Literature DB >> 28655734

Life's Simple 7 and Incident Heart Failure: The Multi-Ethnic Study of Atherosclerosis.

Oluseye Ogunmoroti1,2, Ebenezer Oni3, Erin D Michos4, Erica S Spatz5,6, Norrina B Allen7, Jamal S Rana8,9, Salim S Virani10,11, Ron Blankstein12, Konstantinos N Aronis13, Roger S Blumenthal4, Emir Veledar1,14, Moyses Szklo15, Michael J Blaha4, Khurram Nasir16,17,2,18,4.   

Abstract

BACKGROUND: The American Heart Association introduced the Life's Simple 7 (LS7) metrics to assess and promote cardiovascular health. We sought to examine the association between the LS7 metrics and incident heart failure (HF) in a multiethnic cohort. METHODS AND
RESULTS: We analyzed data from 6506 participants of the Multi-Ethnic Study of Atherosclerosis free of cardiovascular disease at baseline. The LS7 metrics (smoking, physical activity, body mass index, diet, blood pressure, total cholesterol, and blood glucose) were graded on a scale of 0 to 2, with 2 indicating "ideal" status, 1 "intermediate" status, and 0 "poor" status. Points were summed, thus the LS7 score ranged from 0 to 14. Cox proportional hazard ratios and incidence rates of HF per 1000 person-years were calculated. During a median follow-up of 12.2 years, 262 (4%) participants developed HF. Incidence of HF decreased as the number of ideal LS7 metrics increased; 5.9 per 1000 person-years for participants with 0 to 1 ideal metrics and 0.6 per 1000 person-years for those with 6 to 7 ideal metrics. Compared with inadequate scores (0-8 points), hazard ratios for HF were 0.57 (0.43-0.76) and 0.31 (0.19-0.49) for average (9-10 points) and optimal (11-14 points) scores, respectively. A similar pattern was observed when the results were stratified by 4 racial/ethnic groups: white, Chinese American, black, and Hispanic.
CONCLUSIONS: A lower risk of HF with more favorable LS7 status regardless of race/ethnicity suggests that efforts to achieve ideal cardiovascular health may reduce the burden of HF, a major source of morbidity and mortality.
© 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

Entities:  

Keywords:  Life's Simple 7; cardiovascular disease prevention; epidemiology; heart failure; ideal cardiovascular health metrics; risk factor

Mesh:

Substances:

Year:  2017        PMID: 28655734      PMCID: PMC5669160          DOI: 10.1161/JAHA.116.005180

Source DB:  PubMed          Journal:  J Am Heart Assoc        ISSN: 2047-9980            Impact factor:   5.501


Clinical Perspective

What is New?

This study examined the association between the American Heart Association's Life's Simple 7 and incident heart failure in a multiethnic cohort, with Chinese American and Hispanic participants included in the analyses unlike previous studies that examined a similar association in only white or black participants. Our findings show that irrespective of race/ethnicity, greater numbers of the Life's Simple 7 metrics at ideal levels and average as well as optimal Life's Simple 7 scores were associated with a lower risk of heart failure.

What are the Clinical Implications?

Heart failure is responsible for a significant reduction in quality of life and higher mortality rates with a life expectancy of 5 years for ≈50% of patients. An estimated 870 000 new cases are documented in the United States annually, and if the current trend continues, it is projected that by 2030 over 8 million people, aged 18 years or older, will have the disease. The morbidity, mortality, and socioeconomic burden associated with heart failure can be reduced by encouraging the public to improve their cardiovascular health by adopting healthy lifestyles and achieving greater numbers of ideal Life's Simple 7 metrics.

Introduction

Heart failure (HF) prevention is a top public health priority.1 Approximately 23 million people have HF worldwide,2 a number that is expected to rise because of the aging population and increasing prevalence of risk factors.3, 4 In the United States, an estimated 5.7 million people have HF, with a total annual cost of $30.7 billion.5 Incidence and substantial economic burden of HF can be decreased by intensifying efforts to reduce modifiable risk factors, such as tobacco use, sedentary lifestyle, obesity, hypertension, hypercholesterolemia, and diabetes mellitus.1, 6 The American Heart Association introduced the concept of “ideal cardiovascular health (CVH)” with a focus on risk factor prevention to reduce the burden of cardiovascular diseases (CVDs).7 Ideal CVH is defined as meeting the ideal levels for 7 health behaviors and factors called Life's Simple 7 (LS7) metrics.7 These 7 metrics are known traditional risk factors for CVD and they include smoking, physical activity, body mass index (BMI), diet, total cholesterol, blood pressure, and blood glucose.8, 9, 10 Although research has shown that ideal CVH is associated with a lower incidence of CVDs,11, 12, 13, 14, 15, 16, 17 few studies have examined the association between the LS7 metrics and the incidence of HF in an ethnically diverse population.18, 19 The aim of this study is to analyze data from the MESA (Multi‐Ethnic Study of Atherosclerosis), a prospective cohort study, to determine the association between the LS7 metrics and incident HF, based on the hypothesis that favorable LS7 status will confer a lower risk for HF across all 4 racial/ethnic groups independent of other sociodemographic factors such as age, sex, education, income, and health insurance.

Methods

Study Population

The details of the MESA have been previously described by Bild et al.20 In summary, 6814 study participants were recruited between July 2000 and September 2002 from 6 field centers in the United States (Baltimore, MD; Chicago, IL; Forsyth County, NC; Los Angeles, CA; New York City, NY; and St Paul, MN). They included men and women aged between 45 and 84 years, who were free from clinical CVD (including HF) at baseline. Approximately 38% were white, 28% black, 23% Hispanic, and 11% Chinese American. Participants gave informed consent and the institutional review boards of the 6 centers approved the study protocol. Standardized questionnaires were administered to collect information on the use of medications and socioeconomic characteristics, such as education, income, and health insurance.

Baseline Measurement of LS7 Metrics

Baseline levels of LS7 metrics (smoking, physical activity, BMI, diet, total cholesterol, blood pressure, and blood glucose) were measured between 2000 and 2002. Participants were classified as current smokers, former smokers (if they quit within the last 12 months) or never smokers (if they have never smoked or quit more than 12 months ago). BMI (kg/m2) was calculated from weight and height measurements. Physical activity was assessed using the MESA Typical Week Physical Activity Survey adapted from the Cross‐Cultural Activity Participation Study.21 The questionnaire contains 28 detailed questions on time and frequency of activities during a typical week in the previous month. Participants provided responses to questions, such as household chores, lawn/yard/garden/farm, care of children/adults, transportation, walking (not at work), dancing and sport activities, conditioning activities, leisure activities, and occupational and volunteer activities. Minutes spent during activities like walking, conditioning, and leisure (eg, exercises) were also included. The total minutes of moderate and vigorous exercise were estimated from the questionnaire. A validated 120‐item food frequency questionnaire was administered to collect information on the dietary habits of study participants. It was modified from the Insulin Resistance Atherosclerosis Study instrument.22, 23 A healthy diet consisted of adequate quantities of 5 items defined by the American Heart Association (fruits and vegetables, fish, whole grains, sodium <1500 mg per day, and sugar‐sweetened beverages ≤450 kcal [36 oz] per week).7Study participants had their blood pressure assessed from 3 readings taken after they had rested for 5 minutes. The average of the last 2 readings was recorded for analysis. Total cholesterol and blood glucose levels were obtained from fasting blood samples.

Follow‐up and Incident HF Definition

Median follow‐up time was 12.2 years (interquartile range, 11.6–12.7) resulting in 71 718 person‐years of observation. After the baseline examination, study participants were followed up every 9 to 12 months by telephone to obtain information on interim hospital admissions, cardiovascular outpatient diagnoses, and deaths. Self‐reported diagnoses were verified from death certificates, medical records for all hospitalizations, and outpatient diagnoses. Hospital records were abstracted by trained personnel and transmitted to the coordinating center. Two physicians (cardiologists or cardiovascular physician epidemiologists) reviewed the records for independent end point classification and disagreements were adjudicated by both. If disagreements were not resolved the full morbidity and mortality classification committee made the final decision. The end point for our study was a combination of probable and definite HF as defined by previously published research from MESA.24, 25, 26, 27 Both required HF symptoms and/or signs such as shortness of breath or edema. Probable HF was defined as a diagnosis of HF made by a physician and medical treatment for HF. For definite HF, 1 or more additional objective criteria were required, such as pulmonary edema/congestion by chest X‐ray, dilated ventricle or poor left ventricular function by echocardiography or ventriculography, or evidence of left ventricular diastolic dysfunction. For our analysis, we combined incident definite and probable HF as 1 outcome without stratification into preserved or reduced ejection fraction HF.

Statistical Analysis

Baseline characteristics of study participants were compared by race/ethnicity. Categorical variables were reported as proportions and continuous variables as means with standard deviation (SD). We categorized the LS7 metrics into ideal, intermediate, and poor with modifications as previously reported in MESA (Table S1).7, 28 We created the LS7 score from points assigned to each category of the metrics; poor=0 point, intermediate=1 point, and ideal=2 points. The points were summed for a total LS7 score ranging from 0 to 14.29 As previously described, we considered 0 to 8, 9 to 10, and 11 to 14 points as inadequate, average, and optimal scores, respectively.28 The HF incidence rate per 1000 person‐years was calculated for each ideal metric and LS7 score category stratified by race/ethnicity. Hazard ratios (HRs) and 95% confidence intervals (CIs) for incident HF were then calculated using 0 to 1 ideal metric as reference for the number of ideal metrics and using the inadequate score as reference for the LS7 score, with stratification by race/ethnicity. P values for trend were calculated using the log‐rank test. We also calculated the HRs and 95% CIs for incident HF for the intermediate and ideal categories for individual LS7 metrics (using the poor category as reference) stratified by race/ethnicity. Covariates adjusted for included age, sex, race/ethnicity, education, income, and health insurance. We tested for interaction, using the Wald test, between the measures of cardiovascular health (LS7 score and number of ideal metrics) and race/ethnicity by inserting the interaction terms in our models. Kaplan–Meier curves were constructed for HF free survival. A sensitivity analysis was performed where participants with any nonfatal coronary heart disease event at or before the time of incident HF diagnosis were excluded from the study sample. A 2‐sided P value <0.05 was considered as statistically significant. All statistical analyses were performed in STATA (version 12.1; StataCorp LP, College Station, TX).

Results

Baseline Characteristics

Baseline characteristics of study participants varied across race/ethnicity as shown in Table 1. Final sample size for our study was 6506 after exclusion of study participants with incomplete data on the LS7 metrics, education, and income (n=308). Mean age (SD) by categories of the LS7 score are as follows: Optimal, 60 (10.5); Average, 62 (10.5); and Inadequate, 63 (9.8). BMI, systolic and diastolic blood pressure levels were highest among black participants. Along with Hispanic participants, black participants also had the lowest proportion with 6 to 7 ideal metrics and optimal LS7 scores. Hispanic participants had the lowest proportion with at least a bachelor's degree and income >$40 000. Overall, only 0.1% of participants were in ideal CVH (ideal levels for all 7 metrics).
Table 1

Baseline Characteristics of Study Participants: MESA (2000–2002)

Total (N=6506)White (n=2539)Chinese American (n=795)Black (n=1716)Hispanic (n=1456)
Age62.0 (10.2)62.4 (10.2)62.3 (10.3)61.7 (10.0)61.2 (10.4)
Women 53%52%51%56%51%
Education ≥bachelor's degree35.8%50.3%39.0%34.8%10.1%
Income >$40 00049.4%68.1%34.8%48.0%26.4%
No health insurance(9%)2.6%19.4%6.2%17.5%
Current smoking 12.9%12%6%18%13%
Body mass index, kg/m2 28.3 (5.5)27.7 (5.1)24.0 (3.3)30.2 (5.9)29.4 (5.1)
Physical activity, min/w402 (605)435 (591)296 (395)446 (727)348 (554)
Healthy diet score (0–5)1.6 (0.9)1.6 (0.9)1.9 (0.8)1.5 (0.9)1.4 (0.9)
Total cholesterol, mg/dL194 (36)196 (35)192 (32)190 (37)198 (37)
Systolic blood pressure, mm Hg126 (21)123 (20)124 (22)131 (21)127 (22)
Diastolic blood pressure, mm Hg72 (10)70 (10)72 (10)75 (10)72 (10)
Fasting glucose, mg/dL97 (30)91 (21)99 (28)100 (33)104 (39)
Incident heart failure (per 1000 person‐years)3.7 (3.2–4.1)3.8 (3.2–4.1)2.1 (1.4–3.3)4.1 (3.3–5.1)3.7 (2.9–4.8)
Baseline categories of ideal Life's Simple 7 metrics
0 to 226.3%20.8%16.2%33.6%33.8%
3 to 569.6%73.3%76.0%64.9%65.0%
6 to 74.2%5.9%7.8%1.5%2.3%
Baseline Life's Simple 7 score
Inadequate (0–8)47%39%27%61%58%
Average (9–10)33%36%40%28%29%
Optimal (11–14)20%26%33%12%13%

MESA indicates the Multi‐Ethnic Study of Atherosclerosis.

Baseline Characteristics of Study Participants: MESA (2000–2002) MESA indicates the Multi‐Ethnic Study of Atherosclerosis.

Incidence of HF

A total of 262 cases (4%) of incident HF were reported during a median follow‐up of 12.2 years with an incidence rate of 3.7 per 1000 person‐years. Blacks had the highest incidence rate (4.1 per 1000 person‐years; Table 1). Participants who developed HF were older (P<0.0001) and more likely to be men (P<0.0001). They also had higher baseline levels of systolic blood pressure (139 versus 126 mm Hg; P<0.0001) and fasting glucose (110 versus 97 mg/dL; P<0.0001; Table S2). Incidence of HF was 5.9 per 1000 person‐years among participants with 0 to 1 ideal LS7 metrics. Incidence rate decreased to 0.6 per 1000 person‐years for participants with 6 to 7 ideal metrics (Table 2). Participants with optimal LS7 scores had a lower incidence rate of HF compared with those with average and inadequate scores (Figure 1). A Kaplan–Meier curve for HF free survival by the categories of the LS7 score for all 4 racial/ethnic groups combined is illustrated in Figure 2 while Figure S1 shows the Kaplan–Meier curves for each race/ethnicity.
Table 2

Incidence Rates of HF Per 1000 Person‐Years by Baseline Levels of Life's Simple 7 Metrics

TotalWhiteChinese AmericanBlackHispanic
Incidence rates of heart failure by number of Ideal Life's Simple 7 Metrics
0 to 15.9 (4.1–8.5)3.3 (1.4–7.9)4.0 (0.6–28.4)7.8 (4.4–13.7)6.9 (3.7–12.8)
25.6 (4.4–7.0)7.5 (5.2–10.6)2.6 (0.9–8.2)5.2 (3.5–7.9)4.7 (2.9–7.6)
34.1 (3.3–5.0)4.0 (2.8–5.6)3.0 (1.3–6.6)4.2 (2.9–6.2)4.5 (3.0–6.7)
42.9 (2.2–3.8)3.7 (2.6–5.3)2.5 (1.2–5.2)2.5 (1.3–4.6)1.9 (0.9–4.1)
51.6 (1.0–2.6)1.8 (0.9–3.5)1.0 (0.3–4.1)2.2 (0.8–5.8)1.2 (0.3–4.7)
6 to 70.6 (0.2–2.5)1.1 (0.3–4.5)000
Figure 1

Incidence rates for heart failure per 1000 person‐years by Life's Simple 7 Score. The Life's Simple 7 score ranged from 0 to 14 and was classified into inadequate (0–8), average (9–10), and optimal (11–14) based on points assigned to each category of the Life's Simple 7 metrics.

Figure 2

Kaplan–Meier analysis of time to incident heart failure by categories of the Life's Simple 7 Score. The Life's Simple 7 score ranged from 0 to 14 and was classified into inadequate (0–8), average (9–10), and optimal (11–14) based on points assigned to each category of the Life's Simple 7 metrics.

Incidence Rates of HF Per 1000 Person‐Years by Baseline Levels of Life's Simple 7 Metrics Incidence rates for heart failure per 1000 person‐years by Life's Simple 7 Score. The Life's Simple 7 score ranged from 0 to 14 and was classified into inadequate (0–8), average (9–10), and optimal (11–14) based on points assigned to each category of the Life's Simple 7 metrics. Kaplan–Meier analysis of time to incident heart failure by categories of the Life's Simple 7 Score. The Life's Simple 7 score ranged from 0 to 14 and was classified into inadequate (0–8), average (9–10), and optimal (11–14) based on points assigned to each category of the Life's Simple 7 metrics.

Hazards for Developing HF

Table 3 shows adjusted HRs for incident HF by the number of ideal metrics and LS7 score. In the multivariable adjusted model with the 0 to 1 ideal metric serving as reference, HRs decreased as the number of ideal metrics increased. Participants with 2 and 6 to 7 ideal metrics had adjusted HRs of 0.93 (0.60–1.44) and 0.15 (0.04–0.65), respectively. Participants with average and optimal scores had a statistically significant lower risk of developing HF compared with those with inadequate scores (0.57 [0.43–0.76] and 0.31 [0.19–0.49], respectively). Additionally, we found no evidence of interaction between the measures of cardiovascular health (LS7 score and number of ideal metrics) and race/ethnicity.
Table 3

Hazard Ratios for HF by Baseline Levels of Life's Simple 7 Metrics

TotalWhiteChinese AmericanBlackHispanic
Hazard ratios for heart failure by number of ideal Life's Simple 7 metrics
0 to 11 (Ref)1 (Ref)1 (Ref)1 (Ref)1 (Ref)
20.93 (0.60–1.44)2.47 (0.95–6.39)0.83 (0.08–8.41)0.72 (0.36–1.45)0.57 (0.25–1.26)
30.68 (0.45–1.05)1.26 (0.49–3.27)1.12 (0.13–9.75)0.56 (0.28–1.12)0.58 (0.28–1.23)
40.52 (0.33–0.83)1.14 (0.44–2.99)0.99 (0.12–8.38)0.37 (0.16–0.85)0.27 (0.10–0.71)
50.34 (0.18–0.63)0.69 (0.23–2.10)0.41 (0.04–4.71)0.32 (0.10–1.01)0.19 (0.04–0.87)
6 to 70.15 (0.04–0.65)0.49 (0.09–2.57)
P for trend<0.00010.00030.53990.04060.0264
Hazard ratios for heart failure by Life's Simple 7 score
Inadequate (0–8)1 (Ref)1 (Ref)1 (Ref)1 (Ref)1 (Ref)
Average (9–10)0.57 (0.43–0.76)0.58 (0.38–0.88)0.80 (0.31–2.10)0.40 (0.21–0.76)0.62 (0.33–1.16)
Optimal (11–14)0.31 (0.19–0.49)0.31 (0.17–0.58)0.24 (0.05–1.13)0.48 (0.19–1.20)0.11 (0.01–0.79)
P for trend<0.0001<0.00010.07730.00410.0035

– signifies extremely small hazard ratios. Hazard ratios were adjusted for age, sex, race/ethnicity, education, income, and health insurance. Hazard ratios stratified by race/ethnicity were not adjusted for race/ethnicity. P for trend was calculated using log‐rank test.

Hazard Ratios for HF by Baseline Levels of Life's Simple 7 Metrics – signifies extremely small hazard ratios. Hazard ratios were adjusted for age, sex, race/ethnicity, education, income, and health insurance. Hazard ratios stratified by race/ethnicity were not adjusted for race/ethnicity. P for trend was calculated using log‐rank test. Table 4 shows adjusted HRs for incident HF by the categories of each LS7 metrics. For the entire study population, the ideal categories of smoking, BMI, physical activity, blood pressure, and blood glucose were associated with a statistically significant lower risk of developing HF compared with the poor category after adjusting for age, sex, race/ethnicity, education, income, and health insurance. Although there was an increased risk of HF for participants in the ideal categories of diet and total cholesterol, the associations were not statistically significant. Across the racial/ethnic groups, we found a statistically significant lower risk of HF for the ideal versus poor categories of smoking in black; BMI in white; physical activity in Hispanic; blood pressure in white, black and Hispanic; and blood glucose in Chinese American, black, and Hispanic.
Table 4

Hazard Ratios for HF by Baseline Levels of Life's Simple 7 Metrics

TotalWhiteChinese AmericanBlackHispanic
Smoking
Poor1 (Ref)1 (Ref)1 (Ref)1 (Ref)1 (Ref)
Intermediate0.51 (0.12–2.12)0.46 (0.06–3.54)1.17 (0.15–8.91)
Ideal0.64 (0.45–0.93)0.56 (0.31–1.03)0.57 (0.33–0.99)1.02 (0.40–2.62)
Body mass index
Poor1 (Ref)1 (Ref)1 (Ref)1 (Ref)1 (Ref)
Intermediate0.64 (0.48–0.84)0.73 (0.48–1.13)0.34 (0.07–1.71)0.54 (0.32–0.91)0.55 (0.30–1.00)
Ideal0.58 (0.41–0.81)0.45 (0.27–0.77)0.28 (0.06–1.32)0.58 (0.30–1.13)0.99 (0.51–1.96)
Physical activity
Poor1 (Ref)1 (Ref)1 (Ref)1 (Ref)1 (Ref)
Intermediate0.96 (0.66–1.39)0.95 (0.51–1.76)1.33 (0.29–6.04)1.09 (0.55–2.17)0.79 (0.38–1.63)
Ideal0.72 (0.54–0.96)0.76 (0.46–1.24)1.39 (0.38 5.11)0.85 (0.49–1.45)0.41 (0.22–0.74)
Diet
Poor1 (Ref)1 (Ref)1 (Ref)1 (Ref)1 (Ref)
Intermediate1.05 (0.82–1.36)0.97 (0.65–1.43)0.61 (0.21–1.80)1.26 (0.79–2.02)1.00 (0.59–1.68)
Ideal1.12 (0.35–3.57)1.58 (0.38–6.69)1.57 (0.21–11.79)
Total cholesterol
Poor1 (Ref)1 (Ref)1 (Ref)1 (Ref)1 (Ref)
Intermediate1.12 (0.74–1.69)0.95 (0.52–1.74)0.73 (0.15–3.69)1.71 (0.66–4.43)1.12 (0.49–2.55)
Ideal1.28 (0.85–1.92)1.16 (0.64–2.11)1.09 (0.24–5.00)1.72 (0.67–4.40)1.13 (0.51–2.50)
Blood pressure
Poor1 (Ref)1 (Ref)1 (Ref)1 (Ref)1 (Ref)
Intermediate0.55 (0.41–0.75)0.52 (0.32–0.83)0.41 (0.11–1.47)0.37 (0.19–0.72)1.01 (0.57–1.79)
Ideal0.40 (0.27–0.57)0.45 (0.27–0.75)0.34 (0.09–1.25)0.40 (0.19–0.85)0.33 (0.13–0.82)
Blood glucose
Poor1 (Ref)1 (Ref)1 (Ref)1 (Ref)1 (Ref)
Intermediate0.53 (0.36–0.76)0.74 (0.35–1.57)0.60 (0.19–1.92)0.44 (0.23–0.83)0.52 (0.25–1.06)
Ideal0.36 (0.26–0.48)0.53 (0.28–1.00)0.24 (0.08–0.71)0.31 (0.19–0.52)0.34 (0.19–0.61)

– signifies extremely small hazard ratios. Hazard ratios were adjusted for age, sex, race/ethnicity, education, income, and health insurance. Hazard ratios stratified by race/ethnicity were not adjusted for race/ethnicity.

Hazard Ratios for HF by Baseline Levels of Life's Simple 7 Metrics – signifies extremely small hazard ratios. Hazard ratios were adjusted for age, sex, race/ethnicity, education, income, and health insurance. Hazard ratios stratified by race/ethnicity were not adjusted for race/ethnicity.

Sensitivity Analysis

In the sensitivity analysis, we excluded participants with incident nonfatal coronary heart disease (n=72). Overall, the associations remained the same as shown in Table S3. In addition, incidence rates and hazard ratios for HF decreased with greater numbers of ideal LS7 metrics and higher scores, regardless of age or sex (Tables S4 and S5).

Discussion

In this large, multiethnic population of adults free of clinically evident CVD at baseline, achieving a greater number of ideal LS7 metrics was associated with a lower incidence of HF. Study participants with average and optimal scores were less likely to develop HF compared with those with inadequate scores, though incidence and risk of HF were much lower for those with optimal scores. Across racial/ethnic groups, a similar trend was observed, but many of the associations were not statistically significant. The findings of this study are consistent with the results of 2 recently published studies that examined the association between the LS7 metrics and incidence of HF among the offspring of the original cohort of the Framingham study and the ARIC (Atherosclerosis Risk in Communities) Study.18, 19 These studies, though not as ethnically diverse as ours, demonstrated that higher LS7 scores were associated with a lower risk of HF. In the Framingham study, LS7 scores of 8 to 9 and 10 to 14 were associated with a 45% and 66% lower risk of HF, respectively, compared with scores of 0 to 7. In the ARIC study, LS7 scores of 5 to 9 and 10 to 14 were associated with a 51% and 78% lower risk of HF, respectively, compared with scores of 0 to 4. In our study, LS7 scores of 9 to 10 (average) and 11 to 14 (optimal) were associated with a 43% and 69% risk of HF, respectively, compared with scores of 0 to 8 (inadequate). Moreover, achieving greater numbers of ideal LS7 metrics was associated with a lower risk of HF in the ARIC study,19 which is similar to the findings of our study. We showed that black participants had the highest incidence of HF followed by Hispanic, white, and Chinese American participants. Bahrami et al, using the same study population had previously reported comparable results and attributed the high incidence of HF found among black participants to the higher prevalences of hypertension and diabetes mellitus, in addition to lower socioeconomic status and higher dietary caloric intake.25 In our study, black participants had the poorest CVH status followed by Hispanic participants. The proportion of current smokers, mean BMI, systolic and diastolic blood pressure levels were highest among black participants while Hispanic participants had the lowest mean dietary score, highest mean cholesterol, and fasting glucose levels. A lower proportion of black and Hispanic participants achieved optimal LS7 scores and greater numbers of ideal metrics compared with white and Chinese American participants. The racial/ethnic differences in the risk of HF in this study is attributable to the higher prevalence of risk factors and lower achievement of ideal LS7 metrics among black and Hispanic participants; nevertheless previous research has demonstrated that factors such as disparities in access to and quality of health care play a major role in the differences observed across the racial/ethnic groups.25, 30 HF is responsible for a significant clinical and socioeconomic burden. People with HF often experience a reduction in quality of life, higher mortality rates, and increased risk for other CVD events.31, 32, 33, 34 More than half of the people diagnosed with HF will die within 5 years.32, 33 An estimated 870 000 new cases of HF are documented in the United States annually, and, if the current trend continues, it is projected that by 2030 over 8 million people, aged 18 years or older, will have the disease.5 The financial burden associated with managing HF is also expected to increase by over 120% to ≈$70 billion in the next 14 years. To address this public health issue, the American Heart Association emphasizes the prevention of risk factors in its 2020 strategic impact goals. The goals are to “improve the CVH of all Americans by 20% and reduce the mortality from CVDs and stroke by 20%.”7 The LS7 metrics and the construct of “ideal CVH” were introduced to evaluate the achievement of the goals by monitoring the changing CVH status of individuals and populations within the United States.7 Several studies have documented that the achievement of ideal CVH is associated with a lower incidence of CVDs and all‐cause mortality.11, 12, 13, 14, 15, 16, 35 Thus, the morbidity, mortality, and socioeconomic burden associated with HF can likely be reduced by encouraging the public to improve their cardiovascular health by adopting healthy lifestyles and achieving greater numbers of ideal LS7 metrics in midlife.7, 19 Strengths of our study include the large ethnically diverse population that included Chinese and Hispanic study participants who were not included in previous studies.18, 19 The findings from these 2 populations underscore the importance of CVD risk factor prevention across all racial/ethnic groups. Additional strengths include the standardized methods/procedures for the measurement of the LS7 metrics and the inclusion of only participants free of CVD at baseline. HF events were carefully adjudicated by trained physicians, and the longitudinal design of the study allowed for the assessment of incident HF rather than HF prevalence. Our study has limitations. Because the same objective criteria were used by MESA in diagnosing incident HF in all 4 racial/ethnic groups and no adjustment made for race/ethnicity, incident HF may have been underdiagnosed in Chinese American participants because left ventricular dimensions are mostly smaller and ejection fraction higher in Asian populations compared with people of European or African descent.36 Overall, participants with average and optimal scores had a lower risk for HF regardless of HF subtype (preserved and reduced ejection fraction) in comparison to those with inadequate scores although the associations were not statistically significant. However, the low number of events precluded the assessment of our associations across all 4 racial/ethnic groups by HF subtype because of the limited power for subanalysis. Additionally, a single baseline measurement of the LS7 metrics may not reflect past or future CVH status of study participants. The data collected on smoking, physical activity, and diet from the self‐administered questionnaires may be subject to recall bias. Future modifications of the LS7 metrics could make BMI specific for each racial/ethnic group because some studies have demonstrated that Asians are at a higher risk of weight‐related diseases, such as CVDs, at lower BMIs.37, 38, 39, 40 In conclusion, our study shows that favorable Life's Simple 7 status, as indicated by higher scores or a greater number of metrics at ideal levels, is associated with a lower risk of incident HF. Of note, patterns were the same for all racial/ethnic groups. These findings suggest that prevention of risk factors has the potential to reduce the burden of HF and the associated healthcare costs.

Sources of Funding

The Multi‐Ethnic Study of Atherosclerosis is supported by contracts N01‐HC‐95159, N01‐HC‐95160, N01‐HC‐95161, N01‐HC‐95162, N01‐HC‐95163, N01‐HC‐95164, N01‐HC‐95164, N01‐HC‐95165, N01‐HC‐95166, N01‐HC‐95167, N01‐HC‐95168, and N01‐HC‐95169 from the National Heart, Lung, and Blood Institute (NHLBI) and by grants UL1‐RR‐024156 and UL1‐RR‐025005 from the National Center for Research Resources (NCRR).

Disclosures

None. Table S1. Distribution of Life's Simple 7 Metrics Table S2. Baseline Characteristics of Participants by Development of Heart Failure Table S3. Hazard Ratios for Heart Failure After Exclusion of Participants with Nonfatal CHD* Table S4. Incidence Rates of Heart Failure Per 1000 Person‐Years by Sex and Age Table S5. Hazard Ratios for Heart Failure by Age (<65 and ≥65) and Sex Table S6. Hazard Ratios by Heart Failure Subtype Figure S1. Kaplan–Meier analysis of time to incident heart failure by categories of the Life's Simple 7 Metrics. Click here for additional data file.
  39 in total

1.  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.

Authors:  J Stamler; R Stamler; J D Neaton; D Wentworth; M L Daviglus; D Garside; A R Dyer; K Liu; P Greenland
Journal:  JAMA       Date:  1999-12-01       Impact factor: 56.272

2.  Health related quality of life in patients with congestive heart failure: comparison with other chronic diseases and relation to functional variables.

Authors:  J Juenger; D Schellberg; S Kraemer; A Haunstetter; C Zugck; W Herzog; M Haass
Journal:  Heart       Date:  2002-03       Impact factor: 5.994

3.  Changes in cardiovascular risk factors after 5 years of implementation of a population-based program to reduce cardiovascular disease: The Heart of New Ulm Project.

Authors:  Abbey C Sidebottom; Arthur Sillah; Michael D Miedema; David M Vock; Raquel Pereira; Gretchen Benson; Jackie L Boucher; Thomas Knickelbine; Rebecca Lindberg; Jeffrey J VanWormer
Journal:  Am Heart J       Date:  2016-02-17       Impact factor: 4.749

4.  Moderate physical activity patterns of minority women: the Cross-Cultural Activity Participation Study.

Authors:  B E Ainsworth; M L Irwin; C L Addy; M C Whitt; L M Stolarczyk
Journal:  J Womens Health Gend Based Med       Date:  1999 Jul-Aug

5.  Ethnic-Specific Normative Reference Values for Echocardiographic LA and LV Size, LV Mass, and Systolic Function: The EchoNoRMAL Study.

Authors: 
Journal:  JACC Cardiovasc Imaging       Date:  2015-05-14

6.  Differences in the incidence of congestive heart failure by ethnicity: the multi-ethnic study of atherosclerosis.

Authors:  Hossein Bahrami; Richard Kronmal; David A Bluemke; Jean Olson; Steven Shea; Kiang Liu; Gregory L Burke; João A C Lima
Journal:  Arch Intern Med       Date:  2008-10-27

7.  Association of lipids with incident heart failure among adults with and without diabetes mellitus: Multiethnic Study of Atherosclerosis.

Authors:  Imo A Ebong; David C Goff; Carlos J Rodriguez; Haiying Chen; Christopher T Sibley; Alain G Bertoni
Journal:  Circ Heart Fail       Date:  2013-03-25       Impact factor: 8.790

8.  Cardiovascular health among diverse Hispanics/Latinos: Hispanic Community Health Study/Study of Latinos (HCHS/SOL) results.

Authors:  Hector M González; Wassim Tarraf; Carlos J Rodríguez; Linda C Gallo; Ralph L Sacco; Gregory A Talavera; Gerardo Heiss; Jorge R Kizer; Rosalba Hernandez; Sonia Davis; Neil Schneiderman; Martha L Daviglus; Robert C Kaplan
Journal:  Am Heart J       Date:  2016-02-19       Impact factor: 4.749

9.  Cardiovascular health metrics and all-cause and cardiovascular disease mortality among middle-aged men in Korea: the Seoul male cohort study.

Authors:  Ji Young Kim; Young-Jin Ko; Chul Woo Rhee; Byung-Joo Park; Dong-Hyun Kim; Jong-Myon Bae; Myung-Hee Shin; Moo-Song Lee; Zhong Min Li; Yoon-Ok Ahn
Journal:  J Prev Med Public Health       Date:  2013-11-28

10.  "Life's Simple 7" and Long-Term Mortality After Stroke.

Authors:  Michelle P Lin; Bruce Ovbiagele; Daniela Markovic; Amytis Towfighi
Journal:  J Am Heart Assoc       Date:  2015-11-20       Impact factor: 5.501

View more
  37 in total

1.  Associations of Combined Genetic and Lifestyle Risks With Incident Cardiovascular Disease and Diabetes in the UK Biobank Study.

Authors:  M Abdullah Said; Niek Verweij; Pim van der Harst
Journal:  JAMA Cardiol       Date:  2018-08-01       Impact factor: 14.676

Review 2.  The American Heart Association Heart Failure Summit, Bethesda, April 12, 2017.

Authors:  Pamela N Peterson; Larry A Allen; Paul A Heidenreich; Nancy M Albert; Ileana L Piña
Journal:  Circ Heart Fail       Date:  2018-10       Impact factor: 8.790

3.  Race and Sex Differences in Modifiable Risk Factors and Incident Heart Failure.

Authors:  Danielle M Kubicki; Meng Xu; Elvis A Akwo; Debra Dixon; Daniel Muñoz; William J Blot; Thomas J Wang; Loren Lipworth; Deepak K Gupta
Journal:  JACC Heart Fail       Date:  2019-11-11       Impact factor: 12.035

4.  Sociodemographic Determinants of Life's Simple 7: Implications for Achieving Cardiovascular Health and Health Equity Goals.

Authors:  Brent M Egan; Jiexiang Li; Susan E Sutherland; Daniel W Jones; Keith C Ferdinand; Yuling Hong; Eduardo Sanchez
Journal:  Ethn Dis       Date:  2020-09-24       Impact factor: 1.847

5.  Heart Failure Risk Distribution and Trends in the United States Population, NHANES 1999-2016.

Authors:  Peter A Glynn; Hongyan Ning; Aakash Bavishi; Priya M Freaney; Sanjiv Shah; Clyde W Yancy; Donald M Lloyd-Jones; Sadiya S Khan
Journal:  Am J Med       Date:  2020-08-20       Impact factor: 4.965

6.  The Strong Hearts, Healthy Communities Program 2.0: An RCT Examining Effects on Simple 7.

Authors:  Rebecca A Seguin-Fowler; David Strogatz; Meredith L Graham; Galen D Eldridge; Grace A Marshall; Sara C Folta; Kristin Pullyblank; Miriam E Nelson; Lynn Paul
Journal:  Am J Prev Med       Date:  2020-05-07       Impact factor: 5.043

7.  Association of sleep characteristics with cardiovascular health among women and differences by race/ethnicity and menopausal status: findings from the American Heart Association Go Red for Women Strategically Focused Research Network.

Authors:  Nour Makarem; Marie-Pierre St-Onge; Ming Liao; Donald M Lloyd-Jones; Brooke Aggarwal
Journal:  Sleep Health       Date:  2019-07-10

8.  Associations of ideal cardiovascular health with GlycA, a novel inflammatory marker: The Multi-Ethnic Study of Atherosclerosis.

Authors:  Eve-Marie A Benson; Martin Tibuakuu; Di Zhao; Akintunde O Akinkuolie; James D Otvos; Daniel A Duprez; David R Jacobs; Samia Mora; Erin D Michos
Journal:  Clin Cardiol       Date:  2018-11-19       Impact factor: 2.882

9.  Trends in Racial/Ethnic and Nativity Disparities in Cardiovascular Health Among Adults Without Prevalent Cardiovascular Disease in the United States, 1988 to 2014.

Authors:  Arleen F Brown; Li-Jung Liang; Stefanie D Vassar; Jose J Escarce; Sharon Stein Merkin; Eric Cheng; Adam Richards; Teresa Seeman; W T Longstreth
Journal:  Ann Intern Med       Date:  2018-03-20       Impact factor: 25.391

10.  Identifying blood pressure loci whose effects are modulated by multiple lifestyle exposures.

Authors:  Oyomoare L Osazuwa-Peters; R J Waken; Karen L Schwander; Yun Ju Sung; Paul S de Vries; Sarah M Hartz; Daniel I Chasman; Alanna C Morrison; Laura J Bierut; Chengjie Xiong; Lisa de Las Fuentes; D C Rao
Journal:  Genet Epidemiol       Date:  2020-03-29       Impact factor: 2.135

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.