusted only for age by 6% for women and 10% for men, and for cardiovascular mortality by 8% for women and 13% for men.

Both men and women benefited from physical activity. According to the authors’ subgroup analyses, risk reductions were larger for women than for men after stratifying the populations according to the method that had been used to assess physical activity. With regard to age, most studies in this review focused on middle-aged populations. Three studies [18,26,31] included older participants and reported similar decreases in mortality.

Although the large majority of studies reported that physical activity had protective effects on both cardiovascular and all-cause mortality, the risk reductions varied considerably. The most important reason for heterogeneity was the differing methods used to assess physical activity. The authors included studies that assessed physical fitness (i.e. a physiological state measured by treadmill tests) as well as studies that relied on patient self-reports of the duration and intensity of physical activities. Studies with a more objective means of assessment tended to report larger risk reductions. Accordingly, a study by Myers et al. [4], which directly compared both methods found that exercise testing outperformed self-reported physical activity in predicting mortality. It seems likely that participants overestimated their levels of physical activity in self-reports, thus minimising the true protective effect. However, even studies based on the less reliable self-reported measures of activity have shown marked protective effects on mortality.

The authors’ study has several important limitations. Based on the authors’ inclusion and exclusion criteria, a bias in the selection of studies is possible. The authors included only large studies with more than 5000 participants. Though this was an arbitrary cut-off, the large number of studies that fulfilled this criterion (i.e. with a total of nearly 900000 participants) and the overall homogeneity in the direction of effects support the validity of the authors’ findings. Another limitation is that the participants were not classified into distinct activity groups in a homogenous manner across the studies, especially when classification was based on patient questionnaires. Moreover, the number of activity categories differed across studies. Whereas most studies compared three physical activity groups (e.g. low, moderate, and high), some studies categorized the populations into four or five subgroups, thus increasing the range between the least and most active groups. Including only studies that compared three distinct activity groups, however, had only small effects on overall risk reductions.

These results once again confirm the impressive protective effect of physical activity. Despite this knowledge, a large majority of individuals still lead a primarily sedentary life. Numerous studies have addressed the question of how to promote physical activity [39]. Positive results have been shown for information campaigns, behavioural and social interventions, and environmental interventions, such as providing easy access to sports or exercise facilities. The key is to translate these findings into permanent public health efforts.

Acknowledgements

Competing interests: none.

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