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Death Rates Table

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Death Rate Report for South Dakota by County

Lung & Bronchus, 2011-2015

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

Sorted by Rate
County
 sort alphabetically by name ascending
Met Healthy People Objective of 45.5?
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 42.9 (41.1, 44.7) 436 falling falling trend -2.0 (-3.2, -0.8)
United States Yes 43.4 (43.3, 43.5) 155,959 falling falling trend -3.1 (-3.6, -2.6)
Shannon County No 61.3 (37.9, 92.3) 5
*
*
McCook County No 60.5 (38.8, 91.5) 5
*
*
Butte County No 54.5 (38.5, 75.7) 8 stable stable trend -0.3 (-2.7, 2.2)
Davison County No 51.4 (39.9, 65.5) 14 stable stable trend 0.4 (-1.5, 2.3)
Walworth County No 49.8 (31.9, 76.9) 5 stable stable trend -0.8 (-3.2, 1.8)
Clay County No 49.6 (33.3, 71.4) 6 stable stable trend -2.0 (-4.5, 0.6)
Minnehaha County No 48.3 (43.7, 53.3) 85 falling falling trend -0.7 (-1.2, -0.1)
Codington County No 48.3 (38.2, 60.2) 16 stable stable trend -0.1 (-1.5, 1.4)
Brown County No 48.1 (39.7, 58.0) 24 stable stable trend 0.5 (-0.8, 1.7)
Gregory County No 47.5 (26.0, 82.8) 3 stable stable trend 0.4 (-1.4, 2.3)
Meade County No 47.3 (36.4, 60.4) 13 stable stable trend -0.9 (-2.2, 0.4)
Spink County No 46.4 (29.4, 71.4) 5
*
*
Fall River County Yes 44.8 (30.2, 67.2) 6 falling falling trend -13.2 (-24.2, -0.7)
Pennington County Yes 43.5 (38.5, 49.1) 56 falling falling trend -1.3 (-2.2, -0.5)
Yankton County Yes 43.4 (33.4, 55.6) 13 stable stable trend -0.2 (-1.7, 1.4)
Kingsbury County Yes 43.3 (25.8, 71.1) 4 stable stable trend -0.9 (-3.6, 2.0)
Charles Mix County Yes 43.0 (28.6, 63.0) 6 stable stable trend -1.5 (-4.0, 1.0)
Brule County Yes 42.5 (23.9, 71.6) 3 stable stable trend -1.3 (-3.9, 1.3)
Turner County Yes 42.2 (27.6, 63.0) 5 stable stable trend -0.8 (-3.2, 1.6)
Bon Homme County Yes 41.9 (25.5, 66.1) 4
*
*
Roberts County Yes 41.3 (27.8, 60.0) 6 stable stable trend -0.1 (-1.9, 1.8)
Lawrence County Yes 40.4 (31.1, 51.8) 13 falling falling trend -1.4 (-2.5, -0.2)
Union County Yes 39.8 (27.6, 55.8) 7 stable stable trend -4.5 (-9.0, 0.2)
Beadle County Yes 39.7 (29.2, 53.1) 10 stable stable trend -0.7 (-2.4, 1.0)
Grant County Yes 39.0 (24.3, 61.0) 4 stable stable trend -0.6 (-2.7, 1.5)
Hughes County Yes 35.1 (24.3, 49.2) 7 stable stable trend -1.4 (-3.1, 0.3)
Brookings County Yes 34.3 (25.2, 45.6) 10 stable stable trend -0.4 (-2.4, 1.7)
Lake County Yes 33.4 (22.3, 49.0) 6 stable stable trend -0.4 (-2.5, 1.8)
Lincoln County Yes 32.8 (25.3, 41.9) 14 stable stable trend -0.5 (-2.9, 2.0)
Day County Yes 28.7 (16.2, 50.8) 3 stable stable trend -0.7 (-3.6, 2.3)
Custer County Yes 28.7 (17.4, 47.0) 4 falling falling trend -4.3 (-6.8, -1.7)
Hutchinson County Yes 24.2 (13.6, 42.2) 3 stable stable trend -1.2 (-4.1, 1.8)
Aurora County ***
*
3 or fewer
*
*
Bennett County ***
*
3 or fewer
*
*
Buffalo County ***
*
3 or fewer
*
*
Campbell County ***
*
3 or fewer
*
*
Clark County ***
*
3 or fewer
*
*
Corson County ***
*
3 or fewer
*
*
Deuel County ***
*
3 or fewer
*
*
Dewey County ***
*
3 or fewer
*
*
Douglas County ***
*
3 or fewer
*
*
Edmunds County ***
*
3 or fewer
*
*
Faulk County ***
*
3 or fewer
*
*
Haakon County ***
*
3 or fewer
*
*
Hamlin County ***
*
3 or fewer
*
*
Hand County ***
*
3 or fewer
*
*
Hanson County ***
*
3 or fewer
*
*
Harding County ***
*
3 or fewer
*
*
Hyde County ***
*
3 or fewer
*
*
Jackson County ***
*
3 or fewer
*
*
Jerauld County ***
*
3 or fewer
*
*
Jones County ***
*
3 or fewer
*
*
Lyman County ***
*
3 or fewer
*
*
Marshall County ***
*
3 or fewer
*
*
McPherson County ***
*
3 or fewer
*
*
Mellette County ***
*
3 or fewer
*
*
Miner County ***
*
3 or fewer
*
*
Moody County ***
*
3 or fewer
*
*
Perkins County ***
*
3 or fewer
*
*
Potter County ***
*
3 or fewer
*
*
Sanborn County ***
*
3 or fewer
*
*
Stanley County ***
*
3 or fewer
*
*
Sully County ***
*
3 or fewer
*
*
Todd County ***
*
3 or fewer
*
*
Tripp County ***
*
3 or fewer
*
*
Ziebach County ***
*
3 or fewer
*
*
Notes:
Created by statecancerprofiles.cancer.gov on 03/22/2019 8:02 am.

South Dakota County Name Change: please note that Shannon County, SD (FIPS code=46113) was renamed effective May 1, 2015, Shannon County was renamed Oglala Lakota County (FIPS Code=46102) (effective May 1, 2015). Due to the nature of data submissions, we will use the older code/name this year and transition to the new code/name with our next data release in 2018.

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 rates (cases per 100,000 population per year) are age-adjusted to the 2000 US standard population (19 age groups: <1, 1-4, 5-9, ... , 80-84, 85+). Rates calculated using SEER*Stat. Population counts for denominators are based on Census populations as modified by NCI. The 1969-2015 US Population Data File is used for 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.

* 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 availablility, 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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