Wisconsin Health Trends Progress Reports


2015


2014


2013

Frequently Asked Questions (PDF)

This is an accordion element with a series of buttons that open and close related content panels.

Why do we need a report on health trends in Wisconsin?

Looking at long-term trends on leading health indicators in Wisconsin helps researchers, policy makers and others interested in the health of our state assess where improvements are occurring and what indicators require more attention. Wisconsin may choose to capitalize on already improving trends and invest resources to make them improve at a quicker rate. Conversely (or ideally simultaneously), Wisconsin may choose to focus attention on worsening trends and develop interventions to reverse them.

This report can be used with two other Healthiest State publications in order to provide a better picture of Wisconsin’s health. This report, the Progress Report, helps identify which health indicators have improved or worsened over the past 10 years. The Opportunities to Make Wisconsin the Healthiest State report compares Wisconsin’s health to that of other states and the Report Card explores health disparities by age and subgroup in Wisconsin. Together these reports provide a more complete picture of Wisconsin’s health.

Why are two assessments of each measure presented?

The progress report displays two assessments for each health indicator:

  • an assessment of the health indicator’s trend over the past 10 years and
  • an assessment of the most current year of data compared to where it would be expected to be if the trend line continued through the current year.

We calculated the annual percent change (APC) for each of the 19 health indicators during the past 10 years. An increasing annual percent change indicates a worsening health trend, while a decreasing annual percent change indicates an improving health trend.

indicates Wisconsin’s performance on the health indicator has improved during the past 10 years;
indicates Wisconsin’s performance on the health indicator has been stable during the past 10 years; and
indicates Wisconsin’s performance on the health indicator worsened during the past 10 years.

Using these baseline trends, we determine what the “expected” current rate would be for each indicator if the past 10 year trend continued. We compare this expected rate to the current “observed” rate, to see if it is better or worse. Current progress is determined by comparing the observed rates to the 90% confidence intervals of the expected rates

  •  indicates Wisconsin is performing better than expected for the health indicator;
  •  indicates the current rate is about the same as the expected rate; and
  •   indicates Wisconsin is performing worse than expected for the health indicator

Assessment cut-offs:

How are the disparity graphs helpful?

The disparity graphs highlight important differences in health among subgroups on the same health indicator. The graphs highlight areas where Wisconsin could be doing more to promote the health of all people in the state. For example, smoking rates are much higher for blacks/African Americans compared to whites. Targeted interventions to reduce smoking in the African American population will help reduce this disparity.

How were subgroups chosen to be included in the disparity graphs?

The population subgroups graded in the Progress Report were selected to illustrate a variety of characteristics, or domains, across which health disparities exist. The areas match the disparities highlighted in the Report Card. A total of four domains were selected for inclusion in the Progress Report: gender, education, county urbanization, and race/ethnicity. This list does not cover all disparity domains, such as income, disability, and sexual orientation; because comparable and reliable data on populations defined by those important characteristics were not readily available.

Gender: Although some differences in health between males and females may be due to biological differences between the sexes, other gender differences in health represent inequities – or differences in health that are unfair or unjust.

Education: The domain of education was included in the Progress Report as an illustration of socioeconomic disparities in health.

Urbanization: Where someone lives can have an impact on their health, so the domain of urbanization was included to illustrate differences in health based on the physical and social environment. Urbanization is a measure of the degree of urban, or city-like, character of the county in which a person lives.

Race/ethnicity: Health disparities between racial and ethnic groups exist in Wisconsin and across the entire United States. For this Progress Report, health is assessed for all racial/ethnic groups where data is available.

Although the disparity graphs are broken out by subgroup, these subgroups are not independent of one another. For instance, a higher rate of poverty, lower level of educational attainment and clustering in urban areas are common among minority ethnic/racial groups at the state level. These disparity graphs are a snapshot into the ways in which disparities exist among health factors and outcomes in the state. Developing an understanding of why these disparities occur requires knowledge about existing programs and policies and also health behavior patterns of the different subgroups. We encourage using these graphs as a starting point for further investigation into why disparities exist, why some are worsening, and for finding interventions to reduce and eliminate them.

What are the urbanization classifications used for each county?
The urbanization classifications for each county in Wisconsin are listed here. Wisconsin has one large urban county, 13 suburban/urban counties, 24 non-urban counties, and 34 rural counties.

The four urbanization classifications used in this Progress Report were based on the set of six urbanization classifications outlined by the National Center for Health Statistic (NCHS). The “large central metro” NCHS classification is represented in the report as “large urban”; the NCHS classes of “large fringe metro” and “medium metro” were combined to create the report classification of “suburban/urban”; the NCHS classes of “small metro” and “micropolitan” were combined to create the “non-urban” classification; and the NCHS classification of “non-core” is reflected in the report as “rural.” A detailed description of the classifications can be found in the table below.

Health of Wisconsin Progress Report Urbanization Classification National Center for Health Statistics 2006 Urban-Rural Classification* National Center for Health Statistics Classification Description*
Large urban Large central metro Counties in a metropolitan statistical area of 1 million or more population:

1) that contain the entire population of the largest principal city of the metropolitan statistical area, or

2) whose entire population resides in the largest principal city of the metropolitan statistical area, or

3) that contain at least 250,000 of the population of any principal city in the metropolitan statistical area

Suburban/urban Large fringe metro Counties in a metropolitan statistical area of 1 million or more population that do not qualify as large central
Medium metro Counties in a metropolitan statistical area of 250,000 to 999,999 population
Non-urban Small metro Counties in a metropolitan statistical area of 50,000 to 249,999 population
Micropolitan Counties in a micropolitan (urban cluster of 10,000 or more people) statistical area
Rural Noncore Counties that are neither metropolitan nor micropolitan
*Ingram DD and Franco S. 2006 Urban-Rural Classification Scheme for Counties. Online at http://ftp.cdc.gov/pub/health_statistics/nchs/Dataset_Documentation/OAE/urbanrural/methodology.pdf.

How was the Assessment of Wisconsin’s Health Trends Performed? (PDF)

This is an accordion element with a series of buttons that open and close related content panels.

What measure is used to evaluate the trend over the past ten years?

We calculated the annual percent change (APC) for each of the 20 health indicators during the past 10 years. An increasing annual percent change indicates a worsening health trend, while a decreasing annual percent change indicates an improving health trend.

or  indicates Wisconsin’s performance on the health indicator improved during the past 10 years with APC’s < -0.5% and < -1.0% for light and dark green arrow, respectively;
indicates Wisconsin’s performance on the health indicator has been stable during the past 10 years (-0.5%/year= APC =+0.5%/year); and
 or  indicates Wisconsin’s performance on the health indicator during the past 10 years with APC’s > +0.5% and > +1.0% for light and dark red arrow, respectively.

For more information about how the APC was calculated see “Estimating average annual percent change in trend analysis” by Clegg LX, Hankey BF, Tiwari R, Feuer EJ, Edwards BK.

How is the current year of data assessed and evaluated?

Using the 10-year baseline trends, we determine what the “expected” current rate would be for each indicator if the past 10 year trend continued. We compare this expected rate to the current “observed” rate, to see if it is better or worse. Current progress is determined by comparing the observed rates to the 90% confidence intervals of the expected rates.

  •  indicates Wisconsin is performing better than expected for the health indicator;
  •  indicates the current rate is about the same as the expected rate; and
  •  indicates Wisconsin is performing worse than expected for the health indicator.
Current Progress:
 = Current rate is worse than expected rate (p<0.10)
 = Current rate is no different than expected rate
 = Current rate is better than expected rate (p<0.10)

 

How does Wisconsin compare with other states?

Data, where available, for the best and worst performing states for the “Current Observed Value” are presented in the online version of the 2015 Health Progress Assessment Table: here.
Data, where available, for the best and worst performing states for the “Current Observed Value” are presented in the online version of the 2014 Health Progress Assessment Table: here.
Data, where available, for the best and worst performing states for the “Current Observed Value” are presented in the online version of the 2013 Health Progress Assessment Table: here.

 

What are some limits of this method?

This is only one way to assess health trends. Our method may be limited by the fact that we assume a linear trend for all measures. This may not be the case for all health factors, such as unemployment, which is cyclical in nature.

The regressions we constructed used only 10 years of data. Regression analyses perform better statistically with more data points. However, due to our interest in present trends we chose to only use the 10 most recent years of data to construct the regression trend lines.

We report all measures independently as if each one impacts health by itself. In reality the many factors that impact health are intertwined. For instance, a parent who is unemployed may also have children in poverty and be uninsured. Health factors relate and work together.