Health of Wisconsin Report Card 2007

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Foreword Overview Report Card for Infant Health Report Card for Child and Young Adult Health Report Card for Working-age Adult Health Report Card for Older Adult Health Data Sources and Methods

Frequently Asked Questions (PDF)

• Why do we need a report card on health and health disparities in Wisconsin?
  Public and private sector policy makers are making decisions every day regarding programs and policies that affect health in the state, from medical care to public health to socioeconomic status. Knowing how healthy the population is overall and for specific subpopulations can be useful in resource allocation decisions for health improvement. In addition, this information is intended to be useful in developing the second five year plan for the Wisconsin Partnership Program as well as the State Health Plan for 2020.
• Why does Wisconsin receive two separate grades for health and health disparity instead of one overall grade?
  This Report Card grades Wisconsin separately on health and health disparity in order to assess the state's progress towards achieving two of the goals outlined by the Healthiest Wisconsin 2010 state health plan: to protect and promote health for all, and eliminate health disparities. Wisconsin's health grade of B- is based on the average health of its residents and, therefore, is dominated by the health of the majority population. Even if Wisconsin were to receive a grade of A for health, it could still be performing poorly in terms of health disparities and have numerous population subgroups in need of improved health. For these reasons, health and health disparity were assessed separately in this report.
• How does Wisconsin compare to other states for health and health disparity?
  Sixteen states receive better grades than Wisconsin for health, including the neighboring states of Minnesota (B) and Iowa (B). Other states performing better than Wisconsin in terms of health include Massachusetts, New York, and New Hampshire. States receiving the same grade as Wisconsin for health (B-) include California, Nebraska, and New Jersey.
  
  Twenty states receive better grades than Wisconsin for health disparity, including again Iowa (B) and Minnesota (B-). Massachusetts, New York, California, and Kansas are among the states with better health disparity grades than Wisconsin, while sixteen other states share Wisconsin's health disparity grade of D.
  
  Health and health disparity grades for all 50 states overall and for each life stage (infants, children and young adults, working-age adults, and older adults) are available.
• How can Wisconsin receive a health disparity grade of D if it receives a grade similar to or better than over half of the other states?
  Because the goal is to eliminate health disparities, the life stage grades for health disparity were graded against an absolute scale of no diparities rather than being graded relative to the performance of other states on health disparities. Since all states are struggling with health disparities, no state currently earns higher than a B for health disparity within any life stage.
• How does this report card relate to other recent reports on state health?
  Every fall, the United Health Foundation publishes "America's Health Rankings", ranking the health of the 50 states. However, the focus of this report is almost entirely on health, not health disparities. Other recent rankings from the federal Agency for Health Research and Quality and from the Commonwealth Fund report primarily on the quality of the State's health care systems (e.g.., hospitals, doctors, home health care) and not on the overall health outcomes of the population and subpopulations.
• If our health care in Wisconsin ranks #1 in the nation, why aren't our health and health disparity grades better?
  The quality of health care is only one factor in being healthy. Those with no access to health care don't experience this quality, and health is also determined by individual behaviors and social factors like income, education, and social relationships. This mismatch suggests that improving access to health care as well as public health approaches may need a higher priority in our state.
• How were the subgroups included in the report selected?
  The population subgroups graded in the Report Card were selected to illustrate the variety of characteristics, or domains, across which health disparities exist. A total of four domains were selected for inclusion in the Report Card: gender, education, urbanization of county, and race/ethnicity. This list does not cover all of the disparity domains reflected in the Healthy People 2010 goal to eliminate health disparities, 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. For example, homicide rates are higher for men and depression is more common among women.
  Education: The domain of education was included in the Report Card as an illustration of socioeconomic disparities in health. Educational attainment was examined for adults 25 years of age and older, but this same descriptor is not applicable for children who are currently in school. Therefore, the domain of education was not included for children and young adults. For infants, the education of the mother was used for this domain.
  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 Report Card, health is assessed for five racial/ethnic groups, with all groups other than Hispanic/Latino representing non-Hispanic ethnicity. Racial and ethnic groups with a substantial population in Wisconsin but for whom reliable data were not available for a particular measure are noted in the Report Card with a grade of "I" representing "incomplete" data.

Calculating Grades and Ranks (PDF)

• How were the life stage grades for health assigned?
  In order to give Wisconsin and its residents grades for the health outcomes of mortality and unhealthy days, we created grading scales. We looked at the distribution of health within each life stage for each of the 50 states to see how spread out each state's rate was from the average for the life stage (see figure below for an example for working-age adult mortality). We then assigned cutoff points for grades based on distance from the average (i.e., based on standard deviations from the mean). Rates that were closest to the average (between 0.5 standard deviations below the mean to 0.5 standard deviations above the mean) were assigned a C. Rates that were further away above and below the average were assigned a D (0.5 to 1.5 standard deviations above the mean) or a B (1.5 to 0.5 standard deviations below the mean) respectively. The highest (worst) rates were assigned Fs (more than 1.5 standard deviations above the mean) and the lowest (best rates) were assigned As (more than 1.5 standard deviations below the mean). The grading scales are listed in the table below. For the working-age and older adult life stages, the life stage health grades are an average of the grades for mortality and unhealthy days.
• What scales were used for the life stage grades for health?

  Age group	2005 WI Population (%)	Outcome	A	B	C	D	F
  Infants	69,856 (1.3%)	Mortality	<5.0	5.0-6.3	6.3-7.7	7.7-9.1	>9.1
  Child/Young Adults	1,813,574 (32.5%)	Mortality	<31.9	31.9-42.3	42.3-52.7	52.7-63.1	>63.1
  Working-Age Adults	2,970,814 (53.2%)	Mortality	<259	259-324	324-390	390-455	>455
  		Unhealthy Days	<4.8	4.8-5.5	5.5-6.2	6.2-6.9	>6.9
  Older Adults	727,595 (13.0%)	Mortality	<4278	4278-4710	4710-5142	5142-5574	>5574
  		Unhealthy Days	<5.5	5.5-6.3	6.3-7.0	7.0-7.8	>7.8

• How was the state grade for health assigned?
  To determine Wisconsin's health grade, we averaged the four life stage health grades to calculate an overall GPA. We then converted the overall GPA back to a grade.
• What scale did you use to convert GPA scores back to grades?

  GPA range	Grade
  3.75 – 4.0	A
  3.50 – 3.74	A-
  3.26 – 3.49	B+
  2.75 – 3.25	B
  2.50 – 2.74	B-
  2.26 – 2.49	C+
  1.75 – 2.25	C
  1.50 – 1.74	C-
  1.26 – 1.49	D+
  0.75 – 1.25	D
  < 0.75	F

• How are all of the grades for the different outcomes and life stages weighted in order to combine all of these measures into an overall grade for health?
  The health grades from the four life stages are equally weighted when they are averaged to calculate the overall grade for health, so each life stage grade contributes one-forth of the final health grade. However, the working-age adult and older adult life stage health grades are created by equally combining the life stage health grades for mortality and unhealthy days, while the infant and children/young adult health grades are based solely on mortality rates. The unhealthy days measure only contributes to the overall health grade through these life stages, making the overall health grade effectively based 75% on mortality rates and 25% on unhealthy days.
• How were the subgroup grades for health assigned within each life stage?
  The outcome/life stage grading scales constructed to assign each state a life stage grade for health were also used to assign grades for each population subgroup within that outcome and life stage.
• How were the life stage grades for health disparity assigned?
  The life stage health disparity grades are based on a weighted proportion of subgroup grades that were less than the best grade achieved by any subgroup. The method is based on an approach recommended by the U.S. Department of Health and Human Services (Keppel K, Pamuk E, Lynch J, et al. Methodological issues in measuring health disparities. National Center for Health Statistics. Vital Health Stat 2(141. 2005). This approach is being used to monitor progress towards the Healthy People 2010 goals to eliminate health disparities by assessing disparity across multiple subgroups using an index of disparity.
  
  To calculate life stage health disparity scores, we assigned a score of 4 for an A, 3 for a B, 2 for a C, 1 for a D, and 0 for an F to each subgroup's grade for mortality, and where applicable, unhealthy days. We then summed the differences between the best subgroup grade and each subgroup score, divided this sum by the number of subgroups minus one, and converted this score to a percent scale by dividing by four. The resulting disparity score can range from a value of zero percent disparity when all subgroups have the same grade to 100% disparity where one subgroup grade is an A and all other subgroup grades are Fs. (For the two younger life stages, the disparity score was based solely on available mortality rates for subgroups, whereas the disparity score for the two older life stages was based on an average of the scores for mortality and unhealthy days.) We then assigned grades to these scores.
• What scale was used for grading the life stage health disparity scores?

  Grade	Disparity score	Interpretation
  A	(0-15%)	Very Good
  B	(15-30%)	Good
  C	(30-45%)	Fair
  D	(45-60%)	Poor
  F	(> 60%)	Failing

• How was the stage grade for health disparity assigned?
  To determine Wisconsin's health disparity grade, we averaged the four life stage health disparity grades to calculate an overall GPA. We then converted the overall GPA back to a grade.
• How are all of the different subgroups, outcomes, and life stages weighted in combining all these measures into an overall grade for health disparity?
  Within every life stage, each subgroup with available data contributed equally to the calculation of the life stage disparity grade. However, because there were not equal numbers of subgroups within each domain (gender, education, type of county, race/ethnicity), the domains are not given equal weight in the life stage disparity grade. For example, for infants there are four subgroups under "type of county" and only two subgroups under "gender," so the domain of type of county contributes twice as much to the calculation of the life stage disparity grade as the domain of gender. In addition, subgroup data are not available for some racial/ethnic groups in every life stage and for the education domain for children and young adults; only the subgroups with available data were included in the life stage health disparity calculations. In calculating the overall health disparity grade for Wisconsin, the four life stage health disparity grades were given equal weight.
• How were the life stage ranks for health and health disparity calculated?
  For health, mean state values were used to assign ranks. The average of the two outcomes ranks was used for working-age and older adults. Life stage health disparities ranks were based on the state disparity scores described above. Because the ranks were constructed in a slightly different manner for working-age and older adults than the grades were constructed, the ranks displayed below do not necessarily reflect a ranked order of the grades received by each state.
  
  The health and health disparity ranks for all 50 states for each life stage (infants, children and young adults, working-age adults, and older adults) are available.

Detailed Information on Measures and Data Sources (PDF)

• What are mortality rates?
  Mortality rates are based on counts of the number of deaths occurring in a population group divided by the total number of people in that group. These numbers are then converted to reflect rates of death per 100,000 people (per 1,000 births for infants). We report rates based on the most recent 3-year period for which data are available nationally: 2002-2004 (except for education of infants' mothers, 2000-2002). The mortality rates are adjusted for age (except the rates for infants and older adults by education).
• Where do the mortality data used in this Report Card come from?

  Life stage	Domain	Data source
  Infants	Gender	CDC WONDER: Mortality – underlying cause of death
  	Education of mother	CDC WONDER: Infant deaths
  	Type of county	CDC WONDER: Mortality – underlying cause of death
  	Race / ethnicity	WISH: Infant mortality query (Mortality query – Asian rate)
  Children and young adults	Gender	CDC WONDER: Mortality – underlying cause of death
  	Type of county	CDC WONDER: Mortality – underlying cause of death
  	Race / ethnicity	WISH: Mortality query
  Working-age adults	Gender	CDC WONDER: Mortality – underlying cause of death
  	Education	Death counts: National Center for Health Statistics mortality detail files Population counts: 2000 U.S. Census
  	Type of county	CDC WONDER: Mortality – underlying cause of death
  	Race / ethnicity	WISH: Mortality query
  Older adults	Gender	CDC WONDER: Mortality – underlying cause of death
  	Education	Death counts: National Center for Health Statistics mortality detail files Population counts: 2000 U.S. Census
  	Type of county	CDC WONDER: Mortality – underlying cause of death
  	Race / ethnicity	WISH: Mortality query

• What are unhealthy days?
  Unhealthy days are a measure of health-related quality of life. We report the mean (average) number of unhealthy days reported per month. The numbers are based on adult (age 25+) respondents' answers to two questions about their health in the past month:

  • how many days was your physical health poor?
  • how many days was your mental health poor?

  We report data for the most recent 3-year period for which data on unhealthy days are available nationally: 2003-2005. The mean number of unhealthy days per month are adjusted for age.
  
  For more information on unhealthy days, see How Should We Measure Health-Related Quality of Life in Wisconsin?.
• Where do the unhealthy days data used in this Report Card come from?
  All of the unhealthy days data are from the Behavioral Risk Factor Surveillance System for the years 2003-2005. The mortality data sources are listed in the table below; all mortality data are for the years 2002-2004, except education of mother which is for 2000-2002.
• Why isn't a measure of health-related quality of life included for infants and children?
  The unhealthy days data used in this Report Card are from the Behavioral Risk Factor Surveillance System, which conducts surveys of adults ages 18 and older. Although some other measures of health-related quality of life – such as general health status – exist for children and adolescents, the measure of healthy days is not readily available for individuals under 18 across the United States. Unhealthy days data for young adults ages 18-24 were not included in the Report Card because this age group is combined with children, for whom unhealthy days data are not available.
• Which measures are adjusted for age?
  Mortality rates: All mortality rates are adjusted for age, except the rates for infants – because these rates are not typically adjusted for age – and older adults by education – because census denominators by age were not readily available for those 65 years and older. Data obtained from WONDER and WISH were requested as age-adjusted numbers in the queries. Mortality rates by education for working age adults were adjusted using the age groups of 25-34, 35-44, and 45-64, and population weights from the U.S. 2000 Standard Million.
  
  Unhealthy days: The mean values for unhealthy days per month for working age adults were adjusted for age using the age groups of 25-34, 35-44, 45-54, and 55-64 and population weights from the U.S. 2000 standard population. The mean values for unhealthy days per month for older adults were adjusted for age using the age groups 65-74 and 75+ and population weights from the US 2000 standard population.
• How were the urbanization classifications created?
  The four urbanization classifications used in this Report Card 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 Report Card 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.
• What are the urbanization classifications for each Wisconsin county?
  The urbanization classifications for each county in Wisconsin are listed on the UWPHI website. Wisconsin has one large urban county, 13 suburban/urban counties, 24 non-urban counties, and 34 rural counties.
• In the Overview of the Report Card, what method was used to project Wisconsin's future mortality rate?
  To calculate the rank of Wisconsin in mortality rates, we used simple linear regression on log-transformed mortality rates from 1992-2002 to identify trends for each state. We obtained our mortality rates from CDC WONDER; the data were age-adjusted to the U.S. 2000 population, included all deaths prior to age 75, and were reported as deaths per 100,000 population. We used 3-year rolled averages to improve stability in the yearly rates (for example, the mortality rates we used for 1992 were an average of the mortality rates for the years 1991, 1992, and 1993). The regression results were used to project each state's mortality rate to 2015. We then ranked states based on the mortality rates for the years 1992, 2002, and 2012.

Media Coverage

• Press Release
• Capital Times
• La Crosse Tribune
• Leader-Telegram Online
• Marshfield News-Herald
• Milwaukee Journal-Sentinel
• Oshkosh Northwestern
• Timesplus Monroe
• Wisconsin Public Radio (requires RealAudio player)
• Wisconsin State Journal
• Kaiser Health Disparities Report