Psychosocial Correlates of Health Status among Asians,
Caucasians, and Multiracial Subjects.(Statistical Data
Included). DEBRA J. VANDERVOORT, PAUL P.
DIVERS and COLBEY
ACOJIDO.
Current
Psychology 19.2 (Summer 2000): p120.
Full Text :COPYRIGHT 2000 Transaction Publishers,
Inc.
The present study assessed the relationship between race and physical health in a multicultural sample. When controlling for a variety of health risk factors, the results revealed a significant relationship between race and recent and chronic physical symptoms (i.e., minor health problems) as well as past major health problems. Multiracial individuals reported more health problems than Asians or Caucasians. These findings may reflect the differences in diet and socioeconomic status (SES) as well as conditions associated with Iow SES such as decreased likelihood of seeking medical services and a variety of psychosocial variables.
Key words: Physical health, Health problems, Physical symptoms, Multiracial peoples, Hawaii
Although members of some ethnic minority groups have lower overall morbidity and mortality rates (e.g., Asians; Chun et al., 1996; Klatsky and Armstrong, 1999; Nickens, 1995; Stavig et al., 1996; Yu and Liu, 1992), members of many ethnic minority groups, including native Hawaiians, have higher morbidity rates for many physical illnesses as well as higher mortality rates than the general population (Alu Like, 1985; Curb et al., 1991; Gardner, 1980; Haas, 1983; Jackson, 1981; National Center for Health Statistics, 1984). Hawaiians, in particular, have the lowest life expectancy of all major racial/ethnic groups in Hawaii (Gardner, 1980). Blaisdell and Mokuau (1991) found that their overall death rate in 1985 was 5.6/1,000. For example, Hawaiians have higher age-adjusted rates of mortality than other ethnic groups for chronic illnesses such as cardiovascular disease (Look, 1982), diabetes (Curb et al., 1991), cancer totaled at all sites (Alu Like, 1985; Burch, 1984; Hinds et al., 1981), and respiratory illnesses (Hawaii State Department of Health, 1991).
Although it is well established that many minority groups have higher morbidity and mortality rates than Caucasians, a review of the medical, psychological, and sociological literature revealed that there was no research conducted on multiracial individuals and their physical health (the most common group in Hawaii), and only a handful on Asian and/or Pacific Islanders. As multiracial individuals will be a new racial category in the upcoming census, coupled with the paucity of literature in this area, the following study was undertaken.
METHODOLOGY
Subjects
Undergraduate students from San Francisco State University and the University of Hawaii at Hilo completed a questionnaire packet including demographic information and measures of physical health and health risk variables, along with other measures not included in this study. The students were given extra credit for their participation and confidentiality was maintained via detachment of identifying information from the questionnaire packet.
Instruments
To investigate the relationship between race and health, the following instruments were employed.
Physical Health Status: Two self-report instruments were used to assess physical health status, the first measuring physical symptoms (The Physical Symptoms Checklist (PSC), which assesses the number as well as the frequency of occurrence of 90 symptoms such as a cold, flu, headache, and infection). Two versions of the scale were used, one using a two week time frame and the other inquiring into the experience of symptoms in general (0 = not at all to 5 = several times a week). The other physical health measure was the Health Problems Scale (HPS) which assesses a wide variety of present and past major health problems or chronic conditions (e.g., hypertension, diabetes, asthma, heart attack). Respondents were asked if a doctor had told them that they had any of the listed disorders. The list of chronic conditions was adopted from that used in the Alameda County Haman Population Monitoring study (Belloc and Breslow, 1972; Belloc et al., 1971), a questionnaire which has been found acceptably reliable and valid in comparison with medical records (Andrews et al., 1977; Meltzer and Hochstim, 1970). Thus, there were six physical health measures: (1) number of recent physical symptoms (#PSC Recent); (2) frequency of recent physical symptoms (FPSC Recent); (3) number of chronic physical symptoms (#PSC Chronic); (4) frequency of chronic physical symptoms (FPSC Chronic); (5) number of present major health problems; and (6) number of past major health problems.
Physical Health Risk Variables: Given that considerable evidence indicates that the following variables are risk factors for a variety of illnesses (Leigh, 1982; Matarazzo and Lechliter, 1988; Moos, 1979; Weiner and Fawzy, 1989), they were included as controls in the multiple regression models. They were: age; gender; body mass index (weight(kg)/height(m)2); alcohol (drinks per week); smoking (currently being a smoker or not); caffeine (drinks per day); exercise (hours per week); and sodium (a scale assessing frequency and quantity of salt added to one's food as well as amount of salty food consumed).
RESULTS
Table 1 provides a descriptive overview of our independent variables. The sample ranged in age from 18-54 (X=27.2, median=23.00) with a greater percentage of females (73.7%) compared to males (26.3%). The collapsed racial groups resulted in a fairly equal distribution: Asian (30.1%), Caucasian (36.6%), and ultiracial (32.3%).
TABLE 1
Descriptive Overview of Independent Variables
Independent Standard
Variable Mean/Frequency(%) Median Deviation
Age 27.21 23.00 8.97
Sex
Male 46 (26.3) -- --
Female 137 (73.7) -- --
Race
Asian 56 (30.1)
Caucasian 68 (36.6) -- --
Multiracial 60 (32.3) -- --
Salt 6.47 6.00 1.86
Exercise 5.26 3.00
5.65
Smoking
No 120 (64.5) -- --
Yes 66 (35.5) -- --
Daily caffeine intake 2.17 2.00 2.29
# of alcoholic drinks
per week 2.25 0.00 4.08
Bodymass (kg/(m2) 23.48 22.31 6.92
Table 2 reports ordinary least squares regression results for models in which the substantive dependent variables change across models. In our first model, we regress the predetermined (predictor) variables on the number of recent physical symptoms reported by respondents. In this model, the Multiracial group reports more physical symptoms than either the Asian or Caucasian groups (b=-5.794, p [is less than] .05;-9.909, p [is less than] .01, respectively). Moreover, we also find that women have more physical symptoms than do men (b=7.157, p [is less than] .01). At a general level, this result implies that women have more physical ailments than men, but we caution the reader since the distribution of men to women responding to the survey was considerable. However, this pattern is consistent with the literature (Taylor, 1995). Finally, we find that the amount of caffeine consumption per day has a statistically significant effect on the number of recent physical symptoms among our sample (b=1.675, p [is less than] .01). Overall, this model accounts for 20 percent of the explained variance of the number of recent physical symptoms.
TABLE 2 Multivariate Regression Analysis for Six Physical Health Variables
Dependent Variables
Predetermined Number of recent Frequency of recent
Variables physical symptoms physical symptoms
(Model 1) (Model 2)
Constant 15.576(*) 34.202
Race(a)
Asian -5.794(*) -15.883(*)
(-.169)(b) (-.166)
White -9.909(**) -23.415(**)
(-.318) (-.269)
Female 7.157(**) 19.122(**)
(.247) (-.172)
Bodymass .171 .274
(.069) (.040)
Age -.258 -.860(*)
(-.144) (-.172)
Exercise (hours per week) .028 -.033
(.012) (-.005)
Caffeine drinks per day 1.675(**) 5.04(**)
(.247) (.268)
Salt .984 2.997(*)
(.127) (.138)
Alcoholic drinks per week .289 .525
(.079) (.051)
Smoking -3.157 -6.222
(.096) (-.068)
[R.sup.2] .201 .194
Number of cases 186 186
Predetermined Number of chronic Frequency of chronic
Variables physical symptoms physical symptoms
(Model 3) (Model 4)
Constant 9.489 44.404
Race(a)
Asian -6.805 -17.32
(-.157) (-.153)
White -8.630(**) -30.899(**)
(-.217) (-.153)
Female 11.832(**) 30.999(**)
(.264) (.266)
Bodymass .601(**) 1.064
(.188) (.128)
Age -.415(*) -1.114(*)
(-.183) (-.189)
Exercise (hours per week) .096 .104
(.033) (-.014)
Caffeine drinks per day .509 3.650(*)
(.058) (.160)
Salt 1.647(*) 2.413
(.166) (.093)
Alcoholic drinks per week .375 .955
(.080) (.079)
Smoking 1.283 -3.351
(.031) (-.031)
[R.sup.2] .192 .212
Number of cases 183 182
Number of present Number of past
Predetermined major health major health
Variables problems problems
(Model 5) (Model 6)
Constant -.758 -2.117
Race(a)
Asian -.496 -2.374
(-.048) (-.146)
White -1.004 -3.095(*)
(-.107) (-.208)
Female 1.370 1.764
(.128) (.104)
Bodymass 0.99 .130
(.136) (.113)
Age -.023 .121
(-.043) (.142)
Exercise (hours per week) -.009 .068
(-.013) (.062)
Caffeine drinks per day .591(**) .100
(.290) (.031)
Salt .095 .466
(.120) (.126)
Alcoholic drinks per week -.008 -.041
(-.007) (-.023)
Smoking -.841 .724
(-.085) (.046)
[R.sup.2] .138 .101
Number of cases 186 186
Note: Ordinary Least Squares (OLS) Estimation. (a) Dummy
variables coded as follows: Ethnicity, 1 if asian, 1 if white, 0 if
multiracial; Sex, 1 if female, 0 if male; Smoking 1 if yes, 0 if no.
(b) Standardized regression coefficients.
In model 2, we regress the predetermined variables on the frequency of recent physical symptoms. Our results here are similar to model 1 but several other predetermined variables appear to effect the dependent variable. Once again we find Multiracial individuals report greater frequency of physical symptoms than either Asians or Caucasians (b=-15.883, p [is less than] .05; b=-23.415, p [is less than] .01, respectively). Again, females report a higher frequency of physical symptoms than do men (b=19.222, p [is less than] .01. Of no surprise, we find that younger individuals report a lower frequency of physical symptoms than do older individuals. This should not be surprising since younger individuals have still managed to avoid other types of physical health problems that usually do not manifest themselves until later in the life cycle. Finally, both the amount of caffeine and salt consumed have predictive effects on the frequency of physical health symptoms. Nineteen percent of the explained variance was accounted for by this model.
In model 3, our substantive dependent variable is the number of chronic physical symptoms experienced by our respondents. In this model, only Caucasians have fewer chronic physical symptoms than Multiracial respondents (b=-8.630, p [is less than] .05). Women once again have more chronic physical symptoms compared to men as seen by the strong positive coefficient (b=11.832, p [is less than] .01). The effect of bodymass in this model begins to show its effect over Chronic health conditions (b=0.601, p [is less than] .01). This might be expected since greater bodymass is often associated with cardiovascular and respiratory problems over time. Age of the respondent again consistently shows that younger individuals experience fewer chronic conditions compared to their older counterparts (b=-0.415, p [is less than] .05). Finally, salt intake tends to be associated with chronic health conditions (b=1.647, p [is less than] .05). Obviously, the amount of salt intake is only one indicator of long term physical health but our model does lend credence to the importance of diet and its effect on long term physical health. Overall, model 3 accounts for 19 percent of the explained variance in the number of chronic physical symptoms of our respondents.
As in model 3, we find that only Caucasians have a statistically significant difference in the frequency of chronic physical symptoms (b=-30.899, p [is less than] .01), again reporting fewer chronic health symptoms compared to the Multiracial group. Consistently, women have a higher frequency of physical health concerns (b=30.999, p [is less than] .01). In this model, we find that caffeine consumption is also a predictor of chronic health problems. Overall, 21 percent of the variance of the dependent variable can be explained by the predetermined variables. Finally, the predetermined variables in models 5 and 6 prove to be weak predictors of present and past major health problems, although in model 6, Caucasians do tend to have fewer past major health problems than multiracial individuals (b=-3.095, p [is less than] .05).
DISCUSSION
The results revealed that the Multiracial individuals reported the poorest health and Caucasians reported the best health. Although the Multiracial individuals were not found to have worse health habits in general, they did have greater bodymass which may be an etiological factor for the results given that obesity has been implicated in the high rates of diabetes and cardiovascular diseases amongst Hawaiians (Curb et al., 1991; Look, 1982), many of whom are Multiracial but still identify themselves as Hawaiians (Blaisdell and Mokuau, 1991). The results of this study may be suggesting that the individuals who fall prey to these deadly illnesses later in life are already experiencing greater health problems in their younger years as well. This is particularly clear in this study since we did have a truncated age group (mean age = 27.2, median age = 23.0). Thus Multiracial individuals tend to exhibit early signs of poor health even during their young adult lives.
Another possible reason for the poor health of Multiracial individuals could be lower socioeconomic status (SES). Although research indicates low SES does not completely account for racial variations in health (Lillie, 1996; Williams, 1996), it is consistently associated with poorer health (Cockerham et al., 1986; d'Houtaud and Field, 1984; Herman, 1972; U.S. Department of Health and Human Services, 1988). Although the data-base includes information on income, it does not include information on their parental SES and as most students are poor, differences were not found to be significant. In general, however, Japanese and Caucasians tend to be of higher SES than other racial groups in the state of Hawaii (Department of Business, Economic Development, and Tourism, 1997).
One reason lower SES individuals have poorer health is that they are less likely to seek treatment (Herman, 1972; U.S. Department of Health and Human Services, 1989, 1992). Although financial issues may be one obvious reason for this, even with access to Medicaid and Medicare (as the latter often don't pay the entire bill), their disadvantaged financial position may not be the main reason for their low use of medical services (Crandall and Duncan, 1981; Rundall and Wheeler, 1979). There are simply not as many medical services available to those of low SES and the services that are available are often inadequate and understaffed (Cockerham et al., 1986; Taylor, 1995). Low SES individuals are also less likely to have a regular physician, which is associated with low utilization of services (Kronenfeld, 1978; Wan and Grey, 1978). Further, the largest gap in service utilization due to income is for preventive health services (e.g., inoculations, mamograms) which also contributes to the higher morbidity and mortality rates among low SES individuals (Taylor, 1995). In addition, differential treatment may be an issue (e.g., many doctors prefer not to deal with the Medicare/Medicaid system as they pay less for many procedures than regular insurance companies). For example, Crawford and colleagues (1994) found that African Americans were less likely to be referred to a cardiologist subsequent to reporting coronary symptoms than Caucasians. Finally, many native born Hawaiians are not acculturated to Western medical practices but prefer to receive health care from their own healers. This skepticism regarding Western medicine may have its origin in Hawaiian history. It is well established that epidemics of infectious diseases devastated the native Hawaiian population upon the arrival of Westerners (Daws, 1968; Nordyke, 1989).
In addition to health risk behavior and difficulties with the medical care system, other health risk factors associated with low SES include higher stress levels and less effectiveness of relaxation techniques (Patel and Marmot, 1988), poorer social support (Liebow, 1967; Stack, 1975; Williams, 1990), less sense of mastery and control over their lives (Mirowsky and Ross, 1986; Williams, 1990), and higher exposure to toxic chemicals (Bryant and Mohai, 1990). Low SES is also associated with greater mental health problems, which, in turn, can lead to more physical health problems (Moyers, 1993; VanderVoort, 1995). For example, the Epidemiologic Catchment Area Study, the largest study of psychiatric disorders ever conducted in the United States, found that low SES predicted higher rates of a broad range of mental health disorders, such as depressive, anxiety, and personality disorders (Holzer et al., 1986; Robins and Reiger, 1991). Thus, any or all of these factors associated with low SES could contribute to the poorer health of Multiracial individuals.
The results suggest that the current practice of including Asians and Pacific Islanders in one racial/ethnic group may be unwarranted, given the differential health results of this study and the many dietary and other lifestyle cultural differences between the various racial groups within this group (Williams, 1996).
Given the paucity of literature on Multiracial individuals, more studies are needed in this area to determine whether the results of this study are generalizable to Multiracial individuals in Hawaii and other parts of the country. Replication with the use of objective health measures, various age groups, and investigation of all the relevant etiological factors for health differences, would help advance our knowledge of Multiracial groups in America.
NOTE
Accepted for publication: 27 March 1999.
Address correspondence to: Debra J. VanderVoort, University of Hawaii at Hilo, College of Arts and Sciences, Social Sciences Division, Department of Psychology, 200 West Kawili Street, Hilo, HI 96720-4091.
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