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National Center for Health Statistics (US). Health, United States, 2015: With Special Feature on Racial and Ethnic Health Disparities. Hyattsville (MD): National Center for Health Statistics (US); 2016 May.

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Health, United States, 2015: With Special Feature on Racial and Ethnic Health Disparities.

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Chartbook With Special Feature on Racial and Ethnic Health Disparities

Mortality

Life Expectancy at Birth, by Country

In 2013, U.S. males and females ranked 25th and 27th, respectively, in life expectancy compared with males and females in other OECD countries.

Life expectancy is often used to evaluate the overall health of a population (1). Life expectancy at birth for males and females in the United States was compared with those for males and females in 30 other countries. In 2013, life expectancy at birth for males ranged from a low of 71.7 years for Mexico to a high of 80.7 years for Switzerland, with the United States (76.4 years) ranking 25th out of 31 countries. Life expectancy at birth for females ranged from a low of 77.4 years for Mexico to a high of 86.6 years for Japan, with the United States (81.2 years) tied with Poland and ranking 27th out of 31 countries.

Figure 1 consists of two bar charts, one for males and one for females, showing life expectancy at birth, by sex and Organisation for Economic Cooperation and Development country for 2013.

Figure 1

Life expectancy at birth, by sex and country: Organisation for Economic Co-operation and Development (OECD) countries, 2013. Excel and PowerPoint: http://www.cdc.gov/nchs/hus/contents2015.htm#fig01 NOTES: Countries with estimated life expectancies or (more...)

Selected Causes of Death

Between 2004 and 2014, the all-cause, age-adjusted death rate decreased 12% among males and 11% among females.

During 2004–2014, age-adjusted death rates among males declined 29% for stroke, 23% for heart disease, 16% for cancer, and 10% for both diabetes and CLRD, and increased 11% for Alzheimer's disease and 4% for unintentional injuries. Among females, age-adjusted death rates declined 29% for stroke, 27% for heart disease, 21% for diabetes, and 13% for cancer, and increased 15% for Alzheimer's disease and 11% for unintentional injuries. In 2014, age-adjusted death rates among males were higher than among females for heart disease, cancer, CLRD, diabetes, stroke, and unintentional injuries and were lower among males than females for Alzheimer's disease.

Figure 2 consists of two line graphs, one for males and one for females, showing age-adjusted death rates for selected causes of death for all ages, for 2004 through 2014.

Figure 2

Age-adjusted death rates for selected causes of death for all ages, by sex: United States, 2004–2014. Excel and PowerPoint: http://www.cdc.gov/nchs/hus/contents2015.htm#fig02 NOTES: CLRD is chronic lower respiratory diseases. A change in the coding (more...)

Suicide and Homicide

In 2014, suicide rates were higher than homicide rates for males and females of all age groups.

In 2014, suicide was the 10th and homicide the 17th leading cause of death in the U.S. (Table 19) (2). Suicide and homicide deaths impose emotional and financial costs on both families and society, and death rates for these causes differ by age and other factors (37). Suicide rates were higher among males than among females overall (21.1 deaths per 100,000 population compared with 6.0) (Table 30) and within each age group. Among males in 2014, suicide rates were higher among those aged 45–64 and 65 and over than among younger age groups. Among females, suicide rates were highest among those aged 45–64.

Homicide rates were higher among males than among females overall (8.0 deaths per 100,000 population compared with 2.0) (Table 29) and within each age group. Among both males and females, homicide rates were higher among those aged 15–24 and 25–44 than among older age groups in 2014.

Figure 3 consists of two bar charts, one for suicide and one for homicide, showing death rates among persons aged 15 and over, by age and sex, for 2014.

Figure 3

Suicide and homicide death rates among persons aged 15 and over, by age and sex: United States, 2014. Excel and Powerpoint: http://www.cdc.gov/nchs/hus/contents2015.htm#fig03 SOURCE: CDC/NCHS, Health, United States, 2015, Tables 29 and 30. Data from the (more...)

Natality

Teenage Childbearing

Between 2004 and 2014, teenage birth rates declined among all racial and ethnic groups.

Teen childrearing often limits the mother's educational and occupational opportunities, and female babies born to teen mothers are more likely to become teen mothers themselves (8,9). In 2014, teen childbearing fell to a historic low of 24.2 per 1,000 females overall and for each race and Hispanic-origin group (8). Between 2004 and 2014, birth rates declined 50% for teenagers aged 15–17 and 36% for those aged 18–19 (Table 3). Among teenagers aged 15–17, birth rates decreased 44% for non-Hispanic white, 51% for American Indian or Alaska Native, 54% for non-Hispanic black, 59% for Hispanic, and 61% for Asian or Pacific Islander females. Among teenagers aged 18–19, birth rates decreased 32% for non-Hispanic white, 39% for American Indian or Alaska Native, 39% for non-Hispanic black, 47% for Hispanic, and 48% for Asian or Pacific Islander females.

Figure 4 consists of two line graphs showing teenage childbearing rates, one for maternal age 15 through 17 and one for maternal age 18 through 19, by race and Hispanic origin, for 2004 through 2014.

Figure 4

Teenage childbearing, by maternal age and race and Hispanic origin: United States, 2004–2014. Excel and Powerpoint: http://www.cdc.gov/nchs/hus/contents2015.htm#fig04 SOURCE: CDC/NCHS, Health, United States, 2015, Table 3. Data from the National (more...)

Morbidity

Notifiable Disease Rates

Between 2003 and 2013, the rates for pertussis—a vaccine-preventable disease—and Lyme disease increased, while rates for tuberculosis, hepatitis A, hepatitis B, and meningococcal disease decreased.

Public health officials rely on regular, frequent, timely reporting of notifiable diseases to identify at-risk groups, monitor trends, and control the spread of infectious diseases (10,11). Between 2003 and 2013, the incidence rates of four selected diseases decreased—hepatitis A (79% decrease), meningococcal disease (70%), hepatitis B (63%), and tuberculosis (41%)— while the rates of Lyme disease (57%) and pertussis (whooping cough) (126%) increased. The hepatitis B rate declined in the past decade, but reported cases increased 5% from 2012 to 2013.

Figure 5 is a bar chart showing rates for selected notifiable diseases for 2003 and 2013.

Figure 5

Selected notifiable disease rates: United States, 2003 and 2013. Excel and PowerPoint: http://www.cdc.gov/nchs/hus/contents2015.htm#fig05 NOTES: Diseases with consistent definitions and the greatest changes between 2003 and 2013 were selected for display. (more...)

Functional Limitations

Disability

In 2014, disabilities related to cognition and independent living were highest in older age groups; more women than men in each age group reported difficulty doing errands alone.

In 2014, among noninstitutionalized men and women, the prevalence of self-reported serious difficulty concentrating, remembering, or making decisions was higher among older age groups (75–84 and 85 and older) than among younger age groups (18–64 and 65–74) and was similar among men and women in each age group. Difficulty doing errands alone—another disability measure—increased with age. Women in all age groups were more likely than men to report difficulty doing errands alone, ranging from 26% more likely among women aged 18–64 to 72% more likely among women aged 85 and over, compared with men in the same age groups.

Figure 6 consists of two bar charts showing two selected disability measures (one measure is for serious difficulty concentrating, remembering, or making decisions and the other is for difficulty doing errands alone), among adults aged 18 and over, by sex and age, for 2014.

Figure 6

Selected disability indicators among adults aged 18 and over, by sex and age: United States, 2014. Excel and PowerPoint: http://www.cdc.gov/nchs/hus/contents2015.htm#fig06 NOTE: See data table for Figure 6.

Health Risk Factors

Current Cigarette Smoking

During 2004–2014, cigarette smoking prevalence declined among women aged 18–44 and adults aged 45–64.

Smoking is associated with an increased risk of heart disease, stroke, lung and other types of cancers, and chronic lung diseases (12). During 2004–2014, the percentage of adults who smoked cigarettes declined for women aged 18–44 and for both men and women aged 45–64, and remained stable for men and women aged 65 and over. For men aged 18–44, smoking prevalence was stable from 2004–2009 and then declined through 2014. The prevalence of smoking generally was higher for men aged 18–44 and 45–64 than for women in the same age groups (except for 2012). Among adults aged 65 and over, the prevalence for men and women was similar for most years; from 2011–2014, prevalence was higher among men than women. In 2014, 18.8% of men and 14.8% of women aged 18 and over were current cigarette smokers (Table 47).

Figure 7 consists of two line graphs, one for men and one for women, showing current cigarette smoking among adults aged 18 and over, by age groups, for 2004 through 2014.

Figure 7

Current cigarette smoking among adults aged 18 and over, by sex and age: United States, 2004–2014. Excel and PowerPoint: http://www.cdc.gov/nchs/hus/contents2015.htm#fig07 SOURCE: CDC/NCHS, Health, United States, 2015, Table 47. Data from the (more...)

Children and Adolescents With Obesity

Between 1999–2002 and 2011–2014, the prevalence of obesity was stable among children aged 6–11; increased among adolescents aged 12–19; and increased from 1999–2002 to 2003–2006 among those aged 2–5, then declined through 2011–2014.

Excess body weight in children is associated with excess morbidity during childhood and excess body weight in adulthood (1316). Obesity among children is defined as a body mass index at or above the sex-and age-specific 95th percentile of the CDC growth charts (15,16). From 1988–1994 to 1999–2002, obesity increased among children aged 2–19. Among children aged 2–5, the prevalence of obesity increased from 1999–2002 to 2003–2006 and then declined through 2011–2014. Among children aged 6–11, the prevalence of obesity was stable from 1999–2002 to 2011–2014. Between 1999–2002 and 2011–2014, the prevalence of obesity among adolescents aged 12–19 increased 28%.

Figure 8 is a line graph showing children and adolescents aged 2 through 19 years with obesity by age for four time periods: 1999 through 2002, 2003 through 2006, 2007 through 2010, and 2011 through 2014.

Figure 8

Obesity among children and adolescents aged 2–19 years, by age: United States, 1999–2002 through 2011–2014. Excel and PowerPoint: http://www.cdc.gov/nchs/hus/contents2015.htm#fig08 SOURCE: CDC/NCHS, Health, United States, 2015, (more...)

Adults With Overweight and Obesity

Between 1999–2002 and 2011–2014, the prevalence of obesity among men (Grades 1, 2, and 3) and women (Grade 3 only) increased, while the prevalence of overweight but not obese declined among men and remained stable among women aged 20 and over.

Reducing the prevalence of obesity is a public health priority because obesity is correlated with excess morbidity and mortality (1719). In particular, Grade 2 or higher obesity significantly increases the risk of death (20). Between 1999–2002 and 2011–2014, the percentage of adults aged 20 and over with Grades 1, 2, and 3 obesity increased among men. For women, the percentage of Grade 1 obesity and Grade 2 obesity remained stable while Grade 3 obesity increased. Meanwhile, the percentage of men aged 20 and over who were overweight but not obese declined and was stable among women. In 2011–2014, women were almost twice as likely to have Grade 3 obesity as men (8.9% compared with 4.9%).

Figure 9 consists of two area graphs, one for men and one for women, showing the percentage of adults who were overweight but not obese and the percentages with Grade 1, Grade 2, and Grade 3 obesity, among adults aged 20 and over for four time periods: 1999 through 2002, 2003 through 2006, 2007 through 2010, and 2011 through 2014.

Figure 9

Overweight and obesity among adults aged 20 and over, by sex and grade of obesity: United States, 1999–2002 through 2011–2014. Excel and PowerPoint: http://www.cdc.gov/nchs/hus/contents2015.htm#fig09 NOTES: BMI is body mass index. Overweight (more...)

Utilization

Pap Test Use

From 2003 to 2013, Pap test utilization decreased for all age groups; the largest decreases were for women aged 18–20 and 65 and over (age groups no longer recommended for routine testing).

Pap tests have reduced cervical cancer deaths by detecting cases at earlier and more treatable stages (21). Current Pap test recommendations suggest limiting routine testing to women aged 21–65 and vary based on individual risk factors including cervical cancer risk, human papillomavirus (HPV) testing, and screening history (22). From 2003 to 2013, recent Pap testing declined for all age groups. The refined recommendations may help explain the decrease for women aged 21–44 (5%) and 45–64 (9%). The greatest decreases were for age groups for which routine testing is no longer recommended: 18–20 (39%), 65–74 (22%), and 75 and over (45%).

Figure 10 is a line graph showing the percentage of women who had a Pap smear within the past 3 years, by age, for 2003, 2005, 2008, 2010, and 2013.

Figure 10

Pap test utilization within the past 3 years, by age: United States, 2003–2013. Excel and PowerPoint: http://www.cdc.gov/nchs/hus/contents2015.htm#fig10 NOTES: Pap tests (Pap smears) may be used for screening or diagnostic purposes; the purpose (more...)

Emergency Department Use

During 2004–2014, adults aged 18–64 with Medicaid coverage were more likely to have visited an emergency department within the past year than those with private coverage or the uninsured.

Emergency departments (EDs) are critical in the U.S. health care system, providing emergency and after hours care (2325). During 2004–2014, adults aged 18–64 with Medicaid coverage were about twice as likely as those with private coverage or the uninsured to have had an ED visit in the past year. During 2004–2014, the percentage with a recent ED visit was stable for adults with Medicaid; for those with private coverage, the percentage was stable through 2010, then declined through 2014; and for the uninsured, the percentage increased during 2004–2011, then declined through 2014. Although adults with Medicaid were more likely to have an ED visit, only 23.4% of all 2014 ED visits were by those with Medicaid; 15.1% were by the uninsured, and 53.6% were by those with private coverage, reflecting the larger percentage of adults with private coverage.

Figure 11 consists of a line graph and a pie chart. The line graph shows emergency department utilization within the past 12 months among adults aged 18 through 64, by type of health insurance coverage for 2004 through 2014. The pie chart shows the distribution of emergency department visits in 2014 by type of health insurance coverage for adults aged 18 through 64.

Figure 11

Emergency department utilization within the past 12 months among adults aged 18–64, by type of coverage: United States, 2004–2014. Excel and PowerPoint: http://www.cdc.gov/nchs/hus/contents2015.htm#fig11 NOTE: See data table for Figure (more...)

Difficulty Accessing Needed Medical Care or Prescription Drugs Due to Cost

Uninsured adults aged 18–64 are more likely than those with Medicaid or private coverage to report difficulties affording needed medical care and prescription drugs.

Uninsured adults are more likely than the insured to delay or forego needed medical care and prescription drugs due to cost (26,27). During 2004–2014, uninsured adults were 4–5 times more likely than those with private coverage and 1½−3 times more likely than those with Medicaid to report medical care and prescription access problems. For adults with Medicaid, medical care access problems were stable until 2008 and then decreased through 2014. For those with private insurance, medical care access problems increased until 2009 and then declined through 2014. For the uninsured, medical care and prescription access problems increased (until 2010 and 2009, respectively) and then were stable for medical care and decreased through 2014 for access to drugs. Drug access problems were stable in 2004–2014 for those with private insurance but decreased for adults with Medicaid.

Figure 12 consists of two line graphs for adults aged 18 through 64, one showing delay or nonreceipt of needed medical care due to cost in the past 12 months and one showing nonreceipt of needed prescription drugs due to cost in the past 12 months, by type of health insurance coverage, for 2004 through 2014.

Figure 12

Delay or nonreceipt of needed medical care and nonreceipt of needed prescription drugs in the past 12 months due to cost among adults aged 18–64, by health insurance coverage: United States, 2004–2014. Excel and PowerPoint: http://www.cdc.gov/nchs/hus/contents2015.htm#fig12 (more...)

Health Care Resources

Electronic Health Record Systems

In 2013, most physician offices had electronic health record (EHR) systems that record patient history and demographic information (83.0%), order prescriptions (82.6%), send prescriptions to the pharmacy (78.7%), warn of drug interactions and contraindications (73.8%), and order lab tests (68.9%).

EHR systems are thought to make health care delivery more efficient by improving clinician decision-making, care coordination, health care safety, and patient outcomes (2830). In 2013, about 8 of every 10 office-based physicians had computerized components that recorded patient history and demographic information, ordered prescriptions, and sent prescriptions to the pharmacy. About 7 of every 10 had a component that warned of drug interactions and contraindications and ordered lab tests. From 2010 to 2013, the percent increase in the use of these EHR components ranged from 12% for components to record patient history and demographic information to 80% for components to send prescriptions to the pharmacy.

Figure 13 is a bar chart showing the percentage of physician offices with electronic health record system components, by type of component, for 2010 and 2013.

Figure 13

Electronic health record system components in physician offices, by selected component type: United States, 2010 and 2013. Excel and PowerPoint: http://www.cdc.gov/nchs/hus/contents2015.htm#fig13 NOTE: See data table for Figure 13.

Physicians Accepting New Patients

In 2013, physicians in urban large fringe areas (suburbs) were less likely to accept new Medicaid patients than physicians in any other urban–rural category.

Under the ACA, more Americans have health care coverage. In some areas, finding a physician who is accepting new patients may be difficult (3133). Physician acceptance of new patients was examined by urban–rural status, which classifies physicians by the location of their practice (34). In 2013, Medicaid acceptance rates varied across urban–rural categories, with the lowest acceptance rates for physicians in urban large fringe counties (suburbs). Physicians in rural areas (micropolitan and noncore) were more likely to accept new Medicaid patients than those in urban areas. Comparing physicians' acceptance of new private to new Medicaid patients, physicians in urban areas were less likely to accept new Medicaid than new private patients, while acceptance rates for new Medicaid and private patients were similar for physicians in rural areas.

Figure 14 is a bar chart showing office-based physicians accepting new patients, by patient source of payment and urban-rural status, for 2013.

Figure 14

Office-based physicians accepting new patients, by patient source of payment and urban–rural status: United States, 2013. Excel and PowerPoint: http://www.cdc.gov/nchs/hus/contents2015.htm#fig14 NOTE: See data table for Figure 14.

Personal Health Care Expenditures

Major Source of Funds

Between 2004 and 2014, Medicare expenditures for personal health care grew more rapidly than out-of-pocket, private insurance spending, and total Medicaid.

Between 2004 and 2014, total personal health care expenditures grew from $1.6 trillion to $2.6 trillion (Table 95). During 2004–2014, the average annual growth in expenditures was 6.8% for Medicare, 5.4% for Medicaid (federal), 4.6% for Medicaid (state), 5.1% for Medicaid (total), 4.4% for private health insurance, and 2.9% for out-of-pocket spending. In 2014, private health insurance accounted for the highest spending on personal health care at $868.8 billion, followed by Medicare at $580.7 billion. Out-of-pocket spending by individuals reached $329.8 billion in 2014, and spending on Medicaid reached $273.6 billion in federal dollars and $171.3 billion in state dollars for a total of $444.9 billion in Medicaid spending. The remainder was paid for by other types of insurance, payers, and programs (Table 95) (35).

Figure 15 is a line graph showing personal health care expenditures, by source of funds, for 2004 through 2014.

Figure 15

Personal health care expenditures, by source of funds: United States, 2004–2014. Excel and PowerPoint: http://www.cdc.gov/nchs/hus/contents2015.htm#fig15 NOTES: Personal health care expenditures are outlays relating directly to patient care. See (more...)

Health Insurance

Coverage Among Adults Aged 18–64

From 2004 to June 2015, the percentage of adults aged 18–64 with Medicaid coverage increased, the percentage with private coverage decreased through 2012 and then increased through June 2015, and the percentage uninsured increased through 2013 and then declined through June 2015.

Health insurance is a major determinant of access to health care (26). Among adults aged 18–64, the percentage with private coverage declined from 2004 (71.1%) to 2012 (65.1%) and then increased through June 2015 (70.6%) (Table 102) (36). As of June 2015, 8.9 million adults aged 18–64 were covered by private plans obtained through the Health Insurance Marketplace or state-based exchanges (36). The percentage with Medicaid coverage increased from 2004 (6.8%) to June 2015 (12.2%) (Table 104) (37). The percentage of adults aged 18–64 who were uninsured increased from 2004 (19.3%) to 2013 (20.5%) and then declined through June 2015 (12.7%) (Table 105) (36).

Figure 16 is a line graph showing trends in health insurance coverage among adults aged 18 through 64, by type of health insurance coverage, for 2004 through June 2015. Data for 2015 are preliminary.

Figure 16

Health insurance coverage among adults aged 18–64, by type of coverage: United States, 2004–June 2015 (preliminary data). Excel and PowerPoint: http://www.cdc.gov/nchs/hus/contents2015.htm#fig16 NOTE: Preliminary estimates for the first (more...)

Coverage by Medicaid Expansion State

Between 2013 and 2014, the percentage of adults aged 18–64 who were uninsured declined in both Medicaid expansion states (by 28%) and nonexpansion states (by 14%), and the percentage covered by Medicaid increased by 25% in Medicaid expansion states.

Under the ACA (38), states are authorized to expand Medicaid coverage to adults with low incomes, up to and including 138% of the poverty level (39). Between 2013 and 2014, the percentage of adults aged 18–64 who were uninsured declined in both Medicaid expansion states and nonexpansion states; however, the decline in the uninsured percentage was greater for states that expanded their Medicaid programs (28% compared with 14%). The percentage covered by private insurance increased by about 4% in both Medicaid expansion and nonexpansion states. Medicaid coverage increased 25% in states that expanded their programs and was stable in states that did not expand their programs.

Figure 17 consists of two bar charts showing the percentage of adults aged 18 through 64 by type of health insurance coverage in states that expanded Medicaid eligibility compared with states that did not expand Medicaid eligibility, for 2013 and 2014.

Figure 17

Health insurance coverage among adults aged 18–64, by state Medicaid expansion status: United States, 2013 and 2014. Excel and PowerPoint: http://www.cdc.gov/nchs/hus/contents2015.htm#fig17 NOTES: States were classified based on their decision (more...)

Special Feature on Racial and Ethnic Health Disparities: 30 Years After the Heckler Report

Introduction

The 1985 Report of the Secretary's Task Force on Black and Minority Health, released by then Secretary of Health and Human Services Margaret Heckler, documented significant disparities in the burden of illness and mortality experienced by blacks and other minority groups in the U.S. population compared with whites (41). The report laid out an ambitious agenda, including improving minority access to high-quality health care, expanding health promotion and health education outreach activities, increasing the number of minority health care providers, and enhancing federal and state data collection activities to better report on minority health issues. In the 30 years since the Heckler Report, national efforts to improve minority health through outreach, programming, and monitoring have included the formation of the Department of Health and Human Services (HHS) Office of Minority Health in 1986 (42); the annual National Healthcare Quality and Disparities Reports first issued in 2003 (43); the adoption of disparities elimination as an overarching goal of Healthy People 2010 (44); and most recently, an HHS Action Plan to Reduce Racial and Ethnic Health Disparities—a comprehensive federal commitment to reduce and eventually eliminate disparities in health and health care (45).

Race is a social construct influenced by a complex set of factors (46,47). Because of the complexity and difficulty in conceptualizing and defining race, as well as the increasing representation of racial and ethnic subgroups in the United States, racial classification and data collection systems continue to evolve and expand. In 1977, the Office of Management and Budget (OMB) required that all federal data collection efforts collect data on a minimum of four race groups (American Indian or Alaskan Native, black, Asian or Pacific Islander, and white) and did not allow the reporting of more than one race (48). In 1997, in response to growing interest in more detailed reporting on race and ethnicity, OMB mandated data collection for a minimum of five race groups, splitting Asian or Pacific Islander into two categories (Asian, and Native Hawaiian or Other Pacific Islander) (49). In addition, the 1997 standards allowed respondents to report more than one race. A minimum of two categories for data collection on ethnicity, “Hispanic or Latino” and “Not Hispanic or Latino,” were also required under the 1997 OMB standards. Consequently, whereas the Heckler Report primarily documented black–white differences in health and mortality due to data limitations, this Special Feature is able to report on more detailed racial and ethnic groups. For example, Figures 19–21 display trends in infant mortality and low-risk cesarean section deliveries, and the current data on preterm births for five Hispanic-origin groups.

At the time of the Heckler Report, 22.3% of the population were considered racial or ethnic minorities (Table 1). Current Census (2014) estimates identify 37.9% of the population as racial or ethnic minorities (50). In 2014, Hispanic persons, who may be of any race, comprised 17.4% of the U.S. population. Non-Hispanic multiple race persons were 2.0% of the population. For the single race groups, non-Hispanic American Indian or Alaska Native persons were 0.7%, non-Hispanic Asian persons were 5.3%, non-Hispanic black persons were 12.4%, non-Hispanic Native Hawaiian or Other Pacific Islander persons were 0.2%, and non-Hispanic white persons were 62.1% of the U.S. population in 2014 (50).

Understanding the demographic and socioeconomic composition of U.S. racial and ethnic groups is important because these characteristics are associated with health risk factors, disease prevalence, and access to care, which in turn drive health care utilization and expenditures. Non-Hispanic white persons are, on average, older than those in other racial and ethnic groups, with a median age of 43.1 years, and Hispanic individuals are the youngest, with a median age of 28.5 years in 2014 (50). About one-quarter of black only persons (26.2%) and Hispanic persons (23.6%) lived in poverty compared with 10.1% of non-Hispanic white only persons and 12.0% of Asian only persons in 2014 (51). Non-Hispanic black only children and Hispanic children were particularly likely to live in poverty (37.3% and 31.9%, respectively, in 2014) (52). However, Hispanic individuals are often found to have quite favorable health and mortality patterns in comparison with non-Hispanic white persons and particularly with non-Hispanic black persons, despite having a disadvantaged socioeconomic profile—a pattern termed the epidemiologic paradox (53).

HHS defines a racial or ethnic health disparity as “a particular type of health difference that is closely linked with social, economic, and/or environmental disadvantage. Health disparities adversely affect groups of people who have systematically experienced greater obstacles to health based on their racial or ethnic group” (54). There are many different ways to measure racial and ethnic differences in health and mortality, which can lead to different conclusions (5558). This Special Feature on Racial and Ethnic Health Disparities (Special Feature) uses the maximal rate difference, one of three overall measures used in Healthy People 2020 to measure differences among groups of people (see Technical Notes). The maximal rate difference is an overall measure of health disparities calculated as the absolute difference between the highest and lowest group rates in the population for a given characteristic (59). The identification of groups that experience the highest and lowest rates in this Special Feature was based on observed rates and was not tested for a statistically significant difference against other rates. Ties in highest or lowest rates were resolved by examining decimal places. With respect to changes in health disparities over time, tracking the maximal rate difference over time enables one to determine whether the absolute difference between the highest and lowest group rates is increasing, decreasing, or stable.

The Special Feature charts that follow provide detailed comparisons of key measures of mortality, natality, health conditions, health behaviors, and health care access and utilization, by race, race and ethnicity, or by detailed Hispanic origin, depending on data availability. A majority of the 10 graphs in this year's Special Feature present trends in health from 1999–2014. Results indicate that trends in health were generally positive for the overall population and several graphs illustrate success in narrowing gaps in health by racial and ethnic group. Differences in life expectancy, infant mortality, cigarette smoking among women, influenza vaccinations among those aged 65 and over, and health insurance coverage narrowed among the racial and ethnic groups. For example, the absolute difference in infant mortality rates between infants born to non-Hispanic black mothers (highest rate) and infants born to non-Hispanic Asian or Pacific Islander mothers (lowest rate) narrowed between 1999–2014. Differences by racial and ethnic group in the prevalence of high blood pressure and smoking among adult men remained stable throughout the study period, with non-Hispanic black adults more likely to have high blood pressure than adults in other racial and ethnic groups throughout the period, and non-Hispanic black and non-Hispanic white males more likely to be current smokers than Hispanic and non-Hispanic Asian men. For low-risk cesarean sections, influenza vaccinations among adults aged 18–64, and unmet dental care needs, the gap widened among the racial and ethnic groups between 1999–2014.

Despite improvements over time in many of the health measures presented in this Special Feature, disparities by race and ethnicity were found in the most recent year for all 10 measures, indicating that although progress has been made in the 30 years since the Heckler Report, elimination of disparities in health and access to health care has yet to be achieved.

Life Expectancy at Birth

In 2014, life expectancy was longer for Hispanic men and women than for non-Hispanic white or non-Hispanic black men and women.

Life expectancy is a measure often used to gauge the overall health of a population. Life expectancy at birth represents the average number of years that a group of infants would live if the group were to experience the age-specific death rates present in the year of birth. Differences in life expectancy among various demographic subpopulations, including racial and ethnic groups, may reflect subpopulation differences in a range of factors such as socioeconomic status, access to medical care, and the prevalence of specific risk factors in a particular subpopulation (60,61).

During 1980–2014, life expectancy at birth in the United States increased from 70.0 to 76.4 years for males and from 77.4 to 81.2 years for females (Table 15, and data table for Figure 18). During this period, life expectancy at birth for males and females was longest for white persons and shortest for black persons. For both males and females, racial differences in life expectancy at birth narrowed, but persisted during 1980–2014. Life expectancy at birth was 6.9 years longer for white males than for black males in 1980, and this difference narrowed to 4.2 years in 2014. In 1980, life expectancy at birth was 5.6 years longer for white females than for black females, and this difference narrowed to 3.0 years in 2014.

In 2014, Hispanic males and females had the longest life expectancy at birth, and non-Hispanic black males and females had the shortest. In 2014, life expectancy at birth was 7.2 years longer for Hispanic males than for non-Hispanic black males and 5.9 years longer for Hispanic females than for non-Hispanic black females.

Figure 18 consists of a line graph showing life expectancy at birth by sex and race for 1980 through 2014 and a bar chart showing life expectancy at birth by sex, race, and Hispanic origin for 2014.

Figure 18

Life expectancy at birth, by sex, race and Hispanic origin: United States, 1980–2014. Excel and PowerPoint: http://www.cdc.gov/nchs/hus/contents2015.htm#fig18 NOTES: Life expectancy data by Hispanic origin were available starting in 2006 and were (more...)

Infant Mortality

During 1999–2013, infant mortality rates were highest among infants born to non-Hispanic black women (11.11 infant deaths per 1,000 live births in 2013).

Infant mortality, the death of a baby before his or her first birthday, is an important indicator of the health and wellbeing of a country. It not only measures the risk of infant death but it is used as an indicator of maternal health, community health status, and availability of quality health services and medical technology (62,63).

The infant mortality rate in the United States decreased from 7.04 infant deaths per 1,000 live births in 1999 to 6.75 in 2007, and then decreased at a faster rate to 5.96 in 2013. Trends in infant mortality rates during 1999–2013 varied among the five racial and ethnic groups. During 1999–2013, infants born to non-Hispanic black mothers experienced the highest rates of infant mortality (11.11 in 2013) and infants born to non-Hispanic Asian or Pacific Islander mothers experienced the lowest rates (3.90 in 2013). The difference between the highest and lowest infant mortality rates among the five racial and ethnic groups was stable from 1999 to 2006 and then narrowed from 2006 to 2013. The difference between the highest (non-Hispanic black) and lowest (non-Hispanic Asian or Pacific Islander) infant mortality rates was 9.41 deaths per 1,000 live births in 1999, compared with 7.21 in 2013.

For infants born to Hispanic mothers, the infant mortality rate remained stable during 1999–2008 (5.71 infant deaths per 1,000 live births in 1999) and then decreased to 5.00 in 2013. During 1999–2013, the infant mortality rate for Hispanic infants varied by the mother's Hispanic-origin group. Throughout this period, infants born to Puerto Rican mothers experienced the highest mortality rates. In all years except 2009, infants born to Cuban mothers and those born to Central and South American mothers experienced the lowest mortality rates at alternate times throughout 1999–2013. The difference between the highest (Puerto Rican) and lowest (Cuban) infant mortality rates among Hispanic-origin groups narrowed from 3.71 deaths per 1,000 live births in 1999 to 2.88 in 2013. During 1999–2013, the difference in infant mortality rates was narrower for mothers in the Hispanic-origin groups than for mothers in the five racial and ethnic groups.

Preterm Births

In 2014, non-Hispanic black mothers had the highest percentage of preterm births of the five racial and ethnic groups, and Puerto Rican mothers had the highest percentage of preterm births of the five Hispanic-origin groups.

An infant's gestational age is an important predictor of his or her survival and subsequent health (6470). Preterm birth prior to 37 weeks gestation affects infant mortality rates and racial and ethnic disparities in infant mortality (Figure 19) (71). The degree of prematurity matters—infants born prior to 32 weeks gestation are at greatest risk of death during infancy, with the risk of infant death decreasing as gestational age increases (72).

Figure 19 consists of two line graphs, one for race and Hispanic origin of mother and one for detailed Hispanic origin of mother, showing infant mortality rates, for 1999 through 2013.

Figure 19

Infant mortality rates, by race and Hispanic origin and detailed Hispanic origin of mother: United States, 1999–2013. Excel and PowerPoint: http://www.cdc.gov/nchs/hus/contents2015.htm#fig19 NOTES: Highest and lowest rates are based on observed (more...)

In 2014, 7.7% of singleton births occurred before 37 weeks of gestation; 5.7% at 34–36 weeks; 0.8% at 32–33 weeks gestation; and 1.2% before 32 weeks (data table for Figure 20). In 2014, among the five racial and ethnic groups, non-Hispanic black women had the highest percentage of singleton births before 37 weeks (11.1%) and non-Hispanic Asian or Pacific Islander women had the lowest percentage (6.8%). Non-Hispanic black women also had the highest percentage of singleton preterm births at each preterm gestational age. The difference between the highest (non-Hispanic black) and lowest (non-Hispanic Asian or Pacific Islander) percentages of singleton preterm births among the five racial and ethnic groups was 4.3 percentage points (before 37 weeks), 2.0 percentage points (34–36 weeks), 0.6 percentage points (32–33 weeks), and 1.7 percentage points (before 32 weeks).

Among Hispanic-origin groups in 2014, Puerto Rican mothers had the highest percentage of singleton births before 37 weeks (9.1%) and Cuban mothers had the lowest percentage (7.2%). The difference between the highest (Puerto Rican) and lowest (Cuban) percentages of singleton preterm births among the Hispanic-origin groups was 1.9 percentage points (before 37 weeks) and 1.3 percentage points (34–36 weeks). Central and South American mothers had the lowest percentage of singleton births before 34 weeks. For preterm births before 34 weeks, the difference between the highest (Puerto Rican) and lowest (Central and South American) percentages was 0.2 percentage points (32–33 weeks) and 0.6 percentage points (before 32 weeks).

Figure 20 consists of two bar charts, one for race and Hispanic origin of mother and one for detailed Hispanic origin of mother, showing preterm births, by gestational age, for 2014.

Figure 20

Preterm births, by gestational age and race and Hispanic origin and detailed Hispanic origin of mother: United States, 2014. Excel and PowerPoint: http://www.cdc.gov/nchs/hus/contents2015.htm#fig20 NOTES: Preterm births are based on the obstetric estimate (more...)

Low-risk Births Delivered by Cesarean Section

During 1999–2014 non-Hispanic black mothers experienced the highest percentage of low-risk cesarean deliveries among the five racial and ethnic groups (29.9% in 2014); Cuban mothers experienced the highest percentage of low-risk cesarean deliveries among the five Hispanic-origin groups (41.4% in 2014).

Cesarean deliveries comprise approximately one-third of all births in the United States (32.2% in 2014) and can place mothers and infants at increased risk for poor health outcomes (74). Over the past decade, professional medical groups have attempted to reduce low-risk cesarean deliveries defined as cesarean deliveries among full term (37 or more completed weeks of gestation), singleton, vertex (head first) births to women giving birth for the first time (75,76).

The percentage of low-risk births that were delivered by cesarean section increased from 19.5% to 26.6% during 1999–2005, stabilized during 2005–2009, and then decreased to 26.0% in 2014 (data table for Figure 21). Throughout the period 1999–2014, non-Hispanic black mothers experienced the highest percentage of low-risk cesarean deliveries (29.9% in 2014) among the five racial and ethnic groups, while non-Hispanic American Indian or Alaska Native mothers experienced the lowest percentage (21.5% in 2014). The difference between the highest (non-Hispanic black) and lowest (non-Hispanic American Indian or Alaska Native) percentages widened from 4.8 percentage points in 1999 to 8.4 percentage points in 2014.

Among Hispanic mothers, the percentage of low-risk births that were delivered by cesarean section increased from 18.7% to 24.6% during 1999–2004, increased at a slower rate from 2004–2009, and then remained stable during 2009–2014 (data table for Figure 21). Throughout the period 1999–2014 Cuban mothers experienced the highest percentage of low-risk cesarean deliveries (41.4% in 2014), while Mexican mothers experienced the lowest percentage (24.1% in 2014). Among Hispanic-origin groups, the difference between the highest and lowest percentages of low-risk cesarean deliveries was stable during 1999–2002, widened sharply during 2002–2006, and then narrowed during 2006–2014. The difference between the highest (Cuban) and lowest (Mexican) percentages was 11.7 percentage points in 1999, 21.5 percentage points in 2006, and 17.3 percentage points in 2014.

Figure 21 consists of two line graphs, one for race and Hispanic origin of mother and one for detailed Hispanic origin of mother, showing the percentage of low-risk births delivered by cesarean section, for 1999 through 2014.

Figure 21

Low-risk births delivered by cesarean section, by race and Hispanic origin and detailed Hispanic origin of mother: United States, 1999–2014. Excel and PowerPoint: http://www.cdc.gov/nchs/hus/contents2015.htm#fig21 NOTES: The term low-risk cesarean (more...)

Children and Adolescents With Obesity

In 2011–2014 for children and adolescents aged 2–19 years, Hispanic children and adolescents had the highest prevalence of obesity and non-Hispanic Asian children had the lowest prevalence.

Childhood obesity is a serious public health challenge in the United States and many other industrialized nations in the world (Figure 8) (19,77,78). Excess body weight in children is associated with excess morbidity in childhood and excess body weight in adulthood (13,14). Obesity among children and adolescents is defined as a body mass index at or above the sex-and age-specific 95th percentile of the CDC growth charts (15). Between 1999–2000 and 2013–2014, the percentage of children and adolescents aged 2–19 with obesity increased from 13.9% to 17.2% (79). However, among youth aged 2–19, the prevalence of obesity did not change from 2003–2004 through 2013–2014 (79).

In 2011–2014 for children and adolescents aged 2–19, the percentage with obesity was highest for Hispanic children and adolescents and lowest for non-Hispanic Asian children and adolescents. For those aged 2–19, the difference between the highest (Hispanic) and lowest (non-Hispanic Asian) percentages was 13.3 percentage points.

For children aged 2–5, the percentage with obesity was highest for Hispanic children and lowest for non-Hispanic white children. (The estimate for non-Hispanic Asian children aged 2–5 was not stable and is not shown.) The difference between the highest (Hispanic) and lowest (non-Hispanic white) percentages was 10.4 percentage points for children aged 2–5. For children aged 6–11, the percentage with obesity was highest for Hispanic children and lowest for non-Hispanic Asian children. For children aged 6–11, the difference between the highest (Hispanic) and lowest (non-Hispanic Asian) percentages was 15.2 percentage points.

In 2011–2014 for adolescents aged 12–19, the percentage with obesity was highest for Hispanic adolescents and lowest for non-Hispanic Asian adolescents. The difference between the highest (Hispanic) and lowest (non-Hispanic Asian) percentages was 13.4 percentage points for adolescents aged 12–19 years.

Figure 22 is a bar chart showing children and adolescents aged 2 through 19 years with obesity, by age and race and Hispanic origin, for 2011 through 2014.

Figure 22

Obesity among children and adolescents aged 2–19 years, by age and race and Hispanic origin: United States, 2011–2014. Excel and PowerPoint: http://www.cdc.gov/nchs/hus/contents2015.htm#fig22

Hypertension

In 2011–2014, non-Hispanic black men and women were the most likely to have hypertension compared with adults in the other racial and ethnic groups.

Hypertension is an important risk factor for cardiovascular disease, stroke, kidney failure, and other health conditions (80,81). In 2011–2014, 84.1% of adults with hypertension were aware of their status, and 76.1% were taking medication to lower their blood pressure (82). Despite improvement in increasing the awareness, treatment, and control of hypertension, diagnosis and treatment of hypertension among minority groups remains a challenge (83).

Hypertension is defined as reporting taking antihypertensive medication and/or having a measured systolic blood pressure of at least 140 mm Hg or a measured diastolic blood pressure of at least 90 mm Hg. The age-adjusted percentage of adults aged 20 and over with hypertension was stable during 1999–2014 (30.8% in 2013–2014) (data table for Figure 23). During 1999–2014, non-Hispanic black adults had the highest percentage with hypertension among the three racial and ethnic groups (42.7%, age-adjusted in 2013–2014), while with the exception of 1999–2000, adults of Mexican origin had the lowest percentage with hypertension (28.8%, age-adjusted in 2013–2014). The difference between the highest and lowest age-adjusted percentages of adults with hypertension among the three racial and ethnic groups was stable during 1999–2014; in 2013–2014, the difference between the highest (non-Hispanic black) and lowest (Mexican-origin) percentages was 13.9 percentage points.

In 2011–2014, the age-adjusted percentage of adult men and women with hypertension was similar (31.0% and 29.7%, respectively, data table for Figure 23). The difference between the highest (non-Hispanic black) and lowest (Hispanic) age-adjusted percentages of men with hypertension among the four racial and ethnic groups was 14.7 percentage points; for women, the difference between the highest (non-Hispanic black) and lowest (non-Hispanic Asian) was 19.0 percentage points in 2011–2014.

Figure 23 consists of a line graph for both sexes combined showing hypertension among adults aged 20 and over, by race and Hispanic origin, for 1999 to 2000 through 2013 to 2014, and a bar chart for men and women showing hypertension among adults aged 20 and over, by race and Hispanic origin, for 2011 through 2014.

Figure 23

Hypertension among adults aged 20 and over, by sex and race and Hispanic origin: United States, 1999–2000 through 2013–2014. Excel and PowerPoint: http://www.cdc.gov/nchs/hus/contents2015.htm#fig23 NOTES: Estimates are age-adjusted. Hypertension (more...)

Current Cigarette Smoking

During 1999–2014, differences in cigarette smoking between racial and ethnic groups were larger for women than for men.

Smoking causes more than 480,000 deaths each year, accounting for about one in five deaths in the United States (84). Smokers are more likely to develop heart disease, stroke, and cancer. Smoking also increases the risk for diabetes, cataracts, rheumatoid arthritis, and stillbirth (85).

During 1999–2014, the age-adjusted percentage of adults aged 18 and over who were current cigarette smokers decreased from 25.2% to 19.0% for men and from 21.6% to 15.1% for women (data table for Figure 24). Within each of the four racial and ethnic groups, men were more likely to be current cigarette smokers than women.

In 2014 for men, the age-adjusted percentage of current cigarette smokers was highest for non-Hispanic black men (22.0%) and lowest for Hispanic men (13.8%). The difference between the highest and lowest age-adjusted percentages of current cigarette smokers among the four racial and ethnic groups remained stable during 1999–2014 because levels for men in all racial and ethnic groups declined similarly during this period. The difference between the highest (non-Hispanic black) and lowest (Hispanic) percentages for men was 8.2 percentage points in 2014.

For women, non-Hispanic white women consistently had the highest age-adjusted percentage of current cigarette smokers among the four racial and ethnic groups throughout 1999–2014 (18.3% in 2014), while non-Hispanic Asian women had the lowest age-adjusted percentage (5.1% in 2014). For women, the difference between the highest (non-Hispanic white) and lowest (non-Hispanic Asian) percentages narrowed from 17.5 percentage points in 1999 to 13.2 in 2014. During 1999–2014, racial and ethnic differences in cigarette smoking prevalence were larger for women than for men.

Figure 24 consists of two line graphs, one for men and one for women, showing current cigarette smoking among adults aged 18 and over, by race and Hispanic origin, for 1999 through 2014.

Figure 24

Current cigarette smoking among adults aged 18 and over, by sex and race and Hispanic origin: United States, 1999–2014. Excel and PowerPoint: http://www.cdc.gov/nchs/hus/contents2015.htm#fig24 NOTES: Estimates are age-adjusted. Three-year average (more...)

Influenza Vaccination

During 1999–2014, influenza vaccination was highest for those aged 65 and over and lowest for those aged 18–64, for all racial and ethnic groups.

Influenza is a serious illness that can lead to hospitalization and sometimes death. Influenza vaccination is especially important for people who are at risk of getting seriously ill from influenza, including those with chronic conditions, older adults, and young children.

The percentage of adults aged 18–64 who received an influenza vaccination in the past 12 months remained stable during 1999–2006 and then increased to 35.8% in 2014 (data table for Figure 25). This pattern was present for all racial and ethnic groups. Decreases in influenza vaccination coverage in 2005 were related to a vaccine shortage (86). For those aged 18–64, no racial and ethnic group was consistently the most likely to receive influenza vaccination during 1999–2014. In 2014, non-Hispanic Asian adults had the highest percentage for influenza vaccination receipt (41.3%) and Hispanic adults had the lowest percentage (27.9%). For adults aged 18–64, the difference between the highest and lowest percentages of adults receiving an influenza vaccination among the four racial and ethnic groups widened from 6.9 percentage points in 1999 (non-Hispanic white compared with Hispanic) to 13.4 in 2014 (non-Hispanic Asian compared with Hispanic).

For adults aged 65 and over, the percentage who received an influenza vaccination in the past 12 months increased from 65.7% to 70.1% during 1999–2014. During this period, trends in influenza vaccination coverage varied by racial and ethnic group, and no racial and ethnic group was consistently the most or least likely to receive influenza vaccination. In 2014, non-Hispanic Asian adults had the highest percentage for receipt of influenza vaccination (72.7%) and non-Hispanic black adults had the lowest (57.4%). For adults age 65 and over, the difference between the highest (non-Hispanic Asian) and lowest (non-Hispanic black) percentages of older adults receiving an influenza vaccination among the four racial and ethnic groups was stable during 1999–2003 and then narrowed to 15.3 percentage points in 2014.

Figure 25 consists of two line graphs, one for adults aged 18 through 64 and one for those aged 65 and over, showing influenza vaccination, by race and Hispanic origin, for 1999 through 2014.

Figure 25

Influenza vaccination among adults aged 18 and over, by age and race and Hispanic origin: United States, 1999–2014. Excel and PowerPoint: http://www.cdc.gov/nchs/hus/contents2015.htm#fig25 NOTES: Three-year average annual estimates for the American (more...)

Health Insurance Coverage

During 1999 through the first 6 months of 2015 among adults aged 18–64, lack of health insurance coverage was highest among Hispanic adults.

Health insurance is a major determinant of access to health care. Children are less likely to be uninsured than adults aged 18–64 because they are more likely to qualify for public coverage, primarily Medicaid and the Children's Health Insurance Program (CHIP) (see data table for Figure 26 for estimates for children) (26,87). Passage of the Affordable Care Act (ACA) in 2010 (38) authorized states to expand Medicaid eligibility (88) and to establish the health insurance marketplace in 2014.

For adults aged 18–64, the percentage without coverage increased from 17.9% to 20.5% during 1999–2013, and then decreased to 12.7% in the first 6 months of 2015 (36). During this period, the trend for lack of coverage varied by racial and ethnic group.

During 1999–June 2015, Hispanic adults aged 18–64 had the highest percentage without coverage (27.2% in the first 6 months of 2015), and non-Hispanic white adults aged 18–64 had the lowest, except in the first 6 months of 2015, when non-Hispanic Asian adults had the lowest percentage without coverage.

The difference between the highest and lowest percentages of adults aged 18–64 without health insurance among the four racial and ethnic groups narrowed from 1999–June 2015. This difference was 24.9 percentage points in 1999 (Hispanic adults compared with non-Hispanic white adults) and 19.9 percentage points in the first 6 months of 2015 (Hispanic adults compared with non-Hispanic Asian adults).

Figure 26 is a line graph showing no health insurance coverage among adults aged 18 through 64, by age, race, and Hispanic origin, for 1999 through June 2015. Data for 2015 are preliminary.

Figure 26

No health insurance coverage among adults aged 18–64, by race and Hispanic origin: United States, 1999–June 2015 (preliminary data). Excel and PowerPoint: http://www.cdc.gov/nchs/hus/contents2015.htm#fig26 NOTES: Preliminary estimates (more...)

Difficulty Accessing Needed Dental Care Due to Cost

During 1999–2014 among adults aged 18–64, nonreceipt of needed dental care due to cost was lowest among non-Hispanic Asian adults.

Oral health is integral to general health and wellbeing, and forgoing needed dental health care can have serious health effects (89). In general, fewer adults have dental coverage than medical coverage, and dental coverage tends to be less comprehensive (9092). In 2012, 44% of dental expenditures among adults aged 18–64 were paid out of pocket, a higher out-of-pocket percentage than for any other type of personal health care expenditure (93).

The percentage of adults aged 18–64 who did not receive needed dental care in the past 12 months due to cost increased from 9.3% to 17.3% during 1999–2010, and then decreased to 12.6% in 2014 (data table for Figure 27).

During 1999–2014, non-Hispanic Asian adults aged 18–64 had the lowest percentage of not receiving needed dental care due to cost (6.3% in 2014) among the four racial and ethnic groups. No racial and ethnic group consistently had the highest percentage of not receiving needed dental care due to cost during 1999–2014. The difference between the highest and lowest percentages of adults not receiving needed dental care due to cost among the four racial and ethnic groups widened during 1999–2010, and then remained stable from 2010–2014 for those aged 18–64. This difference was 5.9 percentage points in 1999 (non-Hispanic black compared with non-Hispanic Asian) and 9.4 percentage points in 2014 (Hispanic compared with non-Hispanic Asian).

Figure 27 is a line graph showing nonreceipt of needed dental care in the past 12 months due to cost among adults aged 18 through 64, by race and Hispanic origin, for 1999 through 2014.

Figure 27

Nonreceipt of needed dental care in the past 12 months due to cost among adults aged 18–64, by race and Hispanic origin: United States, 1999–2014. Excel and PowerPoint: http://www.cdc.gov/nchs/hus/contents2015.htm#fig27 NOTES: Three-year (more...)

Chartbook Data Tables

All 27 chartbook figures have an accompanying data table either in this section or the Trend Table section.

Data table for Figure 6. Selected disability indicators among adults aged 18 and over, by sex and age: United States, 2014

Data table for Figure 11. Distribution of emergency department visits within the past 12 months for adults aged 18–64, by type of coverage: United States, 2014

Data table for Figure 13. Electronic health record system components in physician offices, by selected component type: United States, 2010 and 2013

Data table for Figure 14. Office-based physicians accepting new patients, by patient source of payment and urban–rural status: United States, 2013

Data table for Figure 17. Health insurance coverage among adults aged 18–64, by state Medicaid expansion status: United States, 2013 and 2014

Data table for Figure 18. Life Expectancy at birth, by sex, race and Hispanic origin: United States, 1980–2014

Data table for Figure 19. Infant mortality rates, by race and Hispanic origin of mother: United States, 1999–2013

Data table for Figure 20. Preterm births, by gestational age and race and Hispanic origin and detailed Hispanic origin of mother: United States, 2014

Data table for Figure 21. Low-risk births delivered by cesarean section, by race and Hispanic origin and detailed Hispanic origin of mother: United States, 1999–2014

Data table for Figure 22. Obesity among children and adolescents aged 2–19, by age and race and Hispanic origin: United States, 2011–2014

Data table for Figure 23. Hypertension among adults aged 20 and over, by sex and race and Hispanic origin: United States, 1999–2000 through 2013–2014

Data table for Figure 24. Current cigarette smoking among adults aged 18 and over, by sex and race and Hispanic origin: United States, 1999–2014

Data table for Figure 25. Influenza vaccination among adults aged 18 and over, by age and race and Hispanic origin: United States, 1999–2014

Data table for Figure 26. No health insurance coverage among persons under age 65, by age and race and Hispanic origin: United States, 1999–June 2015 (preliminary data)

Data table for Figure 27. Nonreceipt of needed dental care in the past 12 months due to cost among adults aged 18–64, by race and Hispanic origin: United States, 1999–2014

Technical Notes

Data Sources

Data for the Health, United States, 2015 Chartbook come from many surveys and data systems and cover a broad range of years. Detailed descriptions of the data sources included in the Chartbook are provided in Appendix I. Data Sources. Additional information clarifying and qualifying the data is included in the table notes and in Appendix II. Definitions and Methods.

Data Presentation

Many measures in the Chartbook are shown for people in specific age groups because of the strong effect of age on most health outcomes. Age-adjusted rates and age-adjusted percentages are computed to eliminate differences in observed rates that result from age differences in population composition (see Appendix II, Age adjustment). Age-adjusted rates and age-adjusted percentages are noted as such in the text; rates and percentages without this notation are crude rates and crude percentages. For some charts, data years are combined to increase sample size and the reliability of the estimates. Some charts present time trends, and others focus on differences in estimates among population subgroups for the most recent time point available. Figures 1–17 and the Highlights section generally present trends for the recent 10-year period. For some indicators, a slightly longer or shorter period may be shown due to design or data comparability issues. Trends are generally shown on a linear scale to emphasize absolute differences over time. The time trends for the overall mortality measures are shown on a logarithmic (log) scale to enable measures with large differences in magnitude to be shown on the same chart.

Point estimates and standard errors for Figures 1–17 are available either in the Trend Table and Excel spreadsheet specified in the note below the chart, or in the Chartbook tables section. For the Special Feature on racial and ethnic health disparities (Figures 18–27), data tables with point estimates and standard errors are contained in the Chartbook tables section. These data tables may include additional data that were not graphed because of space considerations.

Reliability of Estimates

Overall estimates generally have relatively small sampling errors, but estimates for certain population subgroups may be based on small numbers and have relatively large sampling errors. Numbers of deaths obtained from the National Vital Statistics System represent complete counts and therefore are not subject to sampling error. They are, however, subject to random variation, which means that the number of events that actually occur in a given year may be considered as one of a large series of possible results that could have arisen under the same circumstances. When the number of events is small and the probability of such an event is small, considerable caution must be observed in interpreting the conditions described by the charts. Estimates that are unreliable because of large sampling errors or small numbers of events have been noted with an asterisk. The criteria used to designate or suppress unreliable estimates are indicated in the notes to the applicable tables or charts.

For NCHS surveys, point estimates and their corresponding variances were calculated using the SUDAAN software package, which takes into consideration the complex survey design (94). Standard errors for other surveys or data sets were computed using the methodology recommended by the programs providing the data, or were provided directly by those programs.

Statistical Testing

Data trends can be described in many ways. For most trend analyses presented in the Chartbook, increases or decreases in the estimates during the entire time period shown are assessed by the weighted least squares regression method in the National Cancer Institute's Joinpoint software (with Grid search and Bayesian Information Criterion (BIC) model selection). The default maximum number of joinpoints based on the number of available data points in the trend was used. Statistically significant changes in the trend were assessed at the 0.05 level. For more information on Joinpoint, see: http://surveillance.cancer.gov/joinpoint. Statistical significance of differences between regression coefficients at the 0.05 level was also taken into account to select a model with the fewest joinpoints or changes in trend. For some trend charts, there were too few observations for Joinpoint analysis. In those cases, either the difference between two points was assessed for statistical significance using z-tests or the statistical testing methods recommended by the data systems were used. Trend analyses using weighted least squares regression for Figures 1–17 were carried out on the log scale so that results provide estimates of percent change. However, as discussed below, trend analyses for figures in the Special Feature were carried out on the linear scale.

For analyses that show two time points, differences between the two points were assessed for statistical significance at the 0.05 level using two-sided significance tests (z-tests) without correction for multiple comparisons. Trend and data tables include point estimates and standard errors for users who would like to perform additional statistical tests.

Terms such as “similar,”“stable,” and“no difference” used in the text indicate that the statistics being compared were not significantly different. Lack of comment regarding the difference between statistics does not necessarily suggest that the difference was tested and found to be not significant. Because statistically significant differences or trends are partly a function of sample size (the larger the sample, the smaller the change that can be detected), they do not necessarily have public health significance (95).

Special Feature on Racial and Ethnic Health Disparities (Figures 18–27)

In general, the starting time period for trend analysis in the Special Feature is 1999. This is the earliest year for which National Health Interview Survey (NHIS) data were available for detailed racial and ethnic groups (see Appendix II, Race). Trend data on race and ethnicity are presented in the greatest detail possible after taking into account the quality of the data, the amount of missing data, and the number of observations. These issues significantly affect the availability of reportable data for certain populations, such as the Native Hawaiian or Other Pacific Islander population and the American Indian or Alaska Native population. Estimates for the Native Hawaiian or Other Pacific Islander population were unstable and are not presented. Three years of data were combined in order to present estimates for the American Indian or Alaska Native population in the data tables that accompany Figures 24–27.

There are various ways to quantify racial and ethnic differences in health and mortality, and different measures of disparity may lead to different conclusions (5558). This Special Feature uses the maximal rate difference, one of three overall measures used in Healthy People 2020, to measure racial and ethnic disparities (59). The maximal rate difference is an overall measure of health disparities calculated as the absolute difference between the highest and lowest group rates in the population for a given characteristic, irrespective of other, intermediate rates (59). A decrease in the maximal rate difference does not capture whether the population health outcome overall is improving; rather it reflects progress toward eliminating disparities. As the absolute difference between the highest and lowest rates decreases toward 0, all the pairwise absolute differences between population subgroups will tend to 0. For determination of the highest and lowest group rates, estimates were ranked from highest to lowest based on the observed value to six decimal places, to avoid ties. Tests of statistical significance against other rates were not conducted. For consistency with the use of the absolute difference to measure disparity, all analyses in the Special Feature are carried out on the linear scale. For each figure in the Special Feature that shows trends (Figures 19, 21, 23–27) the following analyses were carried out:

  1. trend analysis of overall estimates;
  2. trend analysis of estimates for each racial and ethnic group; and
  3. trend analysis of the maximal rate difference.

These trend analyses provide information used to:

  1. describe the trend in overall estimates as increasing, decreasing, or stable, and any changes in trend over the time period;
  2. indicate whether the trend in estimates for different racial and ethnic groups is similar to the overall trend; and
  3. describe the trend in disparity as measured by the maximal difference in rates as increasing, decreasing, or stable and any changes in trend over the time period.

In addition, a one-sided z-test was conducted to test whether the maximal difference in rates was 0 vs. >0 at the most recent time point (59). For figures in the Special Feature that only show estimates at a single time point, the maximal rate difference was calculated for that time point, and a one-sided z-test was conducted to test whether the maximal difference in rates was 0 vs. >0.

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