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Suicide Mortality in the United States, 1999-2017 Key findings Data from the National Vital Statistics System, Mortality

Authors:

Abstract

Since 2008, suicide has ranked as the 10th leading cause of death for all ages in the United States (1). In 2016, suicide became the second leading cause of death for ages 10–34 and the fourth leading cause for ages 35–54 (1). Although the Healthy People 2020 target is to reduce suicide rates to 10.2 per 100,000 by 2020 (2), suicide rates have steadily increased in recent years (3,4). This data brief uses final mortality data from the National Vital Statistics System (NVSS) to update trends in suicide mortality from 1999 through 2017 and to describe differences by sex, age group, and urbanization level of the decedent’s county of residence
NCHS Data Brief No. 330 November 2018
U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES
Centers for Disease Control and Prevention
National Center for Health Statistics
Suicide Mortality in the United States, 1999–2017
Holly Hedegaard, M.D., Sally C. Curtin, M.A., and Margaret Warner, Ph.D.
Key findings
Data from the National
Vital Statistics System,
Mortality
From 1999 through 2017,
the age-adjusted suicide rate
increased 33% from 10.5 to
14.0 per 100,000.
Suicide rates were
significantly higher in 2017
compared with 1999 among
females aged 10–14 (1.7 and
0.5, respectively), 15–24 (5.8
and 3.0), 25–44 (7.8 and 5.5),
45–64 (9.7 and 6.0), and 65–74
(6.2 and 4.1).
Suicide rates were
significantly higher in 2017
compared with 1999 among
males aged 10–14 (3.3 and 1.9,
respectively), 15–24 (22.7 and
16.8), 25–44 (27.5 and 21.6),
45–64 (30.1 and 20.8) and
65–74 (26.2 and 24.7).
In 2017, the age-adjusted
suicide rate for the most rural
(noncore) counties was 1.8 times
the rate for the most urban (large
central metro) counties (20.0 and
11.1 per 100,000, respectively).
Since 2008, suicide has ranked as the 10th leading cause of death for all ages
in the United States (1). In 2016, suicide became the second leading cause
of death for ages 10–34 and the fourth leading cause for ages 35–54 (1).
Although the Healthy People 2020 target is to reduce suicide rates to 10.2
per 100,000 by 2020 (2), suicide rates have steadily increased in recent years
(3,4). This data brief uses final mortality data from the National Vital Statistics
System (NVSS) to update trends in suicide mortality from 1999 through 2017
and to describe differences by sex, age group, and urbanization level of the
decedent’s county of residence.
From 1999 through 2017, suicide rates increased for
both males and females, with greater annual percentage
increases occurring after 2006.
From 1999 through 2017, the age-adjusted suicide rate increased 33%
from 10.5 per 100,000 standard population to 14.0 (Figure 1). The rate
0
5
10
15
20
25
Female2
Male1
Total2
2017201520132011200920072005200320011999
Figure 1. Age-adjusted suicide rates, by sex: United States, 1999–2017
¹Stable trend from 1999 through 2006; significant increasing trend from 2006 through 2017, p < 0.001.
²Significant increasing trend from 1999 through 2017 with different rates of change over time, p < 0.001.
NOTES: Suicides are identified using International Classification of Diseases, Tenth Revision underlying cause-of-death codes
U03, X60–X84, and Y87.0. Age-adjusted death rates were calculated using the direct method and the 2000 U.S. standard
population. Access data table for Figure 1 at: https://www.cdc.gov/nchs/data/databriefs/db330_tables-508.pdf#1.
SOURCE: NCHS, National Vital Statistics System, Mortality.
Deaths per 100,000 standard population
NCHS Data Brief No. 330 November 2018
2  ■
increased on average by about 1% per year from 1999 through 2006 and by 2% per year
from 2006 through 2017.
For males, the rate increased 26% from 17.8 in 1999 to 22.4 in 2017. The rate did not
significantly change from 1999 to 2006, then increased on average by about 2% per year
from 2006 through 2017.
For females, the rate increased 53% from 4.0 in 1999 to 6.1 in 2017. The rate increased
on average by 2% per year from 1999 through 2007 and by 3% per year from 2007
through 2017.
Suicide rates for females aged 10–74 were higher in 2017 than in 1999.
Suicide rates for females were highest for those aged 45–64 in both 1999 (6.0 per 100,000)
and 2017 (9.7) (Figure 2).
Suicide rates were significantly higher in 2017 compared with 1999 among females aged
10–14 (1.7 and 0.5, respectively), 15–24 (5.8 and 3.0), 25–44 (7.8 and 5.5), 45–64 (9.7 and
6.0), and 65–74 (6.2 and 4.1).
The suicide rate in 2017 for females aged 75 and over (4.0) was significantly lower than the
rate in 1999 (4.5).
75 and over65–7445–6425–4415–2410–14
1999 2017
Age group (years)
Figure 2. Suicide rates for females, by age group: United States, 1999 and 2017
¹Significantly different from 1999 rate, p < 0.05.
²Significantly higher than rates for all other age groups in 1999, p < 0.05.
³Significantly higher than rates for all other age groups in 2017, p < 0.05.
NOTES: Suicides are identified using International Classification of Diseases, Tenth Revision underlying cause-of-death codes U03, X60–X84, and Y87.0.
Access data table for Figure 2 at: https://www.cdc.gov/nchs/data/databriefs/db330_tables-508.pdf#2.
SOURCE: NCHS, National Vital Statistics System, Mortality.
0
2
4
6
8
10
0.5
11.7
3.0
5.5
26.0
4.1
15.8
17.8
1,39.7
16.2
4.5
14.0
Deaths per 100,000 in specified group
NCHS Data Brief No. 330 November 2018
3  ■
Suicide rates for males aged 10–74 were higher in 2017 than in 1999.
Suicide rates for males were highest for those aged 75 and over in both 1999 (42.4 per
100,000) and 2017 (39.7) (Figure 3).
Suicide rates were significantly higher in 2017 compared with 1999 among males aged
10–14 (3.3 and 1.9, respectively), 15–24 (22.7 and 16.8), 25–44 (27.5 and 21.6), 45–64
(30.1 and 20.8), and 65–74 (26.2 and 24.7).
The suicide rate in 2017 for males aged 75 and over (39.7) was significantly lower than the
rate in 1999 (42.4).
0
10
20
30
40
50
75 and over65–7445–6425–4415–2410–14
1.9
13.3
16.8
21.6 20.8
24.7
122.7
127.5
130.1
126.2
242.4
1,339.7
Figure 3. Suicide rates for males, by age group: United States, 1999 and 2017
¹Significantly different from 1999 rate, p < 0.05.
²Significantly higher than rates for all other age groups in 1999, p < 0.05.
³Significantly higher than rates for all other age groups in 2017, p < 0.05.
NOTES: Suicides are identified using International Classification of Diseases, Tenth Revision underlying cause-of-death codes U03, X60–X84, and Y87.0.
Access data table for Figure 3 at: https://www.cdc.gov/nchs/data/databriefs/db330_tables-508.pdf#3.
SOURCE: NCHS, National Vital Statistics System, Mortality.
Deaths per 100,000 in specified group
1999 2017
Age group (years)
NCHS Data Brief No. 330 November 2018
4  ■
The difference in age-adjusted suicide rates between the most rural and
most urban counties was greater in 2017 than in 1999.
In both 1999 and 2017, the age-adjusted suicide rate increased with decreasing urbanization
(Figure 4). In 1999, the age-adjusted suicide rate for the most rural (noncore) counties (13.1
per 100,000) was 1.4 times the rate for the most urban (large central metro) counties (9.6).
This difference increased in 2017, with the suicide rate for the most rural counties (20.0 per
100,000) increasing to 1.8 times the rate for the most urban counties (11.1).
The age-adjusted suicide rate for the most urban counties in 2017 (11.1 per 100,000) was
16% higher than the rate in 1999 (9.6).
The age-adjusted suicide rate for the most rural counties in 2017 (20.0 per 100,000) was
53% higher than the rate in 1999 (13.1).
0
5
10
15
20
25
20171,2
19991
Figure 4. Age-adjusted suicide rates, by county urbanization level: United States, 1999 and 2017
1Significantly increasing suicide rates by decreasing urbanization, p < 0.05.
2Significantly higher than 1999 rate for each level of urbanization, p < 0.05.
NOTES: Suicides are identified using International Classification of Diseases, Tenth Revision underlying cause-of death codes U03, X60–X84, and Y87.0.
Age-adjusted death rates are calculated using the direct method and the 2000 U.S. standard population. Classification of the decedent’s county of residence is
based on the 2006 NCHS Urban–Rural Classification Scheme for Counties, available from: https://www.cdc.gov/nchs/data/series/sr_02/sr02_154.pdf. Categories
are presented from most urban (large central metro) to least urban (small metro), and from rural (micropolitan) to most rural (noncore). Access data table for
Figure 4 at: https://www.cdc.gov/nchs/data/databriefs/db330_tables-508.pdf#4.
SOURCE: NCHS, National Vital Statistics System, Mortality.
Deaths per 100,000 in specified group
Large fringe metro Medium metroLarge central metro Small metro
Micropolitan Noncore
10.7
12.0 12.2
13.1
11.1
12.5
15.4
18.4
20.0
17.2
9.6 9.3
NCHS Data Brief No. 330 November 2018
5  ■
Summary
This report highlights trends in suicide rates from 1999 through 2017. During this period, the
age-adjusted suicide rate increased 33% from 10.5 per 100,000 in 1999 to 14.0 in 2017. The
average annual percentage increase in rates accelerated from approximately 1% per year from
1999 through 2006 to 2% per year from 2006 through 2017. The age-adjusted rate of suicide
among females increased from 4.0 per 100,000 in 1999 to 6.1 in 2017, while the rate for males
increased from 17.8 to 22.4. Compared with rates in 1999, suicide rates in 2017 were higher for
males and females in all age groups from 10 to 74 years. The differences in age-adjusted suicide
rates between the most rural (noncore) and most urban (large central metro) counties was greater
in 2017 than in 1999. In 1999, the age-adjusted suicide rate for the most rural counties (13.1 per
100,000) was 1.4 times the rate for the most urban counties (9.6), while in 2017, the age-adjusted
suicide rate for the most rural counties (20.0) was 1.8 times the rate for the most urban counties
(11.1). The age-adjusted suicide rate for the most urban counties in 2017 (11.1 per 100,000) was
16% higher than the rate in 1999 (9.6), while the rate for the most rural counties in 2017 (20.0)
was 53% higher than the rate in 1999 (13.1).
NCHS Data Brief No. 330 November 2018
6  ■
Data sources and methods
Data were analyzed using the NVSS multiple cause-of-death mortality files for 1999 through
2017 (5). Suicide deaths were identified using International Classification of Diseases, Tenth
Revision (ICD–10) underlying cause-of-death codes U03, X60–X84, and Y87.0 (6). Age-adjusted
death rates were calculated using the direct method and the 2000 U.S. standard population (7).
Suicides for persons aged 5–9 years were included in the total numbers and age-adjusted rates but
not shown as part of the age-specific numbers or rates, due to the small number of suicide deaths
among this age group.
Urbanization level of the decedent’s county of residence was categorized using the 2006
NCHS Urban–Rural Classification Scheme for Counties (8). Counties were classified into six
urbanization levels based on metropolitan–nonmetropolitan status, population distribution, and
other factors. The six urbanization levels ranged from the most urban (large central metro) to the
most rural (noncore). Metropolitan counties include large central counties, the fringes of large
counties (suburbs), medium counties, and small counties. Nonmetropolitan counties (i.e., rural
counties) include micropolitan statistical areas and noncore areas, including open countryside,
rural towns (populations of less than 2,500), and areas with populations of 2,500–49,999 that are
not part of larger labor market areas (metropolitan areas).
Trends in age-adjusted death rates were evaluated using the Joinpoint Regression Program (9).
The Joinpoint software was used to fit weighted least-squares regression models to the estimated
proportions on the linear scale. The default settings allowed for as few as four observed time
points in the beginning, ending, and middle line segments, including the joinpoints. Using these
settings, a maximum of three joinpoints were searched for using the grid search algorithm and
permutation test, and an overall alpha level of 0.05 (10). Pairwise comparisons of rates in Figures
2–4 were conducted using the z test statistic with an alpha level of 0.05 (7).
About the authors
Holly Hedegaard is with the National Center for Health Statistics, Office of Analysis and
Epidemiology, and Sally C. Curtin and Margaret Warner are with the National Center for Health
Statistics, Division of Vital Statistics.
NCHS Data Brief No. 330 November 2018
7  ■
References
1. Centers for Disease Control and Prevention. CDC WISQARS: Leading causes of death
reports, 1981–2016. Available from: https://webappa.cdc.gov/sasweb/ncipc/leadcause.html.
2. U.S. Department of Health and Human Services. Healthy People 2020: Mental health status
improvement. 2010. Available from: https://www.healthypeople.gov/2020/topics-objectives/topic/
mental-health-and-mental-disorders/objectives.
3. Hedegaard H, Curtin SC, Warner M. Suicide rates in the United States continue to increase.
NCHS Data Brief, no 309. Hyattsville, MD: National Center for Health Statistics. 2018. Available
from: https://www.cdc.gov/nchs/data/databriefs/db309.pdf.
4. Curtin SC, Warner M, Hedegaard H. Increase in suicide in the United States, 1999–2014.
NCHS Data Brief, no 241. Hyattsville, MD: National Center for Health Statistics. 2016. Available
from: https://www.cdc.gov/nchs/data/databriefs/db241.pdf.
5. National Center for Health Statistics. Public-use data files: Mortality multiple cause files.
2017. Available from: https://www.cdc.gov/nchs/data_access/vitalstatsonline.htm#Mortality_
Multiple.
6. World Health Organization. International statistical classification of diseases and related
health problems, tenth revision (ICD–10). 2008 ed. Geneva, Switzerland. 2009.
7. Xu JQ, Murphy SL, Kochanek KD, Bastian B, Arias E. Deaths: Final data for 2016. National
Vital Statistics Reports; vol 67 no 5. Hyattsville, MD: National Center for Health Statistics. 2018.
Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr67/nvsr67_05.pdf.
8. Ingram DD, Franco SJ. NCHS urban–rural classification scheme for counties. National Center
for Health Statistics. Vital Health Stat 2(154). 2012. Available from: https://www.cdc.gov/nchs/
data/series/sr_02/sr02_154.pdf.
9. National Cancer Institute. Joinpoint Regression Program (Version 4.4.0.0) [computer
software]. 2016.
10. Ingram DD, Malec DJ, Makuc DM, Kruszon-Moran D, Gindi RM, Albert M, et al. National
Center for Health Statistics Guidelines for Analysis of Trends. National Center for Health
Statistics. Vital Health Stat 2(179). 2018. Available from: https://www.cdc.gov/nchs/data/series/
sr_02/sr02_179.pdf.
NCHS Data Brief No. 330 November 2018
Keywords: death certificates • intentional self-harm • urban-rural • National
Vital Statistics System
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Suggested citation
Hedegaard H, Curtin SC, Warner M. Suicide
mortality in the United States, 1999–2017.
NCHS Data Brief, no 330. Hyattsville, MD:
National Center for Health Statistics. 2018.
Copyright information
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National Center for Health
Statistics
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Director for Science
Office of Analysis and Epidemiology
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Irma E. Arispe, Ph.D., Acting Associate
Director for Science
Division of Vital Statistics
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Hanyu Ni, Ph.D., M.P.H., Associate Director
for Science
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Importance: Although suicide attempts remain the strongest risk factor for future suicide, little is known about recent trends in the prevalence of and risk factors for suicide attempts and past-year use of services among adults who attempted suicide. Objective: To estimate annual rates of suicide attempts and use of mental health services among US adults from 2008 to 2019. Design, setting, and participants: This US nationally representative cross-sectional study used the National Survey of Drug Use and Health (NSDUH) from 2008 through 2019. Participants included noninstitutionalized US civilians 18 years or older (n = 484 732). The overall annual rates of suicide attempts per 100 000 adults in the general population and national trends from 2008 to 2019 were estimated, with suicide attempts defined as self-reported efforts to kill one's self in the past 12 months. Subgroup analyses were also performed by demographic characteristics and clinical conditions. The trends in past-year use of mental health services among those who reported past-year suicide attempts were then examined. Data were analyzed from October to December 2021. Main outcomes and measures: Rate of suicide attempts from 2008 to 2019. Multivariate-adjusted logistic regression analyses were used to determine whether adjusting for sociodemographic and clinical factors associated with past-year suicide attempts could account for the change within the study period. Results: Of 484 732 survey participants, most were 35 years or younger (69.8%), women (51.8%), and non-Hispanic White individuals (65.7%). From 2008 to 2019, the weighted unadjusted suicide attempt rate per 100 000 population increased from 481.2 to 563.9 (odds ratio [OR], 1.17 [95% CI, 1.01-1.36]; P = .04) and remained significant after controlling for sociodemographic characteristics (adjusted OR [aOR], 1.23 [95% CI, 1.05-1.44]; P = .01). Rates of suicide attempt increased particularly among young adults aged 18 to 25 years (aOR, 1.81 [95% CI, 1.52-2.16]; P < .001), women (aOR, 1.33 [95% CI, 1.09-1.62]; P = .005), those who were unemployed (aOR, 2.22 [95% CI, 1.58-3.12]; P < .001) or never married (aOR, 1.60 [95% CI, 1.31-1.96]; P < .001), and individuals who used substances (aOR, 1.44 [95% CI, 1.19-1.75]; P < .001). In multivariate analyses, the temporal trend of increasing suicide attempts remained significant even after controlling for other significant sociodemographic and clinical factors (aOR, 1.36 [95% CI, 1.16-1.60]; P < .001). Several sociodemographic and clinical subgroups remained independently associated with suicide attempts, especially those with serious psychological distress (aOR, 7.51 [95% CI, 6.49-8.68]; P < .001), major depressive episodes (aOR, 2.90 [95% CI, 2.57-3.27]; P < .001), and alcohol use disorder (aOR, 1.81 [95%CI, 1.61-2.04]; P< .001) as well as individuals who reported being divorced or separated (aOR, 1.65 [95% CI, 1.35-2.02]; P < .001) or being unemployed (aOR, 1.47 [95% CI, 1.27-1.70]; P< .001) and those who identified as Black (aOR, 1.41 [95% CI, 1.24-1.60]; P < .001) or American Indian or Alaska Native, Asian, or Native Hawaiian or Other Pacific Islander (aOR, 1.56 [95% CI, 1.26-1.93]; P < .001). Among adults with a suicide attempt, there was no significant change in the likelihood of receiving past-year mental health or substance-related services. During the study period, 34.8% to 45.5% reported needing services but did not receive them, with no significant change from 2008 to 2019. Conclusions and relevance: Although suicide attempts appear to be increasing, use of services among those who attempted suicide has not increased, suggesting a need to expand service accessibility and/or acceptability, as well as population-wide prevention efforts.
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PurposeSuicidal thoughts and behaviors have been on the rise in the recent years in the US. There is a well-known link between heavy alcohol use/alcohol use disorders (AUDs) and suicidal thoughts and behaviors. An increase in the respective risk relationships is one way in which heavy alcohol use/AUDs may be driving the increase in the rate of suicidal thoughts and behaviors. The objective of the current study was to investigate whether the gender-specific risk relationships between heavy alcohol use/AUDs and past-year (1) suicidal thoughts and (2) attempted suicide have increased over time.Methods Individual-level annual data from the National Survey on Drug Use and Health for the past 12 years (2008–2019) were utilized. Year- and gender-specific multivariate binary logistic regression analyses were first conducted. Gender-stratified random-effects meta-regressions across study years were then conducted.ResultsHeavy alcohol use/AUDs were associated with elevated odds of past-year suicidal thoughts and attempted suicide for both men and women; however, a linear increase in the risk relationships over time was not found.Conclusion Although a temporal increase in the risk relationships of interest was not found, until additional research in this area is conducted, heavy alcohol use/AUDs cannot be ruled out as being a driving force behind the increasing rate of suicidal thoughts and behaviors in the US.
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Many reports present analyses of trends over time based on multiple years of data from National Center for Health Statistics (NCHS) surveys and the National Vital Statistics System (NVSS). Trend analyses of NCHS data involve analytic choices that can lead to different conclusions about the trends. This report discusses issues that should be considered when conducting a time trend analysis using NCHS data and presents guidelines for making trend analysis choices. Trend analysis issues discussed include: choosing the observed time points to include in the analysis, considerations for survey data and vital records data (record level and aggregated), a general approach for conducting trend analyses, assorted other analytic issues, and joinpoint regression. This report provides 12 guidelines for trend analyses, examples of analyses using NCHS survey and vital records data, statistical details for some analysis issues, and SAS and SUDAAN code for specification of joinpoint regression models. Several an lytic choices must be made during the course of a trend analysis, and the choices made can affect the results. This report highlights the strengths and limitations of different choices and presents guidelines for making some of these choices. While this report focuses on time trend analyses, the issues discussed and guidelines presented are applicable to trend analyses involving other ordinal and interval variables.
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Key findings: Data from the National Vital Statistics System, Mortality •From 1999 through 2014, the age-adjusted suicide rate in the United States increased 24%, from 10.5 to 13.0 per 100,000 population, with the pace of increase greater after 2006. •Suicide rates increased from 1999 through 2014 for both males and females and for all ages 10-74. •The percent increase in suicide rates for females was greatest for those aged 10-14, and for males, those aged 45-64. •The most frequent suicide method in 2014 for males involved the use of firearms (55.4%), while poisoning was the most frequent method for females (34.1%). •Percentages of suicides attributable to suffocation increased for both sexes between 1999 and 2014.
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This report details the National Center for Health Statistics' (NCHS) development of the 2006 NCHS Urban-Rural Classification Scheme for Counties and provides some examples of how the scheme can be used to describe differences in health measures by urbanization level. The 2006 NCHS urban-rural classification scheme classifies all U.S. counties and county-equivalents into six levels--four for metropolitan counties and two for nonmetropolitan counties. The Office of Management and Budget's delineation of metropolitan and nonmetropolitan counties forms the foundation of the scheme. The NCHS scheme also uses the cut points of the U.S. Department of Agriculture Rural-Urban Continuum Codes to subdivide the metropolitan counties based on the population of their metropolitan statistical area (MSA): large, for MSA population of 1 million or more; medium, for MSA population of 250,000-999,999; and small, for MSA population below 250,000. Large metro counties were further separated into large central and large fringe metro categories using classification rules developed by NCHS. Nonmetropolitan counties were assigned to two levels based on the Office of Management and Budget's designated micropolitan or noncore status. The 2006 scheme was applied to data from the National Vital Statistics System (NVSS) and the National Health Interview Survey (NHIS) to illustrate its ability to capture health differences by urbanization level. Application of the 2006 NCHS scheme to NVSS and NHIS data shows that it identifies important health disparities among communities, most notably those for inner city and suburban communities. The design of the NCHS Urban-Rural Classification Scheme for Counties makes it particularly well-suited for assessing and monitoring health differences across the full urbanization continuum.
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This report presents final 2016 data on U.S. deaths, death rates, life expectancy, infant mortality, and trends, by selected characteristics such as age, sex, Hispanic origin and race, state of residence, and cause of death.
Suicide rates in the United States continue to increase
  • H Hedegaard
  • S C Curtin
  • M Warner
Hedegaard H, Curtin SC, Warner M. Suicide rates in the United States continue to increase. NCHS Data Brief, no 309. Hyattsville, MD: National Center for Health Statistics. 2018. Available from: https://www.cdc.gov/nchs/data/databriefs/db309.pdf.
Hyattsville, MD: National Center for Health Statistics
NCHS Data Brief, no 241. Hyattsville, MD: National Center for Health Statistics. 2016. Available from: https://www.cdc.gov/nchs/data/databriefs/db241.pdf.