Current Nutrition Reports

, Volume 2, Issue 2, pp 113–125

Dietary Patterns, Smoking, and Cardiovascular Diseases: A Complex Association

Dietary Patterns and Behavior (LM Steffen, Section Editor)

DOI: 10.1007/s13668-013-0043-5

Cite this article as:
Kimokoti, R.W. & Newby, P.K. Curr Nutr Rep (2013) 2: 113. doi:10.1007/s13668-013-0043-5

Abstract

Diet and cigarette smoking are key determinants of cardiovascular diseases (CVD). The associations of some nutrients/foods with CVD are unclear, however, and the dietary pattern approach may better inform the relationships. Furthermore, diet and smoking often occur together as part of lifestyle patterns. In this article, studies that evaluated the associations of dietary patterns and smoking status with CVD as well as relationships between lifestyle patterns and CVD were reviewed. Evidence supports the protective role of plant-based dietary patterns for coronary artery disease (CAD) and cardiovascular mortality among nonsmokers and smokers. The interrelationships of dietary patterns and smoking status on subclinical CVD, stroke, hypertension, heart failure, and peripheral arterial disease are inconclusive. Dietary patterns high in refined grains, meats, and sugar-sweetened beverages are harmful, especially for smokers. A healthy lifestyle protects against CAD, hypertension, and cardiovascular mortality, and probably stroke. More prospective studies in diverse populations would be beneficial.

Keywords

Cardiovascular diseasesDiet qualityDietary patternLifestyle patternPreventionSmoking

Introduction

Cardiovascular diseases (CVD) remain the leading cause of morbidity and mortality globally accounting for an estimated 12 % of the global disease burden [1••] and approximately US$863 billion in healthcare costs [2•, 3]. Approximately one-third of deaths in adults both globally and in the United States are attributable to CVD [2•, 4•].

Diet is a key determinant of CVD, and a large body of literature has examined the impact of the roles of individual foods, nutrients, and beverages [57]. The Global Burden of Disease Study 2010 found that dietary factors that contributed the most to the global CVD burden were diets low in fruits and high in sodium as well as those low in nuts and seeds, whole grains, vegetables, docosahexaenoic acid, and eicosapentaenoic acid [8•]. In the United States, diets high in salt and trans fatty acids and low in omega-3 fatty acids were the most prevalent factors in 2005 [9]. While there is strong evidence for the cardioprotective effects of fruits, vegetables, whole grains, nuts, omega-3 fatty acids, and moderate alcohol intake and harmful effects of trans fatty acids and high salt intake [1012], evidence for the associations of saturated fatty acids, monounsaturated fatty acids, and linoleic acid with CVD is inconclusive due in part to collinearity among the lipids [11, 1315], which is difficult to examine in “single nutrient” studies. Challenges like these have led to the growing appreciation for considering dietary patterns in nutritional epidemiologic research when examining associations between diet and health outcomes. The dietary pattern approach, which considers the cumulative effects and interactions of nutrients and foods as well as biological interactions among nutrients/foods and other metabolic factors, has emerged as an alternative and complementary approach to the conventional single nutrient/food analysis and is strategic in guiding nutrition policy [6, 7, 16, 17••, 18].

Smoking is an additional lifestyle variable associated with CVD, and tobacco use is the single major preventable cause of mortality, contributing to approximately 10 % of cardiovascular deaths globally and one-third of CVD deaths in the United States [9, 1921]. Nearly a quarter (24 %) of adults worldwide and one-fifth (19 %) of U.S. adults are cigarette smokers [22, 23]. Compared with nonsmokers, smokers have a two- to fourfold risk for both coronary artery disease (CAD) and stroke [21, 24, 25]. Smoking cessation lowers risk of nonfatal myocardial infarction (MI) by approximately 32 % and that of mortality by 36 % among smokers with CAD; approximately 5 years after quitting, smokers’ risk of stroke is equivalent to that of nonsmokers [4•, 20, 21]. Notably, improved diet and decreases in cigarette smoking (albeit offset recently by the rising obesity rates) in addition to better treatment have contributed to much of the decline in cardiovascular mortality globally during the past three decades [26].

Whereas smoking and diet both contribute independently to CVD, the two exposures often are correlated and often occur together as part of overall lifestyle patterns, an expansion of the dietary pattern approach in which multiple behaviors are included in a distinct pattern (e.g., diet, smoking, physical activity, sedentary behavior, alcohol use, etc.) [2738]. The goal of this article was to review studies that have considered the role of smoking status on the relationship between dietary patterns and CVD as well as studies that evaluated associations of lifestyle patterns and CVD.

Dietary and Lifestyle Patterns, Smoking, and CVD

As noted, two types of dietary patterns are commonly used in nutritional epidemiology. A priori or theoretical patterns are hypothesis-driven and are based on expert dietary guidelines (such as the Healthy Eating Index [39]), which measures adherence to the U.S. Dietary Guidelines for Americans [40]), healthful traditional diets (such as the Mediterranean diet [41]), or composite evidence-based nutrients and foods (such as the Alternate Healthy Eating Index [42]). A priori patterns use a score-based approach and are generally termed diet quality indices [16, 4345]. A posteriori or empirical patterns are data-driven and define food and nutrient intake as actually consumed. They are derived statistically mainly by factor analysis and less commonly by cluster analysis. Reduced rank regression, less frequently employed, utilizes food groups that maximally explain intermediary biomarkers of disease to predict health outcomes and derives a hybrid of a priori and posteriori patterns [16, 43, 46].

In various populations, CVD-protective dietary patterns are characterized by greater consumption of plant-based foods, such as vegetables, fruits, nuts, and whole grains, lean proteins, such as fish, poultry, and soy, unsaturated vegetable oils, and moderate alcohol consumption. Conversely, CVD-promoting patterns generally include higher intakes of refined grains, red and processed meats, trans fats, and sugar-sweetened beverages [4348, 49•]. Dietary intakes are shown to differ by smoking status. For example, nonsmokers and former smokers tend to have higher quality diets [5055]; the converse is true of smokers [50, 52, 53, 5558]. Moreover, unhealthy lifestyle habits, including poor quality diet, high alcohol intake, cigarette smoking, and physical inactivity, tend to cluster [2738]. Thus, smoking can be considered as both a potential confounder and effect modifier of the diet-CVD relationship. Specifically, smoking is correlated with both diet and CVD but is not in the causal pathway, thus it may confound the association if not controlled for in multivariable adjustment. As an effect modifier, smoking may modify the effect of diet on CVD risk or may interact with diet such that its impact on CVD varies depending on whether one is a smoker or not. Studies considering the interrelations of diet, smoking, and CVD have tested for both confounding and interaction (effect modification) effects.

Mechanisms that Link Diet and Smoking with CVD

Atherosclerosis, whereby plaque builds up in the arteries, is one mechanism underlying the development of CVD [4•, 59]. Inflammation is the key underlying feature of atherosclerosis [59]. Such dietary factors as refined carbohydrates and animal fat are hypothesized to induce oxidative stress that stimulates secretion of proinflammatory cytokines [60, 61]. Other foods and nutrients, including fruits, vegetables, fiber, and alcohol are anti-inflammatory and suppress oxidative stress, as do bioactive compounds, such as phenolic compounds in extra virgin oil and resveratrol in red grapes [60, 61]. Smoking similarly causes oxidative stress [21].Additionally, smoking induces insulin resistance that partly underlies the development of obesity, hypertension, glucose intolerance, and dyslipidemias (hypertriglyceridemia, elevated LDL-cholesterol, and low HDL-cholesterol), which are established risk factors for CVD. Furthermore, hypertrophied adipocytes particularly visceral adipocytes produce free fatty acids (FFA), which in turn stimulate insulin resistance, inflammation, and oxidative stress. Adipocytes also produce proinflammatory cytokines. Insulin resistance further enhances lipolysis and increases FFA production, resulting in a vicious circle of lipolysis, increased FFA, insulin resistance, and inflammation. Smoking likewise causes hypertension through the sympathomimetic effects of nicotine [21, 6163]. Smoking cessation promotes insulin sensitivity thereby improving metabolic profile [21].

Associations of A Priori Dietary Patterns and Smoking Status with CVD

One cross-sectional study [64] and 17 prospective studies [35, 6580] in the United States and Europe have evaluated the interrelationships of smoking status and a broad range of diet quality indices with CVD. The Study of Health in Pomerania examined the cross-sectional association between lifestyle factors and carotid atherosclerosis among men and women [64]. Mean carotid intima media thickness values were higher in never smokers with an unfavorable Food frequency pattern (higher in meats, potatoes, pasta, and lower in vegetables, fruits, fish) compared with those with an optimal pattern (0.750 vs. 0.723 mm; P < 0.04). Dietary patterns were not associated with carotid atherosclerosis among smokers.

Prospective studies are better able to show clear associations between exposures and disease, and many studies have prospectively examined the effect of smoking status on the relationship between diet quality indices and CAD, stroke, heart failure, total CVD, and cardiovascular mortality [35, 6580] (Table 1). No statistically significant interactions were reported in any of the studies that tested for interactions [35, 6567, 6973, 7578, 80]. However, interaction effects can be difficult to detect [17••, 81] and statistical interaction must be evaluated in light of biological plausibility. Furthermore, while smoking can occur as part of an overall lifestyle pattern, smoking also can confound diet–CVD relationships. Five studies thus conducted stratified analyses despite the nonsignificant interactions [67, 6971, 73] and two studies stratified analyses based on a priori hypotheses [68, 80]. In the Nurses’ Health Study, a higher Alternate Mediterranean Diet (aMED) score (higher in vegetables, fruits, whole grains, legumes, nuts, fish, ratio of monounsaturated to saturated fat, lower in red and processed meats, and moderate in alcohol) conferred lower risk for CAD in all women than a lower score (relative risk (RR) 0.71; 95 % confidence interval (CI) 0.62–0.82), a finding that was attenuated and became insignificant in current smokers (RR 0.81; 95 % CI 0.56–1.77). However, the index was not associated with stroke overall or among nonsmokers and smokers [67].
Table 1

Associations of a priori dietary patterns and smoking status with cardiovascular diseases in prospective studiesa

Reference

Study population

Sex (%)

F/U (yrs)

Diet Quality Index

Results

Coronary artery disease

Osler et al., 2002 [65]

Danish MONICA cohort 5,834 adults, aged 30–70 yr

M: 51 F: 49

4–13

Healthy food index

High HFI vs. low HFI: RR (95 % CI) 1.21 (0.8–1.82) (P-interaction NS)

Buckland et al., 2009 [66]

Spanish EPIC cohort 41,078 adults, aged 20–69 yr

M: 38 F: 62

10.4

Relative Mediterranean Diet score

High rMED vs. low rMED: HR (95 % CI) 0.6 (0.47–0.77) (P-interaction NS)

Fung et al., 2009 [67]

NHS cohort 74,886 adults, aged 38–63 yr

W: 100

20

Alternate Mediterranean Diet score

Quintiles 5 vs. quintile 1: RR (95 % CI) All women: 0.71 (0.62–0.82) (P-interaction NS) Nonsmokers: 0.66 (0.56–0.77); Smokers: NS

Halton et al., 2006 [68]

NHS cohort 82,802 women, mean age 56 yr

W: 100

20

Low-Carbohydrate Diet score

Decile 10 vs. decile 1: RR (95 % CI) All adults: 0.94 (0.76–1.18) [Stratified analyses: data not available]

Fung et al., 2008 [69]

NHS cohort 88,517 women, aged 34–59 yr

W: 100

24

DASH score

Quintile 5 vs. quintile 1: RR (95 % CI) All women: 0.76 (0.67–0.85) (P-interaction NS) Nonsmokers: 0.8) (95 % CI not available; reported as significant); Smokers: 0.65 (95 % CI not available; reported as significant)

Stroke

Fung et al., 2009 [67]

NHS cohort 74,886 women, aged 38–63 yr

W: 100

20

Alternate Mediterranean Diet score

Quintile 5 vs. quintile 1: RR (95 % CI) All women, nonsmokers, and smokers: NS (P-interaction NS)

Fung et al., 2008 [69]

NHS cohort 88,517 women, aged 34–59 yr

W: 100

24

DASH score

Quintile 5 vs. quintile 1: RR (95 % CI) All women: 0.82 (0.71–0.94) (P-interaction NS) Non-smokers: 0.9 (95 % CI not available; reported as significant); Smokers: 0.67 (95 % CI not available; reported as significant)

Heart failure

Levitan et al., 2009 [70]

SMC 36,019 women, aged 48–83 yr

W: 100

7

DASH score

Quartile 4 vs. quartile 1: RR (95 % CI) All women: 0.63 (0.48–0.81) (P-interaction NS) Non-smokers: 0.7 (0.47–0.86); Smokers: NS

Levitan et al., 2009 [71]

COSM cohort 38,987 men, aged 45–79 yr

M: 100

8

DASH score

Quartile 4 vs. quartile 1: RR (95 % CI) All men: 0.78 (0.65–0.95) (P-interaction NS) Non-smokers and smokers: NS

Total cardiovascular diseases

McCullough et al., 2000 [72]

HPFS cohort 38,622 men, aged 40–75 yr

M: 100

8

FFQ-derived Healthy Eating Index (HEI-f)

Quintiles 5 vs. 1: RR (95 % CI) All men: 0.72 (0.6–0.88) [P-interaction and stratified analyses not available]

McCullough et al., 2000 [73]

NHS cohort 67,272 women, aged 38–63 yr

W: 100

12

FFQ-derived Healthy Eating Index (HEI-f)

Quintiles 5 vs. 1: RR (95 % CI) All women: NS (P-interaction NS) [Stratified analyses: Data not available]

Fitzgerald et al., 2012 [74]

WHS cohort 34,827 women, aged ≥45 yr

W: 100

14.6

DASH score

Quintiles 5 vs. 1: HR (95 % CI) Multivariable-adjusted: 0.64 (0.53–0.77) MV-adjusted + smoking: 0.82 (0.68–1.00)

Mortality

Seymour et al., 2003 [75]

ACS CPS II Nutrition Cohort 115,833 adults, aged 50–79 yr

M: 45.5 W: 54.5

4

Diet Quality Index

Low DQI vs. high DQI: RR (95 % CI) Men: NS; Women: NS (P-interaction NS)

Kant et al., 2000 [76]

BCDDP cohort 42,254 women, mean age 61 yr

W: 100

5.6

Recommended food score

Quartile 5 vs. quartile 1: RR (95 % CI) CAD: 0.67 (0.47–0.95) Stroke: 0.58 (0.35–0.96) (P-interaction NS)

Kaluza et al., 2003 [77]

COSM cohort 40,837 men, aged 45–79 yr

M: 100

7.7

Recommended food score; non-recommended food score

High RFS vs. low RFS HR (95 % CI 0.71 (0.54–0.93) (P-interaction NS) High non-RFS vs. low non-RFS: HR (95 % CI) 1.27 (1.05–1.54) (P-interaction NS)

Knoops et al., 2004 [35]

HALE cohort 2,339 adults, aged 70–90 yr

M: 64.4 W: 35.6

10

Mediterranean diet score

High MDS vs. low MDS: HR (95 % CI) CAD mortality: 0.61 (0.43–0.88) CVD mortality: 0.71 (0.58–0.88) (P-interaction NS)

Kant et al., 2009 [78]

NIH-AARP Diet and Healthy Study 350,886 adults, aged 50–71 yr

M: 57 W: 43

10.5

Dietary behavior score

Quintile 5 vs. quintile 1: RR (95 % CI) CAD mortality Men: 0.77 (0.67–0.88) Women: 0.7 (0.56–0.87) [P-interaction and stratified analyses not available]

Kant et al., 1995 [79]

NHANES I Epidemiologic follow-up study 10,337 adults, aged 25–74 yr

Not available

14

Dietary diversity score

Smoking status appears to have attenuated the inverse association of DDS and CVD mortality but data not available

Fung et al., 2010 [80]

NHS cohort 85,168 women, aged 40–65 yr

W: 100

26

Low-carbohydrate diet score

Decile 10 vs. decile 1: RR (95 % CI) Overall low-carbohydrate score: NS Animal low-carbohydrate score Men: 1.21 (1.01–1.44); Women: NS Vegetable low-carbohydrate score Men: 0.77 (0.65–0.92) Women: 0.77 (0.66–0.91) Smokers and non-smokers: Comparable results (data not available)

 

HPFS cohort 44,545 men, aged 50–85 yr

M: 100

20

aFor each outcome, arranged according to follow-up duration. Diet was assessed using the food frequency questionnaire in all studies.

MONICA = Multinational MONItoring of trends and determinants in CArdiovascular disease; EPIC = European Prospective Investigation into Cancer and Nutrition; NHS = Nurses Health Study; DASH = Dietary Approaches to Stop Hypertension; SMC = Swedish Mammography Cohort; COSM = Cohort of Swedish Men; HPFS = Health Professionals Follow-up Study; WHS = Women’s Health Study; ACS CPS II = American Cancer Society Cancer Prevention Study II; BCDDP: Breast Cancer Detection Demonstration Project; HALE = Healthy Ageing: a Longitudinal study in Europe; NIH-AARP = National Institutes of Health–American Association of Retired Persons Diet and Health Study; NHANES = National Health and Nutrition Examination Survey.

The Dietary Approaches to Stop Hypertension (DASH) diet that is high in vegetables, fruits, whole grains, legumes, nuts, and low-fat dairy and low in red meats, processed meats, refined grains, sugar-sweetened beverages, and sodium [82] is recommended as an example of a healthy pattern by the U.S. Dietary Guidelines for Americans [40] and the American Heart Association [18] for CVD prevention. Women in the Nurses' Health Study with high intakes on foods included in the DASH diet similarly had lower risk for CAD when comparing the extreme quintiles. However, unlike the aMED, risk for CAD was lower among smokers (35 %) than nonsmokers (20 %) as was risk for stroke (33 % vs. 10 % in nonsmokers) [69]. The DASH diet also lowered risk for heart failure among nonsmokers (RR 0.63; 95 % CI 0.48–0.81) in the Swedish Mammography Cohort [70] but was not associated with heart failure among nonsmokers or smokers in the Cohort of Swedish Men [71]. Adjusting for cigarette smoking, which was considered as a confounder, is reported to have had the strongest influence on the inverse association of the DASH diet with total CVD in the Women’s Health Study and attenuated the findings. Additional stratified analyses were not done [74].

Health effects of carbohydrate-restricted diets are unclear and likely depend on type of fat and protein consumed as part of the overall dietary pattern. Three low-carbohydrate diets, including an overall low-carbohydrate-diet (high in fat and protein and low in carbohydrate), a vegetable low-carbohydrate (high in vegetable protein and fat), and an animal low-carbohydrate (high in animal protein and fat) were evaluated for their interactions with smoking status on CAD [68•] and cardiovascular mortality [80] in the Nurses’ Health Study (NHS) and the Health Professionals Follow-up Study (HPFS). The overall low-carbohydrate-diet index was not associated with CAD in women (NHS) or cardiovascular mortality among women and men (HPFS). However, the vegetable low-carbohydrate score lowered risk for mortality in both women (RR 0.77; 95 % CI 0.66–0.91) and men (RR 0.77; 95 % CI 0.65–0.92), whereas an animal low-carbohydrate score conferred risk for mortality in men only (RR 1.21; 95 % CI 1.01–1.44), comparing the highest and lowest deciles. Smoking status had no effect on these relationships.

The relationship of the dietary behavior score and smoking status with CAD mortality was assessed in the National Institutes of Health–American Association of Retired Persons Diet and Health Study. Participants with a higher score (higher in vegetables, fruits, whole grains, low-fat dairy, lean meats, poultry, and lower in solid fat intake) had a lower risk for CAD mortality relative to those with a lower score. Findings for the stratified analyses were not presented [67].

In summary, limited evidence based on only one cross-sectional study suggests higher quality diet is beneficial for nonsmokers with subclinical CVD. For CAD, evidence supports a protective effect of high-quality diet in nonsmokers than smokers. Findings for stroke based on two studies in one cohort of women are limited and inconclusive, which necessitates more studies in other populations. Studies on stroke subtypes also are essential because subtypes differ in their pathophysiology [83, 84]. Evidence for the associations of diet quality indices and smoking status with heart failure is equivocal. Additionally, studies on heart failure subtypes are needed as underlying mechanisms may vary [85]. Findings for total CVD are uncertain, but studies on individual diseases may be more informative. Accruing evidence for mortality suggests that high-quality diet benefits both nonsmokers and smokers. Conversely, lower diet quality confers risk for both groups of smokers. There are no studies on peripheral artery disease (PAD), yet smoking is the strongest behavioral risk factor for the condition [86].

Associations of A Posteriori Dietary Patterns and Smoking Status with CVD

Most of the studies that examined relationships of smoking status and a posteriori patterns with CVDs were in the United States and Europe [65, 8797].

Three cross-sectional studies evaluated the interrelationships of dietary patterns and smoking status with subclinical CVD and hypertension [8789]. A reduced rank regression-derived pattern (high in total fat, saturated fat, processed meats, sodas and low in fiber, vegetables) was positively associated with carotid artery atherosclerosis in the Multi-Ethnic Study of Atherosclerosis [87]. A fruit and milk pattern conferred low risk for hypertension in the Shanghai Men’s Health Study comparing the highest to lowest intake [89], as did a fruit and vegetable pattern among military personnel in Cameroon [88]. There were no statistically significant interactions between the patterns and smoking status in all the studies. However, the inverse association between the fruit and milk pattern and hypertension was stronger in smokers.

To elucidate the relationships, nine studies prospectively assessed the associations of empirical patterns and smoking status on subclinical heart disease, CAD, stroke, and cardiovascular mortality [65, 9097] (Table 2). Stratified analyses were conducted based on a priori hypotheses in three studies [90, 92, 93]. Studies that tested for interactions did not report any statistically significant results [65, 9497]; of these, three studies performed stratified analyses [9496]. In the Framingham Offspring/Spouse Study, women with a Heart Healthy pattern (higher in vegetables, fruits, low-fat dairy, and legumes and lower in diet beverages) who had never smoked or formerly smoked were less likely to develop subclinical heart disease than current smokers with less heart healthy patterns. Heart healthy never smokers had the lowest risk (83 %) for carotid artery stenosis. Heart healthy former smokers (odds ratio (OR) 0.41; 95 % CI 0.2–0.79), less heart healthy, never smokers (OR 0.33; 95 % CI 0.21–0.53), and less heart healthy, former smokers (OR 0.34; 95 % CI 0.21–0.57) had substantially low risk as well. Only the heart healthy pattern in association with current smoking was not significantly associated with carotid stenosis (OR 0.56; 95 % CI 0.21–1.34), which the authors attributed to the cluster’s small sample size. As such, it appears that the heart healthy pattern benefited smokers as well [90].
Table 2

Associations of a posteriori dietary patterns and smoking status with cardiovascular diseases in prospective studiesa

Reference

Study population

Sex (%)

F/U (yrs)

Dietary patterns

Results

Subclinical cardiovascular disease

Millen et al., (2004) [90]

FOS cohort 1,423 women, aged 18–76 yr

F: 100

12

5 clusters Heart healthy; light eating; wine and moderate eating; high fat; empty calorie

Carotid artery stenosis Heart healthy, current smoker vs. less heart healthy, current smoker OR: 0.17 (95 % CI: 0.07–0.36)

Coronary artery disease

Osler et al., 2002 [65]

Danish MONICA 5,834 adults, aged 30–70 yr

M: 51 F: 49

4–13

2 factors Prudent Western

HR (95 % CI) per score unit increase All adults: both factors NS (P-interaction NS)

Meyer et al., 2011 [91]

Augsburg MONICA 981 men, aged 45–64 yr

M: 100

8–17

Reduced rank regression (RRR)-derived pattern

Higher vs. lower score: HR (95 % CI) Multivariable-adjusted: 1.33 (1.06–1.67) MV-adjusted + smoking: 1.15 (0.91–1.45)

Hu et al., 2000 [92]

HPFS cohort 44,875 men, aged 40–75 yr

M: 100

8

2 factors Prudent Western

Quintile 5 vs. quintile 1: RR (95 % CI) Prudent factor All men: 0.7 (0.56–0.86) Non-smokers: 0.64) (95 % CI not available; reported as significant); Smokers: 0.82 (95 % CI not available; reported as significant). Western factor All men: 1.64 (1.24–2.17) Non-smokers: 1.21) (95 % CI not available; reported as significant); Smokers: 2.7 (95 % CI not available; reported as significant)

Fung et al., 2001 [93]

NHS Cohort 69,017 women, aged 38–63 yr

F: 100

12

2 factors Prudent Western

Quintile 5 vs. quintile 1: RR (95 % CI) Prudent factor: 0.76 (0.6–0.98) Western factor: 1.46 (1.07–1.99) Smokers and nonsmokers: comparable results (data not available)

Stroke

     

Fung et al., 2004 [94]

NHS Cohort 71,768 women, aged 38–63 yr

F: 100

14

2 factors Prudent Western

Quintile 5 vs. quintile 1: RR (95 % CI Total strokes Prudent factor: 0.78 (0.61–1.01) Western factor: 1.58 (1.15–2.15) Ischemic stroke: comparable to total stroke Hemorrhagic stroke: NS Smokers and nonsmokers: comparable results (data not available) (P-interaction NS)

Mortality

Chen et al., 2012 [95]

HEALS Cohort 11,116 adults, aged 18–75 yr

Not available

6.6

3 factors Balanced Animal protein Gourd & root vegetable

HR (95 % CI) per SD ↑ in diet pattern score Animal protein factor All adults and nonsmokers: NS Smokers: 1.17 (1.02–1.34) (P-interaction NS)

Shimazu et al., 2007 [96]

Ohsaki NHI cohort 40,547 adults, aged 40–79 yr

Not available

7

3 factors Japanese Animal food High-dairy, high-fruit-and-vegetable, low-alcohol (DFA)

Quartile 5 vs. quartile 1: HR (95 % CI) Japanese factor All adults: 0.73 (0.59–0.9) Never-smokers: 0.54 (0.38–0.78) Former smokers: 0.53 (0.32–0.89) Current smokers: 0.92 (0.64–1.33) (P-interaction NS)

Meyer et al., 2011 [91]

Augsburg MONICA 981 men, aged, 45–64 yr

M: 100

13–23

RRR-derived pattern (high in saturated and total fat; low in fiber)

Higher vs. lower score: HR (95 % CI) Multivariable-adjusted: 1.38 (1.07–1.79) MV-adjusted + smoking: 1.18 (0.9–1.54)

Heidemann et al., 2008 [97]

NHS cohort 72,113 women, mean age 38–63 yr

W: 100

18

2 factors Prudent Western

Quintile 5 vs. quintile 1: RR (95 % CI) Prudent factor: 0.72 (0.6–0.87) Western factor: 1.22 (1.01–1.48) (P-interaction NS)

aFor each outcome, arranged according to follow-up duration. Diet was assessed using the food frequency questionnaire in all studies.

FOS = Framingham Offspring/Spouse Study; MONICA = Multinational MONItoring of trends and determinants in CArdiovascular disease; HPFS = Health Professionals Follow-up Study; NHS = Nurses Health Study; HEALS = Health Effects of Arsenic Longitudinal Study; NHI = National Health Insurance study.

In both the Health Professionals Follow-up Study (HPFS) [92] and the Nurses’ Health Study (NHS) [93], the Prudent pattern (high in vegetables, fruits, whole grains, legumes) conferred lower risk for CAD, whereas the western pattern (high in refined grains, red and processed meats, high-fat dairy, sugar sweetened beverages) was associated with greater risk when comparing the highest to the lowest quintile. Comparable findings were observed in smokers and nonsmokers. Among men (HPFS), the Prudent pattern had a greater effect in non-smokers (36 % lower risk vs. 18 % in smokers), whereas associations with the western pattern were stronger in smokers (2.7-fold higher risk vs. 21 % in nonsmokers). In women (NHS), a higher western pattern score likewise increased risk for total stroke (relative risk (RR) 1.58; 95 % CI 1.15–2.15) and ischemic stroke (RR 1.56; 95 % CI 1.05–2.33); the Prudent pattern was not associated with stroke. Both patterns were not associated with hemorrhagic stroke most likely due to the limited number of hemorrhagic stroke cases. Smoking status did not modify these results [94].

Among middle-aged and older participants of the Ohsaki National Health Insurance study, current smoking status attenuated the inverse relationship between the Japanese factor (high in vegetables, fruits, soybean products, fish, seaweeds, green tea) and cardiovascular mortality, which subsequently became insignificant [96]. Another prospective study in Bangladesh showed that the animal protein factor (high in eggs, milk, red meat, poultry, wheat bread, vegetables) was associated with cardiovascular mortality only among smokers (RR 1.17; 95 % CI 1.02–1.34) [95]. Greater consumption of a comparable pattern derived by reduced rank regression (high in meat, soft drinks, beer and lower in vegetables, fruits, whole-meal bread, cereals, dairy products) increased risk for CAD and CVD mortality in a German cohort. In this study, adjustment for smoking status, which was considered as a confounder, attenuated the findings; however, stratified analyses were not conducted [91].

In summary, limited evidence suggests higher quality diet benefits nonsmokers and former smokers with subclinical CVD. Emerging evidence suggests that higher quality diet also is beneficial for both nonsmokers and smokers with CAD. For stroke, there is inconclusive evidence that is based on only one study. More studies, including studies on stroke subtypes, are required. Findings for hypertension based on cross-sectional studies suggest higher quality diet protects against hypertension in both nonsmokers and smokers. Limited evidence for mortality suggests a protective effect of higher quality diet for never smokers and former smokers, but the evidence for smokers is uncertain. Lower quality diet is shown to be harmful, particularly for smokers. There is a need for prospective studies on hypertension, PAD, and heart failure.

Associations of Lifestyle Patterns with CVD

Because lifestyle variables tend to cluster together (e.g., diet, smoking, alcohol use, physical activity, sedentary behavior), investigators have more recently began to examine lifestyle patterns to better understand the relationships between behavioral factors and health outcomes. Several studies in predominantly Caucasian cohorts have prospectively evaluated the combined effect of dietary patterns, smoking, alcohol consumption, physical activity, overweight/obesity, and abdominal obesity on CVD [2838] (Table 3). In nine prospective studies, having a low-risk lifestyle (a healthy diet, not currently a smoker, low to moderate alcohol intake, physically active, not overweight or obese (body mass index (BMI) <25 kg/m2), not abdominally obese (WHR <0.85 [women]) was associated with a lower risk for MI, total CAD, hypertension, total CVD, and cardiovascular mortality [2831, 3438]. Findings for stroke were inconsistent with one study by Ford et al. [29] showing no association with total stroke. Hemorrhagic stroke also was not associated with a healthy lifestyle in the Women’s Health Study [32] perhaps due to the small sample size. Additionally, individual factors independently lowered risk for CVD except the Alternate Healthy Eating Index, which was found to increase risk for stroke in the Women’s Health Study [32].
Table 3

Associations of lifestyle patterns with cardiovascular diseases in prospective studiesa

Reference

Study population

Sex (%)

F/U (yr)

Low-risk lifestyle

Results

Coronary artery disease

Akesson et al., 2007 [28]

SMC 24,444 women, aged 48–83 yr

W: 100

6.2

WHR <0.85; nonsmoking status PA: ~40 min/d + 1 hr exercise/wk Alcohol intake: >5 g/d Healthy dietary pattern: Quintiles 3–5

Myocardial infarction 5 vs. 0 factors RR: 0.08 (95 % CI: 0.02-0.28)

Ford et al., 2009 [29]

EPIC-Postdam cohort 23,153 men and women, aged 35–65 yr

M: 38.7 W: 61.3

7.8

BMI <30 kg/m2; PA: ≥3.5 hr/week Never-smoking status Healthy dietary pattern: Score > median

4 vs. 0 factors RR (95 % CI) 81 % (47–93 %) lower risk

Stampfer et al., 2000 [30]

NHS cohort 84,129 women, aged 34–59 yr

W: 100

14

BMI <25 kg/m2; Nonsmoking status PA: ≥30 min/d (moderate to vigorous) Alcohol intake: 5–15 g/d (moderate) AHEI-based diet: Top 40 % of score

All: 5 vs. 0 factors RR: 0.17 (95 % CI: 0.07–0.41) Nonsmokers RR: 0.25 (95 % CI: 0.1–0.6)

Chiuve et al., 2006 [31]

HPFS cohort 42,847 men, aged 40–75 yr

M: 100

16

BMI <25 kg/m2; Nonsmoking status PA: ≥30 min/d; Alcohol intake: 5–30 g/d; AHEI-based diet: Top 40 % of score

5 vs. 0 factors RR: 0.13 (95 % CI: 0.09–0.19)

Stroke

Ford et al., 2009 [29]

EPIC-Postdam cohort 23,153 men and women, aged 35–65 yr

M: 38.7 W: 61.3

7.8

BMI <30 kg/m2; PA: ≥3.5 hr/week Never-smoking status Healthy dietary pattern: Score > median

4 vs. 0 factors NS

Kurth et al., 2009 [32]

WHS cohort 37,636 women, aged ≥45 yr

W: 100

10

Health index BMI <22 kg/m2; PA: ≥4 times/wk Nonsmoking status Alcohol intake: 4–10.5 drinks/week AHEI-based diet: Top 40 % of score

Higher score vs. lower score Total stroke HR: 0.45 (95 % CI: 0.24–0.83) Ischemic stroke HR: 0.29 (95 % CI: 0.14–0.63) Hemorrhagic stroke NS

Chiuve et al., 2008 [33]

NHS cohort 71,243 women, mean age 50 yr HPFS cohort 43,685 men, mean age 54 yr

W: 100 M: 100

14

BMI <25 kg/m2 PA: ≥30 min /d (moderate to vigorous) Never smoking status Alcohol intake: moderate (Men; 5–30 g/d; women: 5–15 g/d) AHEI-based diet: Top 40 % of score

5 vs. 0 factors RR (95 % CI) Total stroke Men: 0.31 (0.19–0.53) Women: 0.21 (0.12–0.36) Ischemic stroke Men: 0.2 (0.1–0.42) Women: 0.19 (0.09–0.4) Hemorrhagic stroke No data (small sample)

Hypertension

Forman et al., 2009 [34]

NHS cohort 83,882 women, aged 27–44 yr

W: 100

14

BMI <25 kg/m2; PA: ≥30 min/d; Never smoking status; Alcohol intake: 5–10 g/d; DASH diet: Top 20 % of score Non-narcotic analgesics use Supplemental folate use: ≥400 μg/d

6 vs. 0 factors HR: 0.22 (95 % CI 0.1–0.51)

Total cardiovascular diseases

Stampfer et al., 2000 [30]

NHS cohort 84,129 women, aged 34–59 yr

W: 100

14

BMI <25 kg/m2; PA: ≥30 min/d; Nonsmoking status; Alcohol intake: 5–15 g/d; AHEI-based diet: Top 40 % of score

5 vs. 0 factors RR: 0.17 (95 % CI: 0.07–0.41)

Mortality

Knoops et al., 2004 [35]

HALE cohort 2,339 adults, aged 70–90 yr

M: 64.4 W: 35.6

10

BMI <25 kg/m2; PA: Moderate to vigorous; Nonsmoking status Alcohol intake: >0 g/d (Moderate) Mediterranean diet score: higher score

4 vs. 0 factors HR (95 % CI) CAD: 0.27 (0.14–0.53) CVD: 0.33 (0.22–0.47)

Odegaard et al., 2011 [36]

SCHS cohort 50,466 adults, aged 45–74 yr

Not available

13.5

BMI: 18.5–21.5 kg/m2; PA: ≥2 hr/wk Never-smoked status; Alcohol: 1–14 drinks/wk Healthy dietary pattern: Top 60 % of score Sleep: 6–8 hr/d

6 vs. 0 factors HR (95 % CI) All: 0.24 (0.17–0.34) Men: 0.23 (0.14–0.37) Women: 0.2 (0.1–0.41)

van Dam et al., 2008 [37]

NHS cohort 77,782 women, aged 34–59 yr

W: 100

24

BMI: 18–25 kg/m2 PA: ≥30 min/d Never-smoked status Alcohol intake: ≥1– < 15 g/d AHEI-based diet: Top 40 % of score

HR (95 % CI) All: 5 vs. 0 risk factors 8.17 (4.96 3–13.47) Never smokers: 4 vs. 1 risk factors 3.94 (2.35–6.60)

Chiuve et al., 2011 [38]

NHS cohort 81,722 women, aged 34–59 yr

W: 100

26

BMI <25 kg/m2; PA: ≥30 min/d Nonsmoking status; Alternate Mediterranean diet: Top 40 % of score

Sudden cardiac death 4 factors vs. 0 factors RR: 0.08 (95 % CI: 0.03-0.23)

aFor each outcome, arranged according to follow-up duration.

SMC = Swedish Mammography Cohort; EPIC = European Prospective Investigation into Cancer and Nutrition; NHS = Nurses Health Study; AHEI = Alternate Healthy Eating Index; HPFS = Health Professionals Follow-up Study; WHS = Women’s Healthy Study; DASH = Dietary Approaches to Stop Hypertension; HALE = Healthy Ageing: a Longitudinal study in Europe; SCHS = Singapore Chinese Health Study.

In summary, substantial evidence supports a protective role of a low-risk lifestyle for CAD, total CVD, and cardiovascular mortality. Ischemic stroke may benefit from a low-risk lifestyle; however, findings for hemorrhagic stroke are inconclusive. Limited evidence based on one study suggests that a low-risk lifestyle protects against hypertension. These findings thus indicate a need for more studies on stroke, stroke subtypes, and hypertension. The relationships of healthy behaviors with subclinical CVD, heart failure, and PAD are yet to be evaluated.

Discussion

Together, the evidence from a priori and a posteriori dietary patterns as well as lifestyle patterns show that lifestyle patterns may better inform the associations of diet and smoking with CVD. First, it is well established that smoking confounds the association between diet and CVD. Thus, all studies reviewed adjusted for smoking in their analysis [35, 6480, 8797] and showed that the effect of diet is attenuated when smoking is considered [73, 91]. However, as discussed, smoking may interact with diet and modify the effect of diet on CVD, which has been an increasing focus of more recent studies. The studies show that higher quality diet protects against CAD, cardiovascular mortality, hypertension, and subclinical CVD in nonsmokers and smokers [35, 64, 66, 67, 69, 7678, 80, 8890, 92, 93, 95, 97]. That said, a healthy diet might similarly potentially benefit nonsmokers and smokers with stroke and heart failure [6971]. However, lack of a detected interaction between dietary patterns and smoking status in the studies is not unusual because interaction effects can be difficult to detect. Moreover, even when observed, effect modification often is not replicable [17••, 81]. Thus, some studies stratified analyses by smoking categories and demonstrated that a healthy diet protects against CAD [69, 92, 93] and probably subclinical CVD [90], ischemic stroke [94], hypertension [89], as well as cardiovascular mortality [80] among both nonsmokers and smokers.

Perhaps in part because of the difficulty in teasing out the complex associations between diet and smoking, specifically due to its impact as both a confounder and effect modifier, the more recent studies on overall lifestyle patterns have contributed to our understanding of relationships between diet and CVD. Findings show that it is important to consider all CVD lifestyle factors together and that a healthy lifestyle is protective of CVD. Although most of the studies were performed in whites, findings may be generalizable to other racial/ethnic populations because the underlying biological mechanisms of lifestyle factors and CVD are likely similar in humans, although genetics may account for any within- and between-population differences. For example, the INTERHEART study [98, 99] showed that low intakes of vegetables and fruits, smoking, high alcohol consumption, and physical inactivity contributed to much of the MI and stroke burdens in all world regions. The study also demonstrated that the western pattern conferred risk for MI, whereas a healthy pattern protected against MI and stroke in all populations, which included Africans, Asians, Hispanics, and Caucasians [99, 100]. Thus, a standardized approach can be adopted for CVD prevention.

Conclusions

The current body of scientific evidence, albeit mainly from western countries, supports the protective role of diets high in plant-based foods, fish, poultry, and low-fat dairy as well as moderate alcohol consumption for CAD and cardiovascular mortality among both nonsmokers and smokers. The associations of dietary patterns and smoking status on subclinical CVD, stroke, hypertension, and heart failure are inconclusive, whereas relationships on PAD are yet to be examined. “Western”-type diets high in refined grains, meats, high-fat dairy, and sugar-sweetened beverages appear to confer risk in all individuals, and the effect appears to be larger among smokers. A growing body of literature considering diet and smoking together alongside other lifestyle variables has shown that a healthy lifestyle is beneficial for CAD, hypertension, and cardiovascular mortality, and potentially protective against stroke; this approach may offer more insight into the complex relationships of diet and smoking status with CVD. To move forward our understanding of CVD outcomes, including subclinical heart disease, heart failure, and PAD, more prospective studies are needed, and studies in diverse populations would be beneficial.

Conflict of Interest

Ruth W. Kimokoti declares that she has no conflict of interest.

P.K. Newby declares that she has no conflict of interest.

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Department of NutritionSimmons CollegeBostonUSA
  2. 2.Program in Gastronomy, Culinary Arts, and Wine Studies at Boston University and Program in Environmental Sciences at Harvard Extension SchoolBostonUSA