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Death Rates Table

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Death Rate Report for South Dakota by County

All Cancer Sites, 2012-2016

All Races (includes Hispanic), Both Sexes, All Ages

Sorted by Rate
County
 sort alphabetically by name ascending
Met Healthy People Objective of 161.4?
Age-Adjusted Death Rate
deaths per 100,000
(95% Confidence Interval)
 sort by rate ascending
Average Annual Count
 sort by count descending
Recent Trend
Recent 5-Year Trend in Death Rates
(95% Confidence Interval)
 sort by trend descending
South Dakota Yes 160.5 (156.9, 164.1) 1,648 falling falling trend -0.9 (-1.1, -0.7)
United States Yes 161.0 (160.8, 161.1) 590,623 falling falling trend -1.5 (-1.6, -1.5)
McCook County No 240.4 (192.6, 297.5) 19 stable stable trend 0.9 (-0.4, 2.3)
Buffalo County No 234.9 (131.0, 385.1) 3
*
*
Dewey County No 232.0 (172.9, 304.2) 11 stable stable trend -0.6 (-2.1, 1.0)
Shannon County No 231.9 (184.3, 286.8) 18 falling falling trend -2.0 (-3.0, -0.9)
Todd County No 224.0 (170.6, 287.4) 13 stable stable trend -1.1 (-2.5, 0.4)
Bennett County No 210.0 (145.9, 292.8) 7 stable stable trend -0.3 (-2.5, 1.9)
Corson County No 200.4 (139.2, 278.7) 7 stable stable trend -0.2 (-1.7, 1.3)
Hanson County No 194.9 (129.1, 281.4) 6 stable stable trend 0.3 (-1.3, 1.9)
Kingsbury County No 193.7 (151.8, 245.6) 16 stable stable trend -0.5 (-1.6, 0.7)
Jackson County No 193.7 (133.3, 272.8) 7 stable stable trend -1.2 (-3.1, 0.8)
Miner County No 188.7 (125.9, 276.1) 7 stable stable trend 0.4 (-1.4, 2.2)
Fall River County No 185.7 (151.9, 226.7) 24 stable stable trend -0.6 (-1.6, 0.4)
Clay County No 185.0 (151.4, 223.9) 22 stable stable trend -0.6 (-1.8, 0.6)
Codington County No 182.7 (163.1, 204.3) 65 falling falling trend -0.7 (-1.3, -0.1)
Roberts County No 179.6 (148.0, 216.3) 25 stable stable trend -0.9 (-1.9, 0.1)
Minnehaha County No 175.5 (166.6, 184.7) 312 falling falling trend -0.8 (-1.1, -0.4)
Brule County No 174.8 (133.4, 226.3) 13 stable stable trend -0.7 (-2.1, 0.8)
Faulk County No 173.7 (119.1, 250.3) 7 stable stable trend -1.5 (-3.5, 0.6)
Mellette County No 173.0 (103.2, 273.1) 4 stable stable trend -0.2 (-2.3, 1.9)
Gregory County No 171.9 (131.9, 223.4) 14 stable stable trend -0.1 (-1.2, 1.0)
Sanborn County No 170.4 (111.8, 252.2) 6 stable stable trend -1.4 (-3.4, 0.6)
Charles Mix County No 169.3 (138.7, 205.3) 23 stable stable trend -0.4 (-1.8, 1.1)
Brown County No 167.2 (150.9, 184.9) 83 falling falling trend -0.8 (-1.5, -0.2)
Davison County No 167.0 (145.6, 190.9) 48 stable stable trend -0.9 (-1.8, 0.0)
Lyman County No 165.8 (117.5, 228.6) 8 stable stable trend -1.6 (-3.3, 0.1)
Brookings County No 164.7 (144.1, 187.5) 48 stable stable trend -0.4 (-1.1, 0.3)
Douglas County No 164.6 (114.4, 233.0) 9 stable stable trend -0.7 (-2.6, 1.2)
Beadle County No 163.9 (141.8, 188.9) 41 falling falling trend -1.0 (-1.8, -0.2)
Turner County No 163.7 (132.1, 201.4) 20 falling falling trend -1.9 (-3.0, -0.8)
Stanley County Yes 160.5 (106.6, 233.6) 6 falling falling trend -2.4 (-4.1, -0.7)
Spink County Yes 159.9 (125.4, 202.3) 16 stable stable trend -1.3 (-2.6, 0.0)
Hughes County Yes 159.3 (135.6, 186.1) 34 stable stable trend -0.2 (-1.1, 0.8)
Perkins County Yes 159.2 (111.1, 224.9) 8 stable stable trend 0.9 (-1.1, 3.0)
Sully County Yes 157.9 (93.0, 261.0) 4 stable stable trend -1.9 (-4.5, 0.8)
Marshall County Yes 157.5 (117.5, 208.5) 11 stable stable trend 0.4 (-1.0, 1.8)
Meade County Yes 156.3 (136.0, 178.9) 45 falling falling trend -1.0 (-2.0, -0.1)
Moody County Yes 155.9 (119.5, 200.8) 13 stable stable trend 0.2 (-1.0, 1.3)
Pennington County Yes 155.7 (145.9, 166.0) 197 falling falling trend -1.3 (-1.7, -0.9)
Haakon County Yes 155.3 (94.3, 247.1) 5 stable stable trend -1.1 (-3.6, 1.4)
Walworth County Yes 155.1 (120.0, 199.2) 15 falling falling trend -1.8 (-3.3, -0.4)
Butte County Yes 154.3 (126.0, 187.7) 22 stable stable trend -0.6 (-2.2, 0.9)
Hamlin County Yes 151.5 (114.3, 197.8) 12 stable stable trend -0.5 (-1.6, 0.5)
Lawrence County Yes 149.3 (131.2, 169.4) 52 falling falling trend -1.0 (-1.7, -0.3)
Union County Yes 147.7 (123.8, 175.2) 28 falling falling trend -1.6 (-2.5, -0.6)
Tripp County Yes 145.8 (112.5, 187.9) 15 stable stable trend -1.2 (-2.6, 0.2)
Lake County Yes 144.4 (119.6, 173.5) 25 stable stable trend -0.9 (-2.0, 0.1)
Jerauld County Yes 144.2 (94.7, 219.2) 6 stable stable trend 0.5 (-1.4, 2.3)
Yankton County Yes 144.2 (125.6, 164.9) 46 falling falling trend -1.0 (-1.8, -0.2)
Hand County Yes 143.6 (99.9, 203.4) 9 stable stable trend -1.2 (-2.6, 0.3)
Custer County Yes 142.6 (116.2, 175.1) 22 stable stable trend -1.1 (-2.1, 0.0)
Potter County Yes 142.4 (98.1, 208.6) 7 stable stable trend -0.6 (-2.3, 1.1)
Bon Homme County Yes 135.6 (105.7, 172.7) 15 stable stable trend -0.5 (-1.9, 0.9)
Clark County Yes 133.8 (95.8, 185.4) 9 stable stable trend -0.7 (-2.4, 1.1)
Day County Yes 133.4 (100.2, 175.9) 13 falling falling trend -1.3 (-2.5, -0.1)
Aurora County Yes 131.4 (86.3, 195.6) 6 stable stable trend -1.4 (-3.2, 0.5)
Grant County Yes 130.1 (101.4, 165.8) 15 stable stable trend -0.9 (-1.9, 0.1)
McPherson County Yes 128.5 (87.6, 190.3) 7 stable stable trend -1.3 (-3.3, 0.6)
Edmunds County Yes 123.9 (88.4, 172.0) 8 falling falling trend -2.2 (-3.9, -0.6)
Deuel County Yes 121.2 (87.7, 166.1) 9 falling falling trend -1.9 (-3.1, -0.7)
Hutchinson County Yes 119.3 (92.5, 152.8) 17 falling falling trend -1.9 (-3.3, -0.4)
Lincoln County Yes 117.4 (103.4, 132.8) 54 falling falling trend -5.0 (-7.0, -2.9)
Campbell County Yes 113.5 (65.7, 205.4) 3 stable stable trend -1.7 (-3.7, 0.3)
Harding County ***
*
3 or fewer
*
*
Hyde County ***
*
3 or fewer
*
*
Jones County ***
*
3 or fewer
*
*
Ziebach County ***
*
3 or fewer
*
*
Notes:
Created by statecancerprofiles.cancer.gov on 04/02/2020 4:15 pm.

South Dakota County Name Change: please note that Shannon County, SD (FIPS code=46113) was renamed effective May 1, 2015, and the new name is Oglala Lakota County (FIPS Code=46102). Due to the nature of data submissions, we will use the older code/name this year and transition to the new code/name with a future data release.

State Cancer Registries may provide more current or more local data.
Trend
Rising when 95% confidence interval of average annual percent change is above 0.
Stable when 95% confidence interval of average annual percent change includes 0.
Falling when 95% confidence interval of average annual percent change is below 0.

† Death data provided by the National Vital Statistics System public use data file. Death rates calculated by the National Cancer Institute using SEER*Stat. Death rates are age-adjusted to the 2000 US standard population (19 age groups: <1, 1-4, 5-9, ... , 80-84, 85+). The Healthy People 2020 goals are based on rates adjusted using different methods but the differences should be minimal. Population counts for denominators are based on Census populations as modified by NCI.
The 1969-2016 US Population Data File is used with mortality data.
The Average Annual Percent Change (AAPC) is based on the APCs calculated by Joinpoint. Due to data availability issues, the time period used in the calculation of the joinpoint regression model may differ for selected counties.

Healthy People 2020 Objectives provided by the Centers for Disease Control and Prevention.

Health Service Areas are a single county or cluster of contiguous counties which are relatively self-contained with respect to hospital care. For more detailed information, please see Health Service Area information page.
* Data has been suppressed to ensure confidentiality and stability of rate estimates. Counts are suppressed if fewer than 16 records were reported in a specific area-sex-race category. If an average count of 3 is shown, the total number of cases for the time period is 16 or more which exceeds suppression threshold (but is rounded to 3).


Please note that the data comes from different sources. Due to different years of data availability, most of the trends are AAPCs based on APCs but some are APCs calculated in SEER*Stat. Please refer to the source for each graph for additional information.

Interpret Rankings provides insight into interpreting cancer incidence statistics. When the population size for a denominator is small, the rates may be unstable. A rate is unstable when a small change in the numerator (e.g., only one or two additional cases) has a dramatic effect on the calculated rate.

Data for United States does not include Puerto Rico.

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