Contributors to Wisconsin’s persistent black-white gap in life expectancy

Background Although the black-white gap in life expectancy has narrowed in the U.S., there is considerable variability across states. In Wisconsin, the black-white gap exceeds 6 years, well above the national average. Reducing this disparity is an urgent public health priority, but there is limited understanding of what contributes to Wisconsin’s racial gap in longevity. Our investigation identifies causes of death that contribute most to Wisconsin’s black-white gap in life expectancy among males and females, and highlights specific ages where each cause of death contributes most to the gap. Methods Our study employs 1999–2016 restricted-use mortality data provided by the National Center for Health Statistics. After generating race- and sex-specific life tables for each 3-year period of observation (e.g., 1999–2001), we trace recent trends in the black-white life expectancy gap in Wisconsin. We subsequently conduct a series of analyses to decompose the black-white gap in three time periods into 13 separate causes and 19 different age groups. Results In 2014–16, Wisconsin’s black-white gap in life expectancy was 7.34 years for males (67% larger than the national gap), and 5.61 years for females (115% larger than the national gap). Among males, homicide was the single largest contributor, accounting for 1.56 years of the total gap. Heart disease and cancer followed, contributing 1.43 and 1.42 years, respectively. Among females, heart disease and cancer were the two leading contributors to the gap, accounting for 1.12 and 1.00 years, respectively. Whereas homicide contributed most to the racial gap in male longevity during late adolescence and early adulthood, heart disease and cancer exerted most of their influence between ages 50–70 for both males and females. Other notable contributors were unintentional injuries (males), diabetes and cerebrovascular disease (females), and perinatal conditions (males and females). Conclusions Our study identifies targets for future policy interventions that could substantially reduce Wisconsin’s racial gap in life expectancy. Concerted efforts to eliminate racial disparities in perinatal mortality and homicide early in the life course, and chronic conditions such as cancer and heart disease in later life, promise to help Wisconsin achieve the public health objective of racial parity in longevity. Electronic supplementary material The online version of this article (10.1186/s12889-019-7145-y) contains supplementary material, which is available to authorized users.


INTRODUCTION
In the United States, the overall black-white gap in life expectancy has been shrinking for decades; from 7.6 years in 1970, to 5.7 years in 2000, down to 3.6 years in 2013 (Kochanek, Arias, & Anderson, 2015;Harper, MacLehose, & Kaufman, 2014;Kochanek, Arias, & Anderson, 2013). The consistent improvement in the black-white gap is attributable to non-Hispanic blacks experiencing greater increases in life expectancy from birth than their white counterparts (Kochanek, Arias, & Bastian, 2016). However, it is important to note that life expectancy has risen substantially among men and women from both racial groups since the 1970s (Levine, Foster, R. Fullilove, M. Fullilove, Briggs, Hull, Husaini, & Hennekens, 2001).
While the national black-white gap in life expectancy has narrowed over time, blacks have nevertheless consistently maintained life expectancies that are lower than their white counterparts (Harper et al., 2014).
Despite encouraging national trends, substantial variability persists across states with respect to black-white disparities in life expectancy Harper et al., 2014). For example, a study by Harper et al. (2014) found that as of 2009 the black-white gap in life expectancy had narrowed to an all-time low of 3.0 years or less among non-Hispanic men and women in Nevada, New Mexico and Oregon. Conversely, black-white life expectancy disparities tended to stagnate at a relatively high level in Midwestern states between 1990 and 2009 and, in the case of Wisconsin, they actually increased for women. In fact, in Wisconsin the black-white gap in life expectancy among non-Hispanic men reached 8.2 years in 2009-the widest gap for either men or women in any of the 50 states (Harper et al., 2014).
In the following sections, I address this concerning finding by analyzing age-and cause-specific contributions to the life expectancy gap between non-Hispanic black and white populations in Wisconsin. Through an investigation of leading causes of death and the life stages at which these causes exert the most influence, I aim to explain why Wisconsin has experienced unfavorable improvement in the black-white gap in life expectancy.

State Variation in Black-White Life Expectancy Disparities
From 1999 to 2011, the national black-white gap in life expectancy improved for males by nearly two years, while females experienced an improvement of 1.7 years (Kochanek, Murphy & Xu, 2015;Hoyert, Arias, Smith, Murphy & Kochanek, 2001). Prior research documents that state level differences in the gap can contribute to the overall national gap (Bharmal et al., 2012). These state level gaps can vary and result from a multitude of factors relating to lower than average life expectancies among whites, or higher than average life expectancies among blacks.
Relatively small racial disparities in life expectancy can occur in states with below national average life expectancy among whites, and above average life expectancy among blacks. Such was the case in a study by Bharmal, Tseng, Kaplan, & Wong (2012) in 2004 for males in Kentucky (black-white gap of 4.37 years), and West Virginia (blackwhite gap of 4.42 years). Similar circumstances were found to affect the black-white gap for women in New Mexico and New York, where black females experienced life expectancies substantially greater than the national average, resulting in a black-white gap of less than four years.
In contrast, states with the largest racial disparities in life expectancy can be a result of whites with higher than average life expectancy and blacks with lower than average life expectancy. This was the case for men in New Jersey and Wisconsin, where the black-white gap was greater than eight years, and for women in Illinois and Wisconsin, where the gap was greater than six years (Bharmal et al., 2012). The growing disparity in Wisconsin can be linked to these circumstances, if these patterns have persisted over time. If blacks in Wisconsin are facing poor improvement in their life expectancy relative to national trends, and whites are continuing to improve at a steady rate, it can be expected that the life expectancy gap will continue to grow. What factors then could be acting against the black population to hinder their increasing life expectancy? It is best to next look at the causes of death, which directly contribute to life expectancy in these populations.

Contribution of Cause of Death to Black-White Life Expectancy Disparity
The role of cause of death, or the incidence component of life expectancy, can contribute to the changing black-white disparities observed across states (Acciai et al., 2015;Kochanek et al., 2013;Harper et al., 2007). Consequently, it is important to explore the major causes of death in Wisconsin.
Causes of death vary by gender and race-and also across periods of observation. This means that particular causes of death may affect the black-white gap differently over time for men and women.
Heart disease and cancer have consistently been the leading causes of death across gender and race groups (Kochanek et al., 2013). Heart disease alone accounts for more than 25% of all mortality in the U.S. . Therefore, substantial changes in death rates from these conditions can heavily influence life expectancy among all these groups. Non-Hispanic whites experienced a gain of 1.93 years of life expectancy from 2000-2014 due to relatively large decreases in rates among these causes of death (Kochanek, et al. 2016). At the same time, increased rates of suicide, accidents, liver disease, and hypertension can act to reduce or even reverse gains in life expectancy (Kochanek et al., 2016).
Heart disease, malignant neoplasms, cerebrovascular disease, and accidents are consistently leading causes of death among both blacks and whites. However, other causes of death have a tendency to rank among the leading causes of death for some groups but not others . For example, in 2014 homicide ranked as the fifth leading cause of death among black males nationwide, but did not even register in the top ten leading causes among white males (Heron, 2016). Furthermore, whereas homicide accounts for .87 of the 4.70-year difference in life expectancy between black and white males, it has a negligible impact on the gap between black and white females (Kochanek et al., 2013). This phenomenon exists at the state-level within Wisconsin, where homicide is the fourth leading cause of death among black males, yet does not rank in the top ten among white males (Wisconsin Department of Health Services, 2010).
Relatively high rates of homicide mortality among black males reduces their life expectancy, which can work to increase the gap with their white counterparts. Similarly, whites may experience relatively high rates of certain causes of death, leading to a shrinking black-white disparity. Such a cause of death could include suicide, which ranked as the seventh leading cause of death among white males, but tenth for black males in Wisconsin in 2009. Meanwhile, some age-specific causes of death can work to maintain the black-white life expectancy gap, such as high rates of infant mortality among blacks. The Wisconsin Department of Health Services recognizes the disproportionate infant mortality among blacks as another concern within the state. In 2010, black infant mortality accounted for 24% of all infant mortality in the state, when they accounted for only 10% of all live births (Wisconsin Department of Health Services, 2012). These large disparities in infant mortality have brought Wisconsin's overall rank based on African American infant mortality down to among the worst in the nation.

Age-Specific Mortality Risk and Black-White Life Expectancy Disparities
Variation in life expectancy across time has been found to be directly related to changes in age-specific mortality rates and age-specific cause of death rates (Kochanek, et al., 2016). Causes of death vary substantially across the life course, with those ages 65+ most affected by chronic conditions including cardiovascular disease, malignant neoplasms, and hypertension. At earlier ages, preventable causes of death such as accidents make important contributions to life expectancy World Health Organization, 2002). Changes in life expectancy are affected by age-specific death rates, thus the age component becomes an important factor when trying to explain variation in the black-white gap in life expectancy (Kochanek et al., 2016;. Homicide, for example, is a cause of death that disproportionately affects those at younger ages . In a state like Wisconsin that has relatively high rates of homicide among young black males, higher mortality rates at young ages removes years of potential life lived by these individuals, thus decreasing the overall life expectancy for that group. While blacks tend to experience relatively high mortality rates at young ages, whites experience unusually high mortality at other life stages. Case and Deaton (2015) recently found that middle-aged non-Hispanic whites have experienced an increase in all-cause mortality in the U.S., which is unique among developed countries. This increase has been explained by increased death rates due to drug and alcohol poisoning, suicide, and chronic liver diseases. As mentioned in the previous section, this age-specific increase in mortality among whites can work to reduce the black-white gap in life expectancy.

Why do Blacks have Unfavorable Health Outcomes?
Much of the health disparities observed between black and white populations are related to a myriad of social and economic factors including educational attainment, income, and socioeconomic status. Blacks have been persistently marginalized in the US, deprived of resources and left with a sense of disempowerment and loss of control (Marmot, 2015). Poor social conditions lie at the root of black health disparities and must be addressed in order to improve health among blacks.
The social characteristics hypothesis suggests that when relevant demographic, social, familial, and economic characteristics are accounted for, mortality differences across race groups will cease to exist (Rogers, 1992). For example, marriage promotes social integration and healthful behavior, and those married often experience lower levels of mortality than those who are not (Mergenhagen, Lee, and Gove, 1985). However, blacks are less likely than their white counterparts to marry, thus contributing to their disadvantage, which may in turn affect the black-white gap in mortality and health outcomes (Bennett, Bloom, & Craig, 1989). Additionally, factors such as increased income can result in access to high-quality health care, diets, and housing, all of which can translate into positive health outcomes and decreases in mortality (Rogers, 1992).
Research has suggested that poverty, race, and place are among factors that influence premature mortality among youth and young adults (Geronimus, Bound, Waidmann, Colen, & Steffick, 2001). For example, residing in an area that is considered unsafe due to high levels of crime can have an immediate impact on the risk of homicide or accidents. Being trapped in poverty subjects individuals and families to poor housing options that can also produce high levels of stress in their lives. So does it not make the most sense for blacks to move out of these bad neighborhoods? Yes, but the ability to make such a decision relies on the circumstances of the individual and without control of their situation, they are incapable of taking responsibility (Marmot, 2015) Moreover, without sufficient financial resources, these individuals may be unable to secure access to proper health care that could help combat resulting negative health outcomes. These unfavorable living conditions contribute to what Geronimus (2006) calls the weathering hypothesis, which postulates that blacks suffer premature health deterioration resulting from persistent social and economic adversity and political marginalization. These acute and chronic stressors thus have serious effects on one's health.
Educational attainment can influence many social and health disparities for black populations. During the 1980's and 1990's, improvements in life expectancy occurred almost exclusively for those who had high levels of education (Meara, Richards, & Cutler, 2008). Low levels of education inhibit opportunities for social capital accumulation and health improvement. Conversely, high levels of education are associated with good-paying jobs and mobility into better neighborhoods, which increase social capital. Due to all the social, financial, and health benefits that come with higher education, highly educated Americans, on average, live longer lives than Americans with lower levels of educational attainment (Sasson, 2016).
Research shows that relatively poor health among blacks is almost entirely rooted in socioeconomic inequality. However, it is important to note that linking theoretical perspectives to persistent black-white disparities in life expectancy in Wisconsin is beyond the scope of this thesis. Without socioeconomic and sociodemographic data to pair with existing mortality data, I can only speculate about explanations for poor health outcomes.

Research Aims
To date there have been insufficient state-specific analyses of black-white gaps in life expectancy, particularly among those states experiencing the widest racial disparities.
A rare phenomenon is underway in Wisconsin, one in which the large black-white gap in life expectancy has persisted and even increased. Contrary to the encouraging national improvement in the gap, blacks in Wisconsin are at a great health disadvantage relative to their white counterparts. The large mortality disparity between blacks and whites is a public health concern that requires prompt action in order to reverse the current disparity in Wisconsin.
To the best of my knowledge, this study is the first to examine age-and causespecific contributions to a state-specific black-white life expectancy gap. The first research aim of this study is to determine exactly how many years of additional life could be lived if particular causes of death were eliminated. The second aim is to apply demographic techniques to examine how different causes of death have contributed to the black-white life expectancy gap in Wisconsin from 1999-2001to 2009-2011 study carefully examines the life stages most affected by these disparities, as this will have important implications for targeted public health responses. Lastly, this study examines how each cause of death has contributed to changes in life expectancy within each group across time. By addressing the impact that selected causes of death have and the ages at which they are most likely to occur, this study seeks to identify those groups that are most at risk of death with hopes of informing policy that can be implemented to change the current black-white health disparity patterns taking place in Wisconsin.

Data
For this study, I draw data from the multiple cause of death mortality -all county micro data files for 1999-2001 and 2009-2011(hereafter 2000 to 2010) as provided by the National Center for Health Statistics (NCHS). These data have been compiled through the Vital Statistics Cooperative Program and collected from the 50 vital statistics jurisdictions (NCHS, 1999(NCHS, -2001(NCHS, & 2009(NCHS, -2011. The multiple cause of death mortality files are county-level national mortality data based on death certificates for U.S. residents. The NCHS aggregates mortality files by race, ethnicity, age, sex, and cause of death. All causes of death are classified in accordance with the International Classification of Disease (ICD), 10 th revision for both 2000and 2010(NCHS, 2010.
NCHS data also include U.S. Census Bureau population estimates by sex, age, ethnicity and race, which I utilize to generate life tables for my analyses.
I pooled six years of data together (1999-2001 and 2009-2011) to form two aggregate cross-sections of time, 1 -2000 and 2 -2010, in order to capture sufficient mortality counts for each cause of death selected for my analyses. I have chosen these two periods for two reasons: First, due to the availability of data from the NCHS, and second, to compare and contrast the change in the black-white gap between these two periods. This particular data granted to me by the NCHS are restricted access, and therefore are not subject to censoring or suppression of mortality counts ranging from 1-9 cases, as are the conditions for public access data. In accordance with the NCHS terms and conditions of restricted data use, I acted appropriately throughout the study to guarantee confidentiality of all cases. The Institutional Review Board at Utah State University exempted this study from oversight as it uses secondary data analysis and does not involve human subjects.  (Kochanek et al., 2013).

Measures
Within the state of Wisconsin, I restrict my analyses to non-Hispanic populations, as Hispanics are distinct from non-Hispanic blacks and whites in terms of social and economic factors and subsequent health outcomes Morales, Lara, Kington, Valdez, & Escarce, 2002). Ethnicity is reported separately on the death certificate of the deceased in accordance with standards of the Office of Management and Budget. Ethnicity of the decedent is reported by the funeral director as provided by an informant or, in the event an informant is unavailable, on the basis of observation (NCHS, 2010). My analysis will focus on four groups: non-Hispanic black males, non-Hispanic black females, non-Hispanic white males, and non-Hispanic white females (hereafter, black males, black females, white males, and white females). I have included all ages in the analysis with age categories created for less than one year, and one to four years of age. I generate five-year age categories for all remaining ages from five to 84, with a remaining open-ended age category for 85+. This system of age categorization is standard in the construction of period life tables, and appears in all ensuing tables.   Tables 1 and 2). Table 1 Life Expectancy at Birth by Gender, Race, Ethnicity, and Period in the US (in Years) Table 2 Life Expectancy at Birth by Gender, Race, Ethnicity, and Period in Wisconsin (in Years)      At the end of the graph (ages 85+) there is a crossover of malignant neoplasms and heart disease, indicating increased mortality rates among white males for these  (2000) conditions, which prevents the overall gap in life expectancy from becoming even larger.

RESULTS
These crossovers represent comparative advantages for black males, which work to slightly reduce the overall size of the life expectancy gap. This phenomenon is consistent with literature citing the black-white mortality "crossover", in which blacks at ages beyond 80 are more likely to have greater life expectancies than their white counterparts (Fenelon, 2013;Masters, 2012).  experience an improvement in the gap due to relatively high rates of heart disease mortality among elderly white females. Similar to the crossover phenomenon for heart disease in Figure 1 and Figure 2, white females experience much higher rates of heart  (2000) disease mortality at ages 85+, which helps to reduce the overall size of the gap in life expectancy.  White females experience high rates of heart disease mortality at ages 80+, just as black females experience a rise of malignant neoplasm mortality at the same age group.
This essentially results in the two causes canceling out their effects on the gap at this life stage, contrary to mortality outcomes observed in Figures 1-3.

Within Group Age-and Cause-Specific Decompositions
The following step, and final research aim, decomposes gaps in life expectancy by age and cause of death within each group. Figure 5 presents the five leading contributors to improved life expectancy for black males across the two periods. The leading contributors include heart disease, malignant neoplasms, cerebrovascular disease,

DISCUSSION
As this study has shown, heart disease and malignant neoplasms make the largest contributions to the life expectancy gap, both between and within groups, particularly in mid to late life. Among females, diabetes proved to be a leading contributor to the blackwhite gap as well, contributing most after the age of 50. Moreover, mortality conditions at young ages have implications for overall life expectancy. For example, perinatal conditions among blacks were consistent contributors to the black-white gap, particularly among females. Similarly, homicide among black males, particularly youths, made substantial contributions to the gap and consistently ranked near heart disease and malignant neoplasms as a leading contributor to racial disparities.

Policy Implications
Health policy in Wisconsin should make it a priority to address heart disease and malignant neoplasms among blacks and whites, particularly between the ages of 50-74.
Blacks and whites alike in the state would benefit immensely from reductions in mortality rates from these contributors. By successfully reducing these mortality rates all groups would experience substantial gains in life expectancy and, in improving conditions for blacks, the gap would narrow. Prompt action is also needed by policy makers in Wisconsin to address the contributions of perinatal conditions and diabetes among females and homicide among males to the life expectancy gap. Mortality reduction among these three causes could substantially alleviate the stagnating life expectancy gap. However, the solution to decreasing mortality rates from these causes among blacks may not be a simple one.
As postulated by the weathering and social characteristics hypotheses, poor health outcomes among blacks are attributable to marginalization in society and unfavorable social conditions. The solution may not be to simply provide health insurance to more perpetuating the life expectancy gap with their white counterparts. In order to resolve these issues, policy should focus on reducing poverty. Better quality public schools, antidiscrimination laws, and more government assistance can work to address issues related to poverty among blacks in Wisconsin.

Limitations and Future Research
Wisconsin is home to a predominately-white population, with a relatively small percentage of blacks in the state. The vast majority of the black population resides in