CURRICULUM FOR THE HEALTH SCIENCES IN SOUTH EASTERN EUROPE
Number (unit, topic):
Review – Status: D
Title
Socio-economic factors – key determinants of health
Author(s), degrees,
Genc Burazeri MD, MPH, Enver Roshi MD, Ph.D.,
institution(s)
ECTS (suggested): 15hours
Ulrich Laaser, MD, DTM&H, MPH
Genc Burazeri, Faculty of Medicine, St. “Dibres”, No.371,
Address for
Tirana, Albania;
Correspondence
Tel.: +3554240401, Fax.: +3554232102;
E-mail: gburazeri@yahoo.com.
Keywords
Absolute depravation, determinant, education, income, health,
inequalities, occupation, relative depravation, socio-economic.
At the end of the module, students should be able to:

Critically appraise the differential toll of ill-health across
populations and population sub-groups;
Learning objectives

Understand the impact of socio-economic environment
on health;

Assess the main socio-economic determinants of health
in their own populations: education, income, occupation,
absolute (material) depravation, and relative depravation.
There is a considerable body of literature indicating a consistent
relationship between socio-economic factors and health. The
principal measures of socio-economic status have been
education, income, and occupation. Education has been the
most frequent measure as it does not usually change (as
income or occupation might) after young adulthood. Information
about education can be obtained easily and it is unlikely that
Synopsis (Abstract)
poor health in adulthood influences level of education. Recent
research undertaken in former communist countries has
developed specific instruments for assessment of individual
socio-economic circumstances. These include “material
depravation” (an index of absolute debasement) and “amenities
at three levels” (self-perceived depravation, an important
psycho-social pathway to ill-health). Assessment of socioeconomic environment is important in order to understand illhealth differences across population sub-groups.

Introductory/theoretic lectures (5 hours) in groups of 1520 post-graduate students.
Teaching methods

Small-group (of 5-7 students each) workshops/seminars
(10 hours), during which students are recommended to be
assigned different tasks.
Specific

recommendations
for teachers
lectures.

Use of flipcharts/blackboard for small-group seminars.

Group assignment (5-7 students): development of
Assessment of
Students
Use of overhead projector/LCD for theoretic/introductory
instruments/tools to assess socio-economic factors.

Individual assignment: take home essay (up to 3000
words, references excluded).
Contents
1. Socio-economic environment and health

What accounts for the gap between and within countries?

Socio-economic circumstances: absolute and relative depravation

Social position and health status: selection or causation?
2. Assessment of socio-economic environment in countries of South Eastern Europe
2.1. Assessment of socio-economic factors

Education

Income

Occupation/profession
2.2. Assessment of absolute and relative depravation in former communist countries

Material depravation

Relative depravation: amenities at three levels
3. Teaching methods

Teaching structure

Teaching tools
4. Assessment of students
5. Specific recommendations for teachers
1. Socio-economic environment and health
What accounts for the health gap between and within countries?
It has been argued that differences in availability, accessibility and affordability of medical care
services account for a considerable proportion of ill-health differences across different sub-groups
of populations (1-2). From this point of view, inequalities in health arise from inequalities in health
care. Yet, medical care fails to address the evident social gradient in the onset of new cases of
diseases which are not issues of medical care per se, or inequalities in mortality from diseases
which are not amenable to medical services (or at least, whose avoidance is questionable) [3].
Moreover, coronary heart disease, which is the main contributor of the mortality gap observed
between Eastern and Western countries, is believed not to be amenable to medical care (4-5).
Furthermore, childhood circumstances, work environment, unemployment, patterns of social
relationships, social exclusion, as well as engagement in unhealthy behavior cannot be accounted
for by lack of access to good-quality medical care.
In addition, the individual/constitutional risk, though partly explains the variation in occurrence of
diseases, fails to explain the marked differences over short periods of time (where genetic
predisposition to disease is assumed not to change substantially) in morbidity/mortality in line with
differences in socio-economic status (6-7). It is also worth distinguishing between individual risk
factors and environmental causes of disease. The attempt to explain ill-health differences across
populations based on individual risk-factor approach only has been persuasively criticized (8).
Beside the partial variation in occurrence of disease, it has proved difficult to modify individual risk
factors by trying to persuade individuals to change their behavior. Notwithstanding successes
achieved with the high at risk groups (e.g. drug treatment for hypertension and/or high cholesterol
levels), while this has benefits for the individuals concerned, it makes a limited contribution to
reducing disease rates in the whole population (7-8). As Geoffrey Rose has suggested, the causes
of individual differences in disease may be different from the causes of differences between
populations (9). Therefore, social determinants play a key role in explaining the ill-health gap
between populations and within population sub-groups.
Socio-economic circumstances: absolute and relative depravation
In attempt to account for the health gap between and within countries, a considerable part of the
research conducted with this regard in the last decades, has linked the ill-health differences
observed between and within countries with a whole array of elements which shape the socioeconomic environment in different countries.
The following phenomena concerning the socio-economic circumstances are evident in different
countries depending on the Gross National Product (GNP) structure:

There is a clear relationship between income and life expectancy (LE) between countries
(10). In poor countries, even small increases in GNP (per capita) are associated with relatively
large increases in LE, which is due mainly to malnutrition and/or infectious diseases. Hence,
the absolute material depravation is an important determinant, which explains the differential
toll of morbidity and mortality between poor and rich countries. From this perspective, for the
poor countries of the world, an increase in living standards that reduces malnutrition and
infectious diseases will make a major contribution to improving health.

In counties with a GNP (per capita) of >$5000, the relationship between GNP and LE is
weak (10). The implication of such relationship is that, above a certain level of income, even
large differences in income between wealthy countries are associated with negligible
differences in respective LE.

For countries with similar levels of income, there is a strong relation between income
inequality and LE (10-11). This is termed “relative depravation”, which is arguably considered
as a major determinant of ill-health in “rich” countries, as opposed to the absolute depravation
which accounts for a considerable proportion of morbidity/mortality in poor countries. Income
inequality reflects the social environment and the way societies are organized. From this point
of view, there is a developing research area that relates disease patterns to the organization of
society and the way society invests in its human capital. In recent years, it is soundly being
argued that many classical risk factors (such as hypertension, alcohol consumption, smoking,
or lack of exercise) have clear social determinants (7,11). Therefore, the excess morbidity and
mortality not explained by the absolute deprivation in rich countries has been linked to the
psycho-social concept (referred to as relative deprivation). A striking example comes from the
Whitehall study (British civil servants), which documented large differences in CHD mortality
patterns associated with the perceived (relative) depravation (12). Form this perspective, for
the rich countries of the world, reduction in socio-economic inequalities will make a major
contribution to improving health.
Social position and health status: selection or causation?
Differences observed in disease rates relate more plausibly to characteristics of the social
environment. The causal direction, therefore, is likely to be from social environment to illness, and
not the other way (7). Nevertheless, it has been intriguingly argued that health status may
determine socio-economic position as well as social circumstances that affect health (13-14). From
this point of view, health could be a major determinant of life chances/opportunities. This
phenomenon has been termed “health selection”. The implication of such a phenomenon is that
health may “select” people into different social strata (layers) [13-14]. According to this, sick
individuals maybe more likely to lose their jobs and remain unemployed than healthy people. This
might bear important implications as to the direction of causality of the relationship between social
position and health. This would lead to the argument that poor health leads to lower position in the
social hierarchy, social exclusion, increased risk of unemployment and job insecurity, less
participation in social networks, unhealthy behavior (diet, smoking, alcohol and drug addiction, as
well as lack of physical activity) [13-14]. However, such a question of “egg and chicken” can be
convincingly addressed in longitudinal (cohort) studies only. So far, current evidence (albeit limited
to few prospective studies) suggests the casual direction to be from social environment to illness
and not vice-versa (15-16).
2. Assessment of socio-economic and psycho-social environment in countries of South
Eastern Europe
2.1. Assessment of socio-economic factors
- Education
Education has been the most widely used measure of socio-economic status in most of research
conducted so far all over the world (17). The advantage of employing such a variable (education)
as a measure of socio-economic position is related to the relatively simple/straightforward
questions, which usually generate a high response rate (17-18). Furthermore, as educational
attainment is usually stable after young adulthood, it is little affected by poor health developed later
in life among adults of both sexes (17-18). However, engagement of education as a measure of
socio-economic position has also some disadvantages, which should be taken into consideration,
especially in countries of South Eastern Europe, or more broadly former communist countries. For
example, in Albania there are huge birth cohort differences in levels of education, so as
psychological and behavioral patterns of a given level of education are different for different
cohorts. In addition, poor illness in childhood may affect the level of education attained in young
adulthood. Nevertheless, due to its simplicity, comparability between countries and especially the
difficult endeavor of measurement of income level, educational attainment is frequently used as the
key measure of social ranking in most of societies.
Most of the research conducted in Eastern European and former Soviet countries has classified
the individual educational attainment into the following 4 categories: primary or less, vocational
(apprenticeship), secondary (or an equivalent level), and university degree (19-22). Nonetheless,
this classification is also contingent to a) specific educational system in each country, and b) the
relative value that each society assigns to development of human resources.
- Income
In addition to education, income is another widely used measure of socio-economic position (1718). However, beside difficulties in assessment of such a variable (e.g. high non-response rates), a
low income level might reflect impaired health (13-14). From this perspective, contrary to
education, income maybe directly affected by health status in adulthood, therefore pointing to
differential life chances/opportunities in adulthood associated with state of health (13-14).
Furthermore, measurement of income is rather complex in all societies; it encompasses not only
individual wages, but also other sources of income such as real estate/property or non-cash
benefits (food stamps, free access to medical care, etc.). Therefore, it might be more useful to
measure the total assets of individuals, which commonly is termed “wealth” (17). However, such a
measurement is a rather difficult job to pursue.
Things get even more complicated in former communist countries where transition towards a free
market system in the last decade is associated with a high degree of distrust/hostility and negative
affection by large segments of populations, which does not permit a reliable estimate of “real”
individual income/wealth in these countries.
In attempt to measure income level among undergraduate university students in Tirana last fall, we
employed the following instrument/question: “How would you rate your monthly family income
including wages, allowances, family businesses, and other sources of income, subtracting the rent
your family might be paying for the apartment or house?” (23-24). However, we got the lowest
response rate for this question (80%), even though we asked for more confidential/sensitive
information (sexual behavior and practices, for which the overall response rate was 87%).
Therefore, other proxy measures should be engaged in parallel with the self-reported income in
order to capture the array of socio-economic position of individuals in Eastern European countries.
- Occupation
Occupation is another variable commonly employed for assessment of socio-economic ranking of
individuals in all societies (17-18). However, the use of such a measure (occupation) usually
involves some categorization. Two famous examples to mention with this regard are the Registrar
General of Great Britain (used since 1911) [25] and the US Bureau of Census (used since 1897)
[26], which are roughly comparable. Occupation is an important characteristic in modern societies
linked with prestige and social status. However, use of occupation as a measure of socio-economic
position bears several disadvantages. As for income, current occupation for certain individuals may
reflect the impact of disease/poor health (13-14). Furthermore, modern research has focused on
the decision latitude, time pressure and social support at work place rather than the classical
categorization of occupations/professions. Thus, Whitehall study (conducted among British civil
servants) [12] in addition to Karasek’s pioneering evidence (27-28), has arguably linked a higher
risk of coronary events and its mortality with work environment/characteristics.
In former communist countries, the employment of current occupation/profession for assessment of
social position is even more difficult. The orientation towards a free-market system in the last
decade
has
been
associated
with
tremendous
changes
in
employment
rates
and
occupational/professional shifting. Beside the exceptionally high unemployment rates, cases where
former (up to 1990s) physicians or other conventional “white-collar” professionals have moved into
manual occupations and/or questionable businesses are not uncommon. On the other hand,
former “blue-collars” (with no university degree) employed currently in the most prestigious
positions are even less uncommon. Furthermore, the overwhelming rapid socio-economic
transition is driving large segments of populations into a multi-occupational fashion (part-time jobs
rather than a permanent full-time position). Therefore, assessment of occupation/profession in
countries of South Eastern Europe must clearly address especially the following issue: assessment
of current or “habitual” occupation? From this perspective, use of current occupation/profession is
rather questionable in these countries. Nonetheless, authoritative research conducted in former
communist countries has, to a certain extent, matched successfully current occupation as a
measure of socio-economic position. Occupation in these studies was classified into 3 broad
categories: managerial/supervisor, other employment and self-employment (19-22).
2.2. Assessment of absolute and relative depravation in former communist countries
Recent research undertaken in former communist countries has developed specific instruments for
assessment of individual socio-economic circumstances. Thereof, a concept of “material
depravation” (19,21-22,29) and a concept of “amenities at three levels” (30) were developed.
- Material depravation
Material depravation was used as an index of absolute depravation in former communist countries.
It is assessed by 3 questions about how often the individuals’ household has difficulties to buy
enough food or clothes and to pay bills for housing, heating and electricity (19,21-22). Possible
answers to these questions (never/almost never, sometimes, often, always) are coded and a
depravation score is derived as the sum, based on which individuals are classified into 2
categories: low material depravation and high material deprivation. This rather simple instrument
has resulted valid in prediction of poor health in vulnerable sub-groups (of low socio-economic
status) [19,21-22,29].
- Relative depravation: amenities at three levels
In attempt to assess the relative (self-perceived) depravation as an important psycho-social
pathway to ill-health, individuals in Hungary were asked to report on household items that they
possessed (30). According to this approach, household items are classified as follows:

Basic items: washing machine, refrigerator, microwave, telephone.

Socially oriented items: color television, radio cassette recorder, car, motorcycle.

Luxury items: cable television, air conditioner, dishwasher, personal computer, summer
house, garden.
Nevertheless, application of this classification must be considered carefully, as different items
might fall into different categories depending on the specific socio-economic environment of each
country. For example, in Albania microwave and car ownership could be better placed into the 3rd
category (i.e. luxury items). However, such a practical classification of amenities might be
extremely useful and worth adopting by all the PH-SEE countries in order to assess the impact on
health associated with both absolute and relative depravation.
Post-graduate public health students are encouraged to adapt and validate these instruments
(material depravation and amenities at 3 levels) for their specific settings/environments.
3. Teaching methods
Teaching structure
The duration of the module is recommended as 15 hours:
1. Five introductory/theoretic lectures in groups of 15-20 post-graduate students is recommended.
2. Ten small-group (of 5-7 students each) workshops/seminars, during which students are
recommended to be assigned different tasks as follows:

One group of students to provide tools for assessing socio-economic position based on
the three components engaged in research studies worldwide (education, income and
occupation/profession). Students should design a simple but comprehensive questionnaire
in order to capture the array of social position/ranking of individuals in their own/specific
settings. It must be noted that for different countries/cultures, education, profession and
income bear different socio-economic connotations. Therefore, students are expected to
design such a tool which would best capture the array of social ranking of individuals of
societies which they belong to.

One group to provide tools for assessing material depravation based on the
questionnaire developed by Bobak et al. This questionnaire, however, should be
adapted/amended in line with the specific socio-economic environment of societies where
students come from.

One group of students to provide means for assessing relative depravation based on
measurement of amenities at 3 levels, as described by Marmot et al. Same as above i.e.
questionnaires should be designed as “setting-specific”.
Teaching tools

Use of overhead projector/LCD for theoretic/introductory lectures is recommended.

Use of flipcharts/blackboard for small-group seminars is recommended.
4. Assessment of students

Group assignment (5-7 students): development of instruments/tools to assess socioeconomic factors.

Individual assignment: take home essay (up to 3000 words, references excluded).
5. Specific recommendations for teachers

For introductory/theoretic lectures: students are encouraged to participate actively during the
lectures; however, frontal lecturing may be more effective in the first 2-3 lectures.

Use of flipcharts during the seminars: flipcharts are considered as a very effective tool for
generation of brainstorming sessions during which students are encouraged to provide
ideas/tools for assessing/measuring socio-economic factors which affect ill-health of their
populations.

At the beginning of each seminar: teachers are recommended to assign a student (on a
rotation base) to facilitate the discussion/session. Students are expected to take a full
leading/active role, whereas the role of teachers is recommended to be rather “passive”. At the
end of each session/seminar, however, the teacher should summarize briefly the main points
made by the students. This teaching tool (active participation of students and “passive” role of
teachers) is in line with the new teaching methodology (i.e. self-discovery methods).

For group-assignments: students are expected to come up with consensual/group
questionnaires, which will help them develop the necessary skills of working in group/team.
This is a very important issue to control/sustain the fragmentized learning/working dimension,
which is rather problematic in SEE countries due to the inherited “Soviet” teaching style. From
this point of view, group assignments are recommended to account for 40% of the overall
grade of the module.

For individual assignments: students are expected to provide a comprehensive literature
review about socio-economic determinants of health, and critically appraise the major socioeconomic factors linked with ill-health of their own populations. Individual assignments are
recommended to account for 60% of the overall grade of the module.
References
1. Rustein DD, Berenberg W, Chalmers TC, Child CG, Fishman AP, Perrin EB. Measuring the
quality of medical care. A clinical method. N Engl J Med 1976; 294:582-588.
2. Boys RJ, Forster DP, Jozan P. Mortality from causes amenable and non-amenable to medical
care: the experience of Eastern Europe. BMJ 1991; 303:879-883.
3. Bobak M, Marmot M. East-West mortality divide and its potential explanations: proposed
research agenda. BMJ 1996; 312:421-425.
4. Loewel H, Dobson A, Keil U, Herman B, Hobbs T, Stewart A, et al. Coronary heart disease
case fatality in four countries. Circulation 1993; 88:2524-2531.
5. Sala J, Marruga J, Maisa R, Porta M. Improvement in survival after myocardial infarction
between 1978-85 and 1986-88 in the REGICOR study. Eur Heart J 1995; 16:779-784.
6. Drever F, Whitehead M, Roden M. Current patterns and trends in male mortality by social class
(based on occupation). Popn Trends 1996; 86:15-20.
7. Marmot M (1998). Introduction to social determinants of health. In: Social determinants of
Health (eds. M Marmot and RG Wilkinson). Oxford University Press, Oxford; pp.1-16.
8. Syme SL (1996). To prevent disease: the need for a new approach. In: Health and Social
Organization (eds. D Blane, E Brunner, and R Wilkinson). Routledge, London; pp.21-31.
9. Rose G (1992). The strategy of preventive medicine. Oxford University Press, Oxford.
10. Kawachi I (2000). Income inequality and health. In: Social Epidmeiology (eds. L Berkman and I
Kawachi). California, USA; pp.76-94.
11. Wilkinson RG (1998). Putting the picture together: prosperity, redistribution, health, and
welfare. In: Social determinants of Health (eds. M Marmot and RG Wilkinson). Oxford
University Press, Oxford; pp.256-274.
12. Marmot M, Shipley MJ. Do socio-economic differences in mortality persist after retirement? 25
year follow up of civil servants from the first Whitehall study. BMJ 1996; 313:1177-1180.
13. Power C, Manor O, Fox J (1991). Health and class: the early years. Chapman & Hall, London.
14. Wadsworth MEJ (1986). Serious illness in childhood and its association with later-life
achievement. In: Class and health (ed. RG Wilkinson). Travistock Publications Ltd, London;
pp.50-74.
15. Blane D, Davey Smith G, Bartley M. Social selection: what does it contribute to social class
differences in health? Sociol Hlth Illness 1993; 15:1-15.
16. Blane D, Brunner EJ, Wilkinson RG (1996). Health and Social Organization. Routledge,
London.
17. Kaplan GA, Keil JE. Socioeconomic factors and cardiovascular disease: a review of the
literature. Circulation 1993; 88:1973-1998.
18. Liberatos P, Link BG, Kelsey JL. The measurement of social class in epidemiology. Epidemiol
Rev 1988; 10:87-121.
19. Pikhart H, Bobak M, Siegrist J, Pajak A, Rywik S, Kyshegyi J, et al. Psychosocial work
characteristics and self-rated health in four post-communist countries. J Epidemiol Community
Health 2001; 55:624-630.
20. Rose R. How much does social capital add to individual health? A survey study of Russians.
Soc Sci Med 2000; 51:1421-1435.
21. Bobak M, Pikhart H, Hertzman C, Rose R, Marmot M. Socio-economic factors, perceived
control and self-reported health in Russia. A cross-sectional survey. Soc Sci Med 1998;
47:269-279.
22. Bobak M, Pikhart H, Rose R, Hertzman C, Marmot M. Socio-economic factors, material
inequalities, and perceived control in self-rated health: cross-sectional data from seven postcommunist countries. Soc Sci Med 2000; 51:1343-1350.
23. Burazeri G, Roshi E, Tavanxhi N, Rrumbullaku L, Dasho E. Knowledge and Attitude of
Undergraduate Students towards Sexually Transmitted Infections in Tirana, Albania. Croat Med
J 2003; 44:86-91.
24. Burazeri G, Roshi E, Tavanxhi N, Orhani Z, Malo A. Sexual Practices of Undergraduate
Students in Tirana, Albania. Croat Med J 2003; 44:80-85.
25. Leete R, Fox J (1977). Registrar General’s social classes: origins and uses. Population Trends.
Routledge, London.
26. Susser M, Watson W, Hopper K (1985). Sociology in Medicine, 3rd ed. Oxford University Press,
New York.
27. Karasek RA. Job demands, job decision latitude, and mental strain: implications for job
redesign. Administrative Science Quarterly 1979; 24:285-308.
28. Karasek RA, Baker D, Marxer F, Ahlbom A, Theorell T. Job decision latitude, job demands and
cardiovascular disease: a prospective study of Swedish men. Am J Public Health 1981;
71:694-705.
29. Bobak M, Hertzman C, Skodova Z, Marmot M. Socioeconomic status and cardiovascular risk
factors in the Czech Republic. Int J Epidemiol 1999; 28:46-52.
30. Marmot M, Bobak M. international comparators and poverty and heath in Europe. BMJ 2000;
321:1124-1128.