Does class matter? SES and psychosocial health among Hungarian adolescents

Does class matter? SES and psychosocial health among Hungarian adolescents

Social Science & Medicine 53 (2001) 817–830 Does class matter? SES and psychosocial health among Hungarian adolescents Bettina Pikoa, Kevin M. Fitzpa...

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Social Science & Medicine 53 (2001) 817–830

Does class matter? SES and psychosocial health among Hungarian adolescents Bettina Pikoa, Kevin M. Fitzpatrickb,* a

Szeged University, Albert-Szent-Gyorgyi Medical and Pharmaceutical Center, Department of Psychiatry, Division of Behavioral Sciences, Szeged, 6722 Hungary b Department of Sociology, University of Alabama at Birmingham, Birmingham, AL 35294-3350, USA

Abstract Previous research finds a significant relationship between socioeconomic inequalities and health status; individuals with lower income, education, and occupational prestige have and report more health problems. Interestingly, this relationship is not consistent across the life cycle; health differences among adolescents across socioeconomic groups are not as clearly defined. Using data (n=1039) on adolescents from southern Hungary, we examine the role of socioeconomic differences in predicting psychosocial health. We argue that this investigation is of particular importance in a post-communist system where the general perception of SES is undergoing significant transformation. Findings show that ‘classical’ SES (socioeconomic status) indicators (manual/nonmanual occupational status) were not significant predictors of psychosocial health in this sample of Hungarian adolescents. While parents’ employment status as a ‘objective’ SES indicator had limited effect, SES self-assessment, as a subjective SES variable, proved to be a strong predictor of adolescents’ psychosocial health. We discuss the implications of these findings for the broader SES–health literature with specific attention paid to the impact these relationships may have for adolescent and young adult development in a post-communist country like Hungary. # 2001 Elsevier Science Ltd. All rights reserved. Keywords: Psychosocial health; Adolescence; SES; Hungary

Introduction Considerable research indicates that socioeconomic inequalities have profound effects on health status and health behavior (Anderson & Armstead, 1995; Haan, Kaplan, & Syme, 1989; Link & Phelan, 1995; Marmot, et al., 1991; Marmot, Ruff, Bumpass, Shipley, & Marks, 1997; National Center for Health Statistics, 1998; Wilkinson, 1997). In both the United States and Europe, empirical studies find higher morbidity and mortality rates among persons with lower education, income, and prestige occupations (Adler, Boyce, Chesney, Folkman, & Syme, 1993; Marmot et al., 1997; Pappas, Queen, Hadden & Fischer, 1993; Power, 1994). Interestingly, the relationship between inequality and health status *Corresponding author. Tel.: +1-205-934-8678; fax: +1205-975-5614. E-mail address: kfi[email protected] (K.M. Fitzpatrick).

does not appear consistent across the life cycle. While the socioeconomic status (SES) and health relationship is well established in adulthood and infancy, the relationship is not as clearly defined in adolescent and young adult populations (Dutton, 1985). We already know that adolescence is an important period of developmental transition. It is characterized by a number of significant biological, psychological and social changes. This time of transition is a period of upheaval during which parental influence is decreasing while at the same time the quest for personal autonomy is increasing (Sebald, 1992). In addition to these changes, as youth make efforts to develop independent lifestyles and habits, these lifestyle changes potentially impact both their health and life chances (Cotterell, 1996; National Research Council, 1993). Compared to adults or children, most adolescent studies find few significant differences by social class in morbidity and mortality rates (Macintyre & West, 1991; Rahkonen &

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Lahelma, 1992; West, Macintyre, Annandale, & Hunt, 1990). In an extensive literature review, West (1997) suggested that youth (12–19 years of age) might be experiencing a period of ‘‘relative SES equality’’ with respect to their health. He concludes that youth, particularly during their secondary education years, exhibit fewer health differences than at any other point in the life cycle. These findings are explained by what is referred to as a ‘process of equalization’ whereby the defining features of youth (school, peers, and youth culture) cut across those associated with social class (family, home, and neighborhood). He argues that the net effect of this association is to create a reversal of social class differences from those experienced during childhood (West, 1997). While equalization is not entirely uniform across all health outcomes, it appears as though class gradients among adolescents are not as apparent as in other stages of the life cycle. Clearly, conflicting evidence exists regarding the exact role of SES in determining adolescent health outcomes, and it is within this research tradition that the current paper examines the SES–health relationship among a sample of Hungarian adolescents. The primary aims of the current study are two-fold. One, based on the findings of earlier work exploring the class gradients in adolescent health, our study attempts to further define the general role of SES in predicting adolescent physical and mental health outcomes. Two, unlike many earlier studies, the current study looks at the role SES in predicting health outcomes by using multiple indicators of SES: mother and father’s education and occupation, as well as an adolescent’s self-assessment of their current SES. The current sample of Hungarian adolescents adds to the growing list of empirical investigations which attempt to explore the complicated weave between SES indicators, sociodemographic characteristics, and psychosocial outcomes for adolescents in a variety of social structural settings. In addition, to our knowledge, there are no studies that have explored these interrelationships among adolescents in a post-communist country like Hungary. As social structures begin to transform with the shifting Hungarian economic system, class has taken on new meaning. Despite the fact that since the 1960s Hungary has been more economically successful than many of its Eastern European neighbors, the mortality and morbidity rates have increased (Cockerham, 1999). Moreover, high socioeconomic gradients in health status have persisted for decades even though the communist state declared itself the guarantor of equality and equity (Csaszi, 1990). Since 1990, with the development of a market economy, Hungarians face increasing socioeconomic differences between classes, and unemployment has become a new phenomenon to consider. Thus, while some empirical evidence suggests social class gradients exist among Hungarian adults’ health (Kopp,

Skrabski, & Szedma´k, 1995), no research has investigated whether those same health inequalities can be found among the current generation of post-communist adolescents. Characteristics of psychosocial health among adolescents Health is a complex concept and, as a result, the measurement of health status assumes several forms (Ware, 1986). Conceptually and practically, an important feature of health is its multidimensionality. The WHO defines health as a state of complex physical, mental, and social well being, and not merely the absence of disease or infirmity (World Health Organization, 1946). Although the WHO definition has been criticized, it emphasizes that the most important feature of health is its multidimensional nature (Piko, 1999). Engel (1977) postulated that the classical biomedical model does not suffice in providing a basis for understanding the determinants and consequences of disease. Humans should be viewed as complex systems, with biological, psychological, and social dimensions all taken into account in order to obtain an accurate picture of one’s health. This approach certainly reflects the biopsychosocial model of health and illness and, as evidenced over the last century, psychosocial factors continue to play an increasingly important role in understanding health and illness (Link & Phelan, 1995). In addition, measurements of adolescent psychosocial health are particularly relevant to consider here for two reasons. One, most adolescents and young adults are free of serious physical illness, yet they experience and report considerable psychosomatic and psychological distress symptomatology (Piko, Barabas, & Boda, 1997). Psychosocial factors may play a decisive role in these complaints. Therefore, if we are interested in detecting whether or not there are social inequalities among adolescent health, the frequency of psychosomatic and psychosocial symptom reporting seems to be an appropriate set of health indicators to be examining. In fact, social inequalities in psychosocial health might suggest that inequalities are not really absent during this stage of the life cycle, rather they are less prominent in morbidity statistics. Two, adolescents undergo major biological and psychosocial changes which have a profound influence on their psychosocial health and health risk behaviors (Mechanic, 1991). Since psychosocial health problems may have major implications for adult morbidity and mortality, factors impacting adolescent’s psychosocial well being should receive investigative priority. The present study examines self-perceived health, psychological well being, and psychosomatic symptoms, which together are indicators of psychosocial health. Despite the fact that psychosocial processes play an important role in all of these self-reported health issues,

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they represent different types of health indicators. Psychosomatic symptomatology reflects the physical bodily complaints resulting from somatization of psychosocial processes (Katon, Kleinman, & Rosen, 1982). Psychosomatic health problems such as sleep disorders, back pain, tension headaches, and chronic fatigue are quite common in both general and adolescent populations (Mays, Chinn, & Ho, 1992; Piko et al., 1997). Notably, adolescents are at high risk for serious headaches and chronic fatigue (Linet, Stewart, Celentano, Ziegler, & Spreecher, 1989). Besides these problems, back pain and sleeping disorders were reported as frequent symptoms in a recent study of Hungarian students (Piko et al., 1997). These symptoms generally were found to be good indicators of adolescents’ increased introspectiveness and symptom reporting (Hansell & Mechanic, 1985). Self-perceived health is a global assessment which focuses on general health rather than specific dimensions of health (Donavan, Frankel, & Eyles, 1993). Although self-perceived health is a subjective assessment, it is very much related to objective health indicators such as physical symptomatology and mortality (Barsky, Cleary, & Klerman, 1992; Idler & Benyamini, 1997). Subjectivity, however, might actually be a strength since it reflects personal views of health and illness, unlike many other measures (Krause & Jay, 1994). This, of course, has special significance for adolescents who tend to focus on making sense of body experiences that impact their health perceptions (Mechanic & Hansell, 1989). Research indicates that young persons, in the absence of chronic health conditions, are more likely to use psychosocial health problems rather than physical assessments as a way of framing their health perceptions than are adults (Krause & Jay, 1994). The selfperception of health is an active process of adolescent development involving cognitive and emotional strategies for understanding self. Psychological well being has always been an important focus for mental health research and its gauging of adolescent psychosocial health. Measures of well being usually reflect actual mood or self-esteem and are often capable of assessing levels of psychological distress. Thus, these measures are often viewed as indicators of self-reported mental health symptomatology (Mechanic & Hansell, 1989). Three sociodemographic factors are included in the analysis between SES and psychosocial health in adolescence: age, gender and the type of school. Health problems have been influenced by gender across all age groups (Verbrugge, 1985). However, the direction and magnitude of gender differences in health vary according to particular symptoms or conditions present during specific phases of the life cycle. In most countries, the mortality rates of men and women differ; with a greater proportion of men reporting serious illness. Beyond the

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biological/genetic factors, there are substantial differences in health behaviors influenced by gender roles (Verbrugge, 1985). While men appear to engage in more risky behaviors, such as smoking or drinking, women are more likely to exhibit preventive behaviors such as health screenings (Waldron, 1991). On the contrary, selfassessments of health consistently find that men evaluate their health more positively than do women (Anson, Paran, Neumann, & Chernichovsky, 1993). Although a significant number of males have physical symptoms and conditions, women tend to report more psychosomatic and distress symptoms (Piko et al., 1997; Macintyre, Hunt, & Sweeting, 1996). Because of age and gender differences in psychosocial health, an appropriate adjustment for these sociodemographics is important to the present study. Besides these sociodemographic factors, type of school is also controlled for, as the three forms of secondary school in Hungary represent a system of hierarchy based on demands, teaching quality and educational success (Piko, 2000). Characteristics of the social inequalities in health Prior research indicates that social class gradients in adolescents’ health may be influenced by measurements of both health and social class (West, 1988). A variety of health indicators from subjective assessments to more objective physical measures related to mortality data have been applied. Although biases in indicators of selfreported health might contribute to the differences or lack of differences observed, self-perceived health, and self-reported mental and physical health symptomatology have been argued to be important in explicating the health–SES gradient among adolescents (West et al., 1990; Gore, Aseltine, & Colton, 1992; Wells, Deykin, & Klerman, 1985). Additionally, while social class is a complex concept, inadequate measurement may be attributed to the lack of observable class differentials in adolescent health. The major indicators of social class (SES) such as education, income or occupation are substantially intercorrelated in most populations, though they may have differential influences in varying instances (Liberatos, Link, & Kelsey, 1988). All these findings provide important evidentiary support for the assumption that while there may be no consequent social class differences in health among adolescents, there may be differences in those factors preceding socioeconomic health differences in adult life. These latent variables include lifestyle factors, as well as cognitive or other psychosocial processes (Tuinstra, Grotthoff, van den Heavel, & Post, 1996). Historically, one of the major studies setting the agenda for subsequent research on health inequalities was the Black report. The report argued for four possible explanations of health inequalities: material circumstances, artifactual effects, behavioral–cultural

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factors and social selection (Department of Health and Social Security, 1980). Research over the past decade has examined a number of potential pathways through which SES influences one’s health (work environments, stress, health behaviors and other psychosocial variables) (Haan et al., 1989). One frequent theme to emerge from this body of research has been SES differences in behavioral risk factors such as smoking, alcohol consumption or diet, accounting for the strong relationship between SES and poor health (Koivusilta, Rimpela¨, & Rimpela¨, 1998). Another approach identifies socioeconomic or material factors (i.e., deprived access to car, medical care, food, public transportation or health knowledge) as the source of poor health (Eachus et al., 1996). Research also emphasizes SES differences in exposures to noxious social and physical environments leading to higher rates of morbidity and mortality in lower SES groups (Fitzpatrick & LaGory, 2000; Jenkins, 1983). Yet there are still other views that propose personal or social characteristics of individuals are important to remaining in poverty, thus strengthening the SES link to health (Stronks, van Mheen, Looman, & Mackenbach, 1996). Increasingly, references have been made to the relationship between personal characteristics and SES differences in health, such as internal/external control, self-efficacy, coherence, hardiness or coping style (Elstad, 1998). There is some evidence that lower SES persons perceive themselves as less in control of external events, and that such beliefs are associated with poorer health (Rodin, 1996; Brunner, 1997). It might be assumed that these measures represent important cognitive assessments of social processes, thus adopting the psychosocial perspective of social inequalities in health (Elstad, 1998). Two possible explanations for this status health link can be argued. First, beliefs and attitudes vary by SES strata, or second, the cognitive evaluation of people influenced by their personality and intrapsychic processes can have a profound impact on attitudes and beliefs. Research by Kopp, Skrabski, and Szedma´k (1995) supports the importance of psychosocial processes in understanding the relationship between SES and health. This study argues that the relationship between the general health status of Hungarian adults and their level of socioeconomic deprivation is a function of the severity of their life dissatisfaction and depressive symptomatology. As such, people must learn how to cope with the changing social, psychological and economic structures, including the ever-widening gap between the social class and developing unemployment. Our review of the current literature suggests a complex model for understanding the social inequalities in health among Hungarian adolescents. While studies from Western European countries (West, 1997; Rahkonen & Lahelma, 1992) have shown that socioeconomic differences in youth are negligible when using ‘classical’

socioeconomic indicators (e.g., parents’ education, occupational class, etc.), explanations of the psychosocial perspectives on health inequalities suggest that the subjective evaluation of one’s own socioeconomic circumstances (i.e., SES self-assessment), as a cognitive process may have more of an impact on health than more objective SES indicators. The use of subjective class assessments in understanding the class–health relationship have a long history (Runciman, 1966). As previous research suggests, even children and adolescents are aware of social inequalities and thus capable of accurately assessing the concomitant unequal chances that they bring (Bugard, Cheyne, & Jahoda, 1989). Prior research among Hungarian adolescents finds that SES self-assessment reflects the socioeconomic situation of the adolescent’s family regardless of their parents’ education and occupational class (Piko, 1996). Findings, however, do not show consistency between the objective and subjective SES indicators, though children of selfemployed and highly qualified parents (i.e., those with successful market positions in the new market economy) tended to evaluate themselves mostly as upper and upper-middle class. There are several arguments for introducing subjective SES assessment into models investigating the SES and health link among Hungarian adolescents. First, status beliefs, or the relative evaluation of one’s material resources, are an important part of the larger processes by which inequality in society is achieved (Ridgeway, Boyle, Kuipers, & Robinson, 1998). While adolescents’ health inequality is generally not a class-based problem, the SES self-assessment seems to be a capable indicator of adolescents’ status beliefs of their relative social deprivation and life chances and relationship with psychosocial health. Second, one possible explanation of the relative SES equality in adolescents’ health, is that in a postmodernist view, biography is individualized and identity is not referenced by class but by the consumer culture (Featherstone, 1991; West, 1997). Individualization, however, also means that a standard biography becomes the chosen biography of most people, regardless of their social status (Beck, Giddens, & Lash, 1994). This time of transition in Eastern European culture moves closer towards an increasing level of individualization and consumerism, particularly in Hungary, where the influx of Western consumer preferences have been present since the late 1960s (Cockerham, 1999). Third, studies of Hungarian youth support the idea that a consumer culture has become dominant among youth (Gabor & Balog, 1995). Thus, SES self-assessment might reflect more of how adolescents can actually realize their life chances and lifestyle choices that are generated by certain desired consumer tastes. Based on empirical evidence and the arguments above regarding the relative SES equality in adolescents’ health in highly developed countries, we believe that ‘classical’

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or objective social class indicators will play a limited role in predicting adolescents’ psychosocial health even in a post-communist country like Hungary. For this reason, we argue that SES self-assessment, expressing the cognitive perception of one’s own relative socioeconomic circumstances, should play a significant role in influencing adolescents’ psychosocial health. Specifically, we hypothesize that even after controlling for sociodemographic differences, the overall effect of social class indicators on psychosocial health should disappear, except for SES self-assessment. Furthermore, we argue that this subjective SES and psychosocial health link may be an important latent association influencing health into adulthood through a variety of difficult to detect cognitive and psychosomatic processes.

Methodology Study population Data were collected in 1996 from students enrolled in the secondary schools of Szeged, southern Hungary. This representative sample, consisting of 1200 students, was stratified by gender and school type. In Hungary, there are three types of secondary schools. A grammar school (4 years) provides a general certificate of education for those wanting to go to a university or college (roughly corresponds to US high school). A secondary modern school (4–5 years) provides both a general certificate of education and some technical qualification for learning a trade. Finally, a secondary technical school (3 years) provides only for some technical qualification for learning a trade without a general certificate of education. Self-administered questionnaires were used to obtain information from students regarding their family structure, psychosocial health, health symptoms, SES assessments and health risk behaviors. Secondary school teachers distributed the questionnaires to students prior to the start of class. Students were given a brief explanation of the objectives of the study and instructions for filling out the questionnaire. Participation in the study was voluntary. Confidentiality of the responses was emphasized, noting that data were used for research purposes. Completed questionnaires were placed in sealed envelopes and collected from each of the participating schools. Of the 1200 questionnaires sent out, 1039 were returned for a response rate of approximately 87%. Measurement Psychosocial health The dependent variables in this study were a set of psychosocial health variables that included: self-

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perceived health, psychosocial well being and the frequency of common psychosomatic symptoms. Selfperceived health was measured by asking respondents how they compared their health status to their peers. The responses included: poor=1; fair=2; good=3; and excellent=4. Psychological well being was coded from high levels of distress to high levels of well being. The aim of this measure was to assess the general well being of adolescents over the last 12 months. The 6-item scale was adopted and modified from the Langner (1962) index by Ross and Hayes (1988). Respondents were asked: ‘‘During the past 12 months, how often have you had trouble sleeping, felt irritable, been in low spirits, felt happy, felt energetic, or felt optimistic?’’ Responses were coded as: nearly always=0; often=1; sometimes=2; seldom=3; and never=4 for the first three items and inversely for the last three items. The final scale had a range of 0–24 and was reliable with a Cronbach’s alpha of 0.78. Self-reported psychosomatic symptoms included: back pain, tension headache, sleeping problems, chronic fatigue, stomach pyrosis, tension, diarrhea and palpitation. This measure was used in order to obtain information on the frequency of these symptoms during the last 12 months (Piko et al., 1997). Respondents were asked: ‘‘During the past 12 months, how often have you had a back pain?’’, etc. Responses were coded as: often=3, sometimes=2, seldom=1, and never=0. The final scale had a range of 0–21 and was reliable with a Cronbach’s alpha of 0.75. Socioeconomic status (SES) As social class can be viewed as a complex concept, we selected those variables which reflect the multidimensionality of SES (Liberatos et al., 1988). In addition to our primary goal, both ‘objective’ and ‘subjective’ SES measures have been applied. Objective social class measures were based on employment status, or occupation, and the education of the student’s mother and father. Occupation is the most frequently used indicator of social class in research investigating the relationship between SES and health in both adults and adolescents (Power, 1994; West et al., 1990). In a majority of Western European studies, the measurement of adolescents’ social class is usually based on the occupation of the head of the household, i.e., father’s occupation (West et al., 1990). Since the socioeconomic structure in Hungary is based on a dual earning family model, we used both mother’s and father’s occupation and education. Occupational categories also provide some indirect assessment of the income status of adolescents’ families, which is not used as a direct SES measurement in our study because of substantial problems with validity. Generally, income has been argued to be relatively unstable over time (Liberatos et al., 1988) and thus it is difficult

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to ask adolescents for a valid perceived status of their family income, particularly in a changing society like Hungary. Employment status or occupation was divided into four groups: professional, managerial and skilled non-manual=1; self-employed or entrepreneur=2; skilled or unskilled manual=3; and unemployed=4. Self-employed or entrepreneurs were combined to form their own category of social class; this group represents the largest level of status inconsistency in the post-communist transition society where people with low educational level are able to achieve considerable economic success. A four-level classification of education was used to measure fathers’ and mother’s schooling: primary education=1; apprenticeship=2; General Certificate of Education (i.e., high school level)=3; and university or college degree=4. In addition to these objective assessments, a subjective evaluation of socioeconomic status (SES) was used. The subjective SES indicator asked adolescents to respond to the following question: ‘How would you rate your family’s socioeconomic status?’ The answer categories included: lower=1; lower-middle=2; middle=3; uppermiddle=4; and upper class=5. Finally, in order to control for other differences that might account for SES variations in adolescent psychosocial health outcomes, we introduced several control variables that included school, which was coded as: grammar=1; modern=2; and technical=3; age which was coded in years, and gender (male=1).

Analysis SPSS for MS Windows Release 8.0 program was used in the calculations with a minimum significance level set at 0.05. Pearson correlation coefficients were calculated to assess bivariate relationships. Multiple regression models were used to examine the relative effects of ‘objective’ and ‘subjective’ SES indicators, controlling for sociodemographics and an interaction term (Gender  SES self-assessment) that is introduced in order to control for the possible confounding effect of gender on the relationship between ‘subjective’ SES and psychosocial health (Kleinbaum, Kupper, & Morgenstern, 1982). Although this statistical technique is more appropriate when variables are measured on interval scales to avoid a significant loss of information, ordinal level variables have been employed in the correlation and regression analysis. While not always appropriate, ordinal variables that are designated as quantitative do appear to meet the conditions for use in linear analysis like regression (Berry, 1993).

Results Table 1 presents a detailed sociodemographic, socioeconomic, and health profile of the Hungarian adolescent sample. The majority of adolescents perceived their own health as good (58.5%) with moderately high scores on the psychological well-being scale (Mean=12.1; SD=4.0) and somewhat lower scores on the psychosomatic symptoms scale (Mean=6.8; SD=4.0). Most of the students considered themselves middle class (60.3%), 5% reported being lower class, and only 1% of the adolescents said they belonged to the upper (elite) class. Table 2 shows the zero-order correlations among the variables. Both father’s and mother’s education were positively related to adolescents’ self-perceived health. In addition, the correlation between the frequency of psychosomatic symptoms and mother’s schooling was significant. Gender is significantly correlated with all of the psychosocial health variables: girls reported more psychosomatic symptoms, had lower levels of psychological well being, and evaluated their own health more negatively compared to boys. The ‘classical’ occupational (nonmanual/manual) categories were not related to adolescents’ psychosocial health. However, father’s self-employed status was associated with a higher level of psychological well being and better self-perception of health. Father’s unemployment status was related to a lower level of self-perceived health. In total, SES self-assessment, as the subjective evaluation of one’s own social circumstances, appeared to be the most significant correlate with the psychosocial health variables, particularly selfperceived health. The primary focus of the analyses is reported in Tables 3–5, which present a series of regression estimates of psychosocial health for this sample of Hungarian adolescents. Multiple regression models were used to examine the relative effects of SES indicators, controlling for sociodemographic variables. The baseline model included variables measuring ‘objective’ SES. In model 2, SES self-assessment as a ‘subjective’ SES indicator was added. In model 3, sociodemographics (gender, age and the type of school) were controlled for and, as mentioned earlier, an interaction term (Gender  SES self-assessment) was added in order to control for the possible interrelationships between gender, psychosocial health and subjective SES assessment. Table 3 shows the regression estimates of adolescents’ self-perceived health. Among the ‘objective’ SES variables, employment status was a significant factor in predicting self-perceived health; adolescents with selfemployed fathers had more positive perceptions of their health. Mother’s schooling was also significant in the baseline model, however, after controlling for other variables, it became nonsignificant. SES self-assessment proved to be the most significant factor contributing to

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B. Piko, K.M. Fitzpatrick / Social Science & Medicine 53 (2001) 817–830 Table 1 General characteristics of Hungarian adolescents (n=1039)a Characteristics Sociodemographic Gender Male Female School type Grammar Modern Technical Age Socioeconomic status Schooling (Father) Primary Apprenticeship General Certificate of Education College/University Schooling (Mother) Primary Apprenticeship General Certificate of Education College/University Occupation (Father) Non-manual Self-employed Manual Unemployed Occupation (Mother) Non-manual Self-employed Manual Unemployed SES self-assessment Lower Lower–middle Middle Upper–middle Upper Health and well being Psychological well-being Physical symptoms Self-perceived health Poor Fair Good Excellent a

%

Mean

SD

17.3

1.4

12.1 6.8

4.0 4.0

43.2% 54.4% 37.3% 55.4% 6.8%

8.0% 31.4% 29.0% 30.2% 11.6% 20.1% 36.7% 30.2% 37.6% 24.3% 30.4% 7.4% 51.0% 14.6% 25.0% 9.4% 5.5% 22.4% 60.3% 10.0% 1.0%

3.4% 20.0% 58.5% 17.1%

Note. Percentages do not add up to 100% in most cases due to some missing values and rounding.

adolescents’ self-perceived health. Neither sociodemographics nor the interaction variable modified the effects of the previous models. The R2 change was significant for all models, except in the final model where the interaction term was added. These blocks of variables explained 6% of the variation in self-perceived health.

Table 4 presents the regression estimates of psychological well being. The baseline model shows that none of the ‘objective’ SES indicators were significant in predicting adolescents’ psychological well being. SES self-assessment was the only significant indicator of SES influencing psychological well being, even after control-

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Variables 1. Psych. well-being 2. Psychosomatic symp. 3. Self-perceived health 4. Gender 5. Age 6. Father schooling 7. Father is nonmanual 8. Father self-employed 9. Father manual 10. Father unemployed 11. Mother schooling 12. Mother nonmanual 13. Mother self-employed 14. Mother manual 15. Mother unemployed 16. SES self-assessment a b

p50.05. p50.01, two-tailed t test.

2

3 b

0.30 } } } } } } } } } } } } } } }

4 b

0.53 0.33b } } } } } } } } } } } } } }

5 b

0.09 0.24b 0.09b } } } } } } } } } } } } }

6 a

0.07 0.04 0.05 0.05 } } } } } } } } } } } }

0.04 0.05 0.08a 0.06a 0.12b } } } } } } } } } } }

7 0.01 0.03 0.02 0.05 0.06 0.60b } } } } } } } } } }

8 a

0.07 0.04 0.11b 0.00 0.03 0.08b 0.44b } } } } } } } } }

9

11

11

12

13

14

15

16

0.06 0.04 0.06 0.03 0.09b 0.55b 0.52b 0.38b } } } } } } } }

0.02 0.05 0.11b 0.05 0.00 0.01 0.22b 0.16b 0.19b } } } } } } }

0.05 0.07a 0.08b 0.09b 0.10b 0.59b 0.38b 0.01 0.37b 0.07a } } } } } }

0.01 0.01 0.02 0.01 0.10b 0.37b 0.37b 0.09b 0.26b 0.09b 0.58b } } } } }

0.02 0.00 0.03 0.01 0.05 0.02 0.13b 0.31b 0.11b 0.09b 0.04 0.42b } } } }

0.01 0.02 0.04 0.01 0.06 3.5b 0.26b 0.17b 0.41b 0.02 0.52b 0.59b 0.24b } } }

0.00 0.01 0.01 0.02 0.01 0.10b 0.11b 0.01 0.04 0.24b 0.17b 0.33b 0.13b 0.19b } }

0.16b 0.09b 0.19b 0.04 0.11b 0.32b 0.27b 0.11b 0.30b 0.15b 0.30b 0.22b 0.08b 0.24b 0.13b }

B. Piko, K.M. Fitzpatrick / Social Science & Medicine 53 (2001) 817–830

Table 2 Zero-order correlation matrix (n=1039)

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Table 3 Regression models for self-perceived health among Hungarian adolescents (n=1039)

Objective SES Father: Schooling Self-employed Manual Unemployed Mother: Schooling Self-employed Manual Unemployed

Model 1

Model 2

Model 3

Model 4

0.06b 0.10b 0.01 0.06

0.04 0.10b 0.02 0.03

0.02 0.10b 0.03 0.03

0.02 0.10b 0.03 0.03

0.09b 0.01 0.07 0.02

0.08 0.01 0.08 0.04

0.05 0.00 0.08 0.03

0.05 0.00 0.08 0.03

0.16c

0.16c

0.16

0.10c 0.02 0.05

0.12 0.02 0.05

2.26c 0.06b

0.02 2.26c 0.06

Subjective SES SES self-assessment Sociodemographics Gender Age Type of school Interaction effect Gender SES self-assess. Constant R2

2.54c 0.03a,c,d

2.17c 0.05c

a

Standardized regression coefficients. p50.05. c p50.01; one-tailed t-test. d 2 R change is based on hierarchical F-test of significance. b

ling for sociodemographics and the interaction term. The R2 change was significant in the second and third models that included SES self-assessment and sociodemographics. In the final model, the ‘subjective’ SES variable was not significantly different from the prior models; those with lower SES assessment reported lower levels of psychological well being. With all blocks of variables included, approximately 5% of the variation in psychological well being was explained. Table 5 displays the regression results for psychosomatic symptomatology. Gender was a significant predictor throughout the models; girls reported more symptomatology than did boys. Among the objective SES indicators, mother’s employment status was a significant variable; adolescents with unemployed mothers reported fewer psychosomatic symptoms. Mother’s schooling was also significant in the first two models, however, after controlling for sociodemographics, it became nonsignificant in the final model. Beyond mother’s employment status, the ‘subjective’ SES indicator remained significant throughout the models. The R2 change was significant in the second and third models. These blocks of variables explained 8% of the variation in psychosomatic symptomatology.

Discussion The focus of our analyses was detecting possible relationships between SES indicators and psychosocial health, i. e., psychological well being, self-perceived health and psychosomatic symptomatology among a sample of Hungarian adolescents. Based on our earlier discussion, we hypothesized that ‘classical’ or objective social class indicators were not likely to play a very important role in predicting adolescents’ psychosocial health, even in a post-communist country like Hungary. On the contrary, we hypothesized that SES selfassessment, a subjective evaluation of one’s own socioeconomic condition, would show a significant association with psychosocial health, even after controlling for other variables. Our results partially confirm our earlier hypotheses. In summary, the results suggest the following: (1) the ‘classical’ SES indicators, i.e., manual/nonmanual occupational class and schooling were not good predictors of adolescent psychosocial health; (2) SES self-assessment proved to be a significant predictor of adolescents’ psychosocial health; (3) parents’ employment status (e.g., unemployed or self-employed) had a limited

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Table 4 Regression models for psychological well-being among Hungarian adolescents (n=1039)

Objective SES Father: Schooling Self-employed Manual Unemployed Mother: Schooling Self-employed Manual Unemployed

Model 1

Model 2

Model 3

Model 4

0.01 0.05 0.04 0.04

0.03 0.05 0.01 0.01

0.03 0.05 0.01 0.02

0.03 0.05 0.01 0.02

0.07 0.02 0.05 0.01

0.05 0.01 0.06 0.03

0.06 0.01 0.05 0.03

0.06 0.01 0.05 0.03

0.18a

0.17a

0.16a

0.08b 0.08b 0.05

0.05 0.08b 0.05

13.17a 0.05a

0.03 13.23a 0.05

Subjective SES SES self-assess. Sociodemographics Gender Age Type of school Interaction effect Gender SES self-assess. Constant R2

11.21a 0.01c,d

8.91a 0.04a

a

p50.01; one-tailed t-test. p50.05. c Standardized regression coefficents. d 2 R change is based on hierarchical F-test of significance. b

influence on their children’s psychosocial health; (4) gender, as a sociodemographic factor, was neither a very good predictor of adolescent psychosocial health (except in the case of psychosomatic symptomatology) nor a confounder in the relationship between SES self-assessment and psychosocial health and; (5) similar to previous research (Macintyre & West, 1991), class gradients in adolescents’ health were neither consistent nor significant. However, we caution the reader that, given the nature of the data and analyses conducted, we are unable to definitively conclude that there are no class-based health inequalities among Hungarian adolescents. The literature suggests that occupational social class, as an indicator of SES, may be a better discriminator of socioeconomic differentials in adult health than education (Davey Smith et al., 1998); however, neither occupation nor education prove to be very good indicators of consistent class differentiation in adolescent health (Macintyre & West, 1991). We found this to be true in the case of adolescents’ health inequality where parent’s schooling was not as an important predictor of psychosocial health. Certain categories of

employment status, however, remained significant predictors after controlling for ‘subjective’ SES and sociodemographics such as mother’s unemployed or father’s self-employed status. The inverse relationship between unemployment and ill health is well established (Bartley, 1994). Our results suggest, however, that mother’s unemployed status actually played a positive role in adolescents’ psychosocial health. We should note that women’s position in the labor market and their role in the family have undergone substantial changes in Hungary in the past 10 years. During the period of socialism, the majority of Hungarian women were full-time employees. Presently, with the economic shift, an increasing number of Hungarian women are becoming unemployed/full-time housewives as there are substantial overlaps between the status of a housewife or a non-employed/unemployed wife. Arber (1997) found that unemployed, married, middle-class women had much better health than those women not married living in poorer material circumstances. It is also important to note the difference between women’s and men’s family roles in the Hungarian social system. While the unemployment

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Table 5 Regression models for psychosomatic symptomatology among Hungarian adolescents (n=1039)

Objective SES Father: Schooling Self-employed Manual Unemployed Mother: Schooling Self-employed Manual Unemployed

Model 1

Model 2

Model 3

Model 4

0.00a 0.03 0.01 0.07

0.01 0.03 0.00 0.05

0.02 0.03 0.01 0.04

0.02 0.03 0.01 0.04

0.12b 0.01 0.07 0.08b

0.11b 0.01 0.07 0.08b

0.08 0.00 0.06 0.07b

0.08 0.00 0.06 0.07b

0.09b

0.08b

0.10b

0.24c 0.05 0.02

0.32b 0.05 0.02

7.60c 0.08b

0.08 7.76c 0.08

Subjective SES SES self-assessment Sociodemographics Gender Age Type of school Interaction effect Gender SES self-assess. Constant R2

8.53c 0.01d

9.68c 0.02b

a

Standardized regression coefficents. p50.05. c p50.01; one-tailed t-test. d 2 R change is based on hierarchical F-test of significance. b

status of the father, as the head of the household, usually plays a negative role in the general health and well being of the family, a non-employed woman becoming a full-time housewife may actually have a positive effect on her children’s psychosocial health. Another ‘social category’ which had some beneficial effect on adolescents’ psychosocial health was father’s self-employed status. Self-employed men can achieve very successful positions in the new market economy, thus improving both their children’s future life chances and their present subjective feelings regarding health and well being. A recent study from the Czech Republic emphasizes the importance of market position in self-reported health (Hraba, Lorenz, Pechacova, & Lin, 1998). Our hypothesis concerning the role of SES selfassessment as a predictor of adolescents’ psychosocial health has been confirmed. Adolescents who evaluate their SES higher, report better psychological well being, lower levels of psychosomatic symptomatology and more positive assessments of their own health. The relationship was the weakest (though still statistically significant) in terms of psychosomatic symptomatology where gender proved to be the most significant predictor

and mother’s unemployment status, as an objective SES indicator, also had some effect. The main findings strengthen the importance of the psychosocial perspective in the significance of social inequalities in understanding health (Wilkinson, 1997). Since adolescents’ SES self-assessment reflect their family’s socioeconomic/financial situation (Piko, 1996), these status beliefs about their relative material advantages or disadvantages in the consumer culture may generate certain levels of social inequality in psychosocial health. The subjective feelings about one’s relative socioeconomic condition and life chances may induce social inequalities in morbidity and mortality rates in later life, particularly when lower levels of SES selfassessment are associated with depressive symptomatology as detected in Hungarian adults (Kopp et al., 1995). Research clearly establishes that socioeconomic deprivation has a profound influence on health through a variety of mechanisms including neuroendocrine responses known to induce anxiety and depression (Brunner, 1997). The fact that our measures of health are based on selfreports and subjective assessments should not detract from their importance. On the contrary, given evidence

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to suggest there are no social class differentials in mortality and longstanding illness in adolescence, any investigation using self-reported psychosocial variables to examine the SES-health link becomes even more important (Marmot et al., 1997; Gore et al., 1992; Elstad, 1998). Mortality is only one strategy for assessing social inequalities in health. Well-being clearly means more than just freedom from sickness and disease, it means possessing positive features of human functioning. Lower SES decreases well being, inhibiting factors which provide protection in the face of significant life stress (Hraba et al., 1998). In addition, inequality is often not found in empirical studies of adolescents partly because standard health indicators (e.g., mortality, chronic disease) do not do a very good job of reflecting how health varies in this particular life stage, and because the ‘classic’ socioeconomic indicators are often imprecise measures based on youth’s perceptions of their parents SES characteristics. Thus, self-assessed SES seems to be a more valid indicator of ones ‘true’ family position in the social hierarchy and in fact where ‘real’ social inequalities emerge are in differences in youth’s psychosocial health. Overall, our results indicate that neither ‘classical’ (manual/nonmanual) occupational class nor schooling generates consistent class gradients in adolescents’ psychosocial health. Therefore, we can conclude that a certain ‘level of equalisation’ in adolescence does appear to exist. However, we should also note that status beliefs, or the subjective feelings about one’s SES, and certain employment categories (parents’ unemployed or self-employed status) are related to adolescents’ psychosocial health, which may impact future life chances and adult morbidity. The present study is an important first step in investigating the relationship between SES and adolescents’ health in a post-communist country. Future research needs to include other variables in the analysis such as social support, lifestyle or other more ‘objective’ health measures using a longitudinal design. Crossnational studies would be particularly useful in detecting and comparing the roles of subjective SES and other psychosocial perspectives on adolescents’ health inequalities. It is true that Hungarian society is in transition, thus stratification and mobility mechanisms are likely to be different from those found in more developed market-driven economies. This obviously impacts adolescents’ psychosocial health, yet given the consumer and lifestyle characteristics relevant for their age, they are surprisingly similar to their Western European peers. Whether or not Hungarian adolescents are substantially different from their Western European counterparts is a question demanding further investigations. While the cross-sectional data limit our ability to address such a time-dependent issue, the preliminary findings are encouraging. Clearly, more extensive longitudinal research is required to more completely

explicate the complicated relationship between psychosocial health and SES during adolescence.

Acknowledgements This research was supported by the OTKA F 017968 research grant of the National Research Fund, Hungary. The authors thank Darlene Wright for her helpful comments regarding the manuscript. An earlier version of this paper was presented at the 2000 American Sociological Association Meetings in Washington, DC.

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