Description
In this task, you will gather data about the local geographical distribution of health-related factors, study the significance of the data, and present the data in a manner illustrating the state of the selected county’s population health. You will explore the community’s health profile and trends as well as factors influencing the county’s current health status. The information you submit will consist of graphics such as maps, trending graphs, comparative charts, and statistical lists. You will summarize key findings and highlight at least one health factor or condition requiring focused attention. You may examine the attached “CDC Data Brief Example” in the Supporting Documents section to obtain a general idea of what the result of this task will look like.
Please replace all bracketed, highlighted fields with your information.
POPULATION HEALTH DATA BRIEF TEMPLATE
[Your Name, Credentials]
Informatics for Transforming Nursing Care
[Month/Year]
[Name of County and State]A. Sociodemographic Profile
1. Key Findings
[In this section, present the key findings from your data brief.]
[These findings should be presented in a bulleted list.]
[Limit this list to five bullets.]
[This list should be single-spaced.]
[There should be two or fewer lines for each finding.]
[Replace the screenshot below with one of your state, showing the county you are investigating.] ***** This is completed******
2. Introductory paragraph
[Replace this text with a brief introduction (suggested length of 1-2 paragraphs) to this section by identifying the source of the data and a summary of findings from the table in part A3 below.]
3. Sociodemographic Profile Table
[Complete the following table by including the most recent census data for your selected county and for the United States, using the QuickFacts function on the www.census.gov website. After clicking on the link, enter the county and state. This will automatically generate a table of census data for the county.]
[Note: If data are not available for a county or U.S. population characteristic, please indicate this by writing “N/A.”]
****BELOW IS COMPLETED****
Population Characteristics
County
United States
Population Estimates
1,393,452
328,239,523
Population Percent Change
21.6%
6.3%
Percentage of Persons Under the Age of 18
22.0%
22.3%
Percentage of Persons 65 Years and Over
12.3%
16.5%
Percentage of Women
50.9%
50.8%
Percentage White Alone
68.0%
76.3%
Percentage Hispanic Alone
32.7%
18.5%
Percentage of Foreign-Born Persons
21.6%
13.6%
Percentage Language Other Than English Spoken at Home, Percent of Persons Age 5+
36.9%
21.6%
Percentage of Houses with a Computer
94.4%
90.3%
Percentage with High School Graduate or Higher
88.5%
88.0%
Percentage with a Disability, Under Age 65 Years
7.8%
8.6%
Percentage without Health Insurance, Under Age 65 Years
14.8%
9.5%
Percentage in Civilian Labor Force Age 16 Years+
67.1%
63.0%
Percentage of Women in Labor Force Age 16 Years+
62.1%
58.3%
Total Healthcare and Social Assistance Revenue
8,920,887
2,040,441,203
Total Retail Sales Per Capita
$19,125
$13,443
Per Capita Income in the Past 12 Months
$30,456
$34,103
Percentage of Persons in Poverty
12.6%
10.5%
Population Per Square Mile
1,268.5
87.4
B. County Health Trends & Rankings
1. Introductory Paragraph
[Replace this text with a brief introduction (suggested length of 1–2 paragraphs), including why the data for the seven health trends in part B2 were collected and identifying the source of the data and the methods used to gather the data.]
2. Discussion of Health Trends
[Replace this text with a discussion of the use of trend graphs for the seven major health trends of your choice (e.g., adult obesity, alcohol impaired driving deaths, sexually transmitted infections) that you provide below in part B3. This discussion should tell a story about the health of the county and whether the health trend is improving or getting worse. Include the county’s overall health outcomes and length of life ranking.]
3. Health Trends (Visual Graphs)
[Choose seven major health trends for the county being investigated, and for each of your selected health trends, create a trend graph. Use the County Health Rankings site for charts and data. You may use an existing graph at that site, if available, by clicking on the symbol to generate the graphs for the county and copying and pasting it below the heading into the associated health trend section. Use an application that can take a screenshot (e.g., Jing, Snagit, Snipping Tool) to copy the graph. If you would like to select a health trend that does not have an existing graph on the County Health Rankings site, you must create a trend graph for that health trend, using the data provided in your application of choice (e.g., Excel).
Provide the figure number and a descriptive title at the top of the graph and, below the graph, provide a brief caption of the importance of the health trend on the population.
Provide a description that includes enough information so readers know what they are viewing as shown in the following example of “Adult Obesity”:]
Adult Obesity
[Figure 1: Adult Obesity in Saline County, Nebraska]
[Figure 1: Obesity trend over time, comparing the county, state, and national rates. This graph indicates an increase in county adult obesity rates from 2004 to 2014 of 9% as compared to a 6% increase in the state of Nebraska and a 4% increase nationally.]
• health trend 1
• health trend 2
• health trend 3
• health trend 4
• health trend 5
• health trend 6
• health trend 7
4. Health Trends Discussion
[Replace this text with a brief discussion (suggested length 1–2 paragraphs) of how each of the trend graphs tells a story about the health of the county and how the health aspect is improving, worsening, or remaining stable.]
C. Health Factors
1. Health Factors Table
[Complete the following table by including county, state, and national data.]
[Note: If data are not available for a county, state, or U.S. factor influencing health, please indicate this by writing “N/A.”]
Factors Influencing Health
County Data
Top U.S. Performer
State Data
Percentage Adult Smoking
Percentage with Access to Exercise Opportunities
Percentage Excessive Drinking
Primary Care Physicians (Ratio of Population to 1 Physician)
Percentage with High School Graduation
Percentage with Some College
Percentage with Unemployment
Percentage of Children in Single-Parent Households
Social Associations (Number of Associations Per 10,000)
Violent Crime (Number of Violent Crimes Per 100,000)
Injury Deaths (Number of Injury Deaths Per 10,000)
Percentage of Children Eligible for Free or Reduced-Price Lunch
Air Pollution (Average Daily Density of Air Pollutants)
Percentage with Severe Housing Problems
2. Comparison of Data
[Replace this text with an analysis (suggested length 1–2 paragraphs) of background information on health rankings and the purpose of comparing county data to the top performers (data on those who rank highest). The analysis should include successes and challenges for the county when comparing county data to top U.S. performers and state data.]
[Note: Here are some questions you could address in your response: “Is the county significantly different than your overall state data? What about the top performer data? Is the county close to meeting this target?”]
D. Summary
1. Significant Finding(s)
[The seven health trends in part B highlight opportunities for interventions to improve health outcomes in the county. Replace this text with a summary (suggested length of 1–2 paragraphs) of one main health trend from part B that has the potential to be redirected by an action plan to significantly improve community health outcomes in the county. In your summary, you may also include up to three other supplementary health trends that your action plan can leverage to redirect the main health trend.]
2. Action Plan(s)
[Replace this text with the initial steps (suggested length of 1–2 sentences) needed for implementing an action plan to address the main health trend in part D1 and, if supplementary health trends are identified in part D1, any supplementary health trend(s).]
a. Services or Programs
[Replace this text with a discussion (suggested length of 1–2 sentences) of the services or programs that may be introduced in the county to address the identified health trend(s) from part D2.]
b. Raise Public Awareness and Promote Public Engagement
[Replace this text by describing three ways (suggested length of 1–2 paragraphs) that the advanced professional nurse uses technology to integrate informatics into practice to raise public awareness and promote public engagement in the services or programs from part D2a.]
c. Monitoring and Evaluating Action Plan
[Replace this text with a summary (suggested length of 1–2 paragraphs) of how the elements of the proposed action plan from parts D2a and D2b will be monitored, including the data collection tools used to gather, evaluate, and visually represent data for analysis and reporting on progress.]
E. Data Sources & Methods
[Replace this text with information on the sources you used to gather data for your data brief. Discuss how each source was collected and provide links to the sites where the source was found.
Note: For examples of the “Data Sources & Methods” section, see the data briefs on the CDC website or the “CDC Data Brief Example” attachment.]
NCHS Data Brief ■ No. 330 ■ November 2018U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICESCenters for Disease Control and PreventionNational Center for Health StatisticsSuicide Mortality in the United States, 1999–2017Holly Hedegaard, M.D., Sally C. Curtin, M.A., and Margaret Warner, Ph.D.Key findingsData from the NationalVital Statistics System,Mortality● From 1999 through 2017,the age-adjusted suicide rateincreased 33% from 10.5 to14.0 per 100,000.● Suicide rates weresignificantly higher in 2017compared with 1999 amongfemales aged 10–14 (1.7 and0.5, respectively), 15–24 (5.8and 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 weresignificantly higher in 2017compared with 1999 amongmales aged 10–14 (3.3 and 1.9,respectively), 15–24 (22.7 and16.8), 25–44 (27.5 and 21.6),45–64 (30.1 and 20.8) and65–74 (26.2 and 24.7).●● In 2017, the age-adjustedsuicide rate for the most rural(noncore) counties was 1.8 timesthe rate for the most urban (largecentral metro) counties (20.0 and11.1 per 100,000, respectively).Since 2008, suicide has ranked as the 10th leading cause of death for all agesin the United States (1). In 2016, suicide became the second leading causeof 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 10.2per 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 StatisticsSystem (NVSS) to update trends in suicide mortality from 1999 through 2017and to describe differences by sex, age group, and urbanization level of thedecedent’s county of residence.From 1999 through 2017, suicide rates increased forboth males and females, with greater annual percentageincreases 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 rate0510152025Female2Male1Total21999 2001 2003 2005 2007 2009 2011 2013 2015 2017Figure 1. Age-adjusted suicide rates, by sex: United States, 1999–2017¹Stable 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 codesU03, X60–X84, and Y87.0. Age-adjusted death rates were calculated using the direct method and the 2000 U.S. standardpopulation. 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 populationNCHS Data Brief ■ No. 330 ■ November 2018■ 2 ■increased on average by about 1% per year from 1999 through 2006 and by 2% per yearfrom 2006 through 2017.● For males, the rate increased 26% from 17.8 in 1999 to 22.4 in 2017. The rate did notsignificantly change from 1999 to 2006, then increased on average by about 2% per yearfrom 2006 through 2017.● For females, the rate increased 53% from 4.0 in 1999 to 6.1 in 2017. The rate increasedon average by 2% per year from 1999 through 2007 and by 3% per year from 2007through 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 aged10–14 (1.7 and 0.5, respectively), 15–24 (5.8 and 3.0), 25–44 (7.8 and 5.5), 45–64 (9.7 and6.0), 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 therate in 1999 (4.5).10–14 15–24 25–44 45–64 65–74 75 and over1999 2017Age group (years)Figure 2. Suicide rates for females, by age group: United States, 1999 and 2017¹Significantly 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.02468100.511.73.05.526.04.115.817.81,39.716.24.514.0Deaths per 100,000 in specified groupNCHS 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 per100,000) and 2017 (39.7) (Figure 3).● Suicide rates were significantly higher in 2017 compared with 1999 among males aged10–14 (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 therate in 1999 (42.4).0102030405010–14 15–24 25–44 45–64 65–74 75 and over1.913.316.821.6 20.824.7122.7127.5130.1126.2242.41,339.7Figure 3. Suicide rates for males, by age group: United States, 1999 and 2017¹Significantly 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 group1999 2017Age group (years)NCHS Data Brief ■ No. 330 ■ November 2018■ 4 ■The difference in age-adjusted suicide rates between the most rural andmost 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 (13.1per 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 per100,000) 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) was16% 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) was53% higher than the rate in 1999 (13.1).051015202519991 20171,2Figure 4. Age-adjusted suicide rates, by county urbanization level: United States, 1999 and 20171Significantly 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 isbased on the 2006 NCHS Urban–Rural Classification Scheme for Counties, available from: https://www.cdc.gov/nchs/data/series/sr_02/sr02_154.pdf. Categoriesare presented from most urban (large central metro) to least urban (small metro), and from rural (micropolitan) to most rural (noncore). Access data table forFigure 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 groupLarge central metro Large fringe metro Medium metro Small metroMicropolitan Noncore10.712.0 12.213.111.112.515.418.420.017.29.6 9.3NCHS Data Brief ■ No. 330 ■ November 2018■ 5 ■SummaryThis report highlights trends in suicide rates from 1999 through 2017. During this period, theage-adjusted suicide rate increased 33% from 10.5 per 100,000 in 1999 to 14.0 in 2017. Theaverage annual percentage increase in rates accelerated from approximately 1% per year from1999 through 2006 to 2% per year from 2006 through 2017. The age-adjusted rate of suicideamong females increased from 4.0 per 100,000 in 1999 to 6.1 in 2017, while the rate for malesincreased from 17.8 to 22.4. Compared with rates in 1999, suicide rates in 2017 were higher formales and females in all age groups from 10 to 74 years. The differences in age-adjusted suiciderates between the most rural (noncore) and most urban (large central metro) counties was greaterin 2017 than in 1999. In 1999, the age-adjusted suicide rate for the most rural counties (13.1 per100,000) was 1.4 times the rate for the most urban counties (9.6), while in 2017, the age-adjustedsuicide 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) was16% 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 methodsData were analyzed using the NVSS multiple cause-of-death mortality files for 1999 through2017 (5). Suicide deaths were identified using International Classification of Diseases, TenthRevision (ICD–10) underlying cause-of-death codes U03, X60–X84, and Y87.0 (6). Age-adjusteddeath 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 butnot shown as part of the age-specific numbers or rates, due to the small number of suicide deathsamong this age group.Urbanization level of the decedent’s county of residence was categorized using the 2006NCHS Urban–Rural Classification Scheme for Counties (8). Counties were classified into sixurbanization levels based on metropolitan–nonmetropolitan status, population distribution, andother factors. The six urbanization levels ranged from the most urban (large central metro) to themost rural (noncore). Metropolitan counties include large central counties, the fringes of largecounties (suburbs), medium counties, and small counties. Nonmetropolitan counties (i.e., ruralcounties) 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 arenot 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 estimatedproportions on the linear scale. The default settings allowed for as few as four observed timepoints in the beginning, ending, and middle line segments, including the joinpoints. Using thesesettings, a maximum of three joinpoints were searched for using the grid search algorithm andpermutation test, and an overall alpha level of 0.05 (10). Pairwise comparisons of rates in Figures2–4 were conducted using the z test statistic with an alpha level of 0.05 (7).About the authorsHolly Hedegaard is with the National Center for Health Statistics, Office of Analysis andEpidemiology, and Sally C. Curtin and Margaret Warner are with the National Center for HealthStatistics, Division of Vital Statistics.NCHS Data Brief ■ No. 330 ■ November 2018■ 7 ■References
Centers for Disease Control and Prevention. CDC WISQARS: Leading causes of deathreports, 1981–2016. Available from: https://webappa.cdc.gov/sasweb/ncipc/leadcause.html.
U.S. Department of Health and Human Services. Healthy People 2020: Mental health statusimprovement. 2010. Available from: https://www.healthypeople.gov/2020/topics-objectives/topic/mental-health-and-mental-disorders/objectives.
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. Availablefrom: https://www.cdc.gov/nchs/data/databriefs/db309.pdf.
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. Availablefrom: https://www.cdc.gov/nchs/data/databriefs/db241.pdf.
National Center for Health Statistics. Public-use data files: Mortality multiple cause files.
Available from: https://www.cdc.gov/nchs/data_access/vitalstatsonline.htm#Mortality_Multiple.
World Health Organization. International statistical classification of diseases and relatedhealth problems, tenth revision (ICD–10). 2008 ed. Geneva, Switzerland. 2009.
Xu JQ, Murphy SL, Kochanek KD, Bastian B, Arias E. Deaths: Final data for 2016. NationalVital 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.
Ingram DD, Franco SJ. NCHS urban–rural classification scheme for counties. National Centerfor Health Statistics. Vital Health Stat 2(154). 2012. Available from: https://www.cdc.gov/nchs/data/series/sr_02/sr02_154.pdf.
National Cancer Institute. Joinpoint Regression Program (Version 4.4.0.0) [computersoftware]. 2016.
Ingram DD, Malec DJ, Makuc DM, Kruszon-Moran D, Gindi RM, Albert M, et al. NationalCenter for Health Statistics Guidelines for Analysis of Trends. National Center for HealthStatistics. 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 2018Keywords: death certificates • intentional self-harm • urban-rural • NationalVital Statistics SystemFor e-mail updates on NCHS publicationreleases, subscribe online at:https://www.cdc.gov/nchs/govdelivery.htm.For questions or general informationabout NCHS:Tel: 1–800–CDC–INFO (1–800–232–4636)TTY: 1–888–232–6348Internet: https://www.cdc.gov/nchsOnline request form: https://www.cdc.gov/infoISSN 1941–4927 Print ed.ISSN 1941–4935 Online ed.DHHS Publication No. 2019–1209CS298851U.S. DEPARTMENT OFHEALTH & HUMAN SERVICESCenters for Disease Control and PreventionNational Center for Health Statistics3311 Toledo Road, Room 4551, MS P08Hyattsville, MD 20782–2064OFFICIAL BUSINESSPENALTY FOR PRIVATE USE, $300For more NCHS Data Briefs, visit:https://www.cdc.gov/nchs/products/databriefs.htm.FIRST CLASS MAILPOSTAGE & FEES PAIDCDC/NCHSPERMIT NO. G-284Suggested citationHedegaard H, Curtin SC, Warner M. Suicidemortality in the United States, 1999–2017.NCHS Data Brief, no 330. Hyattsville, MD:National Center for Health Statistics. 2018.Copyright informationAll material appearing in this report is inthe public domain and may be reproducedor copied without permission; citation as tosource, however, is appreciated.National Center for HealthStatisticsCharles J. Rothwell, M.S., M.B.A., DirectorJennifer H. Madans, Ph.D., AssociateDirector for ScienceOffice of Analysis and EpidemiologyIrma E. Arispe, Ph.D., DirectorIrma E. Arispe, Ph.D., Acting AssociateDirector for ScienceDivision of Vital StatisticsSteven Schwartz, Ph.D., DirectorHanyu Ni, Ph.D., M.P.H., Associate Directorfor Science
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