Heart Disease and Stroke Statistics—2021 Update

Each chapter listed in the Table of Contents (see next page) is a hyperlink to that chapter. The reader clicks the chapter name to access that chapter.

Table of Contents

Each chapter listed here is a hyperlink. Click on the chapter name to be taken to that chapter.

• Summary e255

• 1. About These Statistics e266

• 2. Cardiovascular Health e270

• Health Behaviors

• 3. Smoking/Tobacco Use e291

• 4. Physical Inactivity e307

• 5. Nutrition e327

• 6. Overweight and Obesity e351

• Health Factors and Other Risk Factors

• 7. High Blood Cholesterol and Other Lipids e367

• 8. High Blood Pressure e380

• 9. Diabetes e398

• 10. Metabolic Syndrome e418

• 11. Adverse Pregnancy Outcomes e439

• 12. Kidney Disease e456

• 13. Sleep e469

• Cardiovascular Conditions/Diseases

• 14. Total Cardiovascular Diseases e478

• 15. Stroke (Cerebrovascular Diseases and Vascular Contributions to Brain Health) e498

• 16. Congenital Cardiovascular Defects and Kawasaki Disease e541

• 17. Disorders of Heart Rhythm e559

• 18. Sudden Cardiac Arrest, Ventricular Arrhythmias, and Inherited Channelopathies e590

• 19. Subclinical Atherosclerosis e613

• 20. Coronary Heart Disease, Acute Coronary Syndrome, and Angina Pectoris e626

• 21. Cardiomyopathy and Heart Failure e649

• 22. Valvular Diseases e665

• 23. Venous Thromboembolism (Deep Vein Thrombosis and Pulmonary Embolism), Chronic Venous Insufficiency, Pulmonary Hypertension e683

• 24. Peripheral Artery Disease and Aortic Diseases e692

• Outcomes

• 25. Quality of Care e714

• 26. Medical Procedures e728

• 27. Economic Cost of Cardiovascular Disease e733

• Supplemental Materials

• 28. At-a-Glance Summary Tables e737

• 29. Glossary e741

Summary

Each year, the American Heart Association (AHA), in conjunction with the National Institutes of Health and other government agencies, brings together in a single document the most up-to-date statistics related to heart disease (HD), stroke, and the cardiovascular risk factors in the AHA’s My Life Check−Life’s Simple 7 (Figure),¹ which include core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure [BP], and glucose control) that contribute to cardiovascular health. The Statistical Update represents a critical resource for the lay public, policy makers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions. Cardiovascular disease (CVD) produces immense health and economic burdens in the United States and globally. The Statistical Update also presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital HD, rhythm disorders, subclinical atherosclerosis, coronary HD [CHD], heart failure [HF], valvular HD, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). Since 2007, the annual versions of the Statistical Update have been cited >20 000 times in the literature.

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Each annual version of the Statistical Update undergoes revisions to include the newest nationally representative available data, add additional relevant published scientific findings, remove older information, add new sections or chapters, and increase the number of ways to access and use the assembled information. This year-long process, which begins as soon as the previous Statistical Update is published, is performed by the AHA Statistics Committee faculty volunteers and staff and government agency partners. Below are a few highlights from this year’s Statistical Update. Please see each chapter for references and additional information.

Cardiovascular Health (Chapter 2)

• The 5 US states with the highest health-adjusted life expectancy at birth include Hawaii, Minnesota, California, Connecticut, and Nebraska. The 5 US states with the lowest health-adjusted life expectancy at birth include West Virginia, Kentucky, Alabama, Oklahoma, and Louisiana.

• High body mass index, high fasting plasma glucose, and smoking are the first, second, and third leading years lived with disability and injury risk factors in the United States in both 1990 and 2019, whereas smoking dropped from first to third leading years lived with disability and injury risk factor during this time period.

• Smoking and high systolic BP remained the first and second leading years of life lost risk factors in the United States in both 1990 and 2019.

• High systolic BP and smoking are the first and second leading years of life lost risk factors globally in 2019.

• High fasting plasma glucose and high body mass index were the first and second leading years lived with disability and injury risk factors globally in 2019.

Smoking/Tobacco Use (Chapter 3)

• The prevalence of cigarette use in the past 30 days among middle and high school students in the United States was 2.3% and 5.8%, respectively, in 2019.

• Although there has been a consistent decline in adult and youth cigarette use in the United States, significant disparities persist. Substantially higher tobacco use prevalence rates are observed in American Indian/Alaska Native individuals and lesbian, gay, and bisexual populations.

• Over the past 8 years, there has been a sharp increase in electronic cigarette use among adolescents, increasing from 1.5% to 27.4% between 2011 and 2019; electronic cigarettes are now the most commonly used tobacco product in this demographic.

• Tobacco use was the second leading cause of disability-adjusted life-years in the United States in 2016. Globally, smoking accounted for 8.7 million deaths worldwide in 2019.

• Tobacco 21 legislation was signed into law in December 2019, increasing the federal minimum age for sale of tobacco products from 18 to 21 years. In January 2020, the US Food and Drug Administration issued a policy prioritizing enforcement against the development and distribution of certain unauthorized flavored electronic cigarette products such as fruit and mint flavors (ie, any flavors other than tobacco and menthol).

Physical Inactivity (Chapter 4)

• In a nationally representative sample of high school students in 2017, 26.1% reported achieving at least 60 minutes of daily physical activity.

• In a nationally representative sample of adults in 2018, 24.0% reported participating in adequate leisure-time aerobic and muscle-strengthening activity to meet US recommendations for physical activity.

• In a harmonization of 8 prospective studies using accelerometry to assess movement, over a median of 5.8 years of follow-up, the highest quartile of light and moderate to vigorous physical activity compared with the lowest quartile (least active) was associated with a lower risk of all-cause mortality. Time in sedentary behavior was associated with a higher risk of all-cause mortality compared with the lowest quartile (least sedentary).

Nutrition (Chapter 5)

• According to NHANES (National Health and Nutrition Examination Survey; 2015–2016), <10% adults met the guidelines for whole grains (≥3 servings per day), whole fruits (≥2 cups per day), and nonstarchy vegetables (≥2.5 cups per day).

• According to the AHA primary diet score, 47.8% of US adults had poor diet quality in 2015 to 2016. On the basis of the secondary score, 36.4% of US adults had poor diet quality in 2015 to 2016.

• In a large primary prevention trial among patients with CVD risk factors, patients randomized to unrestricted-calorie Mediterranean-style diets supplemented with extra-virgin olive oil or mixed nuts had a ≈30% reduction in the risk of stroke, myocardial infarction, and death attributable to cardiovascular causes, without changes in body weight.

Overweight and Obesity (Chapter 6)

• According to NHANES 2015 to 2018, among US adults ≥20 years of age, the age-adjusted prevalence of obesity was 39.9% in males and 41.1% in females; the prevalence of extreme obesity was 6.2% in males and 10.5% in females; the overall prevalence of obesity among youth 2 to 19 years of age was 19.0%.

• In a study of 2625 participants with new-onset diabetes pooled from 5 longitudinal cohort studies, rates of total, CVD, and non-CVD mortality were higher among normal-weight people than among overweight participants and participants with obesity, with adjusted hazard ratios (HRs) of 2.08, 1.52, and 2.32, respectively.

• In the Systolic Blood Pressure Intervention Trial (SPRINT), there was a J-shaped associated between body mass index and all-cause mortality and risk of stroke. An increased risk of stroke was also seen when participants with obesity were compared with normal-weight participants in the Copenhagen City Heart Study (HR, 1.4) and the Copenhagen General Population Study (HR, 1.1).

• In a retrospective cohort study of individuals with a median follow-up of 3.9 years, patients in the bariatric surgery group had a cumulative incidence of major adverse cardiac events of 30.8% compared with 47.7% among matched patients who did not undergo bariatric surgery.

High Blood Cholesterol and Other Lipids (Chapter 7)

• The Healthy People 2020 target is a mean population total cholesterol level of 177.9 mg/dL for adults, which had not been achieved among the population of US adults or in any race/ethnicity subgroup as of 2015 to 2018 NHANES data. Conversely, the Healthy People 2020 target of ≤13.5% for the proportion of adults with high total cholesterol ≥240 mg/dL has been achieved as of the combined period 2015 to 2018 for adults overall and all race-sex subgroups.

• Long-term exposure to even modestly elevated cholesterol levels can lead to CHD later in life. In an analysis of time-weighted average exposures to low-density lipoprotein cholesterol (LDL-C) during young (18–39 years of age) versus later (≥40 years of age) adulthood among 36 030 participants from 6 US cohorts, CHD rates were significantly elevated among individuals who had young adult LDL-C ≥100 (versus <100) mg/dL, independently of later adult exposures (adjusted HR, 1.64). Specifically, compared with LDL-C <100 mg/dL, adjusted HRs were as follows: for LDL-C 100 to 129 mg/dL, 1.62; for LDL-C 130 to 159 mg/dL, 1.89; and for LDL-C ≥160 mg/dL, 2.03.

• In a 20-year follow-up study, early initiation of statin treatment among 214 children with familial hypercholesterolemia was associated with a decrease in LDL-C by 32%, slowed progression of subclinical atherosclerosis, and lower cumulative incidence by 39 years of age of cardiovascular events compared with affected parents (0% versus 7% and 1% versus 26% of fatal and nonfatal cardiovascular events, respectively).

• Among 5693 participants in PALM (Patient and Provider Assessment of Lipid Management), a nationwide registry of ambulatory community practices, females were less likely than males to receive statin dosing at the guideline-recommended intensity (36.7% versus 45.2%; P<0.001) and were more likely to not ever have been offered statin therapy despite being eligible (18.6% versus 13.5%) compared with males.

High Blood Pressure (Chapter 8)

• Analysis of NHANES 1999 to 2002, 2007 to 2010, and 2015 to 2018 found large increases in hypertension awareness, treatment, and control (≈10%) within each race/ethnicity and sex subgroup except for Black females. Among Black females, levels of hypertension awareness, treatment, and control increased between 1999 to 2002 and 2007 to 2010 but decreased between 2007 to 2010 and 2015 to 2018.

• With the use of 2017 guidelines from the American Academy of Pediatrics, analysis of data for children and adolescents 8 to 17 years of age (n=12 249) from NHANES 2003 to 2004 through NHANES 2015 to 2016 found that the prevalence of either elevated BP or hypertension (combined) significantly declined from 16.2% in 2003 to 2004 to 13.3% in 2015 to 2016 and the prevalence of hypertension declined from 6.6% to 4.5% in this age group.

• In NHDS (National Hospital Discharge Survey) data compiled by the Centers for Disease Control and Prevention, chronic hypertension in pregnancy (defined as systolic BP ≥140 mm Hg or diastolic BP ≥90 mm Hg either before pregnancy or up to the first 20 weeks during pregnancy) increased >13-fold between 1970 and 2010. Black women had a persistent 2-fold higher rate of chronic hypertension compared with White women over the 40-year period.

Diabetes (Chapter 9)

• ▪ On the basis of data from NHANES 2013 to 2016, an estimated 26 million adults have diagnosed diabetes, 9.4 million adults (3.7%) have undiagnosed diabetes, and 91.8 million adults (37.6%) have prediabetes.

• ▪ The age-adjusted prevalence of diagnosed diabetes in adults ≥18 years of age increased from 6.4% in 1999 to 2002 to 9.4% in 2013 to 2016. In contrast, the age-adjusted prevalence of undiagnosed diabetes was similar from 1999 to 2002 (3.1%) and 2013 to 2016 (2.6%).

• ▪ Among adults with diagnosed diabetes in NHANES 2013 to 2016, 9.9% had a hemoglobin A_1c ≥10.0%, and this was more prevalent among adults 18 to 44 years of age (16.3%) than adults ≥65 years of age (4.3%).

• ▪ In NHIS (National Health Interview Survey) 2013 to 2017, adults with diabetes <65 years of age were more likely to report overall financial hardship from medical bills (41.1%) than adults with diabetes ≥65 years of age (20.7%). The prevalence of cost-related medication nonadherence was 34.7% and delayed medical care was 55.5% among adults with diabetes <65 years of age.

• ▪ In 2016, of 154 health conditions evaluated, diabetes had the highest public insurance spending ($55.4 billion).

Metabolic Syndrome (Chapter 10)

• Uncertainty remains concerning the definition of the obesity component of metabolic syndrome (MetS) in the pediatric population because it is age dependent. Therefore, use of body mass index percentiles and waist-height ratio has been recommended. According to the Centers for Disease Control and Prevention and FitnessGram standards for pediatric obesity, the prevalence of MetS in obese youth ranges from 19% to 35%.

• On the basis of NHANES 2007 to 2014, the overall prevalence of MetS was 34.3% and was similar for males (35.3%) and females (33.3%). The prevalence of MetS increased with age, from 19.3% among people 20 to 39 years of age to 37.7% for people 40 to 59 years of age and 54.9% among people ≥60 years of age.

• Each 1000-steps-per-day increase is associated with lower odds of having MetS (odds ratio, 0.90) in American men.

• In a meta-analysis including 17 prospective longitudinal studies with 602 195 women and 15 945 cases of breast cancer, MetS was associated with increased risk of incident breast cancer in postmenopausal women (adjusted relative risk, 1.25) but significantly reduced breast cancer risk in premenopausal women (adjusted relative risk, 0.82). Further analyses showed that the association between MetS and increased risk of breast cancer was observed only among White and Asian women, whereas there was no association in Black women.

Adverse Pregnancy Outcomes (Chapter 11)

• Adverse pregnancy outcomes (including hypertensive disorders of pregnancy, gestational diabetes, preterm birth, and small for gestational age at birth) occur in 10% to 20% of pregnancies.

• According to a meta-analysis of individual participant data from 265 270 females from 39 European, North American, and Oceanic cohort studies, risk of adverse pregnancy outcomes was greater with higher categories of prepregnancy body mass index and greater degree of gestational weight gain, with an adjusted odds ratio of 2.51 for women with prepregnancy obesity and high gestational weight gain.

• On the basis of a meta-analysis of 9 studies, gestational hypertension was associated with a 67% higher risk of subsequent CVD, and preeclampsia was associated with a 75% higher risk of subsequent CVD-related mortality.

• Among 2 141 709 live-born singletons in the Swedish Birth Registry from 1973 to 1994 followed up through 2015 (maximum, 43 years of age), gestational age at birth was inversely associated with risk for premature CHD (adjusted HRs at 30–43 years of age versus full-term [39–41 weeks] births: for preterm [<37 weeks], 1.53; for early term [37–38 weeks], 1.19).

Kidney Disease (Chapter 12)

• Overall prevalence of chronic kidney disease (estimated glomerular filtration rate <60 mL·min⁻¹·1.73 m⁻² or albumin-to-creatinine ratio ≥30 mg/g) was 14.8% (2013–2016).

• Incidence of end-stage kidney disease in the United States is projected to increase 11% to 18% through 2030.

• In NHANES 1999 to 2014, 34.9% of adults with chronic kidney disease used an angiotensin-converting enzyme inhibitor/angiotensin receptor blocker.

• Rates of stress testing among Medicare beneficiaries declined from 2008 to 2012, but rates were 5% to 15% higher for those with chronic kidney disease and end-stage kidney disease than for those without chronic kidney disease.

Sleep (Chapter 13)

• Analysis of 2018 BRFSS (Behavioral Risk Factor Surveillance System) data indicated that the proportion of adults reporting inadequate sleep (<7 hours) was 35.4%. Older people (>65 years of age) were less likely to report sleeping <7 hours, and younger males (<45 years of age) were more likely to report sleeping <7 hours.

• In the 2018 BRFSS, non-Hispanic Black people had the highest percentage of respondents reporting sleeping <7 hours per night (45.4%), whereas non-Hispanic White people had the lowest percentage (33.2%) of respondents reporting sleeping <7 hours.

• A meta-analysis of 15 prospective studies observed a significant association between the presence of obstructive sleep apnea and the risk of cerebrovascular disease (HR, 1.94).

• An analysis of the global prevalence and burden of obstructive sleep apnea estimated that 936 million males and females 30 to 69 years of age have mild to severe obstructive sleep apnea (apnea-hypopnea index ≥5) and 425 million have moderate to severe obstructive sleep apnea (apnea-hypopnea index ≥15) globally. The prevalence was highest in China, followed by the United States, Brazil, and India.

Total Cardiovascular Diseases (Chapter 14)

• On the basis of NHANES 2015 to 2018 data, the prevalence of CVD (comprising CHD, HF, stroke, and hypertension) in adults ≥20 years of age is 49.2% overall (126.9 million in 2018) and increases with age in both males and females. CVD prevalence excluding hypertension (CHD, HF, and stroke only) is 9.3% overall (26.1 million in 2018).

• From the combination of estimates from NHANES, REGARDS (Reasons for Geographic and Racial Differences in Stroke), and randomized controlled trials for BP-lowering treatments, it was estimated that achieving the 2017 American College of Cardiology/AHA BP goals could prevent 3.0 million (uncertainty range, 1.1 million–5.1 million) CVD events (CHD, stroke, and HF) compared with current BP levels, but achieving the 2017 American College of Cardiology/AHA BP goals could also increase serious adverse events by 3.3 million (uncertainty range, 2.2 million–4.4 million).

• The US IMPACT (International Model for Policy Analysis of Agricultural Commodities and Trade) Food Policy Model, a computer simulation model, projected that a national policy combining a 30% fruit and vegetable subsidy targeted to low-income Supplemental Nutrition Assistance Program recipients and a population-wide 10% price reduction in fruits and vegetables in the remaining population could prevent ≈230 000 deaths by 2030 and reduce the socioeconomic disparity in CVD mortality by 6%.

Stroke (Cerebrovascular Diseases and Vascular Contributions to Brain Health) (Chapter 15)

• In a county-level study, stroke mortality rates among US adults 35 to 64 years of age increased from 14.7 per 100 000 in 2010 to 15.4 per 100 000 in 2016. Rates decreased among adults ≥65 years of age from 299.3 per 100 000 in 2010 to 271.4 per 100 000 in 2016.

• In a meta-analysis of 35 studies (n=2 458 010 patients), perioperative or postoperative atrial fibrillation (AF) was associated with an increased risk of early stroke (odds ratio, 1.62) and later stroke (HR, 1.37). This risk was found in both patients undergoing noncardiac surgery (HR, 2.00) and those undergoing cardiac surgery (HR, 1.20).

• An analysis of the NHIS demonstrated that awareness of stroke symptoms and signs among US adults improved from 2009 to 2014. In 2014, 68.3% of the survey respondents were able to recognize 5 common stroke symptoms, and 66.2% demonstrated knowledge of all 5 stroke symptoms and the importance of calling 9-1-1.

• In a meta-analysis of 9 studies, subclinical or silent brain infarcts were associated with decline in cognitive function on the Mini-Mental State Examination score (standardized mean difference, −0.47). In the same meta-analysis, among 4 studies, subclinical or silent brain infarcts were associated with cognitive dysfunction on the Montreal Cognitive Assessment Scale (standardized mean difference, −3.36).

Congenital Cardiovascular Defects and Kawasaki Disease (Chapter 16)

• In 2018, the age-adjusted death rate attributable to congenital cardiovascular defects in the United States was 0.9 per 100 000. The death rate was higher for males than females.

• In a recent study, adults with congenital cardiovascular defects requiring hospital admission for HF demonstrated higher odds of longer length of stay, incident arrhythmias, and in-hospital mortality compared with adults with HF without congenital cardiovascular defects.

• The incidence of Kawasaki disease appears to be rising worldwide, with potential contributions from improved recognition, more frequent diagnosis of incomplete Kawasaki disease, and true increasing incidence.

Disorders of Heart Rhythm (Chapter 17)

• In 2018, 53 895 deaths had arrhythmias as the primary cause of death, and 564 182 included arrhythmia as one of the causes of death.

• The prevalence of AF in the United States was estimated to be 5.2 million in 2010, increasing to 12.1 million in 2030. In the United States, 1.2 million people were newly diagnosed with AF in 2010. This number is projected to increase to 2.6 million by 2030.

• The lifetime risk of AF has been estimated to be 1 in 3 among White people and 1 in 5 among Black people.

• Hypertension accounts for the largest proportion of AF (≈22%), followed by obesity, smoking, cardiac disease, and diabetes.

• A study examining public and private health insurer records from 1996 to 2016 reported that AF was 33rd in spending for health conditions with an estimated $28.4 billion in 2016 dollars, with an annualized rate of change of 3.4% during this period.

• In a controlled trial randomizing alcohol drinkers with paroxysmal AF either to alcohol abstinence or to continue their usual alcohol consumption, AF recurred in 53% of the abstinence group and 73% of the control group. Compared with the control group, the abstinence group had a significantly longer duration without AF recurrence (HR, 0.55) and significantly lower AF burden (median percent time in AF, 0.5% versus 1.2%).

Sudden Cardiac Arrest, Ventricular Arrhythmias, and Inherited Channelopathies (Chapter 18)

• Sudden cardiac arrest and sudden cardiac death result from many different disease processes, each of which can have different risk factors. Among patients with out-of-hospital cardiac arrest (OHCA) resuscitated and hospitalized from 2012 to 2016, acute coronary syndrome and other cardiac causes accounted for the largest proportion of causes. Among patients with in-hospital cardiac arrest, respiratory failure was the most common cause.

• Among 5869 autopsied subjects with sudden cardiac death, excluding cases with noncardiac causes of death, in Finland between 1998 and 2017, ischemic cardiac disease represented 4392 (74.8%) and nonischemic cardiac diseases represented 1477 (25.2%). Over time, the proportion of ischemic sudden cardiac death declined from 78.8% (1998–2002) to 72.4% (2013–2017).

• According to multiple studies, sudden cardiac arrest is more common in males than in females. Females compared with males with OHCA are older, less likely to present with shockable rhythms, and less likely to collapse in public. Despite these factors that would reduce survival, females have equivalent or higher rates of survival to hospital discharge or to 30 days relative to males.

• Incidence of emergency medical services–treated OHCA in people of any age is 76.5 individuals per 100 000 population according to the 2019 CARES (Cardiac Arrest Registry to Enhance Survival) registry, with >2-fold variation between states (range, 41.8–126.1). Survival after emergency medical services–treated OHCA was 10.6% in the 2019 CARES registry, with variation between states reporting data.

Subclinical Atherosclerosis (Chapter 19)

• Among 1585 participants free of CHD and free of MetS, those who were obese had a higher prevalence of coronary artery calcification than individuals with a normal weight, with a prevalence ratio of 1.59.

• A single-nucleotide-polymorphism genetic risk score for type 2 diabetes composed of 48 variants was associated with carotid plaque and atherosclerotic CVD events in ≈160 000 individuals, suggesting a causal role between genetic predisposition to type 2 diabetes and atherosclerotic CVD.

• In overweight and obese children 6 to 13 years of age, greater nut consumption was associated with lower carotid intima-media thickness (β=0.135 mm) when controlled for confounders.

Coronary Heart Disease, Acute Coronary Syndrome, and Angina Pectoris (Chapter 20)

• Data from the National Center for Health Statistics on trends in CHD death rates from 1999 to 2009 indicate disparities in the trends by rural-urban status. An overall 40% decline in the rate of CHD death was observed; however, the decline was greater in urban areas (large metropolitan: 42% decline; from 284 to 164 per 100 000 from 1999–2009; medium metropolitan: 40% decline; from 244 to 147 per 100 000) compared with rural areas (35% decline; from 266 to 173 per 100 000).

• According to the Centers for Medicare & Medicaid Services Hospital Inpatient Quality Reporting Program data on 2363 hospitals in 2018, the average 30-day mortality after acute myocardial infarction was 13.6%, with higher mortality observed in rural hospitals (from 13.4% to 13.8% for the most urban to most rural hospitals).

• The rapid increase in the population ≥65 years of age has resulted in a slowing of HD mortality. According to the Centers for Disease Control and Prevention WONDER (Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiological Research) data from 2011 through 2017, a deceleration in the decline in HD mortality was observed with a <1% annualized decrease. The increase in the growth of the population ≥65 years of age, combined with the slowing of the decrease in HD mortality, resulted in an increase in the absolute number of HD deaths since 2011 (50 880 deaths; 8.5% total increase). However, the age-adjusted mortality for CHD continued to decline (2.7% annualized decrease) and the absolute number of CHD deaths declined (2.5% total decrease over the time period) between 2011 to 2017.

• Among 366 103 Medicare fee-for-service beneficiaries eligible for cardiac rehabilitation in 2016, only 24.4% participated in cardiac rehabilitation; among those who participated, the mean number of days to initiation was 47.0, and 26.9% completed cardiac rehabilitation with ≥36 sessions. Participation decreased with increasing age and was lower in females, Hispanic individuals, Asian individuals, those eligible for dual Medicare/Medicaid coverage, and those with ≥5 comorbidities.

Cardiomyopathy and Heart Failure (Chapter 21)

• The prevalence of HF continues to rise over time, with aging of the population. An estimated 6 million American adults ≥20 years of age had HF according to 2015 to 2018 data. Prevalence is higher in women than men ≥80 years of age; overall prevalence is especially high in both Black females and Black males.

• Of incident hospitalized HF events, approximately half are characterized by reduced ejection fraction and the other half by preserved ejection fraction.

• The prevalence of HF is highly variable across the world, with the lowest in sub-Saharan Africa. Prevalence of HF risk factors also varies worldwide, with hypertension being most common in Latin America, the Caribbean, Eastern Europe, and sub-Saharan Africa. Ischemic HD is most prevalent in Europe and North America. Valvular HD is more common in East Asia and Asia-Pacific countries.

Valvular Diseases (Chapter 22)

• The incidence of valvular HD is 64 per 100 000 person-years, with aortic stenosis (47.2%), mitral regurgitation (24.2%), and aortic regurgitation (18.0%) contributing most of the valvular diagnoses.

• In 1950, ≈15 000 Americans died of rheumatic fever/rheumatic HD compared with ≈3400 annually in the present era. Recent declines in mortality have been slowest in the South compared with other regions.

Venous Thromboembolism (Deep Vein Thrombosis and Pulmonary Embolism), Chronic Venous Insufficiency, Pulmonary Hypertension (Chapter 23)

• In 2016, there were an estimated ≈1 220 000 total venous thromboembolism cases in the United States.

• According to 2018 data, ≈25 000 deaths (any mention) resulted from pulmonary hypertension.

• Hospitalized patients are at particularly high risk of venous thromboembolism; asymptomatic deep vein thrombosis was associated with 3-fold greater risk of death among acutely ill hospitalized patients.

• In the ARIC study (Atherosclerosis Risk in Communities), the presence of HF was associated with a 3-fold greater venous thromboembolism risk. The association was present for HF with both preserved and reduced ejection fraction.

Peripheral Artery Disease and Aortic Diseases (Chapter 24)

• The lifetime risk (80-year horizon) of peripheral arterial disease was estimated at ≈19%, 22%, and 30% in White, Hispanic, and Black individuals, respectively, from pooled data from 6 US community-based cohorts.

• A large-scale genome-wide association study in >31 000 peripheral artery disease cases and >211 000 controls from the Million Veterans Program and the UK Biobank identified 18 new peripheral arterial disease loci. Eleven of the loci were associated with disease in 3 vascular beds, including LDLR, LPA, and LPL, whereas 4 of the variants were specific for peripheral arterial disease (including variants in TCF7L2 and F5).

• Patients with microvascular disease, defined as retinopathy, neuropathy, and nephropathy, were at increased risk for amputation (HR, 3.7), independently of traditional risk factors and prevalent peripheral arterial disease, among 135 674 patients in the Veterans Aging Cohort Study (enrollment 2003–2014).

• Between 1999 and 2016, deaths resulting from ruptured thoracic aortic aneurysm and abdominal aortic aneurysm declined significantly from 5.5 to 1.8 million and 26.3 to 7.9 per million, respectively, according to US National Vital Statistics data.

Quality of Care (Chapter 25)

• Among hospitals that care for Medicare fee-for-service beneficiaries, the implementation of hospital readmission reduction programs for acute myocardial infarction was associated with a reduction in 30-day postdischarge mortality.

• For HF, the Hospital Readmissions Reduction Program was associated with a reduction in 1-year risk adjusted readmission rate.

• Higher quality of care for OHCA is associated with an increase in adjusted survival to discharge and adjusted rates of favorable neurological outcome.

Medical Procedures (Chapter 26)

• Data from the Society of Thoracic Surgeons Congenital Heart Surgery Database indicate that a total of 123 777 congenital heart surgeries were performed from January 2015 to December 2018 and that delayed sternal closure was the most common primary procedure.

• In 2019, 3552 heart transplantations were performed in the United States, the most ever.

Economic Cost of Cardiovascular Disease (Chapter 27)

• The average annual direct and indirect cost of CVD in the United States was an estimated $363.4 billion in 2016 to 2017.

• The estimated direct costs of CVD increased from $103.5 billion in 1996 to 1997 to $216.0 billion in 2016 to 2017.

• By event type, hospital inpatient stays accounted for the highest direct cost ($96.2 billion) in 2016 to 2017.

Conclusions

The AHA, through its Statistics Committee, continuously monitors and evaluates sources of data on HD and stroke in the United States to provide the most current information available in the Statistical Update. The 2021 annual Statistical Update is the product of a full year’s worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members, without whom publication of this valuable resource would be impossible. Their contributions are gratefully acknowledged.

Salim S. Virani, MD, PhD, FAHA, Chair

Connie W. Tsao, MD, MPH, Vice Chair

Sally S. Wong, PhD, RD, CDN, FAHA, AHA Science and Medicine Advisor

Debra G. Heard, PhD, AHA Consultant

On behalf of the American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee

Acknowledgments

The Writing Group wishes to thank their colleagues Lucy Hsu and Michael Wolz at the National Heart, Lung, and Blood Institute; Celine Barthelemy and Nikki DeCleene at the Institute for Health Metrics and Evaluation at the University of Washington; and Christina Koutras and Fran Thorpe at the American College of Cardiology for their valuable comments and contributions.

Footnotes

1. About These Statistics

The AHA works with the NHLBI to derive the annual statistics in this Heart Disease and Stroke Statistics Update. This chapter describes the most important sources and the types of data used from them. For more details, see Chapter 29 of this document, the Glossary.

The surveys and data sources used are the following:

• ACC NCDR’s Chest Pain–MI Registry (formerly the ACTION Registry)—quality information for AMI

• ARIC—CHD and HF incidence rates

• BRFSS—ongoing telephone health survey system

• GBD—global disease prevalence, mortality, YLL, and YLD

• GCNKSS—stroke incidence rates and outcomes within a biracial population

• GWTG—quality information for resuscitation, HF, and stroke

• HCUP—hospital inpatient discharges and procedures

• MEPS—data on specific health services that Americans use, how frequently they use them, the cost of these services, and how the costs are paid

• NAMCS—physician office visits

• NHAMCS—hospital outpatient and ED visits

• NHANES—disease and risk factor prevalence and nutrition statistics

• NHIS—disease and risk factor prevalence

• NVSS—mortality for United States

• USRDS—kidney disease prevalence

• WHO—mortality rates by country

• YRBSS—health-risk behaviors in youth and young adults

Disease Prevalence

Prevalence is an estimate of how many people have a condition at a given point or period in time. The CDC/NCHS conducts health examination and health interview surveys that provide estimates of the prevalence of diseases and risk factors. In this Statistical Update, the health interview part of the NHANES is used for the prevalence of CVDs. NHANES is used more than the NHIS because in NHANES, AP is based on the Rose Questionnaire; estimates are made regularly for HF; hypertension is based on BP measurements and interviews; and an estimate can be made for total CVD, including MI, AP, HF, stroke, and hypertension.

A major emphasis of this Statistical Update is to present the latest estimates of the number of people in the United States who have specific conditions to provide a realistic estimate of burden. Most estimates based on NHANES prevalence rates are from data collected from 2015 to 2018. These are applied to census population estimates for 2018. Differences in population estimates cannot be used to evaluate possible trends in prevalence because these estimates are based on extrapolations of rates beyond the data collection period by use of more recent census population estimates. Trends can be evaluated only by comparing prevalence rates estimated from surveys conducted in different years.

In the 2021 Statistical Update, there is an emphasis on social determinants of health that are built across the various chapters, and global estimates are provided when available.

Risk Factor Prevalence

The NHANES 2013 to 2016 data are used in this Statistical Update to present estimates of the percentage of people with high LDL-C and diabetes. NHANES 2015 to 2018 data are used to present estimates of the percentage of people with overweight, obesity, and high TC and HDL-C. BRFSS 2018 data are used for the prevalence of sleep issues. NHIS 2018, BRFSS 2017 and 2018, and NYTS 2018 data are used for the prevalence of cigarette smoking. The prevalence of physical inactivity is obtained from 2017 YRBSS and 2017 and 2018 NHIS.

Incidence and Recurrent Attacks

An incidence rate refers to the number of new cases of a disease that develop in a population per unit of time. The unit of time for incidence is not necessarily 1 year, although incidence is often discussed in terms of 1 year. For some statistics, new and recurrent attacks or cases are combined. Our national incidence estimates for the various types of CVD are extrapolations to the US population from the FHS, the ARIC study, and the CHS, all conducted by the NHLBI, as well as the GCNKSS, which is funded by the NINDS. The rates change only when new data are available; they are not computed annually. Do not compare the incidence or the rates with those in past editions of the Heart Disease and Stroke Statistics Update (also known as the Heart and Stroke Statistical Update for editions before 2005). Doing so can lead to serious misinterpretation of time trends.

Mortality

Mortality data are generally presented according to the underlying cause of death. “Any-mention” mortality means that the condition was nominally selected as the underlying cause or was otherwise mentioned on the death certificate. For many deaths classified as attributable to CVD, selection of the single most likely underlying cause can be difficult when several major comorbidities are present, as is often the case in the elderly population. It is useful, therefore, to know the extent of mortality attributable to a given cause regardless of whether it is the underlying cause or a contributing cause (ie, the any-mention status). The number of deaths in 2018 with any mention of specific causes of death was tabulated by the NHLBI from the NCHS public-use electronic files on mortality.

The first set of statistics for each disease in this Statistical Update includes the number of deaths for which the disease is the underlying cause. Two exceptions are Chapter 8 (High Blood Pressure) and Chapter 21 (Cardiomyopathy and Heart Failure). HBP, or hypertension, increases the mortality risks of CVD and other diseases, and HF should be selected as an underlying cause only when the true underlying cause is not known. In this Statistical Update, hypertension and HF death rates are presented in 2 ways: (1) as nominally classified as the underlying cause and (2) as any-mention mortality.

National and state mortality data presented according to the underlying cause of death were obtained from the CDC WONDER website or the CDC NVSS mortality file.¹ Any-mention numbers of deaths were tabulated from the CDC WONDER website or CDC NVSS mortality file.²

Population Estimates

In this publication, we have used national population estimates from the US Census Bureau for 2018³ in the computation of morbidity data. CDC/NCHS population estimates⁴ for 2018 were used in the computation of death rate data. The Census Bureau website contains these data, as well as information on the file layout.

Hospital Discharges and Ambulatory Care Visits

Estimates of the numbers of hospital discharges and numbers of procedures performed are for inpatients discharged from short-stay hospitals. Discharges include those discharged alive, dead, or with unknown status. Unless otherwise specified, discharges are listed according to the principal (first-listed) diagnosis, and procedures are listed according to all-listed procedures (principal and secondary). These estimates are from the 2016 HCUP.⁵ Ambulatory care visit data include patient visits to primary providers’ offices and hospital outpatient departments and EDs. Ambulatory care visit data reflect the primary (first-listed) diagnosis. These estimates are from the 2016 NAMCS⁶ and 2016 NHAMCS⁷ of the CDC/NCHS. Data for community health centers are included in 2016 NAMCS estimates. Readers comparing data across years should note that beginning October 1, 2015, a transition was made from ICD-9 to ICD-10. This should be kept in mind because coding changes could affect some statistics, especially when comparisons are made across these years.

International Classification of Diseases

Morbidity (illness) and mortality (death) data in the United States have a standard classification system: the ICD. Approximately every 10 to 20 years, the ICD codes are revised to reflect changes over time in medical technology, diagnosis, or terminology. If necessary for comparability of mortality trends across the 9th and 10th ICD revisions, comparability ratios computed by the CDC/NCHS are applied as noted.⁸ Effective with mortality data for 1999, ICD-10 is used.⁹ Beginning in 2016, ICD-10-CM is used for hospital inpatient stays and ambulatory care visit data.¹⁰

Age Adjustment

Prevalence and mortality estimates for the United States or individual states comparing demographic groups or estimates over time are either age specific or age adjusted to the year 2000 standard population by the direct method.¹¹ International mortality data are age adjusted to the European standard population. Unless otherwise stated, all death rates in this publication are age adjusted and are deaths per 100 000 population.

Data Years for National Estimates

In this Statistical Update, we estimate the annual number of new (incidence) and recurrent cases of a disease in the United States by extrapolating to the US population in 2014 from rates reported in a community- or hospital-based study or multiple studies. Age-adjusted incidence rates by sex and race are also given in this report as observed in the study or studies. For US mortality, most numbers and rates are for 2018. For disease and risk factor prevalence, most rates in this report are calculated from the 2015 to 2018 NHANES. Because NHANES is conducted only in the noninstitutionalized population, we extrapolated the rates to the total US resident population on July 1, 2018, recognizing that this probably underestimates the total prevalence given the relatively high prevalence in the institutionalized population. The numbers and rates of hospital inpatient discharges for the United States are for 2016. Numbers of visits to primary providers’ offices and hospital EDs are for 2016, whereas hospital outpatient department visits are for 2011. Except as noted, economic cost estimates are for 2016 to 2017.

Cardiovascular Disease

For data on hospitalizations, primary provider office visits, and mortality, total CVD is defined according to ICD codes given in Chapter 14 of the present document. This definition includes all diseases of the circulatory system. Unless otherwise specified, estimates for total CVD do not include congenital CVD. Prevalence of total CVD includes people with hypertension, CHD, stroke, and HF.

Race/Ethnicity

Data published by governmental agencies for some racial groups are considered unreliable because of the small sample size in the studies. Because we try to provide data for as many racial and ethnic groups as possible, we show these data for informational and comparative purposes.

Global Burden of Disease

The GBD study is an ongoing global effort to measure death and disability attributable to diseases, injuries, and risk factors for all countries from 1990 to the present day. The study seeks to produce consistent and comparable estimates of population health over time and across locations, including summary metrics such as disability-adjusted life years and HALE. Results are made available to policy makers, researchers, governments, and the public with the overarching goals of improving population health and reducing health disparities.

GBD 2019, the study’s most recent iteration, was produced by the collective efforts of >5000 researchers in >150 countries. Estimates were produced for 369 diseases and injuries and 87 risk factors. Detailed methods and results can be found via the study’s online data visualization tools and across a range of peer-reviewed scientific research articles that can be found cited in this publication.

During each annual cycle of the GBD study, population health estimates are reproduced for the full-time series. For GBD 2019, estimates were produced for 1990 to 2019 for 204 countries and territories, stratified by age and sex, with subnational estimates made available for an increasing number of countries. Improvements in statistical and geospatial modeling methods and the addition of new data sources may lead to changes in results across GBD study cycles for both the most recent and earlier years.

For more information about the GBD and to access GBD 2019 resources, data visualizations, and most recent publications, please visit the study’s website.^12–14

Contacts

If you have questions about statistics or any points made in this Statistical Update, please contact the AHA National Center, Office of Science, Medicine and Health. Direct all media inquiries to News Media Relations at http://newsroom.heart.org/connect or 214-706-1173.

The AHA works diligently to ensure that this Statistical Update is error free. If we discover errors after publication, we will provide corrections at http://www.heart.org/statistics and in the journal Circulation.

2. Cardiovascular Health

See Tables 2-1 through 2-10 and Charts 2-1 through 2-5

In 2010, the AHA released an Impact Goal that included 2 objectives that would guide organizational priorities over the next decade: “By 2020, to improve the cardiovascular health of all Americans by 20%, while reducing deaths from CVDs and stroke by 20%.”¹

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The concept of CVH was introduced in this goal and characterized by 7 components (Life’s Simple 7)² that include health behaviors (diet quality, PA, smoking) and health factors (blood cholesterol, BMI, BP, blood glucose). For an individual to have ideal CVH overall, they must have an absence of clinically manifest CVD and the simultaneous presence of optimal levels of all 7 CVH components, including abstinence from smoking, a healthy diet pattern, sufficient PA, normal body weight, and normal levels of TC, BP, and FPG (in the absence of medication treatment; Table 2-1). Because ideal CVH is rare, the distribution of the 7 CVH components is also described with the use of the categories poor, intermediate, and ideal.¹Table 2-1 provides the specific definitions for these categories for each CVH component in both adults and youth.

From 2011 to 2020, this chapter in the annual Statistical Update has published national prevalence estimates for CVH to inform progress toward improvements in the prevalence of CVH. This year, updates to this chapter include prevalence estimates for components of CVH for which newly released NHANES data from 2017 to 2018 were available. New additions this year also include 10-year differences in the leading causes and risk factors for YLDs and YLLs, which highlight the influence of the components of CVH on premature death and disability in populations.

Relevance of Ideal CVH

• Multiple independent investigations (summaries of which are provided in this chapter) have confirmed the importance of having ideal levels of these components, along with the overall concept of CVH. Findings include strong inverse, stepwise associations in the United States of the number of CVH components at ideal levels with all-cause mortality, CVD mortality, IHD mortality, CVD, and HF; with subclinical measures of atherosclerosis such as carotid IMT, arterial stiffness, and CAC prevalence and progression; with physical functional impairment and frailty; with cognitive decline and depression; and with longevity.^6–12 Similar relationships have also been seen in non-US populations.^6,7,13–23

• A large Hispanic/Latino cohort study in the United States confirmed the associations between CVD and status of CVH components in this population and found that the levels of CVH components compared favorably with existing national estimates; however, some of the associations varied by sex and heritage.⁷

• A study of Black people found that risk of incident HF was 61% lower among those with ≥4 ideal CVH components than among those with 0 to 2 ideal components.⁸

• Ideal health behaviors and ideal health factors are each independently associated with lower CVD risk in a stepwise fashion; across any level of health behaviors, health factors are associated with incident CVD, and conversely, across any level of health factors, health behaviors are associated with incident CVD.²⁴

• Analyses from the US Burden of Disease Collaborators demonstrated that poor levels of each of the 7 CVH components resulted in substantial mortality and morbidity in the United States in 2010. The leading risk factor related to overall disease burden was suboptimal diet, followed by tobacco smoking, high BMI, raised BP, high FPG, and physical inactivity.²⁵

• A meta-analysis of 9 prospective cohort studies involving 12 878 participants reported that having the highest number of ideal CVH components was associated with a lower risk of all-cause mortality (RR, 0.55 [95% CI, 0.37–0.80]), cardiovascular mortality (RR, 0.25 [95% CI, 0.10–0.63]), CVD (RR, 0.20 [95% CI, 0.11–0.37]), and stroke (RR, 0.31 [95% CI, 0.25–0.38]) compared with individuals with the lowest number of ideal components.²⁶

• The adjusted PAFs for CVD mortality for individual components of CVH have been reported as follows²⁷:

  • — 40.6% (95% CI, 24.5%–54.6%) for HBP

  • — 13.7% (95% CI, 4.8%–22.3%) for smoking

  • — 13.2% (95% CI, 3.5%–29.2%) for poor diet

  • — 11.9% (95% CI, 1.3%–22.3%) for insufficient PA

  • — 8.8% (95% CI, 2.1%–15.4%) for abnormal glucose levels

• Several studies have been published in which investigators have assigned individuals a CVH score ranging from 0 to 14 on the basis of the sum of points assigned to each component of CVH (poor=0, intermediate=1, ideal=2 points). With this approach, data from the REGARDS cohort were used to demonstrate an inverse stepwise association between a higher CVH score component and lower incidence of stroke. On the basis of this score, every unit increase in CVH was associated with an 8% lower risk of incident stroke (HR, 0.92 [95% CI, 0.88–0.95]), with a similar effect size for White (HR, 0.91 [95% CI, 0.86–0.96]) and Black (HR, 0.93 [95% CI, 0.87–0.98]) participants.²⁸

• The Cardiovascular Lifetime Risk Pooling Project showed that adults with all optimal risk factor levels (similar to having ideal CVH factor levels of cholesterol, blood sugar, and BP, as well as not smoking) have substantially longer overall and CVD-free survival than those who have poor levels of ≥1 of these CVH factors. For example, at an index age of 45 years, males with optimal risk factor profiles lived on average 14 years longer free of all CVD events and 12 years longer overall than people with ≥2 risk factors.²⁹

• Better CVH as defined by the AHA is associated with lower incidence of HF,^6,8,9,11,19 less subclinical vascular disease,^{12,17,20,30,31} better global cognitive performance and cognitive function,^18,32,33 lower hazard of subsequent dementia,³⁴ lower prevalence¹⁰ and incidence³⁵ of depressive symptoms, lower loss of physical functional status,³⁶ longer leukocyte telomere length,³⁷ less ESRD,³⁸ less pneumonia, less chronic obstructive pulmonary disease,³⁹ less VTE/PE,⁴⁰ lower prevalence of aortic sclerosis and stenosis,⁴¹ lower risk of calcific aortic valve stenosis,⁴² better prognosis after MI,⁴³ lower risk of AF,⁴⁴ and lower odds of having elevated resting heart rate.⁴⁵ In addition, a study among a sample of Hispanic/Latino people residing in the United States reported that greater positive psychological functioning (dispositional optimism) was associated with higher CVH scores as defined by the AHA.⁴⁶ A study in college students found that both handgrip strength and muscle mass are positively associated with greater numbers of ideal CVH components,⁴⁷ and a cross-sectional study found that greater cardiopulmonary fitness, upper-body flexibility, and lower-body muscular strength are associated with better CVH components in perimenopausal females.⁴⁸ Furthermore, studies demonstrate that higher quality of life scores are associated with better CVH metrics,⁴⁹ providing additional evidence to support the benefits of ideal CVH on general health and quality of life.

• According to NHANES 1999 to 2006 data, several social risk factors (low family income, low education level, minority race, and single-living status) were related to lower likelihood of attaining better CVH as measured by Life’s Simple 7 scores.⁵⁰ In addition, neighborhood factors and contextual relationships have been found to be related to health disparities in CVH, but more research is needed to better understand these complex relationships.⁵¹ Having more ideal CVH components in middle age is also associated with lower non-CVD and CVD health care costs in later life.⁵² An investigation of 4906 participants in the Cooper Center Longitudinal Study reported that participants with ≥5 ideal CVH components exhibited 24.9% (95% CI, 11.7%–36.0%) lower median annual non-CVD costs and 74.5% (95% CI, 57.5%–84.7%) lower median CVD costs than those with ≤2 ideal CVH components.⁵²

• A report from a large, ethnically diverse insured population found that people with 6 or 7 and those with 3 to 5 of the CVH components in the ideal category had a $2021 and $940 lower annual mean health care expenditure, respectively, than those with 0 to 2 ideal health components.⁵³

CVH: Prevalence (NHANES 2015–2016 and 2017–2018)

(See Table 2-2 and Charts 2-1 through 2-3)

• The national prevalence estimates for children (12–19 years of age) and adults (≥20 years of age) who meet ideal, intermediate, and poor levels of each of the 7 CVH components are displayed in Chart 2-1.⁵⁴ The most current estimates at time of publication were based on data from NHANES 2017 to 2018 for smoking, BMI, PA (for adults), TC, and BP and data from NHANES 2015 to 2016 for PA (for children), diet, and diabetes status. NHANES 2017 to 2018 survey changed the PA assessments for children, so the PA status for children was updated through 2016 only.

• For most components of CVH, prevalence of ideal levels is higher in US children (12–19 years of age) than in US adults (≥20 years of age), except for the Healthy Diet Score and PA, for which prevalence of ideal levels in children is lower than in adults.

• Among US children (12–19 years of age; Chart 2-1), the unadjusted prevalence of ideal levels of CVH components currently varies from <1% for the Healthy Diet Score (ie, <1 in 100 US children meets at least 4 of the 5 dietary components) to >86% for smoking, BP, and diabetes components (unpublished AHA tabulation).

• Among US adults (Chart 2-1), the lowest prevalence of ideal levels for CVH components is <1% for the Healthy Diet Score in adults ≥20 years of age. The highest prevalence of ideal levels for a CVH component is for smoking (79.8% of adults report never having smoked or being a former smoker who has quit for >12 months). In 2017 to 2018, 52.4% of adults had ideal levels of TC (<200 mg/dL).

• Age-standardized and age-specific prevalence estimates for ideal CVH and for ideal levels of individual CVH components for 2015 to 2016 and 2017 to 2018 are displayed in Table 2-2.

• In 2015 to 2018, all individual components of CVH among adults were highest in the youngest age groups (20–39 years of age) and were lowest in the oldest age group (≥60 years of age), except the Healthy Diet Score, for which prevalence of ideal levels was highest in older adults but still <1% according to the 2015 to 2016 NHANES data.

• Chart 2-2 displays the unadjusted prevalence estimates of ideal levels of CVH components for the population of US children (12–19 years of age) by race/ethnicity.

  • — Majority of US children 12 to 19 years of age met ideal criteria for smoking (93.4%–97.4%), BP (80.1%–89.6%), and TC (73.4%–80.0%) in 2017 to 2018 across race/ethnicity subgroups.

  • — Majority of US children 12 to 19 years of age met ideal criteria for diabetes (73.6%–88.0%) in 2015 to 2016 across race/ethnicity groups.

  • — Of US children 12 to 19 years of age, 46.8% to 76.2% met ideal criteria for BMI in 2017 to 2018, whereas only 23.8% to 27.8% of US children met ideal criteria for PA in 2015 to 2016 across race/ethnicity categories.

  • — Few US children 12 to 19 years of age (<1%) met ideal criteria for Healthy Diet Score in 2015 to 2016 across all race/ethnicity groups.

• Chart 2-3 displays the unadjusted prevalence estimates of ideal levels of CVH components for the population of US adults ≥20 years of age by race/ethnicity.

  • — Majority of US adults ≥20 years of age met ideal criteria for smoking (75.9%–90.4%) in 2017 to 2018 across race/ethnicity subgroups.

  • — Fewer than a quarter to a little more than half of US adults ≥20 years of age met ideal criteria for BMI (15.2%–50.5%), TC (49.8%–57.7%), PA (30.4%–42.7%), and BP (31.5%–44.4%) in 2017 to 2018 across race/ethnicity groups.

  • — Of US adults ≥20 years of age, 42.0% to 59.7% met ideal criteria for diabetes in 2015 to 2016 across race/ethnicity categories.

  • — Few US adults ≥20 years of age (0.1%–1.6%) met ideal criteria for Healthy Diet Score in 2015 to 2016 across all race/ethnicity groups.

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CVH: Trends Over Time

(See Charts 2-4 and 2-5)

• The trends in prevalence of meeting ideal criteria for the individual components of CVH from 1999 to 2000 to 2017 to 2018 (for diet, trends from 2003–2004 through 2015–2016) are shown in Chart 2-4 for children (12–19 years of age) and in Chart 2-5 for adults (≥20 years of age).

  • — Among children 12 to 19 years of age from 1999 to 2000 to 2017 to 2018, the prevalence of meeting ideal criteria for smoking and BP has consistently improved, increasing from 76.4% to 95.7% for nonsmoking and from 83.6% to 89.1% for ideal BP. For ideal TC, the prevalence increased from 72.0% to 77.2%. However, a decline in prevalence of ideal levels was observed for BMI, from 69.8% in 1999 to 2000 to 60.1% in 2015 to 2016, although it rebounded slightly to 63.3% in 2017 to 2018.

  • — From 1999 to 2000 to 2015 to 2016, declines in prevalence of ideal levels were observed for PA (38.4% to 25.4%) and diabetes (92.4% to 86.2%) among children.

  • — Among adults, from 1999 to 2000 to 2017 to 2018, the prevalence of meeting ideal criteria for smoking, TC, and BP increased. For example, the prevalence of being a never smoker or having quit ≥1 year prior increased from 72.9% to 79.8%. Over the 18-year period, the prevalence of meeting criteria for ideal TC increased from 45.1% to 52.4%. However, declines in prevalence of ideal levels were observed for PA (from 40.2% to 38.3%) and BMI (from 36.3% to 26.4%) among adults during this period.

  • — Similar to trends observed in children, a decline in prevalence of ideal levels was observed for diabetes among adults, from 69.1% in 1999 to 2000 to 58.4% in 2015 to 2016.

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Trends in Risk Factors and Causes for YLL and YLD in the United States: 1990 to 2019

(See Tables 2-3 through 2-6)

• The leading risk factors for YLLs from 1990 to 2019 in the United States are presented in Table 2-3.

  • — Smoking and high SBP remained the first and second leading YLL risk factors in both 1990 and 2019. Age-standardized rates of YLL attributable to smoking declined by 46.4%, whereas age-standardized rates attributable to high SBP declined 45.8%.

  • — From 1990 to 2019, YLLs caused by drug use rose from 18th to 5th leading YLL risk factor with a 242.3% increase in the age-standardized YLL rate.

• The leading causes of YLLs from 1990 to 2019 in the United States are presented in Table 2-4.

  • — IHD and tracheal, bronchus, and lung cancer were the first and second leading YLL causes in both 1990 and 2019. Age-standardized YLL rates attributable to IHD declined 50.9%, whereas age-standardized YLL rates resulting from tracheal, bronchus, and lung cancer declined 36.1%.

  • — From 1990 to 2019, opioid use disorders rose from 46th to 4th leading YLL cause with a 799.2% increase in the age-standardized YLL rate. Type 2 diabetes also rose from 12th to 6th leading YLL cause, whereas Alzheimer disease and other dementias also rose from 15th to 7th leading YLL cause.

  • — The leading risk factors for YLDs from 1990 to 2019 in the United States are presented in Table 2-5.

  • — High BMI, high FPG, and smoking are among the first, second, and third leading YLD risk factors in both 1990 and 2019, with high BMI and high FPG rising in ranking while smoking dropped from the first to third leading YLD risk factor during this time period. Age-standardized YLD rates attributable to smoking declined by 25.8%, while age-standardized rates attributable to high BMI and high FPG increased by 44.4% and 47.4%, respectively, between 1990 and 2019.

• The leading causes of YLDs from 1990 to 2019 in the United States are presented in Table 2-6.

  • — Low back pain and other musculoskeletal disorders were the first and second leading causes of YLDs in both 1990 and 2019. The age-standardized rates of YLD attributable to low back pain decreased 12.5%, whereas age-standardized YLD rates for other musculoskeletal disorders increased 44.2%.

  • — From 1990 to 2019, type 2 diabetes rose from the ninth to third leading YLD cause with a 55.8% increase in the age-standardized YLD rates.

  • — Opioid use disorders rose from 16th to 4th leading YLD cause between 1990 and 2019 with a 288.7% increase in age-standardized rates of YLD.

Trends in Global Risk Factors and Causes for YLL and YLD: 1990 to 2019

(See Tables 2-7 through 2-11)

• The leading global YLL risk factors from 1990 to 2019 are presented in Table 2-7.

  • — High SBP and smoking were the first and second leading YLL risk factors globally in 2019. Age-standardized YLL rates attributable to HBP and smoking declined 29.0% and 41.3%, respectively, between 1990 and 2019.

  • — From 1990 to 2019, high FPG rose from 14th to 5th leading risk factor of global YLLs with a 1.5% decrease in the age-standardized YLL rates over this period.

• The leading global YLL causes from 1990 to 2019 are presented in Table 2-8.

  • — IHD rose from the third to first leading global YLL cause between 1990 and 2019, whereas age-standardized YLL rates declined by 29.1% during this period. This shift resulted in lower respiratory infections moving from first to second leading cause, and age-standardized YLL rates declined 62.7%.

  • — ICH and ischemic stroke rose from 9th to 4th and from 13th to 8th leading cause of global YLL, respectively, between 1990 and 2019.

  • — Type 2 diabetes also rose from 28th to 14th leading global YLL cause, showing a 9.1% increase in age-standardized YLL rate.

• The leading global risk factors for YLDs from 1990 to 2019 are presented in Table 2-9.

  • — High FPG and high BMI were the first and second leading YLD risk factors globally in 2019, replacing iron deficiency and smoking, which ranked fourth and third, respectively, in 2019. Age-standardized YLD rates attributable to high FPG and high BMI increased 44.1.% and 60.2%, respectively, whereas age-standardized global YLD rates attributable to smoking and iron deficiency deceased 22.9% and 16.7%, respectively.

  • — Ambient particulate matter pollution rose from 17th to 8th leading global risk factor for YLD, resulting in a 64.9% increase in the age-standardized global YLD rates.

• The leading global causes of YLDs from 1990 to 2019 are presented in Table 2-10.

  • — Low back pain and migraine were the first and second leading global causes of YLDs in both 1990 and 2019. The age-standardized rates of YLD attributable to low back pain decreased 16.3%, whereas rates for migraine increased 1.5% across the same time period.

  • — From 1990 to 2019, type 2 diabetes rose from 10th to 6th leading global cause of YLD during this time period, with a 50.2% increase in the age-standardized global YLD rate.

Furthering the AHA’s Impact Through Continued Efforts to Improve CVH

(See Tables 2-3 through 2-6)

• Renewed efforts to maintain and improve CVH will be foundational to successful reductions in mortality and disability in the United States and globally. Individuals with more favorable levels of CVH have significantly lower risk for several of the leading causes of death, including IHD,²⁴ Alzheimer disease,⁵⁵ stroke,^56,57 CKD,⁵⁸ diabetes,^59,60 breast cancer,^61,62 and atrial fibrillation (Tables 2-3 and 2-4). In addition, 6 of the 10 leading US risk factors for YLL and 4 of the 10 leading risk factors for YLD in 2019 were also components of CVH (Tables 2-3 and 2-5). Taken together, these data demonstrate the tremendous importance of continued efforts to improve CVH.

• The expanding efforts of the AHA and American Stroke Association in areas of brain health are also well poised to drive toward improvement in several leading causes of death and disability that influence YLLs and YLDs, including stroke, Alzheimer disease, depression and anxiety disorders, and alcohol and substance use disorders.

• Despite improvements observed in CVH and brain health over the past decade, further progress is needed to more fully realize these benefits for all Americans. Details are described in the AHA presidential advisory on brain health.⁶³

Global Efforts to Improve CVH

(See Tables 2-7 through 2-10)

• Renewal of efforts to improve CVH is a continuing challenge that requires collaboration throughout the global community in ways that aim targeted skills and resources at improving the top causes and risk factors for death and disability in countries. Such efforts are required in countries at all income levels with an emphasis on efforts to halt the continued worsening of the components of CVH (Tables 2-7 through 2-10).

• Many challenges exist related to implementation of prevention and treatment programs in international settings; some challenges are unique to individual countries/cultures, whereas others are universal. Partnerships and collaborations with local, national, regional, and global partners are foundational to effectively addressing relevant national health priorities in ways that facilitate contextualization within individual countries and cultures.

3. SMOKING/TOBACCO USE

See Table 3-1 and Charts 3-1 through 3-6

Tobacco use is one of the leading preventable causes of death in the United States and globally. Cigarette smoking, the most common form of tobacco use, is a major risk factor for CVD and stroke.¹ The AHA has identified never having tried smoking or never having smoked a whole cigarette (for children) and never having smoked or having quit >12 months ago (for adults) as 1 of the 7 components of ideal CVH in Life’s Simple 7.² Unless otherwise stated, throughout the rest of this chapter, we report tobacco use and smoking estimates from the NYTS³ for adolescents and from the NHIS⁴ for adults (≥18 years of age) because these data sources have more recent data. As a survey of middle and high school students, the NYTS may not be generalizable to youth who are not enrolled in school; however, in 2016, 97% of youth 10 to 17 years of age were enrolled in school, which indicates that the results of the NYTS are likely broadly applicable to US youth.³

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Other forms of tobacco use are becoming increasingly common. e-Cigarette use, which involves inhalation of a vaporized liquid that includes nicotine, solvents, and flavoring (“vaping”), has risen dramatically, particularly among young people. The variety of e-cigarette–related products has increased exponentially, giving rise to the more general term electronic nicotine delivery systems.⁵ A notable evolution in electronic nicotine delivery systems technology and marketing has occurred recently with the advent of pod mods, small rechargeable devices that deliver high levels of nicotine derived from nicotine salts in loose-leaf tobacco.⁶ Use of cigars, cigarillos, filtered cigars, and hookah also has become increasingly common in recent years. Thus, each section below addresses the most recent statistical estimates for combustible cigarettes, electronic nicotine delivery systems, and other forms of tobacco use if such estimates are available.

Prevalence

(See Chart 3-1)

Youth

• Prevalence of cigarette use in the past 30 days for middle and high school students by sex and race/ethnicity in 2019 is shown in Chart 3-1.

• In 2019⁷:

  • — 31.2% (95% CI, 29.1%–33.5%) of high school students (corresponding to 4.7 million users) and 12.5% (95% CI, 11.2%–13.9%) of middle school students (corresponding to 1.5 million users) used any tobacco products. In addition, 5.8% (95% CI, 4.6%–7.3%) of high school students (860 000 users) and 2.3% (95% CI, 1.8%–2.9%) of middle school students (270 000 users) smoked cigarettes in the past 30 days.

  • — 4.8% (95% CI, 3.7%–6.3%) of high school students (720 000 users) and 1.8% (95% CI, 1.4%–2.2%) of middle school students (210 000) used smokeless tobacco in the past 30 days.

  • — 7.6% (95% CI, 6.6%–8.8%) of high school students (1.1 million users) and 2.3% (95% CI, 1.9%–2.9%) of middle school students (270 000 users) used cigars in the past 30 days.

• Of youth who smoked cigarettes in the past 30 days in 2019, 28.9% (95% CI, 23.1%–35.5%) of middle and high school students (corresponding to 330 000 users) reported smoking cigarettes on 20 to 30 days of the past 30 days.⁷

• In 2019, tobacco use within the past month for middle and high school students varied by race/ethnicity: The prevalence of past 30-day cigarette use was 5.0% (95% CI, 3.9%–6.4%) in NH White youth compared with 3.1% (95% CI, 2.3–4.1%) in NH Black youth and 3.6% (95% CI, 2.8%–4.5%) in Hispanic youth. For cigars, the respective percentages were 5.1% (95% CI, 4.3%–6.1%), 8.6% (7.0%–10.6%), and 4.8% (95% CI, 3.9%–5.9%).⁷

• The percentage of high school (27.5% or 4 110 000 users) and middle school (10.5% or 1 240 000 users) students who used e-cigarettes in the past 30 days exceeded the proportion using cigarettes in 2019 (Chart 3-1).

Adults

(See Charts 3-2 and 3-3)

• According to the NHIS 2018 data, among adults ≥18 years of age⁴:

  • — 13.7% (95% CI, 13.1%–14.3%) of adults reported cigarette use every day or some days.

  • — 15.6% (95% CI, 14.8%–16.5%) of males and 12.0% (95% CI, 11.2%–12.7%) of females reported cigarette use every day or some days.

  • — 7.8% of those 18 to 24 years of age, 16.5% of those 25 to 44 years of age, 16.3% of those 45 to 64 years of age, and 8.4% of those ≥65 years of age reported cigarette use every day or some days.

  • — 22.6% of NH American Indian or Alaska Native adults, 14.6% of NH Black adults, 7.1% of NH Asian adults, 9.8% of Hispanic adults, and 15.0% of NH White adults reported cigarette use every day or some days.

  • — By annual household income, reported cigarette use every day or some days was 21.3% of people with <$35 000 income compared with 14.9% of those with income of $35 000 to $74 999, 13.3% of those with income of $75 000 to $99 999, and 7.3% of those with income ≥$100 000.

  • — In adults ≥25 years of age, the percentage reporting current cigarette use was 21.8% for those with <12 years of education, 36.0% in those with a General Educational Development high school equivalency, 19.7% among those with a high school diploma, 18.3% among those with some college, 14.8% among those with an associate’s degree, and 7.1% among those with an undergraduate degree compared with 3.7% among those with a graduate degree.

  • — 20.6% of lesbian/gay/bisexual individuals were current smokers compared with 13.5% of heterosexual/straight individuals.

  • — By region, the prevalence of current cigarette smokers was highest in the Midwest (16.2%) and South (14.8%) and lowest in the Northeast (12.5%) and West (10.7%).⁴

• According to data from BRFSS 2018, the state with the highest age-adjusted percentage of current cigarette smokers was West Virginia (26.8%). The states with the lowest age-adjusted percentage of current cigarette smokers were Utah (9.0%) and California (11.4%; Chart 3-2).⁸

• In 2018, smoking prevalence was higher among adults ≥18 years of age who reported having a disability or activity limitation (19.2%) than among those reporting no disability or limitation (13.1%).⁴

• Among individuals reporting serious psychological distress, 31.6% were current smokers compared with 13.0% of those without serious psychological distress.⁴

• Among females who gave birth in 2016, 7.2% smoked cigarettes during pregnancy. Smoking prevalence during pregnancy was greatest for females 20 to 24 years of age (10.7%), followed by females 15 to 19 years of age (8.5%) and 25 to 29 years of age (8.2%).⁹ Rates were highest among NH American Indian or Alaska Native females (16.7%) and lowest in NH Asian females (0.6%). With respect to differences by education, cigarette smoking prevalence was highest among females who completed high school (12.2%), followed by females with less than high school education (11.7%).

• e-Cigarette prevalence in 2017 is shown in Chart 3-3. Comparing e-cigarette prevalence across the 50 states shows that the average age-adjusted prevalence was 5.3%. The lowest age-adjusted prevalence was observed in California (3.2%), and the highest prevalence was observed in Oklahoma (7.5%). The age-adjusted prevalence was 1.3% in Puerto Rico.

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Incidence

• According to the 2018 NSDUH, ≈1.83 million people ≥12 years of age had smoked cigarettes for the first time within the past 12 months compared with 1.90 million in 2017 (2018 NSDUH Table 4.2B).¹⁰ Of new smokers in 2018, 571 000 were 12 to 17 years of age, 781 000 were 18 to 20 years of age, and 360 000 were 21 to 25 years of age; only 113 000 were ≥26 years of age when they first smoked cigarettes.

• The number of new smokers 12 to 17 years of age in 2018 (571 000) decreased from 2017 (604 000). The number of new smokers 18 to 25 years of age in 2018 (1.14 million) also decreased from 2017 (1.15 million) (2018 NSDUH Table 4.2B).¹⁰

• According to data from the PATH Study between 2013 and 2016, in youth 12 to 15 years of age, use of an e-cigarette was independently associated with new ever use of combustible cigarettes (OR, 4.09 [95% CI, 2.97–5.63]) and past 30-day use (OR, 2.75 [95% CI, 1.60–4.73]) at 2 years of follow-up. For youth who tried another non–e-cigarette tobacco product, a similar strength of association for cigarette use at 2 years was observed.¹¹

Lifetime Risk

Youth

• Per NSDUH data for individuals 12 to 17 years of age, overall, the lifetime use of tobacco products declined from 14.9% to 13.4% between 2017 and 2018, with lifetime cigarette use declining from 10.8% to 9.6% during the same time period (2018 NSDUH Tables 2.2B and 2.3B).¹⁰

  • — The lifetime use of tobacco products among adolescents 12 to 17 years of age varied by the following:

    • ▪ Sex: Lifetime use was higher among males (14.7%) than females (12.0%; 2018 NSDUH Table 2.8B).¹⁰

    • ▪ Race/ethnicity: Lifetime use was highest among American Indian and Alaska Native adolescents (18.7%), followed by NH White adolescents (16.3%), Hispanic or Latino adolescents (10.8%), NH Black adolescents (9.8%), and NH Asian adolescents (4.6%; 2018 NSDUH Table 2.8B).¹⁰

Adults

• According to NSDUH data, the lifetime use of tobacco products in individuals ≥18 years of age did not decline significantly between 2017 (67.5%) and 2018 (66.3%). Lifetime cigarette use declined in a similar interval from 61.8% to 60.3% (2018 NSDUH Tables 2.2B and 2.3B).¹⁰ Similar to the patterns in youth, lifetime risk of tobacco products varied by demographic factors (2018 NSDUH Table 2.8B)¹⁰:

  • — Sex: Lifetime use was higher in males (75.0%) than females (58.2%).

  • — Race/ethnicity: Lifetime use was highest in American Indian or Alaska Native adults (78.2%) and NH White adults (74.1%), followed by Native Hawaiian or Other Pacific Islander adults (69.7%), Hispanic or Latino adults (51.6%), NH Black adults (55.1%), and NH Asian adults (40.1%).

• In 2018, the lifetime use of smokeless tobacco for adults ≥18 years of age was 16.7% (2018 NSDUH Table 2.1B).

Secular Trends

(See Chart 3-4)

Youth

The percentage of adolescents (12–17 years of age) who reported smoking cigarettes in the past month declined from 13.0% in 2002 to 2.7% in 2018 (NSDUH Table 7.6B¹⁰; Chart 3-4). The percentages for daily cigarette use among those with past-month cigarette smoking in 12- to 17-year-olds were 31.5% in 2002 and 14.8% in 2018.^10,12 Trends in e-cigarette use and other tobacco product use among high school students between 2011 and 2018 are shown in Chart 3-5.

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Adults

Since the US Surgeon General’s first report on the health dangers of smoking, age-adjusted rates of smoking among adults have declined, from 51% of males smoking in 1965 to 15.6% in 2018 and from 34% of females in 1965 to 12.0% in 2018, according to NHIS data.^4,13 The decline in smoking, along with other factors (including improved treatment and reductions in the prevalence of risk factors such as uncontrolled hypertension and high cholesterol), is a contributing factor to secular declines in the HD death rate.¹⁴

• On the basis of weighted NHIS data, the current smoking status among 18- to 24-year-old males declined 47.5%, from 28.0% in 2005 to 14.7% in 2016; for 18- to 24-year-old females, smoking declined 44.4%, from 20.7% to 11.5%, over the same time period.¹⁵

• According to data from the BRFSS, the prevalence of e-cigarette use increased from 4.3% to 4.8% between 2016 and 2018 in US adults. Increases in e-cigarette use over this period were significant for middle-aged adults, women, and former smokers.¹⁶

• From 2005 to 2015, adjusted prevalence rates for tobacco use in individuals with serious psychological distress (according to the Kessler Scale) went from 41.9% to 40.6%, which represents a nonsignificant decline; however, rates for people without serious psychological stress declined significantly, from 20.3% to 14.0%.¹⁵

CVH Impact

• A 2010 report of the US Surgeon General on how tobacco causes disease summarized an extensive body of literature on smoking and CVD and the mechanisms through which smoking is thought to cause CVD.¹⁷ There is a sharp increase in CVD risk with low levels of exposure to cigarette smoke, including secondhand smoke, and a less rapid further increase in risk as the number of cigarettes per day increases. Similar health risks for CHD events were reported in a systematic review of regular cigar smoking.¹⁸

• Smoking is an independent risk factor for CHD and appears to have a multiplicative effect with the other major risk factors for CHD: high serum levels of lipids, untreated hypertension, and diabetes.¹⁷

• Cigarette smoking and other traditional CHD risk factors might have a synergistic interaction in HIV-positive individuals.¹⁹

• Among the US Black population, cigarette use is associated with elevated measures of subclinical PAD in a dose-dependent manner. Current smokers had an increased adjusted odds of ABI <1 (OR, 2.2 [95% CI, 1.5–3.3]).²⁰

• A meta-analysis of 75 cohort studies (≈2.4 million individuals) demonstrated a 25% greater risk for CHD in female smokers than in male smokers (RR, 1.25 [95% CI, 1.12–1.39]).²¹

• Cigarette smoking is a risk factor for both ischemic stroke and SAH in adjusted analyses and has a synergistic effect on other stroke risk factors such as oral contraceptive use.²²

• A meta-analysis comparing pooled data of ≈3.8 million smokers and nonsmokers found a similar risk of stroke associated with current smoking in females and males.²³

• Current smokers have a 2 to 4 times increased risk of stroke compared with nonsmokers or those who have quit for >10 years.^22,24

• A meta-analysis of 26 studies reported that compared with never smoking, current smoking (RR, 1.75 [95% CI, 1.54–1.99]) and former smoking (RR, 1.16 [95% CI, 1.08–1.24]) were associated with increased risk of HF.²⁵ In MESA, compared with never smoking, current smoking was associated with an adjusted doubling in incident HF (HR, 2.05 [95% CI, 1.36–3.09]). The increased risk was similar for HFpEF (HR, 2.51) and HFrEF (HR, 2.58).²⁶

• Short-term exposure to water pipe smoking is associated with a significant increase in SBP, DBP, and heart rate compared with nonsmoking control subjects,²⁷ but long-term effects remain unclear. Current use of smokeless tobacco was associated with an adjusted 1.27-fold increased risk of CVD events compared with never using. The CVD rate was 11.3 per 1000 person-years in never users and 21.4 in current users of smokeless tobacco.²⁸

• The long-term CVD risks associated with e-cigarette use are not known because of a lack of longitudinal data.^29,30 However, e-cigarette use has been linked to elevated levels of preclinical biomarkers associated with cardiovascular injury such as markers for sympathetic activation, oxidative stress, inflammation, thrombosis, and vascular dysfunction.³¹ In addition, daily and some-day use of e-cigarettes may be associated with MI and CHD.^32,33

• Dual use of e-cigarettes and combustible cigarettes was associated with significantly higher odds of CVD (OR, 1.36 [95% CI, 1.18–1.56]) compared with exclusive combustible cigarette use.³³ The association of dual use (relative to exclusive cigarette use) with CVD was 1.57 (95% CI, 1.18–2.07) for daily e-cigarette users and 1.31 (95% CI, 1.13–1.53) for occasional e-cigarette users.

Family History and Genetics

• Genetic factors contribute to smoking behavior; common and rare variants in several loci have been found to be associated with smoking initiation, number of cigarettes smoked per day, and smoking cessation.^34,35

• Genetics might also modify adverse CVH outcomes among smokers, with variation in ADAMTS7 associated with loss of cardioprotection in smokers.³⁶

Smoking Prevention

Tobacco 21 legislation was signed into law on December 20, 2019, increasing the federal minimum age for sale of tobacco products from 18 to 21 years.³⁷

• Such legislation is likely to reduce the rates of smoking during adolescence—a time during which the majority of smokers start smoking—by limiting access because most people who buy cigarettes for adolescents are <21 years of age.

  • — For instance, investigators compared smoking rates in Needham, MA, after introduction of an ordinance that raised the minimum purchase age to 21 years. The 30-day smoking rate in Needham declined from 13% to 7% between 2006 and 2010 compared with a decline from 15% to 12% (P<0.001) in 16 surrounding communities.³⁸

  • — Another study using BRFSS 2011 to 2016 data before the federal legislation found that metropolitan and micropolitan statistical areas with local Tobacco 21 policies yielded significant reductions in smoking among youth 18 to 20 years of age.³⁹

• In addition, in several towns where Tobacco 21 laws were enacted before federal legislation, reductions of up to 47% in smoking prevalence among high school students have been reported.⁴⁰ Furthermore, the National Academy of Medicine estimates that the nationwide Tobacco 21 law could result in 249 000 fewer premature deaths, 45 000 fewer lung cancer deaths, and 4.2 million fewer life-years lost among Americans born between 2010 and 2019.⁴⁰

• Before the federal minimum age of sale increase, 19 states (Hawaii, California, New Jersey, Oregon, Maine, Massachusetts, Illinois, Virginia, Delaware, Arkansas, Texas, Vermont, Connecticut, Maryland, Ohio, New York, Washington, Pennsylvania, and Utah), Washington, DC, and at least 470 localities (including New York City, NY; Chicago, IL; San Antonio, TX; Boston, MA; Cleveland, OH; and both Kansas Cities [Kansas and Missouri]) passed legislation setting the minimum age for the purchase of tobacco to 21 years.⁴¹

Awareness, Treatment, and Control

Smoking Cessation

• According to NHIS 2017 data, 61.7% of adult ever smokers had stopped smoking; the quit rate has increased 6 percentage points since 2012 (55.1%).⁴²

  • — Between 2011 and 2017, according to BRFSS surveys, quit attempts varied by state, with quit attempts increasing in 4 states (Kansas, Louisiana, Virginia, and West Virginia), declining in 2 states (New York and Tennessee), and not changing significantly in 44 states. In 2017 the quit attempts over the past year were highest in Guam (72.3%) and lowest in Wisconsin (58.6%), with a median of 65.4%.⁴³

  • — According to NHIS 2015 data, the majority (68.0%) of adult smokers wanted to quit smoking; 55.4% had tried in the past year, 7.4% had stopped recently, and 57.2% had received health care provider advice to quit.⁴⁴ Receiving advice to quit smoking was lower among uninsured smokers (44.1%) than among those with health insurance coverage through Medicaid or those who were dual eligible for coverage (both Medicaid and Medicare; 59. 9%).

• Data from clinical settings suggest wide variation in counseling practices related to smoking cessation. In a study based on national registry data, only 1 in 3 smokers who visited a cardiology practice received smoking cessation assistance.⁴⁵

• According to cross-sectional MEPS data from 2006 to 2015, receiving advice to quit increased over time from 60.2% in 2006 to 2007 to 64.9% in 2014 to 2015. In addition, in 2014 to 2015, use of prescription smoking cessation medicine was significantly lower among NH Black (OR, 0.51 [95% CI, 0.38–0.69]), NH Asian (OR, 0.31 [95% CI, 0.10–0.93]), and Hispanic (OR, 0.53 [95% CI, 0.36–0.78]) individuals compared with White individuals. Use of prescription smoking cessation medicine was also significantly lower among those without health insurance (OR, 0.58 [95% CI, 0.41–0.83]) and higher among females (OR, 1.28 [95% CI, 1.10–1.52]).⁴⁶ In 2014 to 2015, receipt of doctor’s advice to quit among US adult smokers was significantly lower in NH Black (59.7 [95% CI, 56.1–63.1]) and Hispanic (57.9 [95% CI, 53.5–62.2]) individuals compared with NH White individuals (66.6 [95% CI, 64.1–69.1]).

  • — The period from 2000 to 2015 revealed significant increases in the prevalence of smokers who had tried to quit in the past year, had stopped recently, had a health professional recommend quitting, or had used cessation counseling or medication.⁴⁴

  • — In 2015, fewer than one-third of smokers attempting to quit used evidence-based therapies: 4.7% used both counseling and medication, 6.8% used counseling, and 29.0% used medication (16.6% nicotine patch, 12.5% gum/lozenges, 2.4% nicotine spray/inhaler, 2.7% bupropion, and 7.9% varenicline).⁴⁴

• Smoking cessation reduces the risk of cardiovascular morbidity and mortality for smokers with and without CHD.

  • — In several studies, a dose-response relationship has been seen among current smokers between the number of cigarettes smoked per day and CVD incidence.^47,48

  • — Quitting smoking at any age significantly lowers mortality from smoking-related diseases, and the risk declines with the time since quitting smoking.¹ Cessation appears to have both short-term (weeks to months) and long-term (years) benefits for lowering CVD risk.⁴⁹

  • — Smokers who quit smoking at 25 to 34 years of age gained 10 years of life compared with those who continued to smoke. Those 35 to 44 years of age gained 9 years, those 45 to 54 years of age gained 6 years, and those 55 to 64 years of age gained 4 years of life, on average, compared with those who continued to smoke.⁴⁷

  • — Among those with a cumulative smoking history of at least 20 pack-years, individuals who quit smoking had a significantly lower risk of CVD within 5 years of smoking cessation compared with current smokers. However, former smokers’ CVD risks remained significantly higher than risks for never smokers beyond 5 years after smoking cessation.⁵⁰

• Cessation medications (including sustained-release bupropion, varenicline, nicotine gum, lozenge, nasal spray, and patch) are effective for helping smokers quit.^51,52

• EVITA was an RCT that examined the efficacy of varenicline versus placebo for smoking cessation among smokers who were hospitalized for ACS. At 24 weeks, rates of smoking abstinence and reduction were significantly higher among patients randomized to varenicline. The abstinence rates at 24 weeks were higher in the varenicline (47.3%) than the placebo (32.5%) group (P=0.012; number needed to treat, 6.8). Continuous abstinence rates and reduction rates (≥50% of daily cigarette consumption) were also higher in the varenicline group.⁵³

• The EAGLES trial⁵⁴ demonstrated the efficacy and safety of 12 weeks of varenicline, bupropion, or nicotine patch in motivated-to-quit patients who smoked with major depressive disorder, bipolar disorder, anxiety disorders, posttraumatic stress disorder, obsessive-compulsive disorder, social phobia, psychotic disorders including schizophrenia and schizoaffective disorders, and borderline personality disorder. Of note, these participants were all clinically stable from a psychiatric perspective and were believed not to be at high risk for self-injury.⁵⁴

• Extended use of a nicotine patch (24 weeks compared with 8 weeks) has been demonstrated to be safe and efficacious in randomized clinical trials.⁵⁵

• An RCT demonstrated the effectiveness of individual- and group-oriented financial incentives for tobacco abstinence through at least 12 months of follow-up.⁵⁶

• In addition to medications, smoke-free policies, increases in tobacco prices, cessation advice from health care professionals, and quit lines and other counseling have contributed to smoking cessation.^44,57

• Mass media antismoking campaigns such as the CDC’s Tips campaign (Tips From Former Smokers) have been shown to reduce smoking-attributable morbidity and mortality and are cost-effective. Investigators estimated that the Tips campaign cost about $48 million, saved ≈179 099 QALYs, and prevented ≈17 000 premature deaths in the United States.⁵⁸

• Despite states having collected $25.6 billion in 2012 from the 1998 Tobacco Master Settlement Agreement and tobacco taxes, <2% of those funds are spent on tobacco prevention and cessation programs.⁵⁹

• A randomized trial of e-cigarettes and behavioral support versus nicotine-replacement therapy and behavioral support in adults attending the UK National Health Service stop-smoking services found that 1-year cigarette abstinence rates were 18% in the e-cigarette group compared with 9.9% in the nicotine-replacement therapy group (RR, 1.83 [95% CI, 1.30–2.58]; P<0.001). However, among participants abstinent at 1 year, in the nicotine-replacement therapy group, only 9% were still using nicotine-replacement therapy, whereas 80% of those in the e-cigarette group were still using e-cigarettes.⁶⁰

• Observational evidence suggests that daily use of e-cigarettes is associated with increased likelihood of combustible cigarette smoking abstinence. However, some-day use of e-cigarettes is not associated with smoking abstinence or reduction.⁶¹

Mortality

• According to the 2020 Surgeon General’s report on smoking cessation, >480 000 Americans die as a result of cigarette smoking and >41 000 die of secondhand smoke exposure each year, ≈1 in 5 deaths annually.

• Of risk factors evaluated by the US Burden of Disease Collaborators, tobacco use was the second leading risk factor for death in the United States and the leading cause of DALYs, accounting for 11% of DALYs, in 2016.⁶² Overall mortality among US smokers is 3 times higher than that for never smokers.⁴⁷

• On average, on the basis of 2016 data, male smokers die 12 years earlier than male never smokers, and female smokers die 11 years earlier than female never smokers.^14,63

• Increased CVD mortality risks persist for older (≥60 years of age) smokers as well. A meta-analysis of 25 studies comparing CVD risks in 503 905 cohort participants ≥60 years of age reported an HR for cardiovascular mortality of 2.07 (95% CI, 1.82–2.36) compared with never smokers and 1.37 (95% CI, 1.25–1.49) compared with former smokers.⁶⁴

• In a sample of Native American individuals (SHS), among whom the prevalence of tobacco use is highest in the United States, the PAR for total mortality was 18.4% for males and 10.9% for females.⁶⁵

• Since the first report on the dangers of smoking was issued by the US Surgeon General in 1964, tobacco control efforts have contributed to a reduction of 8 million premature smoking-attributable deaths.⁶⁶

• If current smoking trends continue, 5.6 million US children will die of smoking prematurely during adulthood.¹⁷

Electronic Cigarettes

(See Charts 3-1 and 3-4)

• Electronic nicotine delivery systems, more commonly called e-cigarettes, are battery-operated devices that deliver nicotine, flavors, and other chemicals to the user in an aerosol. Although e-cigarettes were introduced into the United States only around 2007, there are currently >450 e-cigarette brands on the market, and sales in the United States were projected to be $2 billion in 2014. In 2015, Juul came on the market and has rapidly become the most popular e-cigarette product sold in the United States. The popularity of the Juul likely relates to several factors, including its slim and modern design, appealing flavors, and intensity of nicotine delivery, which approximates the experience of combustible cigarettes.⁶⁷

• e-Cigarette use has become prevalent among never smokers. In 2016, an estimated 1.9 million tobacco users exclusively used e-cigarettes in the United States. Of these exclusive e-cigarette users, 60% were <25 years of age.⁶⁸

• Current e-cigarette user prevalence for 2017 in the United States is shown in Chart 3-3.

• According to the NYTS, in 2019, e-cigarettes were the most commonly used tobacco products in youth: In the past 30 days, 10.5% (1.2 million) of middle school and 27.5% (4.1 million) of high school students endorsed use (Chart 3-1).⁷ A significant nonlinear increase in current e-cigarette use in high school students was observed between 2011 (1.5%) and 2019 (27.4%).^7,69 A significant increase in current e-cigarette use also was observed for middle school students, for whom the corresponding values were 0.6% and 10.5% in the 2 periods.^3,7 Among high school students, rates of use were approximately equal between males (27.6%) and females (27.4%) and most pronounced among NH White students (32.4%). In middle school students, slightly higher rates were observed in females (10.8%) and in Hispanic students (13.1%).⁷

• Frequent use of e-cigarettes among high school students who were current e-cigarette users increased from 27.7% in 2018 to 34.2% in 2019. In middle school students, the percentage using frequently among current e-cigarette users increased from 16.2% in 2018 to 18.0% in 2019.^3,7

• In 2016, 20.5 million US middle and high school students (80%) were exposed to e-cigarette advertising.⁷⁰

• Among US adults, awareness and use of e-cigarettes have increased considerably.⁷¹ In 2018, the prevalence of current e-cigarette use in adults, defined as use every day or on some days, was 3.2% according to data from the NHIS. The prevalence of current e-cigarette use was highest in individuals 18 to 24 years of age (7.6%) and in those with serious psychological distress (6.2%).⁴

• According to BRFSS 2016, current use of e-cigarettes in adults ≥18 years of age was higher in sexual and gender minority individuals. With respect to sexual orientation, 9.0% of bisexual and 7.0% of lesbian/gay individuals were current e-cigarette users compared with 4.6% of heterosexual people. Individuals who were transgender (8.7%) were current e-cigarette users at a higher rate than cisgender individuals (4.7%). Across US states, the highest prevalence of current e-cigarette use was observed in Oklahoma (7.0%) and the lowest in South Dakota (3.1%).⁷²

• e-Cigarettes contain lower levels of most tobacco-related toxic constituents compared with traditional cigarettes,⁷³ including volatile organic compounds.^74,75 However, nicotine levels have been found to be consistent across long-term cigarette and long-term e-cigarette users.^31,76

• e-Cigarette use has a significant cross-sectional association with a less favorable perception of physical and mental health and with depression.^77,78

• According to the BRFSS 2016 and 2017, e-cigarettes are associated with a 39% increased odds of self-reported asthma (OR, 1.39 [95% CI, 1.15–1.68]) and self-reported chronic obstructive pulmonary disease (OR, 1.75 [95% CI, 1.25–2.45]) among never users of combustible cigarette.^79,80 There is a dose-response relationship such that higher frequency of e-cigarette use was associated with more asthma or chronic obstructive pulmonary disease.

• An outbreak of e-cigarette or vaping product use–associated lung injury peaked in September 2019 after increasing rapidly between June and August 2019. Surveillance data and product testing indicate that tetrahydrocannabinol-containing e-cigarettes or vaping products are linked to most e-cigarette or vaping product use–associated lung injury cases. In particular, vitamin E acetate, an additive in some tetrahydrocannabinol-containing e-cigarettes or vaping, has been identified as the primary source of risk, although exposure to other e-cigarette– or vaping-related toxicants may also play a role. As of February 18, 2020, a total of 2807 hospitalized e-cigarette or vaping product use–associated lung injury cases or deaths have occurred in the United States.⁸¹

• Effective August 8, 2016, the FDA’s Deeming Rule prohibited sale of e-cigarettes to individuals <18 years of age.⁸²

• In January 2020, the FDA issued a policy prioritizing enforcement against the development and distribution of certain unauthorized flavored e-cigarette products such as fruit and mint flavors (ie, any flavors other than tobacco and menthol).⁸³

Secondhand Smoke

• Data from the US Surgeon General on the consequences of secondhand smoke indicate the following:

  • — Nonsmokers who are exposed to secondhand smoke at home or at work increase their risk of developing CHD by 25% to 30%.¹⁷

  • — Exposure to secondhand smoke increases the risk of stroke by 20% to 30%, and it is associated with increased mortality (adjusted mortality rate ratio, 2.11) after a stroke.⁸⁴

• A meta-analysis of 23 prospective and 17 case-control studies of cardiovascular risks associated with secondhand smoke exposure demonstrated 18%, 23%, 23%, and 29% increased risks for total mortality, total CVD, CHD, and stroke, respectively, in those exposed to secondhand smoke.⁸⁵

• A meta-analysis of 24 studies demonstrated that secondhand smoke can increase risks for preterm birth by 20%.⁸⁶

• A study using the Framingham Offspring cohort found that there was an 18% increase in AF among offspring for every 1–cigarette pack per day increase in parental smoking. In addition, offspring with parents who smoked had 1.34 (95% CI, 1.17–1.54) times the odds of smoking compared with offspring with nonsmoking parents.⁸⁷

• As of December 31, 2019, 14 states (California, Colorado, Delaware, Hawaii, Massachusetts, New Jersey, New Mexico, New York, North Dakota, Oregon, Rhode Island, South Dakota, Utah, and Vermont), the District of Columbia, and Puerto Rico have passed comprehensive smoke-free indoor air laws that include e-cigarettes. These laws prohibit smoking and the use of e-cigarettes in indoor areas of private worksites, restaurants, and bars.^41,88

• Pooled data from 17 studies in North America, Europe, and Australia suggest that smoke-free legislation can reduce the incidence of acute coronary events by 10% (RR, 0.90 [95% CI, 0.86–0.94]).⁸⁹

• The percentage of the US nonsmoking population with serum cotinine ≥0.05 ng/mL (which indicates exposure to secondhand smoke) declined from 52.5% in 1999 to 2000 to 25.3% in 2011 to 2012, with declines occurring for both children and adults. During 2011 to 2012, the percentage of nonsmokers with detectable serum cotinine was 40.6% for those 3 to 11 years of age, 33.8% for those 12 to 19 years of age, and 21.3% for those ≥20 years of age. The percentage was higher for NH Black individuals (46.8%) than for NH White individuals (21.8%) and Mexican American individuals (23.9%). People living below the poverty level (43.2%) and those living in rental housing (36.8%) had higher rates of secondhand smoke exposure than their counterparts (21.1% of those living above the poverty level and 19.0% of those who owned their homes; NHANES).⁹⁰

Cost

According to the Surgeon General’s 50th anniversary report on the health consequences of smoking, the estimated annual cost attributable to smoking from 2009 to 2012 was between $289 and $332.5 billion: Direct medical care for adults accounted for $132.5 to $175.9 billion; lost productivity because of premature death accounted for $151 billion (estimated from 2005–2009); and lost productivity resulting from secondhand smoke accounted for $5.6 billion (in 2006).¹⁴

• In the United States, cigarette smoking was associated with 8.7% of annual aggregated health care spending from 2006 to 2010, which represented roughly $170 billion per year, 60% of which was paid by public programs (eg, Medicare and Medicaid).⁹¹

• According to the CDC and Federal Trade Commission, the tobacco industry spends about $9.06 billion on cigarette and smokeless tobacco advertising annually, equivalent to $25 million per day.⁹²

• In 2018, 216.9 billion cigarettes were sold by major manufacturers in the United States, which represents a 5.3% decrease (12.2 billion units) from 2017.⁹³

• Cigarette prices in the United States increased steeply between the early 1970s and 2018, in large part because of excise taxes on tobacco products. Per pack in 1970, the average cost was $0.38 and tax was $0.18, whereas in 2018, the average cost was $6.90 and average tax $2.82.⁹⁴

• From 2012 through 2016, e-cigarette sales significantly increased while national e-cigarette prices significantly decreased. Together, these trends highlight the rapidly changing landscape of the US e-cigarette marketplace.⁹⁴

• Despite the morbidity and mortality resulting from tobacco use, Dieleman et al⁹⁵ estimated that tobacco interventions were among the bottom third of health care expenditures of the 154 health conditions they analyzed. They estimated that in 2019 the United States spent $1.9 billion (95% CI, $1.5–$2.3 billion) on tobacco interventions, the majority (75.6%) on individuals 20 to 64 years of age. Almost half of the funding (48.5%) for the intervention came from public insurance.

Global Burden of Tobacco Use

(See Table 3-1 and Chart 3-6)

• According to the GBD synthesis of >2800 data sources, the age-standardized global prevalence of daily smoking in 2017 was 8.7% (95% UI, 7.72%–9.79%) in males and 1.76% (95% UI, 1.52%–2.02%) in females. The investigators estimate that since 1990 smoking rates have declined globally by 23% in males and 42% in females.⁹⁶

• The GBD 2019 study used statistical models and data on incidence, prevalence, case fatality, excess mortality, and cause-specific mortality to estimate disease burden for 369 diseases and injuries and 87 risk factors in 204 countries and territories. Oceania, East and Central Asia, and Eastern Europe have the highest mortality rates attributable to tobacco (Chart 3-6).

• In 2015, there were a total of 933.1 million (95% UI, 831.3–1054.3 million) smokers globally, of whom 82.3% were male. The annualized rate of change in smoking prevalence between 1990 to 2015 was −1.7% in females and −1.3% in males.⁹⁷

• Worldwide, ≈80% of smokers live in low- and middle-income countries.⁹⁸

• Tobacco (including smoking, secondhand smoke, and chewing tobacco) caused an estimated 8.7 million deaths globally in 2019 (6.6 million males and 2.1 million females; Table 3-1).⁹⁹ GBD investigators estimated that in 2019 tobacco was the second leading risk of mortality (high SBP was number 1), and tobacco ranked third in DALYs globally.⁹⁹

• The WHO estimated that the economic cost of smoking-attributable diseases accounted for US $422 billion in 2012, which represented ≈5.7% of global health expenditures.¹⁰⁰ The total economic costs, including both health expenditures and lost productivity, amounted to approximately US $1436 billion, which was roughly equal to 1.8% of the world’s annual gross domestic product. The WHO further estimated that 40% of the expenditures were in developing countries.

• To help combat the global problem of tobacco exposure, in 2003, the WHO adopted the Framework Convention on Tobacco Control treaty. From this emerged a set of evidence-based policies with the goal of reducing the demand for tobacco, entitled MPOWER. MPOWER policies outline the following strategies for nations to reduce tobacco use: (1) monitor tobacco use and prevention policies; (2) protect individuals from tobacco smoke; (3) offer to help with tobacco cessation; (4) warn about tobacco-related dangers; (5) enforce bans on tobacco advertising; (6) raise taxes on tobacco; and (7) reduce the sale of cigarettes. More than half of all nations have implemented at least 1 MPOWER policy.^72,101 In 2018, population cost coverage (either partial or full) for quit interventions increased to 78% in middle-income countries and to 97% in high-income countries; 5 billion people are now covered by at least 1 MPOWER measure. However, only 23 countries offered comprehensive cessation support in the same year.¹⁰²

• The CDC examined data from 28 countries from the 2008 to 2016 Global Adult Tobacco Survey and reported that the median prevalence of tobacco smoking was 22.5% with wide heterogeneity (3.9% in Nigeria to 38.2% in Greece). Among current smokers, quit attempts over the prior 12 months also varied with a median of 42.5% (ranging from 14.4% in China to 59.6% in Senegal). Knowledge that smoking causes heart attacks (median, 83.6%; range, 38.7% in China to 95.5% in Turkey) and stroke (median 73.6%; range, 27.2% in China to 89.2% in Romania) varied widely across countries.¹⁰³

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References

4. PHYSICAL INACTIVITY

See Charts 4-1 through 4-13

Physical inactivity is defined as an insufficient level to meet the current PA recommendations.¹ Physical inactivity is a major risk factor for incident CVD (eg, CHD, stroke, PAD, HF).² Achieving the guideline recommendations for PA is one of the AHA’s 7 components of ideal CVH for both children and adults.³

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The 2018 Physical Activity Guidelines for Americans recommend that children and adolescents accumulate at least 60 minutes of PA daily (including aerobic and muscle- and bone-strengthening activity).⁴ In 2017, on the basis of survey interviews,⁵ only 26.1% of high school students reported achieving at least 60 minutes of daily PA, which is likely an overestimation of those actually meeting the guidelines.⁶

The 2018 Physical Activity Guidelines for Americans⁴ and the 2019 CVD Primary Prevention Clinical Practice Guidelines⁷ recommend that adults accumulate at least 150 min/wk of moderate-intensity or 75 min/wk of vigorous-intensity aerobic activity (or an equivalent combination) and perform muscle-strengthening activities at least 2 d/wk. For many people, examples of moderate-intensity activities include walking briskly or raking the yard, and examples of vigorous-intensity activities include jogging, carrying loads upstairs, or shoveling snow. In a nationally representative sample of adults in 2018, only 24.0% reported participating in adequate leisure-time aerobic and muscle-strengthening activity to meet these criteria (Chart 4-1).⁸

Being physically active is an important aspect of overall health. Meeting recommendations for PA not only reduces premature mortality but also improves risk factors for CVD (such as HBP, diabetes, and obesity) and reduces the likelihood of diseases related to CVD, including CHD, HF, stroke, and aging-related diseases such as dementia.^7,9–11 Benefits from PA are observed across the life span, including for children and older adults, pregnant females, and people with disabilities and chronic conditions. Therefore, the 2018 Physical Activity Guidelines for Americans recommend being as physically active as abilities and conditions allow and that some PA is better than none.⁴ Even small increases in moderate-intensity PA or replacing sedentary behavior (defined as “any waking behavior characterized by an energy expenditure ≤1.5 METs while in a sitting, reclining, or lying posture”¹) with light-intensity PA could provide health benefits.^4,9

Defining and Measuring PA

There are several PA dimensions (eg, mode or type, frequency, duration, and intensity) and PA domains (eg, occupational, domestic, transportation, and leisure time). There are additional considerations of where PA occurs such as in homes, worksites, schools, and communities. The federal guidelines specify the suggested frequency, duration, and intensity of PA and focus on 2 types: aerobic and strengthening.

There are 2 broad categories of methods to assess PA: (1) self-reported methods that use questionnaires and diaries/logs and (2) device-based methods that use wearables (eg, pedometers, accelerometers). Studies that compare the findings between methods show that there is marked discordance between self-reported and measured PA, with respondents often overstating their PA compared with device-based measures.⁶

Another consideration in the measurement of PA is that surveys often ask only about leisure-time PA, which represents PA obtained from a single domain. People who obtain high PA in other domains might be less likely to engage in leisure-time PA. For example, people who spend considerable time and physical effort in occupational, domestic, or transportation activities/domains might be less likely to be identified as meeting the guidelines when assessments focused only on leisure-time PA are used.¹²

PA and cardiorespiratory fitness provide distinct metrics in assessment of CVD risk.¹³ Poor cardiorespiratory (or aerobic) fitness might be a stronger predictor of adverse cardiovascular outcomes than traditional risk factors.¹⁴ Although many studies have shown that increasing the amount and quality of PA can improve cardiorespiratory fitness, other factors such as a genetic predisposition to perform aerobic exercise can contribute.¹⁵ Because cardiorespiratory fitness is directly measured and reflects both participation in PA and the state of physiological systems affecting performance, the relationship between cardiorespiratory fitness and clinical outcomes is often stronger than the relationship of PA to clinical outcomes.¹³ The WHO created an action plan to improve cardiorespiratory fitness globally with a goal to reduce the prevalence of insufficient PA by 15% by 2030.¹⁶

Prevalence

Youth

(See Charts 4-2 through 4-5)

• On the basis of self-reported PA (YRBSS, 2017)⁵:

  • — The prevalence of high school students who met aerobic activity recommendations of ≥60 minutes of PA on all 7 days of the week was 26.1% nationwide and was lower with each successive grade (from 9th [30.6%] to 12th [22.9%] grades). At each grade level, the prevalence was higher in boys than in girls.

  • — The prevalence of high school students who met PA recommendations on all 7 d/wk or on at least 5 of 7 d/wk was higher among boys than girls overall and stratified by race/ethnicity (Chart 4-2).

  • — Among high school students, 15.4% reported that they did not participate in ≥60 minutes of any kind of PA on any 1 of the previous 7 days. Girls were more likely than boys to report not meeting recommendations on any day (19.5% versus 11.0%), with NH Black girls reporting the highest prevalence of inactivity (26.6%; Chart 4-3).

  • — Among high school students, 28.5% of heterosexual students, 14.7% of gay, lesbian, and bisexual students, and 19.0% of students not sure about their sexual identity reported being physically active for at least 60 min/d on all 7 days. The difference between prevalence of being physically active in heterosexual versus gay, lesbian, and bisexual students was larger among male students than among female students (Chart 4-4).

• With the use of accelerometry (NHANES, 2003–2006),¹⁷ youth 6 to 19 years of age had a median of 53 min/d of moderate to vigorous PA.

  • — These levels of moderate to vigorous PA in youth were lower in girls and lower with greater age, with median values ranging from 82 to 138 min/d in boys 6 to 9 years of age and 64 to 111 min/d in girls 6 to 9 years of age, 39 to 67 min/d in boys 10 to 13 years of age and 20 to 49 min/d in girls 10 to 13 years of age, and 29 to 33 min/d in boys 14 to 17 years of age and 14 to 16 min/d in girls 14 to 17 years of age.

• With regard to measured cardiorespiratory fitness (NHANES, 2012)¹⁸:

  • — For adolescents 12 to 15 years of age, boys in all age groups were more likely to have adequate levels of cardiorespiratory fitness than girls (Chart 4-5).

• With regard to self-reported muscle-strengthening activities (YRBSS, 2017)⁵:

  • — The proportion of high school students who participated in muscle-strengthening activities on ≥3 d/wk was 51.1% nationwide and was lower with successively higher grades (9th grade: males, 66.4%, females, 49.3%; 12th grade: males, 56.6%, females, 36.1%).

  • — More high school boys (62.1%) than girls (40.8%) reported having participated in muscle-strengthening activities on ≥3 d/wk.

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Structured Activity Participation in Schools and Sports

• Only 29.9% of students attended physical education classes in school daily (34.7% of boys and 25.3% of girls; YRBSS, 2017).⁵

• Daily physical education class participation was lower with successively higher grades from the 9th grade (45.5% for boys, 39.2% for girls) through the 12th grade (26.5% for boys, 15.9% for girls; YRBSS, 2017).⁵

• Just over half (54.3%) of high school students played on at least 1 school or community sports team in the previous year: 49.3% of girls and 59.7% of boys (YRBSS, 2017).⁵

• Data from the 2017 SummerStyles survey demonstrated that only 16.5% of parents (n=1137) reported that their child walked to school and reported safety concerns and living too far away as barriers limiting commuting as a means of engaging in an active lifestyle.¹⁹

Television/Video/Computers

(See Chart 4-6)

• Research suggests that screen time (watching television or using a computer) can lead to less PA among children.²⁰ In addition, television viewing time is associated with poor nutritional choices, overeating, and weight gain (Chapter 5, Nutrition).

  • — Nationwide, 43.0% of high school students used a computer, tablet, or smartphone for activities other than school work (eg, video games, texting, YouTube, or social media) for ≥3 h/d on an average school day (YRBSS, 2017).⁵

  • — Among high school students, the prevalence of watching television ≥3 h/d was highest among NH Black boys (37.8%) and girls (32.8%), followed by Hispanic boys (21.9%) and girls (19.5%) and NH White girls (18.4%) and boys (16.9%) (YRBSS, 2017).⁵ The prevalence of playing video games or using a computer ≥3 h/d (for activities other than schoolwork) was higher among boys and girls (Chart 4-6) (YRBSS, 2017).⁵

• A nationally representative survey conducted in 2015 of 2658 US children 8 to 18 years of age indicated that tweens (8–12 years of age) use entertainment media (eg, television, video games, internet, music, social media) on average 5 hours 55 minutes per day whereas teenagers (13–18 years of age) average 8 hours 56 minutes per day outside of school or homework.²¹ Total screen time is higher for teenagers (6 hours 40 minutes) than for tweens (4 hours 36 minutes).²¹

• A nationally representative survey conducted in 2017 of 1454 parents of US children ≤8 years of age indicated that on average children spend 2 hours 19 minutes per day on screen media.²² Children ≤2 years of age spend on average 42 min/d on screen media.²² Despite recommendations by the American Academy of Pediatrics²³ to refrain from media use 1 hour before bedtime, 49% of children ≤8 years of age watched television or videos or played video games in the hour before bedtime.²²

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Adults

(See Charts 4-7 through 4-13)

• For self-reported leisure-time aerobic PA (NHIS, 2018)^8,24:

  • — The age-adjusted proportion who reported meeting the 2018 aerobic PA guidelines for Americans (≥150 minutes of moderate PA, ≥75 minutes of vigorous PA, or an equivalent combination each week) through leisure-time activities is shown in Chart 4-7. Among both males and females, NH White adults were more likely to meet the PA aerobic guidelines with leisure-time activity than NH Black and Hispanic adults. For each racial/ethnic group, males had higher PA than females.²⁵

• Adults with disabilities were less likely to meet the federal aerobic PA guidelines through leisure-time activities than those without disabilities (Chart 4-11).⁸ This pattern was similar for meeting recommendations for both aerobic and strengthening.

• In 2018, 25.4% of adults did not engage in leisure-time PA (no sessions of leisure-time PA of ≥10 minutes in duration; Chart 4-12).⁸

• From accelerometer-assessed PA (NHANES, 2005–2006),²⁶ US adults were estimated to participate in 45.1 min/wk (SE, 4.6 min/wk) of moderate PA and 18.6 min/wk (SE, 6.6 min/wk) of vigorous PA. Levels of moderate and vigorous PA were lower in older adults (60–69 years of age; moderate, 32.7 min/wk [SE, 3.6 min/wk]; vigorous, 1.4 min/wk [SE, 0.7 min/wk]) compared with adults in younger age groups (eg, 40–49 years of age; moderate, 54.1 min/wk [SE, 12.8 min/wk]; vigorous, 24.9 min/wk [SE, 16.6 min/wk]).

  • — Accelerometer data (2003–2006) also revealed that rural US adults performed less moderate to vigorous PA than urban adults, but rural adults spent more time in lighter-intensity PA (accelerometer counts per minute, 760–2020) than their urban adult counterparts.²⁷

  • — In contrast to self-reported PA, which suggested that NH White individuals had higher levels of PA,²⁸ data from accelerometer-assessed PA revealed that Mexican American adults had higher total PA and moderate to vigorous PA than NH White or Black adults (≥20 years of age).²⁶

• In a study of almost 5000 British males, among those with low PA in midlife, retirement and the development of cardiovascular-related conditions were identified as factors predicting a decrease in PA over 20 years of follow-up. However, for males who were more active in middle age, retirement is associated with higher PA.²⁹

• A report using data from 2018 indicated that US adults spent on average 10.5 h/d connected to media (eg, television, radio, smartphone, tablet, internet on computer), with adults 50 to 64 years of age spending the most time per day on media compared with any other age group.³⁰ This same report estimated that on average Black adults spent 12 hours 58 minutes, Hispanic adults spent 9 hours 17 minutes, and Asian American adults spent 6 hours 46 minutes per day connected to media. These habits affect time available for PA and contribute to sedentary behavior.