Skip to main content
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2017 May 30.
Published in final edited form as: J Aging Health. 2016 Jul 9;29(3):437–453. doi: 10.1177/0898264316635590

Overall Cardiovascular Health Is Associated With All-Cause and Cardiovascular Disease Mortality Among Older Community-Dwelling Men and Women

Yichen Jin 1, Toshiko Tanaka 2, Stefania Bandinelli 3, Luigi Ferrucci 2, Sameera A Talegawkar 1
PMCID: PMC5140754  NIHMSID: NIHMS832760  PMID: 27036884

Abstract

Objective

The objective of this study was to assess the associations between cardiovascular health and all-cause and cardiovascular disease mortality among community-dwelling elderly.

Method

Secondary data analysis was performed using data collected as part of the InCHIANTI cohort procedures and included 928 participants (55% female) aged 65 years and older. Overall cardiovascular health was assessed using seven health behaviors and factors, scored 0 to 14, with higher scores indicating better cardiovascular health, modeled categorically as tertiles. Vitality status was ascertained using registry information. Cox proportional hazards models were used to examine the associations between cardiovascular health and all-cause and cardiovascular disease mortality.

Results

After an average follow-up of 9.1 years, better overall cardiovascular health (highest tertile) was inversely associated with all-cause (hazard ratio [HR] = 0.68, 95% confidence interval [CI] = [0.51, 0.92]) and cardiovascular disease mortality (HR = 0.61, 95% CI = [0.38, 0.97]) compared with the lowest tertile.

Discussion

Cardiovascular health, even in the elderly, is inversely associated with mortality.

Keywords: mortality, cardiovascular health, elderly, InCHIANTI study

Introduction

The worldwide population of those aged 60 years and older has grown in the past few years and is projected to have a rapidly increasing trajectory for the high-income countries (Vincent & Velkoff, 2010; World Health Organization [WHO], National Institute on Aging, & National Institutes of Health, 2011). Some of the reasons for these increases in longevity have been attributed to a shift to chronic diseases from infectious diseases as the leading cause of death, alone and in combination with improved medical care (Rice & Fineman, 2004; WHO, National Institute on Aging, & National Institutes of Health, 2011). However, it is important to note that among the elderly, chronic diseases are a significant risk factor for declines in physical and cognitive functions (Bayliss, Bayliss, Ware, & Steiner, 2004; Carlo et al., 2000).

In addition to health factors such as high cholesterol, blood pressure, and blood glucose levels, health behaviors such as smoking, poor quality diet, and inadequate physical activity have been shown to be independent risk factors for chronic diseases and mortality (Burr et al., 1989; Chronic Disease Prevention and Health Promotion, 2014; Folsom et al., 1993; Hammond, 1966; Holme & Anderssen, 2015; Johnson, Hayes, Brown, Hoo, & Ethier, 2014; Landahl, Lernfelt, & Sundh, 1987; Prospective-Studies-Collaboration, 2007). Most studies have examined health factors and behaviors individually, and among the few that have used summary measures of either biomedical risk factors (cholesterol, blood pressure, diabetes) or health behaviors (smoking, physical activity, diet, obesity) showed reduced cardiovascular disease (CVD) mortality and all-cause mortality (Chakravarty et al., 2012; Fried et al., 1998; Lloyd-Jones, Dyer, Wang, Daviglus, & Greenland, 2007; Robinson et al., 2013; Stamler et al., 1999; Terry et al., 2005).

Because both health factors and health behaviors are important for reducing the risk for chronic diseases and mortality, in our study, we examined a cardiovascular health score assessing overall cardiovascular health based on American Heart Association’s (AHA) Life’s Simple 7, which includes health behaviors (smoking, body mass index [BMI], physical activity, and diet quality) and health factors (total cholesterol, blood pressure, and fasting plasma glucose; Lloyd-Jones et al., 2010). Specifically, we examined the association between cardiovascular health and all-cause and CVD mortality in a cohort of community-dwelling men and women 65 years and older. We hypothesized that in this elderly cohort, those with higher scores (indicating better cardiovascular health) at baseline would have lower risk of all-cause mortality and death due to CVD over a mean follow-up of 9 years.

Method

Data for these analyses were from the InCHIANTI study of aging. The InCHIANTI study is a prospective population-based study of elderly and includes participants from two cities: Greve in Chianti and Bagno a Ripoli in Tuscany, Italy. Participants were recruited during 1998 to 2000 using a two-stage stratified sampling procedure and were then followed longitudinally. Every 3 years, data on various study variables were collected through home interview, medical exam, and a clinical exam at the study site. A more detailed description of the InCHIANTI study has been provided elsewhere (Ferrucci et al., 2000).

A total of 1,453 participants enrolled at baseline, and out of these, 1,155 people with age greater than or equal to 65 years were included in these analyses. Participants (n = 192) who had missing information on any of the components of the cardiovascular health score or reported extreme energy intakes (defined as > 4,000 or < 600 kcal/day) were excluded. The incidence of all-cause death and CVD mortality was higher among participants with missing information on the cardiovascular health score. In addition, these participants were generally older, more likely to be cognitively impaired, and more likely to report disabilities on activities of daily living (ADL) and instrumental activities of daily living (IADL; data not shown). Furthermore, because some of the components of the overall cardiovascular health score such as diet, physical activity, and smoking status were based on self-report, which may be affected by cognitive status, we also excluded participants (n = 35) who had been diagnosed with dementia at baseline. The final analytical sample included 928 participants.

Overall Cardiovascular Health

Cardiovascular health in this cohort was based on criteria specified by the AHA and included seven health behaviors (smoking, diet quality, BMI, and physical activity) and factors (plasma total cholesterol, fasting glucose concentrations, and blood pressure). The detailed criteria for each cardiovascular health component are shown in the Appendix. We modified the criteria for three of the metrics, smoking, diet quality, and physical activity, to better suit the study population and data availability for the cohort. Smoking, in this study, was classified as never smoking, former smoker, and current smoking (within 3 years). Physical activity was classified as inactive (inactive, or with some walking), light active (light exercise 2–4 hr/week), and active (light exercise for more than 4 hr/week, moderate exercise for at least 1–2 hr/week, or intense exercise many times/week). For diet quality, we examined adherence to a Mediterranean-style diet. The Mediterranean diet score assessed intakes of nine foods, food groups, and nutrients. For food groups and nutrients that were considered beneficial, including vegetables, legumes, fruits and nuts, cereal, fish, and monounsaturated- to-saturated fatty acid ratio, participants received a point of 1 if their intakes were above the sex-specific median. For detrimental food groups (meat, dairy products), participants received 1 point if their intake was below the sex-specific median. For alcohol intake, participants received 1 point if they consumed between 10 g/day and 50 g/day for men and between 5 g/day and 25 g/day for women. A point of 0 would be given otherwise (Trichopoulou, Costacou, Bamia, & Trichopoulos, 2003).

In the cohort, information on smoking status and physical activity was obtained during home interview using standard questionnaires. Weight and height of each participant was measured, and BMI was then calculated as Weight (in kilograms) divided by the square of Height (in meters). A previously validated Food Frequency Questionnaire, which was created for the European Prospective Investigation Into Cancer and Nutrition (EPIC), was used to assess participants’ dietary intake (Pisani et al., 1997). Standard mercury sphygmomanometer was used to measure blood pressure 3 times, 2 min apart while participants were in supine position. Blood pressure was first measured on both arms, and two following measures were conducted on the arm of having higher systolic blood pressure at the first measure. The average of the last two measures was calculated as the final blood pressure of each participant. Total cholesterol and fasting plasma glucose were measured through blood test. Blood samples were collected after at least 8 hr fasting. An enzymatic colorimetric assay using a modified glucose oxidase-peroxidase method and a Roche-Hitachi 917 analyzer (Roche Diagnostics, GmbH, Mannheim, Germany) were used to determine fasting plasma glucose, and total cholesterol was determined by commercial enzymatic tests (Roche Diagnostics). Medication uses for reducing blood pressure, total cholesterol, and plasma glucose were also reported.

Participants were assigned 0 (poor), 1 (intermediate), or 2 (ideal) points based on their status for each of the cardiovascular health components (Appendix). For further analyses, we used the tertiles of the overall cardiovascular health score. For the InCHIANTI participants, the overall cardiovascular score for first, second, and third tertiles ranged from 0 to 6, 7 to 8, and 9 to 12, respectively. Cardiovascular health behaviors (score range: 0–8) and factors (score range: 0–6) were also separately examined.

Mortality—All-Cause and CVD-Specific

As part of cohort procedures, every study participant was contacted for follow-up interviews approximately every 3 years. After ascertaining vitality status, reports on mortality were confirmed using data from Tuscany Region Mortality General Registry and death certificates at the registry office of the municipality of residence. The mortality was recorded from 1998 to 2010. International Classification of Diseases, Ninth Revision (ICD-9) was used for identifying the underlying cause of death. Death due to heart diseases (ICD-9 code: 390-398, 402, 410-429, 440), stroke (ICD-9 code: 430-438), or other CVD (ICD-9 code: 441-448) was classified as CVD death for analyses purposes.

Covariates

The selection of covariates in these analyses was informed by univariate analyses and previously published literature and included age, sex, education, ADL disability, IADL disability, presence of chronic diseases, and impaired cognition. Education was assessed by querying participants’ total years of schooling. The ADL and IADL disabilities indicated the number of basic and instrumental activities of daily living which participants were not able to perform independently at baseline, and the number ranged from 0 to 6 for ADL and 0 to 8 for IADL (Lawton & Brody, 1969). Chronic diseases, including cancer, heart failure, coronary heart disease, stroke, chronic lung disease, hip arthritis, liver disease, gastrointestinal disease, peripheral arterial disease, Parkinson’s disease, and renal disease, was operationalized as the presence (or absence) of any of these specified diseases. The Mini Mental State Examination (MMSE) was used to assess impaired cognition at baseline. The MMSE score ranged from 0 to 30, and the cutoff score of 24 was used such that participants with an MMSE score below 24 were classified as having impaired cognition (Dick et al., 1984).

Statistical Analyses

Baseline sociodemographic and health characteristics were reported as means (standard deviation [SD]) or percentage, and one-way ANOVA for continuous variables and chi-square tests for categorical variables were used to test the difference of variables across the tertiles of overall cardiovascular health score. The incidence of death was calculated per 1,000 person-years. The association between overall cardiovascular health and all-cause and CVD mortality after adjusting for age, sex, education, ADL, IADL, impaired cognition, and chronic diseases were examined though Cox proportional hazards model, and hazard ratios (HRs) and their 95% confidence intervals (CIs) were reported. The proportional hazards assumption was ensured by examining the log–log plot and Schoenfeld residuals test. The non-linear models were also tested by including quadratic term for age, and this term was statistically significant in the CVD mortality model; hence, it was included in the model. We also checked for effect modification by sex, presence of chronic diseases, impaired cognition, ADL, and IADL, and because none of these terms were statistically significant, they were dropped from the final model. We also examined the associations between mortality and cardiovascular health behaviors and factors separately using Cox proportional hazards models, adjusting for all covariates. All analyses were performed using Stata Version 13.1 (StataCorp, 2013), and a p value less than .05 was considered to be statistically significant.

Results

The baseline sociodemographic and health characteristics are described in Table 1. The mean age (SD) of the cohort was 74 (6.67) years, with 55% being women. Participants with a higher overall cardiovascular health score at baseline were younger (p = .06) and reported less difficulties for ADL (p = .016) and IADL (p < .001). The distribution of ideal, intermediate, and poor scores for each component of the overall cardiovascular health score are presented in Figure 1. In this cohort of older individuals, 58.4% had ideal scores for smoking status, 39.1% for physical activity, 28.8% for BMI, 28.9% for diet quality, 29.2% for total cholesterol, 2.4% for blood pressure, and 73.5% for fasting plasma glucose.

Table 1.

Baseline Sociodemographic and Health Characteristics (mean [standard deviation] or percentage) by the Tertiles of Overall Cardiovascular Health Score Among InCHIANTI Participants Aged 65 Years and Older.

Overall cardiovascular health score
1st tertile
2nd tertile
3rd tertile
Variables Total Score = 0–6 Score = 7–8 Score = 9–12 p value
n 928 250 376 302
Overall
cardiovascular
health score
7.58 (1.91) 5.19 (1.08) 7.49 (0.50) 9.69 (0.87)
Female (%) 55.2 55.6 58.0 51.3 .221
Age (years) 74.0 (6.67) 74.6 (6.85) 74.2 (6.54) 73.3 (6.64) .06
Education (years) 5.51 (3.24) 5.48 (3.30) 5.48 (3.10) 5.57 (3.36) .924
MMSE score 25.4 (3.07) 25.3 (2.90) 25.4 (3.08) 25.6 (3.20) .472
Presence of ADL
disabilities (%)
3.99 5.20 5.32 1.32 .016
Presence of IADL
disabilities (%)
19.5 27.2 21.0 11.3 <.001
Presence of chronic
disease (%)
62.2 68.0 62.8 56.6 .022
BMI (kg/m2) 27.5 (4.06) 29.6 (4.30) 27.5 (3.89) 25.8 (3.19) <.001
Mediterranean diet
score
4.47 (1.64) 3.72 (1.63) 4.40 (1.55) 5.18 (1.44) <.001
Total cholesterol
(mg/dl)
219 (38.7) 235 (39.0) 221 (35.1) 203 (36.9) <.001
Systolic blood
pressure (mmHg)
151 (19.5) 155 (17.0) 153 (19.0) 145 (20.8) <.001
Diastolic blood
pressure (mmHg)
84.1 (8.55) 85.6 (7.71) 84.7 (8.39) 82.2 (9.07) <.001
Fasting plasma
glucose (mg/dl)
96.0 (26.3) 110 (33.4) 93.6 (25.4) 87.5 (12.6) <.001
Physical activity (%) <.001
  Sedentary 16.8 35.6 15.2 3.31
  Light active 44.1 50.8 51.1 29.8
  Active 39.1 13.6 33.8 66.9

Note. MMSE = Mini Mental State Examination; ADL = activities of daily living; IADL = instrumental activities of daily living; BMI = body mass index.

Figure 1.

Figure 1

Percentage of ideal, intermediate, and poor for each component of overall cardiovascular health assessment among InCHIANTI participants aged 65 years and older.

Note. BMI = body mass index.

The average follow-up for the cohort was 9.1 years (range: 0.2–11.4 years). By 2010, a total of 301 people died (incidence rate = 35.7 per 1,000 person-years). The incidence of all-cause and CVD mortality was the highest for participants in the first tertile (lowest overall cardiovascular health score; Table 2). Compared with participants in first tertile, the risk of all-cause mortality were significantly lower for participants in the second tertile (HR = 0.67, p = .004, 95% CI = [0.52, 0.88]) and third tertile (HR = 0.68, p = .012, 95% CI = [0.51, 0.92]) after adjusting for sex, age, education, impaired cognition, presence of chronic diseases, ADL, and IADL. There were no statistically significant differences between the second and third tertiles. Protective associations for overall cardiovascular health were observed when the score was examined on a continuous scale, wherein a one unit increase in the score was associated with a 9% lower risk of all-cause mortality (HR = 0.91, p = .001, 95% CI = [0.86, 0.96]; Table 3).

Table 2.

Incidence Rate of All-Cause Mortality and CVD Mortality Among InCHIANTI Participants Aged 65 Years and Older.

All-cause mortality
CVD mortality
Death (n) Incidence ratea Death (n) Incidence ratea
Cardiovascular health score
  1st tertile 108 49.3 48 21.9
  2nd tertile 113 32.8 45 13.1
  3rd tertile 80 28.5 26 9.3
Total 301 35.7 119 14.1

Note. CVD = cardiovascular disease.

a

Incidence rate per 1,000 person-years..

Table 3.

Adjusted Hazard Ratio of All-Cause Mortality and CVD Mortality for Overall Cardiovascular Health Score Among InCHIANTI Participants Aged 65 Years and Older.a

All-cause mortality
CVD mortality
Hazard
ratio
p
value
95%
CI
Hazard
ratio
P
value
95%
CI
Cardiovascular health scoreb
  Per 1 point increase 0.91 .001 [0.86, 0.96] 0.89 .01 [0.81, 0.97]
  1st tertile Ref. Ref.
  2nd tertile 0.67 .004 [0.52, 0.88] 0.62 .033 [0.41, 0.96]
  3rd tertile 0.68 .012 [0.51, 0.92] 0.61 .037 [0.38, 0.97]
Covariatesc
  Aged 1.12 <.001 [1.10, 1.14] 2.68 .003 [1.40, 5.16]
  Female 0.49 <.002 [0.39, 0.63] 0.48 <.001 [0.33, 0.70]
  Education yearsd 0.98 .338 [0.94, 1.02] 0.98 .573 [0.92, 1.05]
  ADL disabilitye 1.20 .034 [1.01, 1.42] 1.17 .197 [0.92, 1.49]
  IADL disabilitye 1.18 <.001 [1.09, 1.28] 1.34 <.001 [1.20, 1.50]
  Cognitive impairment 1.07 .652 [0.80, 1.44] 1.09 .702 [0.71, 1.68]
  Chronic disease 1.66 .001 [1.24, 2.21] 1.53 .107 [0.91, 2.55]

Note. CI = confidence interval; ADL = activities of daily living; IADL = instrumental activities of daily living; CVD = cardiovascular disease.

a

Cox proportional hazard model adjusted for age (years), sex, education (years), impaired cognition (Mini Mental State Examination, [MMSE] score < 24), number of ADL disabilities, number of IADL disabilities, presence of chronic diseases (Y/N), and quadratic term for age for the model of CVD mortality.

b

There were no statistically significant differences between the second and third tertiles, for both, all-cause and CVD mortality.

c

Covariates in the Cox proportional hazard model are for cardiovascular health score modeled as tertiles.

d

Per 1 year increase.

e

Per 1 ADL and IADL disability increase, respectively.

Forty percent of deaths in the cohort were due to CVD (n = 119, incidence rate = 14.1 per 1,000 person-years). Similar to that observed for all-cause mortality, a one unit increase in the overall cardiovascular health score was associated with an 11% lower risk of CVD-related mortality (HR = 0.89, p = .010, 95% CI = [0.81, 0.97]). When tertiles of overall cardiovascular health scores were examined, participants with scores in the second tertile (HR = 0.62, p = .033, 95% CI = [0.41, 0.96]) and third tertile (HR = 0.61, p = .037, 95% CI = [0.38, 0.97]) had significantly lower risk of CVD-related mortality as compared with those in the first tertile. There were no statistically significant differences between participants in the second and third tertiles for CVD mortality.

In sensitivity analysis, we excluded participants who died within 2 years from baseline information collection and then re-ran the analyses for the associations between mortality and cardiovascular health score. The cardiovascular health score was still significantly associated with both all-cause and CVD mortality and demonstrated an even higher risk of mortality for participants with poor cardiovascular health (data not shown).

Summary scores for health behaviors and factors were also associated with reduced risk of all-cause and CVD mortality after adjusting for all covariates (Table 4). For every 1 unit increase in the health behavior score, participants had a 14% lower risk of all-cause mortality (HR = 0.86, p < .001, 95% CI = [0.79, 0.93]) and a 12% lower risk of CVD mortality (HR = 0.88, p = .05, 95% CI = [0.77, 1.00]), whereas for every 1 unit increase in the health factor score, participants had a 14% lower risk of CVD mortality (HR = 0.86, p = .038, 95% CI = [0.74, 0.99]). Associations for the health factor score with all-cause mortality were not statistically significant.

Table 4.

Adjusted Hazard Ratio of All-Cause Mortality and CVD Mortality for Cardiovascular Health Behaviors and Factors Among InCHIANTI Participants Aged 65 Years and Older.a

Hazard ratio p value 95% CI
All-cause mortality
  Health behaviorsb 0.86 <.001 [0.79, 0.93]
  Health factorsc 0.95 .286 [0.85, 1.05]
CVD mortality
  Health behaviorsb 0.88 .05 [0.77, 1.00]
  Health factorsc 0.86 .038 [0.74, 0.99]

Note. CI = confidence interval; CVD = cardiovascular disease; ADL = activities of daily living; IADL = instrumental activities of daily living; BMI = body mass index.

a

Cox proportional hazard model adjusted for age (years), sex, education (years), impaired cognition (Mini Mental State Examination, [MMSE] score < 24), number of ADL disabilities, number of IADL disabilities, presence of chronic diseases (Y/N), and quadratic term for age for the model for CVD mortality.

b

Health behaviors included smoking, physical activity, BMI, diet quality, and score ranged from 0 to 8. Hazard of mortality per 1 point increase of health behavior score.

c

Health factors included blood pressure, total cholesterol, fasting plasma glucose, and score ranged from 0 to 6. Hazard of mortality per 1 point increase of health factor score.

The Kaplan–Meier survival curve also showed a higher survival rate for people in the highest tertile over 11 follow-up years (Figure 2). The mean (SD) survival time for participants in the first tertile was 8.9 (0.19) years, for second tertile it was 9.4 (0.15) years, and for third tertile, it was 9.6 (0.16) years.

Figure 2.

Figure 2

All-cause mortality Kaplan–Meier survival estimates during 11-year follow-up among InCHIANTI participants aged 65 years and older.

Discussion

The goal of this study was to examine whether overall cardiovascular health was associated with mortality among older individuals. Overall cardiovascular health in this study was assessed using a summary measure of four health behaviors and three health factors. Our results indicate that higher scores for overall cardiovascular health (indicating better cardiovascular health) were associated with lower all-cause and CVD-related mortality, suggesting that health behaviors (smoking, physical activity, BMI, diet quality) and factors (total cholesterol, blood pressure, plasma glucose) are important for older individuals in improving life expectancy. Protective associations were also found for summary measures of only the health behaviors (all-cause and CVD mortality) and health factors (CVD mortality only).

The overall cardiovascular health score, based on the AHA’s Life’s Simple 7 metric, assessed smoking status, physical activity, BMI, diet quality, levels of total cholesterol and fasting blood glucose, and measures of blood pressure, all of which are important for CVD prevention and enhancing disease-free life (Lloyd-Jones et al., 2010). Several studies have demonstrated a protective association for higher scores for this summary measure with CVD, including stroke and coronary heart disease (Folsom et al., 2011; Kulshreshtha et al., 2013). And evidence for protective associations have also been reported for other health conditions including chronic kidney disease, venous thromboembolism, subclinical atherosclerosis, inflammation, cognitive decline, and depression (Kronish, Carson, Davidson, Muntner, & Safford, 2012; Muntner et al., 2013; Olson et al., 2015; Thacker et al., 2014; Xanthakis et al., 2014) It is important to note that most of these studies have examined the role of cardiovascular health in young and middle-aged adults, and there are few investigations that have focused on older populations.

Our study demonstrated that overall cardiovascular health, even in older individuals, is protective against all-cause and CVD mortality. The HRs for these associations in this cohort of older adults were similar to those that have been reported in other studies with younger and middle-aged participants (Artero et al., 2012; Ford, Greenlund, & Hong, 2012; Yang et al., 2012). Moreover, distributions of the individual components observed in the present study, including the low number of participants receiving ideal scores for all the health factors and behaviors, are similar to those reported by others (Ford et al., 2012; Yang et al., 2012). One notable difference in this cohort as compared with other studies was the high prevalence of those classified as poor health for the blood pressure criteria. In our cohort, 78% of participants were classified as having either systolic blood pressure equal to or above 140 mmHg or diastolic blood pressure equal to or above 90 mmHg, and participants with blood pressure above 120/80 mmHg had higher risk of death. High prevalence of hypertension has also been reported by other epidemiological investigation in the elderly, suggesting that high blood pressure is a major risk for older adults (Hajjar & Kotchen, 2003; Vokonas, Kannel, & Cupples, 1988).

Our study had several strengths including its prospective design and focus on older individuals. In addition, data on health behaviors and factors were collected using standardized and validated methods. Mortality was also verified by local Mortality General Registry. Information on several confounders and covariates, including cognitive and physical function status and comorbidities, was available in the cohort, and we were able to adjust for these in the analyses. Some limitations include its observational design which could lead to some residual confounding. Our study cohort consisted of 928 older men and women, which is a relatively small sample size; however, it must be noted that post hoc analyses indicated that we were 80% powered to detect a HR of 0.72, assuming two-sided testing at the .05 level. Although not a limitation, we modified the overall cardiovascular health score for diet quality and physical activity from those specified by the AHA for their Life’s Simple 7 metric. Given the age range of the study participants and the previous work that had been published using the physical activity data in the InCHIANTI cohort, we opted to use similar scoring criteria for the cohort (Elosua et al., 2005). Similarly, we used adherence to a Mediterranean-style diet as the diet quality metric, as it better reflected the dietary patterns of the region and had previously been shown to be associated with age-related declines in the cohort (Milaneschi et al., 2011; Talegawkar et al., 2012). Out of the cohort eligible for these analyses, 16.5% had missing data for one or more components of the cardiovascular health score. The incidence of all-cause death and CVD mortality was higher among participants with missing information for the cardiovascular health score. These participants were generally older, had cognitive impairment, and were more likely to report disabilities on ADL/IADL. Given this, the associations obtained in our analyses may be a conservative estimate of the true associations between cardiovascular health and mortality.

In conclusion, even among older individuals, better overall cardiovascular health assessed by health behaviors (smoking, physical activity, BMI, diet) and health factors (cholesterol, blood pressure, plasma glucose) was associated with a lower risk of all-cause mortality and CVD mortality. These relationships allude to the importance of emphasizing health factors and behaviors in the elderly in promoting longevity.

Acknowledgments

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by National Institute of Aging, Grant R03AG048377. The InCHIANTI Study was supported as a “targeted project” (ICS 110.1/RS97.71) by the Italian Ministry of Health and in part by the U.S. National Institute on Aging (Contracts N01-AG-916413 and N01-AG-821336 and AG-020727), and by the Intramural Research Program of the U.S. National Institute on Aging (Contracts 263 MD 9164 13 and 263 MD 821336). None of the sponsoring institutions interfered with the collection, analysis, presentation, or interpretation of the data reported here.

Appendix

Criteria of Each of the Overall Cardiovascular Health Component.

Overall
cardiovascular
health
components
Ideal
(2 points)
Intermediate
(1 point)
Poor
(0 point)
Smoking Non-smoker Former smoker Current smoker within 3 y
Physical activity Light exercise for more than 4 hr/week, moderate exercise for at least 1–2 hr/week, or intense exercise many times/week Light exercise 2–4 hr/week Inactive, or with some walking
Body mass index (kg/m2)    <25    25–29.9    ≥30
Diet quality (Mediterranean diet score)    6–9    4–5    0–3
Total cholesterol (mg/dl)    <200 200–239 or treated to <200    ≥240
Blood pressure (mmHg) SBP < 120 and DBP < 80 SBP: 120–139 or DBP: 80–89 or treated to SBP < 120 and DBP < 80 SBP ≥ 140 or DBP ≥ 90
Fasting plasma glucose (mg/dl)    <100 100–125 or treated to <100    ≥126

Note. SBP = systolic blood pressure; DBP = diastolic blood pressure.

Footnotes

Research Ethics

All respondents signed informed consent, and the Italian National Institute of Research and Care on Aging Ethical Committee approved the study protocol. Furthermore, the institutional review board of George Washington University deemed this secondary analysis plan using de-identified data as not constituting human subjects research.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

References

  1. Artero EG, España-Romero V, Lee DC, Sui X, Church TS, Lavie CJ, Blair SN. Ideal cardiovascular health and mortality: Aerobics center longitudinal study. Mayo Clinic Proceedings. 2012;87:944–952. doi: 10.1016/j.mayocp.2012.07.015. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Bayliss EA, Bayliss MS, Ware JE, Steiner JF. Predicting declines in physical function in persons with multiple chronic medical conditions: What we can learn from the medical problem list. Health and Quality of Life Outcomes. 2004;2(1):47. doi: 10.1186/1477-7525-2-47. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Burr ML, Gilbert J, Holliday R, Elwood P, Fehily A, Rogers S, Deadman N. Effects of changes in fat, fish, and fibre intakes on death and myocardial reinfarction: Diet and reinfarction trial (DART) The Lancet. 1989;334:757–761. doi: 10.1016/s0140-6736(89)90828-3. [DOI] [PubMed] [Google Scholar]
  4. Carlo A, Baldereschi M, Amaducci L, Maggi S, Grigoletto F, Scarlato G, Inzitari D. Cognitive impairment without dementia in older people: Prevalence, vascular risk factors, impact on disability. The Italian Longitudinal Study on Aging. Journal of the American Geriatrics Society. 2000;48:775–782. doi: 10.1111/j.1532-5415.2000.tb04752.x. [DOI] [PubMed] [Google Scholar]
  5. Chakravarty EF, Hubert HB, Krishnan E, Bruce BB, Lingala VB, Fries JF. Lifestyle risk factors predict disability and death in healthy aging adults. The American Journal of Medicine. 2012;125:190–197. doi: 10.1016/j.amjmed.2011.08.006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Chronic Disease Prevention and Health Promotion. Chronic diseases and health promotion. Atlanta, GA: U.S. Department of Health and Human Services; 2014. Available from http://www.cdc.gov/chronicdisease/overview/index.htm. [Google Scholar]
  7. Dick J, Guiloff R, Stewart A, Blackstock J, Bielawska C, Paul E, Marsden C. Mini-mental state examination in neurological patients. Journal of Neurology, Neurosurgery & Psychiatry. 1984;47:496–499. doi: 10.1136/jnnp.47.5.496. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Elosua R, Bartali B, Ordovas JM, Corsi AM, Lauretani F, Ferrucci L. Association between physical activity, physical performance, and inflammatory biomarkers in an elderly population: The InCHIANTI study. The Journals of Gerontology, Series A: Biological Sciences & Medical Sciences. 2005;60:760–767. doi: 10.1093/gerona/60.6.760. [DOI] [PubMed] [Google Scholar]
  9. Ferrucci L, Bandinelli S, Benvenuti E, Iorio A, Macchi C, Harris TB, Guralnik JM. Subsystems contributing to the decline in ability to walk: Bridging the gap between epidemiology and geriatric practice in the InCHIANTI study. Journal of the American Geriatrics Society. 2000;48:1618–1625. doi: 10.1111/j.1532-5415.2000.tb03873.x. [DOI] [PubMed] [Google Scholar]
  10. Folsom AR, Kaye SA, Sellers TA, Hong C-P, Cerhan JR, Potter JD, Prineas RJ. Body fat distribution and 5-year risk of death in older women. Journal of the American Medical Association. 1993;269:483–487. [PubMed] [Google Scholar]
  11. Folsom AR, Yatsuya H, Nettleton JA, Lutsey PL, Cushman M, Rosamond WD. Community prevalence of ideal cardiovascular health, by the American Heart Association definition, and relationship with cardiovascular disease incidence. Journal of the American College of Cardiology. 2011;57:1690–1696. doi: 10.1016/j.jacc.2010.11.041. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Ford ES, Greenlund KJ, Hong Y. Ideal cardiovascular health and mortality from all causes and diseases of the circulatory system among adults in the United States. Circulation. 2012;125:987–995. doi: 10.1161/CIRCULATIONAHA.111.049122. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Fried LP, Kronmal RA, Newman AB, Bild DE, Mittelmark MB, Polak JF, Gardin JM. Risk factors for 5-year mortality in older adults: The Cardiovascular Health Study. Journal of the American Medical Association. 1998;279:585–592. doi: 10.1001/jama.279.8.585. [DOI] [PubMed] [Google Scholar]
  14. Hajjar I, Kotchen TA. Trends in prevalence, awareness, treatment, and control of hypertension in the United States, 1988–2000. Journal of the American Medical Association. 2003;290:199–206. doi: 10.1001/jama.290.2.199. [DOI] [PubMed] [Google Scholar]
  15. Hammond EC. Smoking in relation to the death rates of one million men and women. Journal of the National Cancer Institute Monographs. 1966;19:127–204. [PubMed] [Google Scholar]
  16. Holme I, Anderssen S. Increases in physical activity is as important as smoking cessation for reduction in total mortality in elderly men: 12 years of follow-up of the Oslo II study. British Journal of Sports Medicine. 2015;49:743–748. doi: 10.1136/bjsports-2014-094522. [DOI] [PubMed] [Google Scholar]
  17. Johnson NB, Hayes LD, Brown K, Hoo EC, Ethier KA. CDC National Health Report: Leading causes of morbidity and mortality and associated behavioral risk and protective factors-United States, 2005–2013. Morbidity and Mortality Weekly Report. 2014;63:3–27. [PubMed] [Google Scholar]
  18. Kronish IM, Carson AP, Davidson KW, Muntner P, Safford MM. Depressive symptoms and cardiovascular health by the American Heart Association’s definition in the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study. PLoS ONE. 2012;7(12):e52771. doi: 10.1371/journal.pone.0052771. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Kulshreshtha A, Vaccarino V, Judd SE, Howard VJ, McClellan WM, Muntner P, Cushman M. Life’s Simple 7 and risk of incident stroke the reasons for geographic and racial differences in stroke study. Stroke. 2013;44:1909–1914. doi: 10.1161/STROKEAHA.111.000352. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Landahl S, Lernfelt B, Sundh V. Blood pressure and mortality in old age. Eleven years’ follow-up of a 70-year-old population. Journal of Hypertension. 1987;5:745–748. doi: 10.1097/00004872-198712000-00019. [DOI] [PubMed] [Google Scholar]
  21. Lawton M, Brody EM. Assessment of older people: Self-maintaining and instrumental activities of daily living. Gerontologist. 1969;9:179–186. [PubMed] [Google Scholar]
  22. Lloyd-Jones DM, Dyer AR, Wang R, Daviglus ML, Greenland P. Risk factor burden in middle age and lifetime risks for cardiovascular and non-cardiovascular death (Chicago Heart Association Detection Project in Industry) The American Journal of Cardiology. 2007;99:535–540. doi: 10.1016/j.amjcard.2006.09.099. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Lloyd-Jones DM, Hong Y, Labarthe D, Mozaffarian D, Appel L, Van Horn L American Heart Association Strategic Planning Task Force and Statistics Committee. Defining and setting national goals for cardiovascular health promotion and disease reduction: The American Heart Association’s strategic impact goal through 2020 and beyond. Circulation. 2010;121:586–613. doi: 10.1161/CIRCULATIONAHA.109.192703. [DOI] [PubMed] [Google Scholar]
  24. Milaneschi Y, Bandinelli S, Corsi AM, Lauretani F, Paolisso G, Dominguez LJ, Talegawkar SA. Mediterranean diet and mobility decline in older persons. Experimental gerontology. 2011;46:303–308. doi: 10.1016/j.exger.2010.11.030. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Muntner P, Judd SE, Gao L, Gutiérrez OM, Rizk DV, McClellan W, Warnock DG. Cardiovascular risk factors in CKD associate with both ESRD and mortality. Journal of the American Society of Nephrology. 2013;24:1159–1165. doi: 10.1681/ASN.2012070642. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Olson NC, Cushman M, Judd SE, McClure LA, Lakoski SG, Folsom AR, Zakai NA. American Heart Association’s Life’s Simple 7 and risk of venous thromboembolism: The Reasons for Geographic and Racial Differences in Stroke (REGARDS) Study. Journal of the American Heart Association. 2015;4(3):e001494. doi: 10.1161/JAHA.114.001494. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Pisani P, Faggiano F, Krogh V, Palli D, Vineis P, Berrino F. Relative validity and reproducibility of a food frequency dietary questionnaire for use in the Italian EPIC centres. International Journal of Epidemiology. 1997;26(Suppl. 1):S152–S160. doi: 10.1093/ije/26.suppl_1.s152. [DOI] [PubMed] [Google Scholar]
  28. Prospective-Studies-Collaboration. Blood cholesterol and vascular mortality by age, sex, and blood pressure: A meta-analysis of individual data from 61 prospective studies with 55 000 vascular deaths. The Lancet. 2007;370:1829–1839. doi: 10.1016/S0140-6736(07)61778-4. [DOI] [PubMed] [Google Scholar]
  29. Rice DP, Fineman N. Economic implications of increased longevity in the United States. Annual Review of Public Health. 2004;25:457–473. doi: 10.1146/annurev.publhealth.25.101802.123054. [DOI] [PubMed] [Google Scholar]
  30. Robinson SM, Jameson KA, Syddall HE, Dennison EM, Cooper C, Aihie Sayer A. Clustering of lifestyle risk factors and poor physical function in older adults: The Hertfordshire cohort study. Journal of the American Geriatrics Society. 2013;61:1684–1691. doi: 10.1111/jgs.12457. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Stamler J, Stamler R, Neaton JD, Wentworth D, Daviglus ML, Garside D, Greenland P. Low risk-factor profile and long-term cardiovascular and noncardiovascular mortality and life expectancy: Findings for 5 large cohorts of young adult and middle-aged men and women. Journal of the American Medical Association. 1999;282:2012–2018. doi: 10.1001/jama.282.21.2012. [DOI] [PubMed] [Google Scholar]
  32. StataCorp. Stata Statistical Software: Release 13. College Station, TX: StataCorp LP; 2013. [Google Scholar]
  33. Talegawkar SA, Bandinelli S, Bandeen-Roche K, Chen P, Milaneschi Y, Tanaka T, Ferrucci L. A higher adherence to a Mediterranean-style diet is inversely associated with the development of frailty in community-dwelling elderly men and women. The Journal of Nutrition. 2012;142:2161–2166. doi: 10.3945/jn.112.165498. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Terry DF, Pencina MJ, Vasan RS, Murabito JM, Wolf PA, Hayes MK, Benjamin EJ. Cardiovascular risk factors predictive for survival and morbidity-free survival in the oldest-old Framingham Heart Study participants. Journal of the American Geriatrics Society. 2005;53:1944–1950. doi: 10.1111/j.1532-5415.2005.00465.x. [DOI] [PubMed] [Google Scholar]
  35. Thacker EL, Gillett SR, Wadley VG, Unverzagt FW, Judd SE, McClure LA, Cushman M. The American Heart Association Life’s Simple 7 and incident cognitive impairment: The reasons for geographic and racial differences in stroke (REGARDS) Study. Journal of the American Heart Association. 2014;3(3):e000635. doi: 10.1161/JAHA.113.000635. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Trichopoulou A, Costacou T, Bamia C, Trichopoulos D. Adherence to a Mediterranean diet and survival in a Greek population. New England Journal of Medicine. 2003;348:2599–2608. doi: 10.1056/NEJMoa025039. [DOI] [PubMed] [Google Scholar]
  37. Vincent GK, Velkoff VA. The next four decades: The older population in the United States: 2010 to. 2050. Washington, DC: U.S. Department of Commerce, Economics and Statistics Administration, U.S. Census Bureau; 2010. [Google Scholar]
  38. Vokonas P, Kannel W, Cupples L. Epidemiology and risk of hypertension in the elderly: The Framingham Study. Journal of Hypertension. Supplement: Official Journal of the International Society of Hypertension. 1988;6(1):S3–S9. [PubMed] [Google Scholar]
  39. World Health Organization, National Institute on Aging, & National Institutes of Health. Global health and ageing (NIH Publication No. 11-7737) Washington, DC: WHO, National Institute on Aging, National Institutes of Health, U. S. Department of Health and Human Services; 2011. [Google Scholar]
  40. Xanthakis V, Enserro DM, Murabito JM, Polak JF, Wollert KC, Januzzi JL, Vasan RS. Ideal cardiovascular health: Associations with biomarkers and subclinical disease and impact on Incidence of cardiovascular disease in the Framingham offspring study. Circulation. 2014;130:1676–1683. doi: 10.1161/CIRCULATIONAHA.114.009273. [DOI] [PubMed] [Google Scholar]
  41. Yang Q, Cogswell ME, Flanders WD, Hong Y, Zhang Z, Loustalot F, Hu FB. Trends in cardiovascular health metrics and associations with all-cause and CVD mortality among US adults. Journal of the American Medical Association. 2012;307:1273–1283. doi: 10.1001/jama.2012.339. [DOI] [PMC free article] [PubMed] [Google Scholar]

RESOURCES