TERRY F. BUSS, CSABA BERES, C. RICHARD HOFSTETrER, ALICE POMIDOR
HEALTH STATUS AMONG ELDERLY HUNGARIANS AND AMERICANS
ABSTRACT. Selected health status data for elderly populations from similar industrial cities - Youngstown, Ohio, USA, and Debrecen, Hungary - were compared. Because of their impoverished health care system, unregulated heavily industrialized society, and unhealthful life-styles Hungarians were hypothesized to have poorer health status than Americans, even after taking into account demographic mediating factors. The study provides a health status baseline for elderly Hungarians shortly after communism's fall in 1989-1990 and shows how great a gap exists between Hungarian health status and that in the West. Hungarians were in much poorer health as measured by functional status, symptomatology, medical condition, depression, and subjective health status. Distinctions persisted when controlling for gender, age, and education. Poverty-level (and income) did not explain health status differences. The paper concludes that Hungary should pay more attention to health promotion, prevention, and primary care, as well as to reforming patient management in hospitals, nursing homes, and home care programs.
Key Words: Hungary, United States, health status, elderly Even before the fall of communism in 1989-1990, Hungarians had begun health care reform ("Any Hope of Recovery" 1991; Forgacs and Kokeny 1987; Kaser 1976; Weinerman 1969). In 1972, the Hungarian government declared that every citizen was entitled to free medical care. In 1986, Health for All, a nationwide program to improve Hungarian lifestyles through health promotion and education, was launched. In 1988, health and welfare were merged into the Ministry of Health and Social Affairs to better manage illness related to poverty. In 1989, Social Security (pensions) and Health Insurance funds were separated and required to become self-financing. In 1991, Hungarians created a marketoriented health care system moving away from a socialist to a western model. Government's motivation for reform was the population's diminishing health status, the rising cost of health care, and the ineffectiveness of the socialist health care system (Csaszi and Kulberg 1985; Forgacs and Kokeny 1987; "Program of Reform of Our Health Care System" 1991; Raffel and Raffel 1989). Health reform targeted elderly and young people (not addressed here). The elderly are the fastest growing population segment, consume most health care services, have few personal resources, and need medical care (Csaszi and Kulberg 1985). Many in government, as is the case in America, feel they have a social compact to care for the elderly. Existing health status research, especially on the elderly, is inadequate for policy-making in Hungary. With few exceptions (see Mogey 1989) a literature review turned up mostly articles summarizing prevalence of mortality and morbidity by age for major disease categories. Lack of information makes health care planning difficult and impedes foreign governments and world health organizations in helping with funding and technical assistance. Journal of Cross-Cultural Gerontology 9: 301-322, 1994. 9 1994 Kluwer Academic Publishers. Printed in the Netherlands.
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Health research was often little valued except when serving Communist Party interests (Kullberg 1986). Research costs could not be justified when competing with service delivery needs. When health was studied at all, the resulting reports, hidden in obscure, limited circulation journals, were often not available in English or were very outdated. Frequently health status measures were incompatible with those used in the West, rendering cross-cultural comparisons difficult (e.g., Tamasy 1982). Some studies were of dubious quality (Kullberg 1986). Adequate data in any form do not exist (Cszaszi 1990). As broader social and political reforms emerge (i.e., democratization, privatization, and capitalism), systematic research will facilitate more effective use of scarce Hungarian health care resources. This study compares health status data for elderly populations, systematically collected from comparable industrial cities - Debrecen, Hungary and Youngstown, Ohio, USA. The comparison (1) provides Hungarian policymakers and health care researchers with a baseline against which to measure elderly health status improvements as new reforms are fully implemented, and (2) shows how far Hungarian health policy-makers are from achieving health status outcomes comparable to those generally found in the West. This does not imply that American elderly health status is optimal, but only that Hungarian health care reforms have targeted U.S. and European health status achievements as their goals. This paper looks first at cross-cultural gerontological research issues in the Hungarian and American contexts, and how they were resolved in this study. Next, it compares both cultures and the two study cities. Then results are presented, followed by their implications. COMPARATIVE HEALTH STATUS STUDIES Comparative health studies must be cautiously approached. These issues and their resolution are discussed below. We follow the lead of Ikels (1991) and Liang, Bennett, Whitelaw, and Maeda (1991) in identifying key issues for review. Translation
Numerous problems occur in translation. In our study, for example, we initially asked about social worker contact to explore formal help-giving networks. Hungarians, at the time, had no concept of social worker - social work was not a formal academic discipline - and under communism, since in theory social problems did not exist, social worker was not an occupation. To average citizens, social workers, when directly translated from English into Hungarian, can mean workers employed by state-owned enterprises - the proletariat. Questions asked of Americans were standard U.S. health status measures, also widely used in other countries. To insure that our American-based questionnaire was meaningfully translated into Hungarian, it was first rendered from English
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into Hungarian by a native Hungarian medical doctor. The translation was reviewed by two Hungarian gerontologists in Lajos Kossuth University's Sociology Institute. The questionnaire was reviewed by a Hungarian-speaking American social scientist. Questionnaires were pre-tested on 50 elderly Hungarians. All apparent linguistic anomalies were resolved. Income
Determining income is problematic in American studies and exacerbated in comparative studies. In the U.S. income can be measured as money received from all sources, or income can be expanded to include non-cash benefits (e.g., Medicare, Medicaid, food stamps, respite care, etc.) by converting benefit values into cash. So, for example, Medicare health insurance, a government program, has a comparable market price established by private health insurance premiums. In Hungary, elderly people receive small pensions, less than $100 monthly. But access to services remains great - free health care and subsidized vacations, housing, education, transportation, cultural programs, and so on (though all of these are being privatized). Unlike in the U.S., there is no market value for these benefits as yet. Using income alone to measure wealth or poverty in transforming socialist countries is misleading. To complicate matters, Hungarians use the underground economy, often bartering for goods and services rather than paying cash. In Hungary, building a house using state-owned contractors is difficult. Costs are high, waiting is long, work is shoddy. But black market construction is booming. Craftsmen and homeowners-to-be barter for labor or goods. Cash income fails to take into account gains in wealth through bartering. Black market exchanges frequently use hard currency because of inflated (25-30% annually), only partially convertible Hungarian currency. Because black marketeering is an illegal, imprisonable offense, Hungarians are unlikely to report some hard currency income. Hungary is still emerging from a socialist economy characterized by modest incomes with little spread between high and low earners. With the exception of high-level Communist Party members, there is not enough variation in income levels to explain health status differences. This is generally not so in the United States. Though income comparisons between western and former socialist countries are problematic, solutions do exist. In this study, Hungarians were asked to enumerate cash income from all legal sources. Then official levels $80 ("Affected by Change" 1992) - were used to classify people above or below poverty, and above or below 200% of poverty. Although this does not solve the problem, it has health policy implications: government allocates benefits and establishes need based on official poverty status, not unreported income. Another solution is to analyze education. Hungary's educational system even under communism is highly selective, tending to exclude poor people. Consequently, highly educated Hungarians tend to have higher incomes and occupa-
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tional status than those with less education. The same is true for the United States. Therefore, education may serve as a proxy for income.
Age~Retirement Hungarians retire earlier - 55 years of age for women, 60 for men - than Americans - 65 years of age. Looking at retired people in both countries, therefore, can be misleading. We studied people 62 years of age or older because of America's higher age limit, and because it is a standard cutoff age (along with 65 years) for American elderly studies. This is also the age at which biological and physiological developmental changes begin to increase the prevalence of disease and dysfunction (Tamasy 1982). Five percent of Hungarians worked after retirement age under the Old Regime. But under emerging capitalism, this percentage will likely increase as firms cannot afford to retire people early and government cannot assume pension liabilities. In fact, government has fixed legal retirement at 62 years. Our cut-off age, then, is important for Hungarian health policy.
Race/Ethnicity Ethnicity or race is a good predictor of diminished health status in America, especially for new immigrants, Native Americans, Hispanics, and AfricanAmericans. They are more likely to be poor, discriminated against, and alienated from majority society. Racial impact on health for Americans can be measured by removing minorities from analysis, then comparing majority elderly Americans with Hungarians. Hungarians are ethnically much more homogeneous than Americans, and, therefore, ethnicity cannot explain health status differences among our Hungarian sample. One exception to this homogeneity might be gypsy populations. Gypsies are an underclass that is not socially well-integrated. Unfortunately, Hungarian gypsies are outcasts and not scientifically studied. Relatively little is known about them, but they are negatively stereotyped. Gypsies are few compared to the majority population. They are inaccessible, represent a distinct culture, live in isolated neighborhoods or are highly mobile, resent intrusions, avoid public services, and elude officials census counts. We excluded gypsies for two reasons: first, because gypsies are a small proportion of the population, we would have had to greatly oversample them. Resources did not permit this. Second, gypsies could not be scientifically sampled. Only a qualitative, case study approach would have been possible, but such an approach would not contribute to the statistical analysis of the American and majority Hungarian data. Hopefully, researchers will eventually study this important ethnic group.
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Functional Status Health status measures include medical condition, symptomatology, selfperceived health status, use of medical aids, psychological status, and functional status. Our literature review, coupled with this study, suggests that only functional status poses cross-cultural interpretive problems. Hungary is a western country with many cultural similarities to Europe, especially Austria. Three functional status items were likely to be problematic: working outside the home, managing money, and telephoning. Many Hungarians live in high-rise public housing. As a result, they have no outside maintenance chores. Private homeowners have few outside chores - no lawns to mow, and postponed maintenance because of pollution, expense, availability of materials, or lack of interest. Many Americans, by contrast, must deal with homeowner chores. Managing money is much more complicated in America than Hungary. Hungary is a cash economy: Hungarians have limited access to checking accounts and credit cards. Americans, by contrast, must contend with cash, credit, and electronic banking. Telephones are unobtainable in Hungary. People wait years for one. But many have telephone access. Common practice is for neighbors to take messages and allow others to use their telephones. This is socially acceptable, and not burdensome. Only 4% of households in the Debrecen region have no access to phones. In our study, U.S. functional status measures were not modified to accommodate Hungarians. But individual items were analyzed below for biases.
Independent Living Extended families are common in Hungary, due mostly to housing shortages. Newly married couples move in with parents because they cannot find or afford housing. This arrangement is beneficial for both: grandparents babysit and children care for the elderly. As among earlier generations in America, elderly in Hungary try to remain at home, rather than in institutions as they age (Andorka 1989). This situation is changing in Hungary, as younger people move to the capital city, Budapest, or leave the country. About one-third of the elderly in Hungary and America live alone. Hungary has inadequate numbers of nursing homes and long-term care facilities compared to the U.S. America's long-term care problems are related to insurance and funding issues, not availability. Hungary uses hospitals not only for medical care, but also to support older people who are not ill but who have no where else to go. One-half of patients in some facilities should be cared for elsewhere (Megyeri 1982). This study focuses on independently-living elderly, excluding hospitalized 'social' patients. Gaining access and then sampling them is costly and complex, as in America. But independently-living elderly are a critical health policy target in and of themselves. Keeping them healthy and independent reduces health care
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costs in both countries. Health Status Models
There are many health status models available. We adopted Liang et al.'s (1991) model here. Liang showed that self-reported physical health consists of three dimensions: physical illness, functional status, and self-rated health. In medicine, physical illness is presence or absence of disease (medical condition) or its symptoms (symptomatology). Functional status, a social definition, concerns ability to cope in normal roles and social settings, sometimes using medical aids or devices. Self-rated health refers to individual perception and evaluation of health status. We added a mental health component - depression which may exacerbate physical health status or cause physical health problems. Liang et al. explored underlying structural relationships. We are only tangentially concerned with these interrelationships. Liang et al. (1991) showed that demographic characteristics - especially age, gender, education and marital status - ought to be taken into account in explaining self-reported health. These exogenous variables are good empirical predictors and theoretically relevant. Demographics also establish construct validity. From a policy perspective, demographics can be used to target people in need. Unlike Liang et al., we included poverty status and number of people in the household as independent variables. Poverty is a well-established correlate of health status. Number in household represents social support, a mediator of health status. Although demographics are important 'exogenous' variables, they are not consistently or uniformly related to health status across cultures. In Liang et al.' s study, statistical relationships among demographics and health status differed significantly for elderly Americans and Japanese. Like Liang et al., we treat demographic relationships as open questions subject to empirical testing. These demographic relationships were explored in a multivariate analysis of covariance. TWO CULTURES COMPARED We hypothesize that inadequate health care, unregulated heavily industrialized society, and unhealthful life-styles result in poorer health status among Hungarians than Americans. Health Care
Although under reform, health care delivery remains similar to that under the Communist regime ("Any Hope for Recovery" 1991; Blasszauer 1986; Csaszi and Kullberg 1985; Orosz 1991; Petrovics-Ofner 1992). Medical personnel are poorly paid (AMA 1992), many accept payments from patients "under the table" (Adam 1989; Csaszi 1990; Kullberg 1986; Megyeri 1982; Schiff 1990). Patients
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who cannot pay are denied services, endure long waits, or receive poorer quality care (Deacon 1984; Kullberg 1986; Megyeri 1982). Health care is poorly managed, because no performance incentives exist (Deacon 1984; Kullberg 1986). The average length of stay in Hungarian hospitals is 14 days, compared to 7 in the United States. High-tech and routine working equipment are scarce ("Any Hope for Recovery" 1991; Raffel and Raffel 1989). State-of-the-art treatment is often unavailable (Raffel and Raffel 1989). Hungary has 1 magnetic resonance imaging (MRI) unit. Substandard facilities force overcrowding (Lipinsky and Illsley 1990; Raffel and Raffel 1989; Schiff 1990). Patients lack choice: district physicians control access to statemonopolized clinics and hospitals (Deacon 1984). Staff treat patients badly, deterring help-seeking and increasing stigmatization (Petrovics-Ofner 1992). Patients cannot challenge poor practice (Kullberg 1986). Hungarian health care does not focus on primary care - general practice, community health, family practice, pediatrics (Deacon 1984; Raffel and Raffel 1989). Preventive medicine is insufficient. In 1983, only 14% of health care resources went to primary care. Only the sick access hospitals. Because disease is not diagnosed early through routine physicals and testing (i.e., lab work, xrays, CAT scans), treatment is more difficult, more costly, and less effective. Health care under communism had some positive aspects. Physicians were well-trained - Hungary has a strong education system, especially in math and science. Many physicians studied in the West. Because physicians lack hightech equipment, they have well-developed diagnostic skills. U.S. health care is different: more affluent and geared to the elderly, who predominate. Primary care, high-tech, and quality treatment are widely available. Because care of the elderly is funded under Medicare, Medicaid, or Supplemental Security Income (SSI), few elderly go unserved, although many lack extended care. Because American health care is profit-driven, it does not reach some poor or disadvantaged.
Industrial Society Following World War II, Hungarian Communists forcibly industrialized society, at a heavy price. Environmental protection, public health, and occupational safety were of no concern. As a result, Hungary leads all western countries and many former Communist countries in prevalence of cancer, heart disease, hypertension, and accidental injury. Hungarian mortality rates are high (512 per 100,000 for men, 255 per 100,000 for women) (Lahelma and Valkonen 1990). Life expectancy is low, 71.6 years compared to 75.7 years in the United States (Velkoff 1992), and declining. Fifty years ago, America's industrial society resembled Hungary's today. Through stricter occupational safety and environmental protection laws, a rising standard of living, and changes in public attitudes, many health threats have decreased.
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Life-style Many aspects of the Hungarian life-style lead to poor health (Csaszi 1990; Forgacs and Kokeny 1987; Gy 1986; Kullberg 1986; Makara 1991; Velkoff 1992). Hungarians use alcohol and tobacco heavily. There are 560,000 alcoholics in a country of 10 million people. Nearly one-half smoke, as compared to one-third in America (Forgacs and Kokeny 1987). Many eat foods high in fat, often because they cannot afford food of higher quality (Forgacs and Kokeny 1987). Hungarians exercise little; 9 out of 10 do not exercise or pursue a sport. Obesity is a problem: 60% of the population is overweight. These life-style factors are reflected in high mortality rates for heart, lung, and liver disease (see Table I), and mortality rates are growing at an alarming rate (Forster and Jozan 1990). TABLE I Hungary and U.S. mortality rates for selected causes of death, per 100,000 population, 1987
Hungary United States
Ischemic heart disease
Cerebrovascular disease
Chronic lung disease
Liver disease
Suicide
236 195
173 55
36 8
42 12
40 13
Source: World Health Organization 1991 World Health Statistics Annual, 1990. Geneva: WHO. Some observers believe that health status declines also resulted from the pressures of having two or more jobs, necessary to make ends meet. Stress, strained family relations, and no free time have negative health consequences (Makara 1991). This trend seems to have begun in the 1960s when Hungary liberalized its political and economic systems. The American life-style is not particularly healthy, but public attitudes are changing: smoking, drinking, and poor eating practices are declining. Health indicators are improving. Many Hungarians are pessimistic (Tamasy 1982). They tire of struggles against outside invaders and with internal politics. Elderly Hungarians experienced defeat in World War I, a communist revolution, an autocratic counterrevolution, a return to hard-line communism, a revolt against Russian hegemony, a thawing, and, finally, communism's collapse, and emerging capitalism and democracy. Hungary has the highest suicide (40/100,000 compared to 12/100,000 in the U.S.) and depression rates of any other developed country, especially among the elderly (Rihmer, Barsi, Veg, and Katona 1990).
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YOUNGSTOWN AND DEBRECEN Youngstown, Ohio and Debrecen, Hungary are industrial areas with populations of about one-quarter million (Beres 1991; Buss and Gemmel i990). Youngstown produces automobiles, steel, and metal products; Debrecen makes chemicals and food products. Both have medical schools nearby and several universities. Each is a cultural center with art galleries, theaters, and a symphony orchestra. To test the generalizability of our findings, we compared social, economic, and health data for Debrecen and Youngstown against similar regional cities. Findings suggested that neither city was atypical. METHODOLOGY
The Surveys Personal interviews were conducted in Youngstown, Ohio, and Debrecen, Hungary, with 770 and 501 elderly (62 years of age or older) people, respectively.
Youngstown. In January 1990, non-institutionalized respondents from Youngstown metropolitan area households with at least one elderly resident were interviewed. Elderly persons in nursing homes, adult day care centers, skilled nursing sites, or other long-term care facilities were excluded. Elderly persons living in retirement villages, high rises, and low income housing were included. Households were randomly sampled from telephone directories. Demographics were compared with the decennial census and local surveys employing random digit sampling frames to eliminate bias from unlisted telephone numbers and phoneless households. Interviews averaged one hour. The response rate (number of completed interviews divided by number of eligible persons in the sample) was 85%. Debrecen. Personal interviews in Debrecen replicated the Youngstown study in June 1992. Because few households have telephones, directories were not sampled. Instead, respondents were selected from physician patient lists. Under the national health service, everyone is registered with a district physician. All city districts were identified. Districts were stratified by poverty-level, the proportion of elderly, and geographical location. Within each stratum, we randomly sampled patients from physician lists. The response rate was 90%. Hereafter, the groups under study are referred to as Americans or Hungarians.
Sample Representativeness Sample demographic characteristics were representative of population data in the decennial census (Gillanders, Buss, and Gemmel 1991; Kvale, Gillanders,
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Buss, Hofstetter, and Gemmel 1990). The Hungarian sample was representative of population characteristics from physician patient lists (Gulacsi 1992). Six demographic characteristics - age, sex, marital status, education, number in household, and income - were compared in difference-of-means tests (see Table II). Two measures of income were employed, at or below official poverty and above (Incomel) and at or below 200% of official poverty and above (Income2). Groups differed significantly on six measures (see Table II). Americans were more likely to be male, older, married, living in smaller households, more educated, and wealthier than their Hungarian counterparts. These comparisons comport well with expected cultural differences. TABLE lI Demographic comparison (T-test) for Youngstown and Debrecen Demographic
Youngstown
Debrecen t-ratio
sign
Gender
males females
41.2 58.8
33.5 66.5
2.77
0.006
Age
60-69 70-74 75-79 80+ mean
43.1 25.9 17.1 13.9 72.1 years
50.4 22.8 13.2 13.6 70.1 years
5.06
0.001
Marital status
married 58.5 other 41.5 widowed 31.9 - divorced 6.2 - never married 3.5
53.0 47.0 38.1 6.0 2.0
2.04
0.042
one two three+ mean
29.3 53.0 17.7 2.0 people
30.8 49.4 19.8 2.1 people
1.88
0.060
11.1 years
8.8 years
10.38
0.001
-
Number in household
Education mean Income1
below poverty 19.3 above poverty 80.7
36.1 63.9
6.58
0.001
Income2
below 200% above 200%
96.2 3.8
15.40
0.001
52.8 47.2
Health Status Measures Functional status. Functional status measures how well people perform tasks
associated with activities of daily living (ADL) and instrumental activities of daily living (IADL). This study used the Determination of Need (DON) scale that combines ADL/IADLS and unmet needs. The DON is used in allocating health and human services in Illinois, Oklahoma, and Indiana (Illinois Depart-
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ment of Aging 1983; Kvale et al. 1990). Respondents were presented a list of 16 tasks and asked whether they had any restrictions on activity. In addition to including standard items such as telephoning, shopping, and working around the home, DON also includes a query about functional status affected by routine and special health problems. Routine health concerns general or common problems like mobility limitations associated with aging. Special health focuses on problems that are uncommon - use of wheel chair, blindness, deafness, and so on. Interviewers were provided with a manual that offers guidelines for interpreting routine and special health deficits and needs mentioned by elderly respondents (Illinois Department of Aging 1983). Routine and special health are not intended to duplicate the other 14 ADL/IADLs items. Tasks were scored "0" if the respondent experienced no restriction, "1" if restrictions were slight, "2" if moderate, and "3" if total. For each restricted task, respondents were asked how often they needed, but could not get help: 0 = no need, 1 = need met most of time, 2 = need not met most of the time, and 3 = acute need. ADL/IADL and unmet need scores were summed to yield a functional status scale. Respondents scoring at least 28 qualify for services. Respondents scoring from 9 to 27 are "at risk" (Illinois Department of Aging 1983). Scores of 8 or less indicate no significant impairment or need. Functioning was significantly different (p < 0.05) for Hungarians and Americans once gender, age, education, and Income2 were controlled by analysis of covariance (ANCOVA) although differences in unmet needs for eating did not reach significance. Symptoms. Symptoms indicate presence of medical conditions, disease processes, or dysfunction. Respondents were asked if they experienced any of 31 "symptoms or problems" (a modified version of the Hopkins Syndrome Checklist) (Derogatis, Lepinan, Rickels, Unlentruth, and Covi 1974). If they had experienced a problem, a score of "1" was assigned; "no complaints" was scored "0". Responses were summed in an index. The symptoms/problems list was not exhaustive, but captured major complaints. CNS, memory, weight loss, appetite loss, constipation, sadness, swollen ankles, fatigue, chest pain, stool, walking, pain in housework, and broken hip were significantly different (p < 0.05) for Hungarians and Americans by the above ANCOVA criteria. Subjective health status. Respondents were asked: "How would you rate your overall health at present: excellent, good, fair or poor?" Subjective health status is a key variable: it is the single best indicator of overall health and is correlated with other health status measures (Deyo and Patrick 1989). Medical condition. Twelve of the most common medical conditions or disease processes (e.g., cancer, hypertension, heart disease, etc.) afflicting the elderly were presented (Pope 1988). Responses were scored "1" = presence of any condition, "0" = no condition, and summed. Only heart disease and broken hip were significantly different (p < 0.05) for both groups by above ANCOVA
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criteria for the list.
Medical aids. Use of medical aids not only reflects the presence of dysfunction or disability, but also health care access. Elderly people were asked: "Do you use any of the following special aids or equipment: dentures, cane, walker, wheelchair, leg brace, back brace, pacemaker, hearing aid or glasses?" Responses were scored "1" = use an aid, "0" = aid not used, and summed. Except for backbrace, leg brace, and wheelchair, all aids were significantly different between nations, controlling for gender, age, education, and Income2.
Depression. The Burnam Depression Scale was used to measure depression, including dysthymia (Burnam, Wells, Leake, and Landsverk 1988). The instrumentation is a modification of the CEDS-D scale developed for the Medical Outcome Studies. Tested on primary care patients, the scale demonstrated sensitivity and positive predictive value in detecting depressive disorders, especially recent disorders and those which meet full DSM-III criteria. Except for sleep disorder and sadness, indicators were statistically significant (p < 0.05), for Hungarians and Americans controlling for gender, age, education, and Income2. FINDINGS
Health and Demographics Bivariate analysis. Analysis of Variance (ANOVA) was performed to determine whether American and Hungarian elderly differed significantly on health status when taking into account gender, marital status, education, Incomel, Income2, and age (see Table HI). American elderly people were healthier on all measures than were Hungarians, although differences for medical aids usage were not statistically significant. Hungarians were more at risk (score > 7) of diminished functional status. Americans averaged three symptoms, while Hungarians averaged nine. Medical conditions and disease processes were much less prevalent among Americans than Hungarians. Americans were less depressed than Hungarians. Americans regarded their health as excellent or good, but Hungarians reported their health to be only fair to poor. Gender, age, education and marital status were either significant or at least patterned as hypothesized on all health status measures. Medical aids usage was again an exception. Generally, women, younger elders, better educated and married people enjoyed better health than others. Medical aids did not differ among groups. Incomel, above or below official poverty, was not statistically significant for any health status measure as hypothesized: the poor in both countries have comparable health problems. Moving to a higher income - above or below 200% of poverty - Americans emerged in better health than Hungarians on all
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health status measures. Because official poverty did not discriminate, it was deleted from the multivariate analyses to follow. Even though health status differed at 200% of poverty, there were so few Hungarians above 200% that multivariate analysis was impossible. Therefore, we focused on the next section's analysis on three demographics - age, gender, and education, found to be correlated with health status. To sort out possible racial/ethnic effects stemming from the American sample, A N O V A was run on health status for Americans, excluding minorities, and Hungarians. Results paralleled exactly those in Table 111 (tabular data were not reported to save space). American health status was much better on subjective health, medical condition, functional status, symptomatology, and depression. As before, medical aids was not statistically significant. Two reasons account for this: (1) minorities in the American sample were few, 20%; and (2) health status of minority and majority elderly Americans in Youngstown were similar (Kvale et al. 1990). Individual functional status items were scrutinized by country to discover possible cultural biases. Each A D L and I A D L showed Americans to be better able to function than Hungarians. It is clear that inability to function is associated with both 'routine' and 'special' health problems. These patterns clearly replicate, on a micro-level, larger patterns reflected among health status measures (See Table IV). TABLE IV Function status - those with no problems - by Americans and Hungarians Item:
Americans
Hungarians
)22
Telephoning Laundry Managing money Dressing Work outside home Grooming Shopping Bathing In-out bed Bowel/bladder Preparing meals Routine health Eating Special health Housework Being alone
96.8 93,7 96.4 96.9 93.1 97.6 92.4 95.4 92.3 97.3 94.6 97.0 96.8 96.1 90.3 96.3
84.4 72.1 93.4 89.8 70.9 90.2 71.1 85.8 83.2 88.8 84.0 62.9 93.8 60.7 71.7 78.4
72.30* 116.95" 9.07** 31.13 * 123.68" 33.14" 120.00* 44.86* 29.51 * 26.37* 41.63* 260.90* 9.21"* 263.75" 97.05* 110.51"
Note: Figures are percentages. "*" Indicates statistical significance at p < 0.001; "**" at
p < 0.02.
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Additionally, with respect to working outside the home, other related items shopping, housework and doing laundry - have similar prevalence levels and were inter-correlated. Also, working outside the home, a functional status measure, was associated with related symptoms: pain associated with working in home (gamma = 0.76 and 0.77), difficulty in walking (gamma -- 0.82 and 0.68), and able to move about freely (gamma = 0.74 and 0.50) for Americans and Hungarians, respectively. Loss of hearing was associated with problems in telephoning (gamma = 0.56 and 0.42) for Americans and Hungarians, respectively. And poor eyesight was associated with managing money problems (gamma = 0.53 and 0.47) for Americans and Hungarians, respectively. Concerns about telephoning, working outside the home, and managing money probably are not cultural artifacts, but are problematic for Hungarians as well as Americans because of physical limitations. Analysis of individual items in the symptomatology index revealed Hungarians were significantly worse off than Americans on 25 of the 31 symptoms. Six symptoms were not significantly different for Americans and Hungarians. In no case were Hungarians less symptomatic than Americans (see Table V). On 10 of 12 major medical conditions prevalent among the elderly, Hungarians were significantly in poorer health than Americans. The greatest disparity in health appeared to be in psychological problems, cognitive impairment, respiratory problems, and arthritis. In two cases - cancer and broken hip Hungarians and Americans were identical. Hungarians were not better off on any of the medical conditions listed (see Table VI).
Multivariate Analysis Other comparisons between Hungarian and American elderly were made through multivariate analysis of covariance (MANCOVA) (Tabachnick and Fidell 1989). A 2 x 2 between-subjects MANCOVA was computed on 6 health status measures using country and gender as independent variables and age and education as covariates. First, from Table V we note that controlling for age and education, the main effects of country and gender were significant (p < 0.05) except provision of medical aids by country (p < 0.05). Second, again controlling for age and education, effects of country and gender were significant (p < 0.05) except for medical conditions which nearly attained significance (p < 0.85). Finally, the PiIlais trace, associated with differences among health status measures considered collectively by MANCOVA, after controlling for age and education, was significantly (p < 0.001) different by country, gender, and country and gender (see Table VII). Table VIII shows product/moment correlation coefficients among dependent health status variables. All health status measures were moderately to highly correlated, suggesting that health problems are related, as hypothesized by Liang et al. (1991). The only exception was the lack of significant correlation between medical condition and use of medical aids. Next, discriminant analysis was employed to determine to what extent dependent health status variables predicted whether a person was either an
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TABLE V Analysis of variance: Symptomatology items by Americans and Hungarians (mean scores) a Symptoms:
Americans
Hungarians
F-ratio
P
Can't get body to move Headaches Dizziness, tendency to fall Loss of hearing Vision impairment Taste, smell impairments Fits, seizures Severe pain See and hear things others do not Memory problems Weight loss Appetite loss Sleep disturbances Constipation Feeling sad Shortness o f breath Swollen ankles and feet Tire easily Chest pain Abdominal pain Stool change Blood in stool Control stool Blood in urine Urination Blood vagina Difficulty walking Painful joints Difficulty housework Broken bones Broken hip
0.12 0.11
0.47 0.49
222.06 275.93
0.001 O.001
0.11 0.21 0.15 0.04 0.01 0.12
0.55 0.30 0.55 0.09 0.27 0.39
394.35 12.83 268.17 11.87 265.17 138.76
0.001 0.001
0.01 0.12 0.07 0.06 0.15 0.11 0.08 0.19 0.18 0.23 0.07 0.05 0.07 0.02 0.01 0.01 0.03 0.00 0.20 0.31 0.09 0.05 0.03
0.02 0.19 0.19 0.19 0.44 0.24 0.41 0.27 0.47 0.72 0.22 0.16 0.18 0.01 0.07 0.02 0.10 0.01 0.46 0.58 0.27 0.06 0.02
0.99 11.75 42.89 47.96 150.59 35.43 234.40 11.79 131.76 405.24 64.20 47.93 33.49 1.34 31.85 0.89 21.99 0.91 109.65 106.27 78.54 0.84 1.13
0.001 0.001 0.001 0.001
0.319 0.001 0.001 0.001 0.001 O.001 0.001 O.001 0.001 0.001 0.001 0.001 0.001
0.247 0.001
0.345 O.001
0.340 0.001 0.001 0.001
0.359 0.289
Items scored "0" for absent, "1" for present. Scores may be converted into percentages by multiplying by 100. elderly American or Hungarian. Americans and Hungarians differed significantly when taking all health status measures into account (Wilk's lambda = 0.573, F = 157.43, p < 0 . 0 0 1 ) . Forty-three percent of discriminant score variability was attributable to between-group differences (canonical correlation = 0.653). Canonical discriminant functions, taken at the group means (centroids), also showed how disparate health status was: Americans = -0.69, Hungarians = 1.07, difference = 1.38. Some 82% of the cases were correctly identified as Americans or Hungarians, taking into account health status variables (see Table IX). This is a substantial improvement over the prior
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TABLE VI Analysis of variance: Medical condition by Americans and Hungarians (mean scores)a Medical condition:
Americans
Hungarians
F-ratio
P
Cancer Diabetes, thyroid Blood diseases Psychological problems Hypertension Heart disease Respiratory Ulcers, hernia, cirrhosis Female genital Arthritis, back problems Memory problems Broken hip
0.01 0.00 0.00 0.01 0.01 0.01 0.01 0.00 0.00 0.00 0.02 0.00
0.01 0.02 0.02 0.06 0.03 0.03 0.05 0.03 0.01 0.24 0.13 0.00
1.016 9.960 12.956 33.468 6.675 10.104 26.483 18.106 6.411 223.827 62.831 0.043
0.314 0.002 0.001 0.001 O.01 0.002 O.001 0.001 0. 01 0.001
0.001 0.835
Items scored "0" for absent, "1" for present. Scores may be converted into percentages by multiplying by 100. a
TABLE VII Tests of selected variables by gender and country controlling for age end educationa Country and gender
Gender
Country
Variable:
F(2.1176) P
HEALTH STATUS AMONG ELDERLY HUNGARIANS AND AMERICANS
ABSTRACT. Selected health status data for elderly populations from similar industrial cities - Youngstown, Ohio, USA, and Debrecen, Hungary - were compared. Because of their impoverished health care system, unregulated heavily industrialized society, and unhealthful life-styles Hungarians were hypothesized to have poorer health status than Americans, even after taking into account demographic mediating factors. The study provides a health status baseline for elderly Hungarians shortly after communism's fall in 1989-1990 and shows how great a gap exists between Hungarian health status and that in the West. Hungarians were in much poorer health as measured by functional status, symptomatology, medical condition, depression, and subjective health status. Distinctions persisted when controlling for gender, age, and education. Poverty-level (and income) did not explain health status differences. The paper concludes that Hungary should pay more attention to health promotion, prevention, and primary care, as well as to reforming patient management in hospitals, nursing homes, and home care programs.
Key Words: Hungary, United States, health status, elderly Even before the fall of communism in 1989-1990, Hungarians had begun health care reform ("Any Hope of Recovery" 1991; Forgacs and Kokeny 1987; Kaser 1976; Weinerman 1969). In 1972, the Hungarian government declared that every citizen was entitled to free medical care. In 1986, Health for All, a nationwide program to improve Hungarian lifestyles through health promotion and education, was launched. In 1988, health and welfare were merged into the Ministry of Health and Social Affairs to better manage illness related to poverty. In 1989, Social Security (pensions) and Health Insurance funds were separated and required to become self-financing. In 1991, Hungarians created a marketoriented health care system moving away from a socialist to a western model. Government's motivation for reform was the population's diminishing health status, the rising cost of health care, and the ineffectiveness of the socialist health care system (Csaszi and Kulberg 1985; Forgacs and Kokeny 1987; "Program of Reform of Our Health Care System" 1991; Raffel and Raffel 1989). Health reform targeted elderly and young people (not addressed here). The elderly are the fastest growing population segment, consume most health care services, have few personal resources, and need medical care (Csaszi and Kulberg 1985). Many in government, as is the case in America, feel they have a social compact to care for the elderly. Existing health status research, especially on the elderly, is inadequate for policy-making in Hungary. With few exceptions (see Mogey 1989) a literature review turned up mostly articles summarizing prevalence of mortality and morbidity by age for major disease categories. Lack of information makes health care planning difficult and impedes foreign governments and world health organizations in helping with funding and technical assistance. Journal of Cross-Cultural Gerontology 9: 301-322, 1994. 9 1994 Kluwer Academic Publishers. Printed in the Netherlands.
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Health research was often little valued except when serving Communist Party interests (Kullberg 1986). Research costs could not be justified when competing with service delivery needs. When health was studied at all, the resulting reports, hidden in obscure, limited circulation journals, were often not available in English or were very outdated. Frequently health status measures were incompatible with those used in the West, rendering cross-cultural comparisons difficult (e.g., Tamasy 1982). Some studies were of dubious quality (Kullberg 1986). Adequate data in any form do not exist (Cszaszi 1990). As broader social and political reforms emerge (i.e., democratization, privatization, and capitalism), systematic research will facilitate more effective use of scarce Hungarian health care resources. This study compares health status data for elderly populations, systematically collected from comparable industrial cities - Debrecen, Hungary and Youngstown, Ohio, USA. The comparison (1) provides Hungarian policymakers and health care researchers with a baseline against which to measure elderly health status improvements as new reforms are fully implemented, and (2) shows how far Hungarian health policy-makers are from achieving health status outcomes comparable to those generally found in the West. This does not imply that American elderly health status is optimal, but only that Hungarian health care reforms have targeted U.S. and European health status achievements as their goals. This paper looks first at cross-cultural gerontological research issues in the Hungarian and American contexts, and how they were resolved in this study. Next, it compares both cultures and the two study cities. Then results are presented, followed by their implications. COMPARATIVE HEALTH STATUS STUDIES Comparative health studies must be cautiously approached. These issues and their resolution are discussed below. We follow the lead of Ikels (1991) and Liang, Bennett, Whitelaw, and Maeda (1991) in identifying key issues for review. Translation
Numerous problems occur in translation. In our study, for example, we initially asked about social worker contact to explore formal help-giving networks. Hungarians, at the time, had no concept of social worker - social work was not a formal academic discipline - and under communism, since in theory social problems did not exist, social worker was not an occupation. To average citizens, social workers, when directly translated from English into Hungarian, can mean workers employed by state-owned enterprises - the proletariat. Questions asked of Americans were standard U.S. health status measures, also widely used in other countries. To insure that our American-based questionnaire was meaningfully translated into Hungarian, it was first rendered from English
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into Hungarian by a native Hungarian medical doctor. The translation was reviewed by two Hungarian gerontologists in Lajos Kossuth University's Sociology Institute. The questionnaire was reviewed by a Hungarian-speaking American social scientist. Questionnaires were pre-tested on 50 elderly Hungarians. All apparent linguistic anomalies were resolved. Income
Determining income is problematic in American studies and exacerbated in comparative studies. In the U.S. income can be measured as money received from all sources, or income can be expanded to include non-cash benefits (e.g., Medicare, Medicaid, food stamps, respite care, etc.) by converting benefit values into cash. So, for example, Medicare health insurance, a government program, has a comparable market price established by private health insurance premiums. In Hungary, elderly people receive small pensions, less than $100 monthly. But access to services remains great - free health care and subsidized vacations, housing, education, transportation, cultural programs, and so on (though all of these are being privatized). Unlike in the U.S., there is no market value for these benefits as yet. Using income alone to measure wealth or poverty in transforming socialist countries is misleading. To complicate matters, Hungarians use the underground economy, often bartering for goods and services rather than paying cash. In Hungary, building a house using state-owned contractors is difficult. Costs are high, waiting is long, work is shoddy. But black market construction is booming. Craftsmen and homeowners-to-be barter for labor or goods. Cash income fails to take into account gains in wealth through bartering. Black market exchanges frequently use hard currency because of inflated (25-30% annually), only partially convertible Hungarian currency. Because black marketeering is an illegal, imprisonable offense, Hungarians are unlikely to report some hard currency income. Hungary is still emerging from a socialist economy characterized by modest incomes with little spread between high and low earners. With the exception of high-level Communist Party members, there is not enough variation in income levels to explain health status differences. This is generally not so in the United States. Though income comparisons between western and former socialist countries are problematic, solutions do exist. In this study, Hungarians were asked to enumerate cash income from all legal sources. Then official levels $80 ("Affected by Change" 1992) - were used to classify people above or below poverty, and above or below 200% of poverty. Although this does not solve the problem, it has health policy implications: government allocates benefits and establishes need based on official poverty status, not unreported income. Another solution is to analyze education. Hungary's educational system even under communism is highly selective, tending to exclude poor people. Consequently, highly educated Hungarians tend to have higher incomes and occupa-
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tional status than those with less education. The same is true for the United States. Therefore, education may serve as a proxy for income.
Age~Retirement Hungarians retire earlier - 55 years of age for women, 60 for men - than Americans - 65 years of age. Looking at retired people in both countries, therefore, can be misleading. We studied people 62 years of age or older because of America's higher age limit, and because it is a standard cutoff age (along with 65 years) for American elderly studies. This is also the age at which biological and physiological developmental changes begin to increase the prevalence of disease and dysfunction (Tamasy 1982). Five percent of Hungarians worked after retirement age under the Old Regime. But under emerging capitalism, this percentage will likely increase as firms cannot afford to retire people early and government cannot assume pension liabilities. In fact, government has fixed legal retirement at 62 years. Our cut-off age, then, is important for Hungarian health policy.
Race/Ethnicity Ethnicity or race is a good predictor of diminished health status in America, especially for new immigrants, Native Americans, Hispanics, and AfricanAmericans. They are more likely to be poor, discriminated against, and alienated from majority society. Racial impact on health for Americans can be measured by removing minorities from analysis, then comparing majority elderly Americans with Hungarians. Hungarians are ethnically much more homogeneous than Americans, and, therefore, ethnicity cannot explain health status differences among our Hungarian sample. One exception to this homogeneity might be gypsy populations. Gypsies are an underclass that is not socially well-integrated. Unfortunately, Hungarian gypsies are outcasts and not scientifically studied. Relatively little is known about them, but they are negatively stereotyped. Gypsies are few compared to the majority population. They are inaccessible, represent a distinct culture, live in isolated neighborhoods or are highly mobile, resent intrusions, avoid public services, and elude officials census counts. We excluded gypsies for two reasons: first, because gypsies are a small proportion of the population, we would have had to greatly oversample them. Resources did not permit this. Second, gypsies could not be scientifically sampled. Only a qualitative, case study approach would have been possible, but such an approach would not contribute to the statistical analysis of the American and majority Hungarian data. Hopefully, researchers will eventually study this important ethnic group.
ELDERLYHUNGARIANAND AMERICANHEALTHSTATUS
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Functional Status Health status measures include medical condition, symptomatology, selfperceived health status, use of medical aids, psychological status, and functional status. Our literature review, coupled with this study, suggests that only functional status poses cross-cultural interpretive problems. Hungary is a western country with many cultural similarities to Europe, especially Austria. Three functional status items were likely to be problematic: working outside the home, managing money, and telephoning. Many Hungarians live in high-rise public housing. As a result, they have no outside maintenance chores. Private homeowners have few outside chores - no lawns to mow, and postponed maintenance because of pollution, expense, availability of materials, or lack of interest. Many Americans, by contrast, must deal with homeowner chores. Managing money is much more complicated in America than Hungary. Hungary is a cash economy: Hungarians have limited access to checking accounts and credit cards. Americans, by contrast, must contend with cash, credit, and electronic banking. Telephones are unobtainable in Hungary. People wait years for one. But many have telephone access. Common practice is for neighbors to take messages and allow others to use their telephones. This is socially acceptable, and not burdensome. Only 4% of households in the Debrecen region have no access to phones. In our study, U.S. functional status measures were not modified to accommodate Hungarians. But individual items were analyzed below for biases.
Independent Living Extended families are common in Hungary, due mostly to housing shortages. Newly married couples move in with parents because they cannot find or afford housing. This arrangement is beneficial for both: grandparents babysit and children care for the elderly. As among earlier generations in America, elderly in Hungary try to remain at home, rather than in institutions as they age (Andorka 1989). This situation is changing in Hungary, as younger people move to the capital city, Budapest, or leave the country. About one-third of the elderly in Hungary and America live alone. Hungary has inadequate numbers of nursing homes and long-term care facilities compared to the U.S. America's long-term care problems are related to insurance and funding issues, not availability. Hungary uses hospitals not only for medical care, but also to support older people who are not ill but who have no where else to go. One-half of patients in some facilities should be cared for elsewhere (Megyeri 1982). This study focuses on independently-living elderly, excluding hospitalized 'social' patients. Gaining access and then sampling them is costly and complex, as in America. But independently-living elderly are a critical health policy target in and of themselves. Keeping them healthy and independent reduces health care
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costs in both countries. Health Status Models
There are many health status models available. We adopted Liang et al.'s (1991) model here. Liang showed that self-reported physical health consists of three dimensions: physical illness, functional status, and self-rated health. In medicine, physical illness is presence or absence of disease (medical condition) or its symptoms (symptomatology). Functional status, a social definition, concerns ability to cope in normal roles and social settings, sometimes using medical aids or devices. Self-rated health refers to individual perception and evaluation of health status. We added a mental health component - depression which may exacerbate physical health status or cause physical health problems. Liang et al. explored underlying structural relationships. We are only tangentially concerned with these interrelationships. Liang et al. (1991) showed that demographic characteristics - especially age, gender, education and marital status - ought to be taken into account in explaining self-reported health. These exogenous variables are good empirical predictors and theoretically relevant. Demographics also establish construct validity. From a policy perspective, demographics can be used to target people in need. Unlike Liang et al., we included poverty status and number of people in the household as independent variables. Poverty is a well-established correlate of health status. Number in household represents social support, a mediator of health status. Although demographics are important 'exogenous' variables, they are not consistently or uniformly related to health status across cultures. In Liang et al.' s study, statistical relationships among demographics and health status differed significantly for elderly Americans and Japanese. Like Liang et al., we treat demographic relationships as open questions subject to empirical testing. These demographic relationships were explored in a multivariate analysis of covariance. TWO CULTURES COMPARED We hypothesize that inadequate health care, unregulated heavily industrialized society, and unhealthful life-styles result in poorer health status among Hungarians than Americans. Health Care
Although under reform, health care delivery remains similar to that under the Communist regime ("Any Hope for Recovery" 1991; Blasszauer 1986; Csaszi and Kullberg 1985; Orosz 1991; Petrovics-Ofner 1992). Medical personnel are poorly paid (AMA 1992), many accept payments from patients "under the table" (Adam 1989; Csaszi 1990; Kullberg 1986; Megyeri 1982; Schiff 1990). Patients
ELDERLYHUNGARIANAND AMERICANHEALTHSTATUS
307
who cannot pay are denied services, endure long waits, or receive poorer quality care (Deacon 1984; Kullberg 1986; Megyeri 1982). Health care is poorly managed, because no performance incentives exist (Deacon 1984; Kullberg 1986). The average length of stay in Hungarian hospitals is 14 days, compared to 7 in the United States. High-tech and routine working equipment are scarce ("Any Hope for Recovery" 1991; Raffel and Raffel 1989). State-of-the-art treatment is often unavailable (Raffel and Raffel 1989). Hungary has 1 magnetic resonance imaging (MRI) unit. Substandard facilities force overcrowding (Lipinsky and Illsley 1990; Raffel and Raffel 1989; Schiff 1990). Patients lack choice: district physicians control access to statemonopolized clinics and hospitals (Deacon 1984). Staff treat patients badly, deterring help-seeking and increasing stigmatization (Petrovics-Ofner 1992). Patients cannot challenge poor practice (Kullberg 1986). Hungarian health care does not focus on primary care - general practice, community health, family practice, pediatrics (Deacon 1984; Raffel and Raffel 1989). Preventive medicine is insufficient. In 1983, only 14% of health care resources went to primary care. Only the sick access hospitals. Because disease is not diagnosed early through routine physicals and testing (i.e., lab work, xrays, CAT scans), treatment is more difficult, more costly, and less effective. Health care under communism had some positive aspects. Physicians were well-trained - Hungary has a strong education system, especially in math and science. Many physicians studied in the West. Because physicians lack hightech equipment, they have well-developed diagnostic skills. U.S. health care is different: more affluent and geared to the elderly, who predominate. Primary care, high-tech, and quality treatment are widely available. Because care of the elderly is funded under Medicare, Medicaid, or Supplemental Security Income (SSI), few elderly go unserved, although many lack extended care. Because American health care is profit-driven, it does not reach some poor or disadvantaged.
Industrial Society Following World War II, Hungarian Communists forcibly industrialized society, at a heavy price. Environmental protection, public health, and occupational safety were of no concern. As a result, Hungary leads all western countries and many former Communist countries in prevalence of cancer, heart disease, hypertension, and accidental injury. Hungarian mortality rates are high (512 per 100,000 for men, 255 per 100,000 for women) (Lahelma and Valkonen 1990). Life expectancy is low, 71.6 years compared to 75.7 years in the United States (Velkoff 1992), and declining. Fifty years ago, America's industrial society resembled Hungary's today. Through stricter occupational safety and environmental protection laws, a rising standard of living, and changes in public attitudes, many health threats have decreased.
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Life-style Many aspects of the Hungarian life-style lead to poor health (Csaszi 1990; Forgacs and Kokeny 1987; Gy 1986; Kullberg 1986; Makara 1991; Velkoff 1992). Hungarians use alcohol and tobacco heavily. There are 560,000 alcoholics in a country of 10 million people. Nearly one-half smoke, as compared to one-third in America (Forgacs and Kokeny 1987). Many eat foods high in fat, often because they cannot afford food of higher quality (Forgacs and Kokeny 1987). Hungarians exercise little; 9 out of 10 do not exercise or pursue a sport. Obesity is a problem: 60% of the population is overweight. These life-style factors are reflected in high mortality rates for heart, lung, and liver disease (see Table I), and mortality rates are growing at an alarming rate (Forster and Jozan 1990). TABLE I Hungary and U.S. mortality rates for selected causes of death, per 100,000 population, 1987
Hungary United States
Ischemic heart disease
Cerebrovascular disease
Chronic lung disease
Liver disease
Suicide
236 195
173 55
36 8
42 12
40 13
Source: World Health Organization 1991 World Health Statistics Annual, 1990. Geneva: WHO. Some observers believe that health status declines also resulted from the pressures of having two or more jobs, necessary to make ends meet. Stress, strained family relations, and no free time have negative health consequences (Makara 1991). This trend seems to have begun in the 1960s when Hungary liberalized its political and economic systems. The American life-style is not particularly healthy, but public attitudes are changing: smoking, drinking, and poor eating practices are declining. Health indicators are improving. Many Hungarians are pessimistic (Tamasy 1982). They tire of struggles against outside invaders and with internal politics. Elderly Hungarians experienced defeat in World War I, a communist revolution, an autocratic counterrevolution, a return to hard-line communism, a revolt against Russian hegemony, a thawing, and, finally, communism's collapse, and emerging capitalism and democracy. Hungary has the highest suicide (40/100,000 compared to 12/100,000 in the U.S.) and depression rates of any other developed country, especially among the elderly (Rihmer, Barsi, Veg, and Katona 1990).
ELDERLYHUNGARIANAND AMERICANHEALTHSTATUS
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YOUNGSTOWN AND DEBRECEN Youngstown, Ohio and Debrecen, Hungary are industrial areas with populations of about one-quarter million (Beres 1991; Buss and Gemmel i990). Youngstown produces automobiles, steel, and metal products; Debrecen makes chemicals and food products. Both have medical schools nearby and several universities. Each is a cultural center with art galleries, theaters, and a symphony orchestra. To test the generalizability of our findings, we compared social, economic, and health data for Debrecen and Youngstown against similar regional cities. Findings suggested that neither city was atypical. METHODOLOGY
The Surveys Personal interviews were conducted in Youngstown, Ohio, and Debrecen, Hungary, with 770 and 501 elderly (62 years of age or older) people, respectively.
Youngstown. In January 1990, non-institutionalized respondents from Youngstown metropolitan area households with at least one elderly resident were interviewed. Elderly persons in nursing homes, adult day care centers, skilled nursing sites, or other long-term care facilities were excluded. Elderly persons living in retirement villages, high rises, and low income housing were included. Households were randomly sampled from telephone directories. Demographics were compared with the decennial census and local surveys employing random digit sampling frames to eliminate bias from unlisted telephone numbers and phoneless households. Interviews averaged one hour. The response rate (number of completed interviews divided by number of eligible persons in the sample) was 85%. Debrecen. Personal interviews in Debrecen replicated the Youngstown study in June 1992. Because few households have telephones, directories were not sampled. Instead, respondents were selected from physician patient lists. Under the national health service, everyone is registered with a district physician. All city districts were identified. Districts were stratified by poverty-level, the proportion of elderly, and geographical location. Within each stratum, we randomly sampled patients from physician lists. The response rate was 90%. Hereafter, the groups under study are referred to as Americans or Hungarians.
Sample Representativeness Sample demographic characteristics were representative of population data in the decennial census (Gillanders, Buss, and Gemmel 1991; Kvale, Gillanders,
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Buss, Hofstetter, and Gemmel 1990). The Hungarian sample was representative of population characteristics from physician patient lists (Gulacsi 1992). Six demographic characteristics - age, sex, marital status, education, number in household, and income - were compared in difference-of-means tests (see Table II). Two measures of income were employed, at or below official poverty and above (Incomel) and at or below 200% of official poverty and above (Income2). Groups differed significantly on six measures (see Table II). Americans were more likely to be male, older, married, living in smaller households, more educated, and wealthier than their Hungarian counterparts. These comparisons comport well with expected cultural differences. TABLE lI Demographic comparison (T-test) for Youngstown and Debrecen Demographic
Youngstown
Debrecen t-ratio
sign
Gender
males females
41.2 58.8
33.5 66.5
2.77
0.006
Age
60-69 70-74 75-79 80+ mean
43.1 25.9 17.1 13.9 72.1 years
50.4 22.8 13.2 13.6 70.1 years
5.06
0.001
Marital status
married 58.5 other 41.5 widowed 31.9 - divorced 6.2 - never married 3.5
53.0 47.0 38.1 6.0 2.0
2.04
0.042
one two three+ mean
29.3 53.0 17.7 2.0 people
30.8 49.4 19.8 2.1 people
1.88
0.060
11.1 years
8.8 years
10.38
0.001
-
Number in household
Education mean Income1
below poverty 19.3 above poverty 80.7
36.1 63.9
6.58
0.001
Income2
below 200% above 200%
96.2 3.8
15.40
0.001
52.8 47.2
Health Status Measures Functional status. Functional status measures how well people perform tasks
associated with activities of daily living (ADL) and instrumental activities of daily living (IADL). This study used the Determination of Need (DON) scale that combines ADL/IADLS and unmet needs. The DON is used in allocating health and human services in Illinois, Oklahoma, and Indiana (Illinois Depart-
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ment of Aging 1983; Kvale et al. 1990). Respondents were presented a list of 16 tasks and asked whether they had any restrictions on activity. In addition to including standard items such as telephoning, shopping, and working around the home, DON also includes a query about functional status affected by routine and special health problems. Routine health concerns general or common problems like mobility limitations associated with aging. Special health focuses on problems that are uncommon - use of wheel chair, blindness, deafness, and so on. Interviewers were provided with a manual that offers guidelines for interpreting routine and special health deficits and needs mentioned by elderly respondents (Illinois Department of Aging 1983). Routine and special health are not intended to duplicate the other 14 ADL/IADLs items. Tasks were scored "0" if the respondent experienced no restriction, "1" if restrictions were slight, "2" if moderate, and "3" if total. For each restricted task, respondents were asked how often they needed, but could not get help: 0 = no need, 1 = need met most of time, 2 = need not met most of the time, and 3 = acute need. ADL/IADL and unmet need scores were summed to yield a functional status scale. Respondents scoring at least 28 qualify for services. Respondents scoring from 9 to 27 are "at risk" (Illinois Department of Aging 1983). Scores of 8 or less indicate no significant impairment or need. Functioning was significantly different (p < 0.05) for Hungarians and Americans once gender, age, education, and Income2 were controlled by analysis of covariance (ANCOVA) although differences in unmet needs for eating did not reach significance. Symptoms. Symptoms indicate presence of medical conditions, disease processes, or dysfunction. Respondents were asked if they experienced any of 31 "symptoms or problems" (a modified version of the Hopkins Syndrome Checklist) (Derogatis, Lepinan, Rickels, Unlentruth, and Covi 1974). If they had experienced a problem, a score of "1" was assigned; "no complaints" was scored "0". Responses were summed in an index. The symptoms/problems list was not exhaustive, but captured major complaints. CNS, memory, weight loss, appetite loss, constipation, sadness, swollen ankles, fatigue, chest pain, stool, walking, pain in housework, and broken hip were significantly different (p < 0.05) for Hungarians and Americans by the above ANCOVA criteria. Subjective health status. Respondents were asked: "How would you rate your overall health at present: excellent, good, fair or poor?" Subjective health status is a key variable: it is the single best indicator of overall health and is correlated with other health status measures (Deyo and Patrick 1989). Medical condition. Twelve of the most common medical conditions or disease processes (e.g., cancer, hypertension, heart disease, etc.) afflicting the elderly were presented (Pope 1988). Responses were scored "1" = presence of any condition, "0" = no condition, and summed. Only heart disease and broken hip were significantly different (p < 0.05) for both groups by above ANCOVA
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TERRYF. BUSSET AL.
criteria for the list.
Medical aids. Use of medical aids not only reflects the presence of dysfunction or disability, but also health care access. Elderly people were asked: "Do you use any of the following special aids or equipment: dentures, cane, walker, wheelchair, leg brace, back brace, pacemaker, hearing aid or glasses?" Responses were scored "1" = use an aid, "0" = aid not used, and summed. Except for backbrace, leg brace, and wheelchair, all aids were significantly different between nations, controlling for gender, age, education, and Income2.
Depression. The Burnam Depression Scale was used to measure depression, including dysthymia (Burnam, Wells, Leake, and Landsverk 1988). The instrumentation is a modification of the CEDS-D scale developed for the Medical Outcome Studies. Tested on primary care patients, the scale demonstrated sensitivity and positive predictive value in detecting depressive disorders, especially recent disorders and those which meet full DSM-III criteria. Except for sleep disorder and sadness, indicators were statistically significant (p < 0.05), for Hungarians and Americans controlling for gender, age, education, and Income2. FINDINGS
Health and Demographics Bivariate analysis. Analysis of Variance (ANOVA) was performed to determine whether American and Hungarian elderly differed significantly on health status when taking into account gender, marital status, education, Incomel, Income2, and age (see Table HI). American elderly people were healthier on all measures than were Hungarians, although differences for medical aids usage were not statistically significant. Hungarians were more at risk (score > 7) of diminished functional status. Americans averaged three symptoms, while Hungarians averaged nine. Medical conditions and disease processes were much less prevalent among Americans than Hungarians. Americans were less depressed than Hungarians. Americans regarded their health as excellent or good, but Hungarians reported their health to be only fair to poor. Gender, age, education and marital status were either significant or at least patterned as hypothesized on all health status measures. Medical aids usage was again an exception. Generally, women, younger elders, better educated and married people enjoyed better health than others. Medical aids did not differ among groups. Incomel, above or below official poverty, was not statistically significant for any health status measure as hypothesized: the poor in both countries have comparable health problems. Moving to a higher income - above or below 200% of poverty - Americans emerged in better health than Hungarians on all
ELDERLY HUNGARIAN AND AMERICAN HEALTH STATUS
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health status measures. Because official poverty did not discriminate, it was deleted from the multivariate analyses to follow. Even though health status differed at 200% of poverty, there were so few Hungarians above 200% that multivariate analysis was impossible. Therefore, we focused on the next section's analysis on three demographics - age, gender, and education, found to be correlated with health status. To sort out possible racial/ethnic effects stemming from the American sample, A N O V A was run on health status for Americans, excluding minorities, and Hungarians. Results paralleled exactly those in Table 111 (tabular data were not reported to save space). American health status was much better on subjective health, medical condition, functional status, symptomatology, and depression. As before, medical aids was not statistically significant. Two reasons account for this: (1) minorities in the American sample were few, 20%; and (2) health status of minority and majority elderly Americans in Youngstown were similar (Kvale et al. 1990). Individual functional status items were scrutinized by country to discover possible cultural biases. Each A D L and I A D L showed Americans to be better able to function than Hungarians. It is clear that inability to function is associated with both 'routine' and 'special' health problems. These patterns clearly replicate, on a micro-level, larger patterns reflected among health status measures (See Table IV). TABLE IV Function status - those with no problems - by Americans and Hungarians Item:
Americans
Hungarians
)22
Telephoning Laundry Managing money Dressing Work outside home Grooming Shopping Bathing In-out bed Bowel/bladder Preparing meals Routine health Eating Special health Housework Being alone
96.8 93,7 96.4 96.9 93.1 97.6 92.4 95.4 92.3 97.3 94.6 97.0 96.8 96.1 90.3 96.3
84.4 72.1 93.4 89.8 70.9 90.2 71.1 85.8 83.2 88.8 84.0 62.9 93.8 60.7 71.7 78.4
72.30* 116.95" 9.07** 31.13 * 123.68" 33.14" 120.00* 44.86* 29.51 * 26.37* 41.63* 260.90* 9.21"* 263.75" 97.05* 110.51"
Note: Figures are percentages. "*" Indicates statistical significance at p < 0.001; "**" at
p < 0.02.
ELDERLYHUNGARIANAND AMERICANHEALTHSTATUS
315
Additionally, with respect to working outside the home, other related items shopping, housework and doing laundry - have similar prevalence levels and were inter-correlated. Also, working outside the home, a functional status measure, was associated with related symptoms: pain associated with working in home (gamma = 0.76 and 0.77), difficulty in walking (gamma -- 0.82 and 0.68), and able to move about freely (gamma = 0.74 and 0.50) for Americans and Hungarians, respectively. Loss of hearing was associated with problems in telephoning (gamma = 0.56 and 0.42) for Americans and Hungarians, respectively. And poor eyesight was associated with managing money problems (gamma = 0.53 and 0.47) for Americans and Hungarians, respectively. Concerns about telephoning, working outside the home, and managing money probably are not cultural artifacts, but are problematic for Hungarians as well as Americans because of physical limitations. Analysis of individual items in the symptomatology index revealed Hungarians were significantly worse off than Americans on 25 of the 31 symptoms. Six symptoms were not significantly different for Americans and Hungarians. In no case were Hungarians less symptomatic than Americans (see Table V). On 10 of 12 major medical conditions prevalent among the elderly, Hungarians were significantly in poorer health than Americans. The greatest disparity in health appeared to be in psychological problems, cognitive impairment, respiratory problems, and arthritis. In two cases - cancer and broken hip Hungarians and Americans were identical. Hungarians were not better off on any of the medical conditions listed (see Table VI).
Multivariate Analysis Other comparisons between Hungarian and American elderly were made through multivariate analysis of covariance (MANCOVA) (Tabachnick and Fidell 1989). A 2 x 2 between-subjects MANCOVA was computed on 6 health status measures using country and gender as independent variables and age and education as covariates. First, from Table V we note that controlling for age and education, the main effects of country and gender were significant (p < 0.05) except provision of medical aids by country (p < 0.05). Second, again controlling for age and education, effects of country and gender were significant (p < 0.05) except for medical conditions which nearly attained significance (p < 0.85). Finally, the PiIlais trace, associated with differences among health status measures considered collectively by MANCOVA, after controlling for age and education, was significantly (p < 0.001) different by country, gender, and country and gender (see Table VII). Table VIII shows product/moment correlation coefficients among dependent health status variables. All health status measures were moderately to highly correlated, suggesting that health problems are related, as hypothesized by Liang et al. (1991). The only exception was the lack of significant correlation between medical condition and use of medical aids. Next, discriminant analysis was employed to determine to what extent dependent health status variables predicted whether a person was either an
316
TERRY F. BUSS ET AL.
TABLE V Analysis of variance: Symptomatology items by Americans and Hungarians (mean scores) a Symptoms:
Americans
Hungarians
F-ratio
P
Can't get body to move Headaches Dizziness, tendency to fall Loss of hearing Vision impairment Taste, smell impairments Fits, seizures Severe pain See and hear things others do not Memory problems Weight loss Appetite loss Sleep disturbances Constipation Feeling sad Shortness o f breath Swollen ankles and feet Tire easily Chest pain Abdominal pain Stool change Blood in stool Control stool Blood in urine Urination Blood vagina Difficulty walking Painful joints Difficulty housework Broken bones Broken hip
0.12 0.11
0.47 0.49
222.06 275.93
0.001 O.001
0.11 0.21 0.15 0.04 0.01 0.12
0.55 0.30 0.55 0.09 0.27 0.39
394.35 12.83 268.17 11.87 265.17 138.76
0.001 0.001
0.01 0.12 0.07 0.06 0.15 0.11 0.08 0.19 0.18 0.23 0.07 0.05 0.07 0.02 0.01 0.01 0.03 0.00 0.20 0.31 0.09 0.05 0.03
0.02 0.19 0.19 0.19 0.44 0.24 0.41 0.27 0.47 0.72 0.22 0.16 0.18 0.01 0.07 0.02 0.10 0.01 0.46 0.58 0.27 0.06 0.02
0.99 11.75 42.89 47.96 150.59 35.43 234.40 11.79 131.76 405.24 64.20 47.93 33.49 1.34 31.85 0.89 21.99 0.91 109.65 106.27 78.54 0.84 1.13
0.001 0.001 0.001 0.001
0.319 0.001 0.001 0.001 0.001 O.001 0.001 O.001 0.001 0.001 0.001 0.001 0.001
0.247 0.001
0.345 O.001
0.340 0.001 0.001 0.001
0.359 0.289
Items scored "0" for absent, "1" for present. Scores may be converted into percentages by multiplying by 100. elderly American or Hungarian. Americans and Hungarians differed significantly when taking all health status measures into account (Wilk's lambda = 0.573, F = 157.43, p < 0 . 0 0 1 ) . Forty-three percent of discriminant score variability was attributable to between-group differences (canonical correlation = 0.653). Canonical discriminant functions, taken at the group means (centroids), also showed how disparate health status was: Americans = -0.69, Hungarians = 1.07, difference = 1.38. Some 82% of the cases were correctly identified as Americans or Hungarians, taking into account health status variables (see Table IX). This is a substantial improvement over the prior
ELDERLY HUNGARIAN AND AMERICAN HEALTH STATUS
317
TABLE VI Analysis of variance: Medical condition by Americans and Hungarians (mean scores)a Medical condition:
Americans
Hungarians
F-ratio
P
Cancer Diabetes, thyroid Blood diseases Psychological problems Hypertension Heart disease Respiratory Ulcers, hernia, cirrhosis Female genital Arthritis, back problems Memory problems Broken hip
0.01 0.00 0.00 0.01 0.01 0.01 0.01 0.00 0.00 0.00 0.02 0.00
0.01 0.02 0.02 0.06 0.03 0.03 0.05 0.03 0.01 0.24 0.13 0.00
1.016 9.960 12.956 33.468 6.675 10.104 26.483 18.106 6.411 223.827 62.831 0.043
0.314 0.002 0.001 0.001 O.01 0.002 O.001 0.001 0. 01 0.001
0.001 0.835
Items scored "0" for absent, "1" for present. Scores may be converted into percentages by multiplying by 100. a
TABLE VII Tests of selected variables by gender and country controlling for age end educationa Country and gender
Gender
Country
Variable:
F(2.1176) P
