Self-rated health,objective health,and racial discrimination among African-Americans: Explaining inconsistent findings and testing health pessimism

Abstract

African-Americans sometimes rate their health as Poor/Fair in the absence of chronic diseases. Theoretically, this lack of correspondence between self-rated health and objective health is due to racial discrimination that results in rating one’s health negatively and in terms of social rather than health variables. We tested this Health Pessimism model with 2118 African-Americans. Results revealed that Poor/Fair self-rated health was predicted mostly by objective health for the Low Discrimination group but mostly by demographic variables for the High Discrimination group, in a manner consistent with Health Pessimism. Inconsistencies among prior studies might reflect differences in the prevalence of high discrimination among their samples.

Keywords

African-Americans health pessimism objective health racial discrimination self-rated health

Self-rated health (SRH) refers to people’s subjective perception and overall evaluation of their health (Idler and Angel, 1990). It is usually measured by a single item that asks people to rate their general health on a 5-point Likert-type scale of Poor, Fair, Good, Very Good, and Excellent. This simple question is a robust predictor of subsequent mortality (DeSalvo et al., 2006; Jylhä, 2009), and hence is regarded as a valuable indicator of population health, health trajectories, and health disparities. Thus, the SRH item appears in the population health surveys of several countries including Australia (Jalaludin and Garden, 2011), Canada (Prus, 2011), China, Japan, South Korea, Taiwan, Hong Kong (Hanibuchi et al., 2012; Wang et al., 2013), Germany, Denmark, the United Kingdom (Sacker et al., 2012), and Brazil (Camelo et al., 2014). In the United States, SRH is included in all population health surveys (DeSalvo et al., 2006), for example, the National Health Interview Survey (NHIS) and Behavioral Risk Factor Surveillance System (BRFSS).

The strength of the relationship between SRH and mortality varies considerably by social and cultural variables such as education (Huisman et al., 2007), socioeconomic status (SES; Regidor et al., 2010), country (Jürges, 2007; Sacker et al., 2012), acculturation, nativity, language (Acevedo-Garcia et al., 2010; Huh et al., 2008; Kandula et al., 2007), and race–ethnicity (Benjamin et al., 2012; Borrell and Dallo, 2008; Landrine and Corral, 2014; Su et al., 2013). In the United States, racial–ethnic differences in SRH and in the SRH–mortality relationship have raised questions about whether the SRH item measures the overall health of racial–ethnic minorities or instead measures sociocultural factors and cultural response styles (Landrine and Corral, 2014; Seo et al., 2014).

SRH among US Asians and Latinos

US Asians and Hispanics/Latinos not only tend to rate their health as significantly poorer than Whites but also tend to do so even when they are healthier than Whites, that is, despite objective health indicators to the contrary. Asians and Latinos tend to report Poor or (more often) Fair health in the absence of major diseases and seem reluctant to rate their health as Very Good or Excellent; hence, the SRH–mortality relationship is significantly weaker for Asians and Latinos than for Whites (Borrell and Dallo, 2008; Brewer et al., 2013; Bzostek et al., 2007; Huh et al., 2008; Su et al., 2013). Theories about why Asians and Latinos rate their health Poor/Fair irrespective of their actual health include lack of translation equivalence (translating “Fair” into Spanish as “Regular” and absence of exact-equivalents for “Very Good” and “Excellent” in other languages); somatization of psychological distress; and collectivism, that is, interdependence with family and community that prohibits rating one’s personal health as Very Good or Excellent when others are suffering (Borrell and Dallo, 2008; Bzostek et al., 2007; Landrine and Corral, 2014; Seo et al., 2014; Su et al., 2013; Viruell-Fuentes et al., 2011). These theories are consistent with data indicating that SRH is higher among Asians and Latinos who answer the question in English than in their native languages, is higher among those who are acculturated (Brewer et al., 2013; Kandula et al., 2007; Seo et al., 2014), and varies with social and neighborhood conditions (Ko et al., 2014; Subramanian et al., 2002).

SRH among US African-Americans

African-Americans also tend to rate their health as significantly poorer than Whites and often do so even when matched with Whites on objective health such that the SRH–mortality relationship is significantly weaker for African-Americans than for Whites (Benjamin et al., 2012; Boardman, 2004; Lee et al., 2007; Spencer et al., 2009; Thomas et al., 2010). However, such findings are not consistent; however; some studies found no difference between African-Americans and Whites in SRH (e.g. Boyington et al., 2008; Lo et al., 2013). Others found that the majority of African-Americans rate their health as Good, Very Good, or Excellent, and that these ratings are linked to objective health. For example, in a recent study, 81.8 percent of African-Americans rated their health as Good, Very Good, or Excellent, whereas 18.2 percent rated it as Poor/Fair (Baruth et al., 2014). These ratings were strongly and logically linked to diabetes, hypertension, obesity, and physical activity insofar as those with diagnosed chronic conditions and low physical activity were significantly more likely to rate their health as Poor/Fair (Baruth et al., 2014). Chen and Yang (2014) similarly found significant associations between African-American SRH and chronic health conditions and health behaviors (e.g. physical activity and smoking).

There are two theories about why African-Americans (in some but not all studies) rate their health Poor/Fair despite their objective health. The enduring self-concept model argues that African-Americans’ definition of health is more social and interpersonal than physical and biomedical; hence, SRH is less tied to objective physical health than to social variables (Bailis et al., 2003). This theory is consistent with studies that found strong relationships between African-American SRH and social support, social capital, neighborhood conditions, residential segregation, and other social variables (Chen and Yang, 2014; Ko et al., 2014; Subramanian et al., 2002, 2005). The second theory, health pessimism, argues that African-Americans are more pessimistic than Whites (perhaps in general but definitely) about their health and tend to rate their health negatively irrespective of their actual health (Ferraro, 1993) as a result of racial discrimination (Boardman, 2004). This model is consistent with studies that found a strong relationship between frequent racial discrimination and Poor/Fair SRH among African-Americans (Boardman, 2004; Borrell et al., 2006; Chen and Yang, 2014)—although some studies found no such relationship (Krieger et al., 2011). Both theories suggest that African-American SRH is tied to racial discrimination. Moreover, health pessimism theory predicts that Poor/Fair SRH will be weakly related (or unrelated) to objective health only among African-Americans who have experienced frequent discrimination.

Study purpose

This study contributes to efforts to understand the complex and inconsistent data on African-American SRH. First, we examined the extent to which a large, random sample of African-Americans rated their health as Poor/Fair versus Good, Very Good, or Excellent. Next, we examined associations between Poor/Fair SRH and demographics, objective health (diseases and health behaviors), and recent racial discrimination for the sample. Finally, we segmented the sample into High versus Low Racial Discrimination groups to test health pessimism theory, that is, SRH should be more strongly related to objective health for the Low than for the High Racial Discrimination group.

Method

Participants

Participants were a random, statewide sample of N = 2118, self-identified, US-born, African-American adult residents of California (CA), 1214 women (57.3%), and 904 men (42.7%), whose ages ranged from 18 to 95 years (Mean = 43.8, standard deviation [SD] = 16.2 years). Most (81%) had some form of health insurance.

Procedure

Participants were sampled from randomly selected census tracts (and randomly selected block groups within them) in the seven CA counties in which 90 percent of the CA African-American population resides. Details on the three-stage, random household probability sampling procedure and on the informed consent procedures are provided elsewhere (Corral and Landrine, 2012; Landrine et al., 2013). African-American adult surveyors went door-to-door, on weekends, to every household in the block groups and asked if an African-American adult who resided there would like to participate in a brief, anonymous, health survey for US$10 cash, with only one participant permitted per household. The survey had an 8th-grade reading level and took 15 minutes to complete. Survey completion (response) rates ranged from 85 to 100 percent depending on county and census tract (Landrine et al., 2013). The study had the approval of the Institutional Review Board of San Diego State University.

Measures

Objective health was measured with four standard items from the BRFSS (http://www.cdc.gov/brfss). Each question began, “Has a doctor ever told you that you have.” The end of the questions were as follows: Hypertension (high blood pressure)? Diabetes (high blood sugar)? Cancer of any kind? Heart disease? Two health behaviors were used as a second measure of objective health, as in other studies (Baruth et al., 2014; Chen and Yang, 2014), and were assessed using BRFSS items. Cigarette smoking (smoking) was measured by asking, Have you smoked 100 cigarettes or more in your entire life (yes/no), and Do you smoke cigarettes now, even once in a while (yes/no). Those who answered yes to both questions were categorized as current smokers, and those who answered no to the latter question categorized as non-smokers. Analyses focus on smokers and non-smokers only, with former smokers (yes to the first question, no to the second) excluded. Vigorous physical activity in the past 30 days (PA) was assessed with the question, Did you engage in any vigorous physical activity—one that made you sweat or made your heart race—in the past 30 days (yes/no). SRH was measured with the standard, 5-point Likert-type question. Racial discrimination was assessed by the single item used in prior studies (e.g. Corral and Landrine, 2012; Shariff-Marco et al., 2010), that is, How much racism or discrimination have you personally experienced in the past year. Responses “None” and “A Little” were summed as Low and “Some” and “A Lot” were summed as High Discrimination. Five demographic questions (gender, age, education, annual income, and health insurance (yes/no)) were asked as well. In data analyses, the sample was dichotomized into those with Poor and Fair (Poor/Fair) versus Good, Very Good, and Excellent (Good–Excellent) SRH as in all prior studies of SRH (e.g. Baruth et al., 2014; Chen and Yang, 2014) cited here. All data analyses used SPSS version 20.

Results

The majority (81.8%) of the sample rated their health as Good, Very Good, or Excellent, and 18.2 percent rated their health as Poor/Fair. The distribution of SRH was Poor = 2.4 percent, Fair = 15.8 percent, Good = 37.4 percent, Very Good = 33.7 percent, and Excellent = 10.7 percent.

Univariate analyses revealed associations between SRH and demographic variables: a larger percentage of older (⩾45 years) people (24.3%) than of young (18–24 years) people (9%) rated their health as Poor/Fair (χ² = 44.703, p = .0005). Significantly, more of those with low education (⩽high school, 23%) than with higher education (15.2%) rated their health as Poor/Fair (χ² = 18.365, p = .0005), and a significantly larger percentage of those with the lowest incomes (28.6%) than those with the highest incomes (10.7%) rated their health as Poor/Fair (χ² = 62.891, p = .0005). There were no gender differences in Poor/Fair SRH (men = 17.5%, women = 19.3%, χ² = 1.009, p = .315) and no relationship between Discrimination and Poor/Fair SRH: 18.1 percent of the Low Discrimination and 18.6 percent of the High Discrimination group rated their health as Poor/Fair SRH (χ² = 0.86, p = .770).

A hierarchical, logistic regression predicting Poor/Fair SRH for the sample as a whole was conducted, with the five demographic variables entered on Step 1, racial discrimination entered on Step 2, and objective health (four diseases and two health behaviors) entered on Step 3. As shown in Table 1, income and age contributed to Poor/Fair SRH but education, gender, and health insurance did not. Those with low incomes were 2 to 3 times more likely (than those with the highest incomes) to rate their health as Poor/Fair, and the odds of Poor/Fair SRH increased with age; older groups were 2 to 3 times more likely than the youngest group to rate their health as Poor/Fair. Racial discrimination did not contribute significantly to Poor/Fair SRH after controlling for demographic variables. Objective health however contributed significantly to Poor/Fair SRH. Those diagnosed with hypertension, diabetes, or heart disease were twice as likely to rate their health Poor/Fair, and those who did not engage in PA were 1.8 times more likely to rate their health as Poor/Fair. Neither diagnosed cancer nor cigarette smoking contributed to Poor/Fair SRH. Thus, for the sample as a whole, two of five (40% of) demographic variables and four of six (66.7% of) objective health indicators (three of four diseases and one of two health behaviors) contributed to Poor/Fair SRH.

Table 1.

Logistic regression predicting Fair/Poor self-rated health among African-American adults.

Variables entered	β	P	OR	95% CI
Step 1. Demographic variables
Education
>High school graduate (REF)
<High school graduate	−.359	NS
High school graduate/GED	−.589	NS
Income
⩾U$50,000 (REF)
⩽US$10,999	1.267	.0005	3.552	2.095, 6.021
US$11,000–US$25,999	.996	.0005	2.707	1.621, 4.520
US$26,000–US$49,999	.237	NS
Gender
Women (REF)
Men	.241	NS
Age (years)
18–24 (REF)
25–34	.815	.043	2.260	1.026, 4.981
35–44	.999	.013	2.717	1.239, 5.957
⩾45	1.093	.004	2.982	1.420, 6.263
Health insurance
No (REF)
Yes	−.116	NS
Step 2. Recent/past year discrimination
Low/none (REF)
High	−.130	NS
Step 3. Objective health and health behaviors
Diagnosed hypertension
No (REF)
Yes	.870	.0005	2.387	1.627, 3.500
Diagnosed diabetes
No (REF)
Yes	.773	.0005	2.167	1.414, 3.321
Diagnosed heart disease
No (REF)
Yes	1.004	.001	2.729	1.538, 4.843
Diagnosed cancer
No (REF)
Yes	.454	NS
Vigorous physical activity in the past 30 days
Yes (REF)
No	.592	.001	1.808	1.283, 2.547
Current smoker
Yes (REF)
No	−.326	NS

OR: odds ratio; CI: confidence interval; REF: reference group; GED: general educational development; NS: not significant.

The sample was then divided into Low (n = 1296) versus High (n = 618) Racial Discrimi-nation groups and separate logistic regressions conducted to predict Poor/Fair SRH among each group. As shown in Table 2, for the Low Discrimination group, income was the sole demographic predictor; those with low incomes were 2.4 to 4 times more likely to rate their health Poor/Fair than those with the highest incomes. After controlling for demographic variables, objective health contributed to Poor/Fair SRH for this group; those with diagnosed hypertension, diabetes, or heart disease were 2 to 4 times more likely to rate their health Poor/Fair, and those who did not engage in PA were 1.8 times more likely to rate their health as Poor/Fair. For the Low Discrimination group, one of five (20% of) demographic variables and four of six (66.7% of) objective health indicators (three of four diseases and one of two health behaviors) contributed significantly to Poor/Fair SRH.

Table 2.

Logistic regression predicting Fair/Poor self-rated health among low recent discrimination African-American adults.

Variables entered	β	p	OR	95% CI
Step 1. Demographic variables
Education
>High school graduate (REF)
<High school graduate	.190	NS
High school graduate/GED	−.168	NS
Income
⩾US$50,000 (REF)
⩽US$10,999	1.439	.0005	4.218	2.191, 8.120
US$11,000–US$25,999	.906	.006	2.475	1.299, 4.714
US$26,000–US$49,999	.294	NS
Gender
Women (REF)
Men	−.039	NS
Age (yeas)
18–24 (REF)
25–34	.523	NS
35–44	.490	NS
⩾45	.762	NS
Health insurance
No (REF)
Yes	−.350	NS
Step 2. Objective health and health behaviors
Diagnosed hypertension
No (REF)
Yes	1.051	.0005	2.862	1.782, 4.594
Diagnosed diabetes
No (REF)
Yes	.740	.007	2.095	1.226, 3.582
Diagnosed heart disease
No (REF)
Yes	1.389	.0005	4.010	1.863, 8.629
Diagnosed cancer
No (REF)
Yes	.508	NS
Vigorous physical activity in the past 30 days
Yes (REF)
No	.587	.007	1.783	1.175, 2.707
Current smoker
Yes (REF)
No	−.387	NS

OR: odds ratio; CI: confidence interval; REF: reference group; GED: general educational development; NS: not significant.

Table 3 displays the logistic regression for the High Discrimination group. As shown, all demographic variables except health insurance contributed to Poor/Fair SRH for this group. Those with low educations were 19 to 21 percent less likely to rate their health as Poor/Fair compared to those with some college or higher education. Those with moderately low incomes were 2.9 times more likely to report Poor/Fair health than those with the highest incomes. Men were twice as likely as women to report Poor/Fair health, and older groups were 6 to 8 times more likely to rate their health as Poor/Fair compared to the youngest group. After controlling for demographic variables, diagnosed diabetes and low PA contributed to Poor/Fair SRH. Thus, for the High Discrimination group, four of five (80% of) demographic variables and two of six (33.3%) objective health indicators (one of four diseases and one of two health behaviors) contributed significantly to Poor/Fair SRH.

Table 3.

Logistic regression predicting Fair/Poor self-rated health among high recent discrimination African-American adults.

Variables entered	β	p	OR	95% CI
Step 1. Demographic variables
Education
>High school graduate (REF)
<High school graduate	−1.543	.007	.214	.070, .653
High school graduate/GED	−1.641	.004	.194	.063, .594
Income
⩾US$50,000 (REF)
⩽US$10,999	.619	NS
US$11,000–US$25,999	1.061	.02	2.888	1.182, 7.059
US$26,000–US$49,999	−.246	NS
Gender
Women (REF)
Men	.741	.027	2.097	1.086, 4.050
Age (years)
18–24 (REF)
25–34	1.414	NS
35–44	2.166	.010	8.720	1.691, 44.968
⩾45	1.789	.031	5.984	1.178, 30.392
Health insurance
No (REF)
Yes	.392	NS
Step 2. Objective health and health behaviors
Diagnosed hypertension
No (REF)
Yes	.501	NS
Diagnosed diabetes
No (REF)
Yes	1.037	.007	2.821	1.329, 5.988
Diagnosed heart disease
No (REF)
Yes	.788	NS
Diagnosed cancer
No (REF)
Yes	.124	NS
Vigorous physical activity in the past 30 days
Yes (REF)
No	.756	.023	2.129	1.110, 4.082
Current smoker
Yes (REF)
No	−.149	NS

OR: odds ratio; CI: confidence interval; REF: reference group; GED: general educational development; NS: not significant.

Discussion

This study has four important results. First, the majority of African-Americans (81.8%) rated their health as Good–Excellent, whereas 18.2 percent rated it as Poor/Fair. This finding is consistent with recent studies that found Poor/Fair SRH among a relatively small percentage of African-Americans (e.g. Baruth et al., 2014); indeed, the percentages of Good–Excellent versus Poor/Fair SRH found here are precisely the same as those found by Baruth et al. (2014).

The second notable finding was that racial discrimination did not contribute to Poor/Fair SRH (for the sample as a whole) after controlling for demographic variables. This result is consistent with other studies that found no relationship between discrimination and SRH among African-Americans (Krieger et al., 2011). Nonetheless, however, our finding might be a function of the limitations of the measure of discrimination used in this study. Our measure was limited in that it assessed past year instead of lifetime experiences of racial discrimination. Lifetime exposures to discrimination and disadvantage play a stronger role in African-American health than short-term exposures (Adler and Stewart, 2010; Sharkey, 2008); discrimination might have contributed to SRH if long-term exposures had been measured, that is, the pervasive, lifetime exposures referred to in theories about SRH and discrimination (e.g., Boardman, 2004; Chen and Yang, 2014).

Moreover, we used a single item instead of a scale to measure recent discrimination. We note that studies that have used robust, recent discrimination scales also found no relationship between discrimination and SRH (Krieger et al., 2011) and highlight that the single item used here has strong relationships to African-American health and health behaviors in other studies (e.g. Corral and Landrine, 2012). Nonetheless, a different discrimination–SRH result might have been found if scale had been used.

Finally and importantly, our finding of no relationship between discrimination and SRH might reflect the small percentage of the sample (32%) who reported frequent discrimination. Theories of the relationship between discrimination and SRH argue that experiencing frequent (not infrequent or no) discrimination contributes to Poor SRH among African-Americans (Boardman, 2004; Chen and Yang, 2014). Thus, the absence of a relationship between discrimination and SRH for a sample in which 68 percent reported little or no discrimination might be expected and does not test or reflect on those theories. Indeed, one explanation for the inconsistent findings in the SRH–discrimination literature is possible differences between study samples in frequent discrimination; frequent discrimination might have been more prevalent among the samples in studies that found versus failed to find a relationship between discrimination and SRH.

The third important finding was that SRH was associated with objective health (for the sample as a whole) even after controlling for demographic variables and discrimination. Four of the six (66.7%) objective health indicators contributed significantly to Poor/Fair SRH. This finding is consistent with recent studies that similarly found that chronic conditions and health behaviors contribute to SRH among African-Americans (Baruth et al., 2014; Chen and Yang, 2014) but inconsistent with studies (e.g. Boardman, 2004) that found little or no such relationship. One possible explanation for these inconsistent findings is that African-Americans’ concept of health might be changing from a social contextual definition (Bailis et al., 2003) to a more biomedical definition over time, and particularly in a larger context in which healthcare is increasingly affordable and salient. By making healthcare more accessible to the millions of low-income and racial–ethnic minorities who previously could not obtain it, the 2010 Affordable Health Care Act in the United States (http:// obamacarefacts.com) might be encouraging people to focus on, define, and rate their health in terms of biomedical conditions. Likewise, it is then perhaps not a coincidence that studies that found weak or no relationships between SRH and biomedical conditions among African-Americans were published (and presumably conducted) before the Affordable Health Care Act, whereas those finding strong relationships were published (and presumably conducted) after its passage. Moreover, racial disparities in SRH in the United States continue to decline (Beck et al., 2014), and this too might at least in part reflect an increasingly biomedical definition of health among African-Americans that ties SRH more to objective health than to poor social and neighborhood conditions.

Finally, the fourth notable finding was that SRH was more strongly linked to objective health for the Low than for the High Discrimination group, in a manner consistent with health pessimism theory (Boardman, 2004): 66.7 percent of the objective health indicators (and only 20% of the social variables) were significantly related to Poor/Fair SRH for the Low Discrimination group, whereas only 33.3 percent of the objective health indicators (but 80% of social variables) were related to Poor/Fair SRH for the High Discrimination group. Although this finding is consistent with the health pessimism model, it does not provide direct support for that theory. This is because health pessimism argues that African-Americans who have the same objective health status as Whites rate their health worse than do Whites (and in terms of social instead of health variables) as a result of discrimination. Because we did not have a sample of Whites, we could not test that theory. However, our finding that social variables dominated the predictors of SRH for the High Discrimination group, whereas objective health dominated the predictors for the Low Discrimination group indirectly supports health pessimism.

These findings and interpretations must be considered in the context of the limitations of this study. One obvious limitation (noted previously) is the use of a single item instead of a scale to measure racial discrimination; a different discrimination–SRH relationship might have emerged with a more robust measure. A second limitation is the absence of a sample of US Whites, and hence an inability to assess possible racial disparities in SRH. Although SRH was generally high (Good–Excellent) for this sample, racial disparities nonetheless might have been found if Whites had been included. Likewise and as noted above, the absence of Whites meant that we could not directly test the health pessimism model. An additional limitation is that we did not include the many social-interpersonal (e.g. social support) and neighborhood variables (e.g. residential segregation, community poverty, social capital) that are known predictors of SRH among African-Americans. Theoretically, the strong links between SRH and objective health found for the sample as a whole might have been weaker had such variables been included.

Despite these limitations, this study advances understanding of the complex, inconsistent findings on African-American SRH. Likewise, it provides preliminary, tentative support for health pessimism theory. New studies that use robust discrimination scales and social and neighborhood variables to predict and compare SRH among African-Americans and Whites are needed to clarify questions and inconsistencies in this literature, and advance ongoing efforts to understand and eliminate racial–ethnic disparities in SRH.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by funds provided by Tobacco-Related Disease Research (grant no. 13AT-1500).

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