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Rate/Trend Comparison by Cancer Table

Data Options

Death Rate/Trend Comparison by Cancer, 2016-2020

South Dakota Counties versus United States

All Cancer Sites

All Races, Both Sexes

  Above US Rate Similar to US Rate Below US Rate
Rising
Trend
Priority 1: rising and above

Hanson County
Priority 2: rising and similar

Priority 3: rising and below

Stable
Trend
Priority 4: stable and above

Butte County
Fall River County
McCook County
Mellette County
Todd County
Priority 6: stable and similar

Aurora County
Bennett County
Bon Homme County
Brule County
Charles Mix County
Clark County
Clay County
Corson County
Deuel County
Dewey County
Douglas County
Faulk County
Gregory County
Haakon County
Hamlin County
Hughes County
Jackson County
Kingsbury County
Lyman County
Marshall County
McPherson County
Miner County
Moody County
Perkins County
Potter County
Priority 7: stable and below

Lincoln County
Falling
Trend
Priority 5: falling and above

Meade County
Minnehaha County
Oglala Lakota/Shannon County
Priority 8: falling and similar

Beadle County
Brown County
Codington County
Custer County
Davison County
Day County
Grant County
Hutchinson County
Pennington County
Roberts County
Sanborn County
Spink County
Stanley County
Tripp County
Turner County
Union County
Walworth County
Priority 9: falling and below

Brookings County
Edmunds County
Hand County
Lake County
Lawrence County
Yankton County
Notes:
Created by statecancerprofiles.cancer.gov on 04/26/2024 2:46 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). This website will use Oglala Lakota/Shannon until the next incidence/mortality data release.

Trend2
     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.
Rate Comparison
     Above     when 95% confident the rate is above and Rate Ratio3 > 1.10
     Similar     when unable to conclude above or below with confidence.
     Below     when 95% confident the rate is below and Rate Ratio3 < 0.90

1 Priority indices were created by ordering from rates that are rising and above the comparison rate to rates that are falling and below the comparison rate.
2 Recent trend in death rates is usually an Average Annual Percent Change (AAPC) based on the APCs calculated by Joinpoint Version 4.8.0.0. Due to data availability issues, the time period and/or calculation method used in the calculation of the trends may differ for selected geographic areas.
3 Rate ratio is the county rate divided by the US rate. Previous versions of this table used one-year rates for states and five-year rates for counties. As of June 2018, only five-year rates are used.
Source: 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 US Population Data File is used with mortality data.
Note: 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. Suppression is used to avoid misinterpretation when rates are unstable.

State Cancer Registries may provide more current or more local data. Data presented on the State Cancer Profiles Web Site may differ from statistics reported by the State Cancer Registries (for more information).

Data for the following has been suppressed to ensure confidentiality and stability of rate and trend estimates:
Campbell County, Harding County, Sully County

Trend for the following could not be reliably determined due to small number of deaths per year:
Buffalo County, Hyde County, Jerauld County, Jones County, Ziebach County


Interpret Rankings provides insight into interpreting cancer 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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