Return to Home Mortality > Table

Rate/Trend Comparison by Cancer Table

Data Options

Death Rate/Trend Comparison by Cancer, 2014-2018

South Dakota Counties versus United States

All Cancer Sites

All Races, Female

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

Priority 2: rising and similar

Priority 3: rising and below

Stable
Trend
Priority 4: stable and above

McCook County
Priority 6: stable and similar

Beadle County
Bon Homme County
Brookings County
Brown County
Butte County
Charles Mix County
Clark County
Clay County
Codington County
Davison County
Day County
Dewey County
Douglas County
Edmunds County
Fall River County
Faulk County
Grant County
Gregory County
Hamlin County
Hughes County
Hutchinson County
Kingsbury County
Lake County
Lawrence County
Marshall County
Meade County
Miner County
Moody County
Perkins County
Roberts County
Spink County
Tripp County
Turner County
Union County
Walworth County
Yankton County
Priority 7: stable and below

Falling
Trend
Priority 5: falling and above

Priority 8: falling and similar

Custer County
Minnehaha County
Pennington County
Shannon County
Priority 9: falling and below

Lincoln County
Notes:
Created by statecancerprofiles.cancer.gov on 01/18/2021 5:30 am.

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.

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 1969-2017 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:
Aurora County, Bennett County, Buffalo County, Campbell County, Corson County, Hand County, Harding County, Hyde County, Jackson County, Jerauld County, Jones County, McPherson County, Mellette County, Potter County, Sanborn County, Stanley County, Sully County, Ziebach County

Trend for the following could not be reliably determined due to small number of deaths per year:
Brule County, Deuel County, Haakon County, Hanson County, Lyman County, Todd 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.

Return to Top