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Interpretation of Death Rates Data

Death Rate Report for West Virginia by County

Cervix, 2011-2015

All Races (includes Hispanic), Female, All Ages

Sorted by Name

Explanation of Column Headers

Objective - The objective of 2.2 is from the Healthy People 2020 project done by the Centers for Disease Control and Prevention.

Death Rate (95% Confidence Interval) - The death rate is based upon 100,000 people and is for 5 year(s). Rates are age-adjusted by 5-year age groups to the 2000 U.S. standard million population (the Healthy People 2020 goals are based on rates adjusted using different methods but the differences should be minimal).

Recent Trends - This is an interpretation of the AAPC:

AAPC (95% Confidence Interval) - The Average Annual Percent Change is the change in rate over time. These AAPCs are based upon APCs that were calculated by Joinpoint Regression Program


Other Notes

  • Larger confidence intervals indicate less stability of the data. This is often due to low counts that are not quite low enough to be suppressed.
  • Data is currently being suppressed if there are fewer than 16 counts for the time period.

  • Line by Line Interpretation of the Report


    West Virginia


    United States


    Barbour County


    Berkeley County


    Boone County


    Braxton County


    Brooke County


    Cabell County


    Calhoun County


    Clay County


    Doddridge County


    Fayette County


    Gilmer County


    Grant County


    Greenbrier County


    Hampshire County


    Hancock County


    Hardy County


    Harrison County


    Jackson County


    Jefferson County


    Kanawha County


    Lewis County


    Lincoln County


    Logan County


    Marion County


    Marshall County


    Mason County


    McDowell County


    Mercer County


    Mineral County


    Mingo County


    Monongalia County


    Monroe County


    Morgan County


    Nicholas County


    Ohio County


    Pendleton County


    Pleasants County


    Pocahontas County


    Preston County


    Putnam County


    Raleigh County


    Randolph County


    Ritchie County


    Roane County


    Summers County


    Taylor County


    Tucker County


    Tyler County


    Upshur County


    Wayne County


    Webster County


    Wetzel County


    Wirt County


    Wood County


    Wyoming County




    Notes:
    Created by statecancerprofiles.cancer.gov on 07/21/2019 11:20 am.

    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.