Health development : a study of the determinants of health and the distribution of perceived health in Afghanistan, Armenia and the Russian Federation

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PUBLICATIONS OF

THE UNIVERSITY OF EASTERN FINLAND Dissertations in Social Sciences and Business Studies

ISBN 978-952-61-2264-9 ISSN 1798-5749

Dissertations in Social Sciences and Business Studies

PUBLICATIONS OF

THE UNIVERSITY OF EASTERN FINLAND

This research identifies and estimates the influence of different determinants on perceived

health. The differences in perceived health can be attributed to differential exposure to public services. The reduction of differences in perceived health over time between the socioeconomic groups does not mean that the worse-off group has achieved a better health status. Changes in the distribution of differences in perceived health do not follow the changes in the differences of household income.

PAVITRA PAUL

DISSERTATIONS | PAVITRA PAUL | HEALTH DEVELOPMENT: A STUDY OF THE DETERMINANTS OF... | No 132

PAVITRA PAUL

HEALTH DEVELOPMENT: A STUDY OF THE DETERMINANTS

OF HEALTH AND THE DISTRIBUTION OF PERCEIVED HEALTH

IN AFGHANISTAN, ARMENIA AND THE RUSSIAN FEDERATION

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Health development: a study of

the determinants of health and the

distribution of perceived health

in Afghanistan, Armenia and the

Russian Federation

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Dissertations in Social Sciences and Business Studies No 132

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PAUL PAVITRA

Health development:

a study of the determinants of health and the distribution

of perceived health in

Afghanistan, Armenia and the Russian Federation

Publications of the University of Eastern Finland Dissertations in Social Sciences and Business Studies

No 132

Itä-Suomen yliopisto

Yhteiskuntatieteiden ja kauppatieteiden tiedekunta Kuopio

2016

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Grano Oy Jyväskylä, 2016

Editor-in-Chief: Kimmo Katajala Editor: Eija Fabritius

Sales: University of Eastern Finland Library ISBN (nid): 978-952-61-2264-9

ISSN (nid): 1798-5749 ISSN-L: 1798-5749 ISBN (PDF): 978-952-61-2265-6

ISSN (PDF): 1798-5757

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Paul, Pavitra

Health development: a study of the determinants of health and the distribution of perceived health in Afghanistan, Armenia and the Russian Federation, 109 p.

University of Eastern Finland

Faculty of Social Sciences and Business Studies, 2016 Publications of the University of Eastern Finland,

Dissertations in Social Sciences and Business Studies, no 132 ISBN (nid): 978-952-61-2264-9

ISSN (nid): 1798-5749 ISSN-L: 1798-5749

ISBN (PDF): 978-952-61-2265-6 ISSN (PDF): 1798-5757

Dissertation

ABSTRACT

Health is an outcome of development and also is an important factor of the development. This thesis examines distributional effect of the determinants of health in Afghanistan, Armenia and the Russian Federation.

We study the relationship between the determinants, and the distribution of perceived health in the socioeconomic strata (SES) framework.

We use longitudinal survey datasets from the three countries. The empirical analyses use econometric models to examine the association between different determinants of health and to explain the differences in perceived health. We measure socioeconomic inequalities in perceived health with concentration index (CI), and decompose CI to estimate the contributions of different determinants on health inequalities. The degree of aversion to perceived health inequalities is examined with achievement index.

In Afghanistan, the availability of health facilities and medicines, availability of drinking water and access to education are associated with the households’

living conditions and freedom of movement. Working status, possession of durable assets and household size are associated with perceived health in the Russian Federation. There is a positive association between perceived health and satisfaction with healthcare services in Armenia. The results indicate in-country regional variations in the distribution of perceived health.

In-country variations in the distribution of the determinants of perceived health are more dominant than differences in the distribution of the determinants across SES. Our contribution to the theory of ‘health equity’ is that a reduction of the differences in the perceived health status between socioeconomic groups does not mean reaching a better perceived health status for the worse-off.

Journal of Economic Literature (JEL) classification code: I14.

Keywords: determinants of health; distribution; inequalities; Afghanistan;

Armenia; Russia.

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Paul, Pavitra

Terveyden kehitys: Tutkimus terveyden määrittäjistä ja koetun terveyden jakautumisesta Afganistanissa, Armeniassa ja Venäjällä, 109 s.

Itä-Suomen yliopisto

Yhteiskuntatieteiden ja kauppatieteiden tiedekunta, 2016 Publications of the University of Eastern Finland,

Dissertations in Social Sciences and Business Studies, no 132 ISBN (nid): 978-952-61-2264-9

ISSN (nid): 1798-5749 ISSN-L: 1798-5749

ISBN (PDF): 978-952-61-2265-6 ISSN (PDF): 1798-5757

Väitöskirja

ABSTRAKTI

Terveys on paitsi yhteiskunnan ja sen talouden kehityksen tulos myös kehityksen välttämätön edellytys. Tässä työssä tutkitaan koetun terveyden määrittäjiä ja niiden jakaumavaikutuksia Afganistanissa, Armeniassa ja Venäjällä. Työssä tutkitaan sosioekonomisessa rakenteessa terveyseroja ja terveyden määrittäjien jakaumavaikutuksia, vaikutusta terveyseroihin. Työssä käytetään seuranta- aineistoja kaikista kolmesta maasta. Empiirisissä analyyseissa käytetään erilaisia regressiomalleja terveyden määrittäjien ja terveyden yhteyden ja terveyserojen tukimuksessa. Sosioekonomisia terveyseroja mitataan keskittymisindekseillä, joilla tutkitaan myös terveyden erilaisten määrittäjien osuutta terveyseroissa.

Afghanistanissa pääsy terveydenhuollon palveluihin, puhtaan juomaveden saanti ja koulutus edistävät kotitalouksien elinoloja ja liikkumisen vapautta.

Työmarkkina-asema ja kestokulutustavaroiden omistus ovat yhteydessä parempaan terveyteen Venäjällä. Armeniassa tyytyväisyys terveydenhuoltopalveuihin yhdistyy myös tyytyväisyyteen omaan koettuuun terveyteen. Näissä maissa on suurta sisäistä vaihtelua terveyden jakautumisessa. Maiden sisäinen vaihtelu terveyden määrittäjien jakaumassa ovat suurempia kuin näiden määrittäjien sosioekonomisten ryhmien välinen vaihtelu. Tutkimuksen tuloksena voidaan päätellä, että sosioekonomisten terveyserojen pienentäminen ei välttämättä johda alempien sosioekonomisten ryhmien terveydentilan paranemiseen.

Journal of Economic Literature (JEL) luokitus: I14.

Avainsanat: terveyden jakautuminen; distribution; eriarvoisuus; Afganistan;

Armenia; Venäjä.

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Preface

The development of a society, rich or poor, can be judged by the quality of its population’s health, how fairly health is distributed across the social spectrum, and the degree of protection provided from disadvantage as a result of ill-health (Commission on Social Determinants of Health; WHO, 2008).

Different environmental, physiological, behavioural and psychological contexts influence health development. Health is the extent to which an individual or group of individuals is able, on the one hand, to realise aspirations and safety needs and, on the other hand, to change and cope with the environment (WHO, 1984). Thus, Health is a resource for everyday life, not the objective of living; it is a positive concept, emphasising social and personal resources as well as physical capacities (Ottawa Charter for Health Promotion: WHO, 1986).

In the post-2015 developmental agenda of Sustainable Developmental Goals (SDGs), health is competing with climate change and food security after having intertwined with other areas of public economics. Major shifts are taking place in (1) the global distribution of resources, (2) realignment of influences, (3) defining human capabilities, (4) the expansion of the needs of emerging economies, (5) integrating transitional societies and (6) harnessing the power of information.

Focus is now to leverage the dense relationships of interdependence with interconnectedness across nations and sectors.

There is a clear distinction between the health achievement and the capability to achieve good health – free from escapable illness, avoidable afflictions and premature mortality. Health achievement and the capability of the individual to achieve good health go beyond the delivery and distribution of healthcare services – often the reasons for an illness that is not prevented and left untreated are social reasons (say, poverty and/or the overwhelming force of a community wide epidemic) rather than with personal choice. Sir Michael Marmot and others (CSDH; WHO, 2008) have also brought out the far-reaching effects of social inequality on health and survival.

The approach in achieving of specific health goals as an average for the nation without ensuring equitable distribution across entire population often does not address the need for a fair distribution as well as efficient formation of human capabilities. Thus, the concern for inequality draws the attention for recognising the health status of different socioeconomic groups.

Fundamental to understanding the causes of differences in health is the distinction between the effects of different determinants of health. Socioeconomic gradients in health are simultaneously an association with the distribution of different determinants of health—but which is more important in terms of

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causality? Is the health disadvantage of the least well off part of the population, or is it more a matter of the direct and indirect effects of differences in circumstances associated with the determinants of perceived health?

This thesis is premised on the empirical illustrations in Afghanistan, the Russian Federation and Armenia and analyses the findings with the literature on the determinants of perceived health. The understanding of the distributional effect of different determinants of perceived health is expected to (1) enable us for having interventions focused on maximising optimal health development and (2) contribute to the theories of public policy development.

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Acknowledgements

The opportunity to write this dissertation summary has its origin with the statement “Each generation must develop”. This statement of my late mother is the stimulus for my mid-career drift. Subsequently, in the course of exploration for making some meaningful contribution in expediting the evolutionary development on this earth, a personality that is true in its substance and resilient in its eternity emerged and that is Prof. Hannu Valtonen – the supervisor with a perfect blend of rectitude and affability. Thus, this dissertation is the reflection of the endeavour of Prof. Hannu Valtonen in developing another future-ready cadre of public health economics. The facets of health economics in me do not manifest without Prof. Hannu Valtonen.

This dissertation is testimony of the effectiveness of perpetual high level of logistic support from Prof. Juha Kinnunen, former Dean of the Faculty. I owe the exploration of all new horizons with Russian Longitudinal Monitoring Datasets to Prof. Jürgen Maurer. This dissertation recognises an enormous contribution of The Asia Foundation and Carolina Population Center (CPC - UNC) that have made the datasets available to me with the utmost ease and promptness.

I would also like to take this opportunity to express my unsurpassed gratitude to Prof. Johanna Lammintakanen, the current director of the department, who actively encouraged my latent potential to surface and for the developmental economics in me to become international.

The acceptance of this dissertation summary by the faculty council, Faculty of Social Sciences and Business Studies, University of Eastern Finland is the testimony of immense contributions of the examiners, Prof. Jürgen Maurer, Université de Lausanne and Prof. Jan Klavus, VATT Institute for Economic Research while reviewing the earlier version of this dissertation summary. I remain all time grateful to these luminaries for enabling me to be the part of the global developmental agenda.

I express my special gratitude to Prof. Tuula H. Laaksovirta, the ‘invisible hand’ (economics) in the production of this dissertation summary.

An all-encompassing credit for freeing me from the mundane activities of living, and for enabling me to carry out the mandate of this life unhindered goes to MS. Marja Pekkarinen and to ‘The Mother and Sri Aurobindo’, the supramental force for continuously empowering me with the knowledge, the light and the consciousness. I owe my existence to these personalities for the developmental journey in this world.

15 August 2016.

Paul Pavitra

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The central theme of this thesis is to identify the determinants of health, and to examine the distributional effect of those determinants on perceived health. The datasets used in this thesis are from Afghanistan, the Russian Federation and Armenia – three different countries with three different phases of development.

Paper I describes the in-country distribution of different health determinants and identifies the association between various determinants. This study also examines the regional (districts) effects on health determinants in a post-conflict nation.

Paper II examines the interaction between different determinants of health, measures equity in perceived health status across socioeconomic strata and finally estimates the contribution of factors related socioeconomic strata in the distribution of good (not good) perceived health status for Russians.

Paper III is a life course study of a sample of individuals for 19 years (1994-2013) using a compact panel from the datasets used in paper II. This paper examines the trend in the distribution of perceived health differences across the socioeconomic strata of select individuals in the Russian Federation.

Paper IV identifies the distribution of perceived health status across the socioeconomic strata of the population and examines the relationship of individual satisfaction (a subjective expression of cumulative effect of proximal determinants) with perceived health status, and with healthcare service consumption for Armenia, a country that has experienced a major ethnic crisis (in 1988) and an earthquake in 1988.

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1 Introduction

Health is a form of human capital (Fuchs, 1966; Becker, 1964 and Mushkin 1962).

The Grossman model (1972) has provided much insight into the determinants of health and the production of health through the demand for health capital. The noted economist and philosopher Amartya Sen (1999) argues that ‘development does not simply involve expansion of income’ and his ‘capability approach’ to development attaches intrinsic importance to the nation’s health, where ‘health’ is viewed as central to the development and not just an output from the development process. Health has been positioned as life course capital – that is depleted or protected over time on the basis of relationship between individual (proximal) and structural (distal) determinants (O’Rand and Henretta, 1999). The economic development literature advocates the recognition of health as a reflection of societal well-being, when the development is in transition (Komlos, 1999 and Steckel, 1995). Furthermore, the concern for poverty and inequality necessitates the focus of interest not in health status that is apparent in the society as a whole but in the health status of different socioeconomic groups (Gwatkin, 2000).

Health is a complex construct. Furthermore, the definition of health is contextual;

the interrelated dynamism between individual and population health stems from the individual’s growth, development and participation within the context of an adaptive society (Arah, 2009). Graham (2004) observes that the concept of “social determinants of health” has acquired a dual meaning, referring both to the social factors promoting and undermining the health of individuals and populations and to the social processes underlying the unequal distribution of these factors between groups occupying unequal positions in society. The relationship between individual and population health is entrenched in the contextual definition of health and its life course causes. Context is both individual and collective in nature, in largely inseparable ways and that context is derived from the causally defined life course perspective of health determinants for an individual and for the population, the collective (Arah, 2009). Differences in material standards of living and access to health enhancing resources, differential exposures to social stressors, the psychosocial effect of one’s perceived position in society, lifestyle and behavioural factors all play a role in shaping the socioeconomic gradient in health (Elo, 2009; Pearlin et al., 2005; Lynch et al., 2000 and Wilkinson, 1997).

Viewed in the context of the life course, the evidence suggests that regardless of the specific mechanisms involved, health inequalities between the worse-off and better-off are not levelled with age (Corna, 2013).

The ecosocial theory of health distribution (Krieger,1994) postulates that (1) population health and health inequities must be analysed in a societal, historical and ecological context and (2) neither the forms of social inequality nor

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their association with health status are “fixed”, but are historically contingent.

Krieger’s (2005, 2002 and 2001) “eco-social” approach and other emerging multilevel frameworks have sought to integrate social and biological factors and a dynamic, historical and ecological perspective to develop new insights into the determinants of the population distribution of disease and inequities in health.

According to Krieger (2001), multilevel theories seek to “develop analysis of current and changing population patterns of health, disease and well-being in relation to each level of biological, ecological and social organization”, all the way from the cell to human social groupings at all levels of complexity, through the ecosystem as a whole. In this context, Krieger’s (2001) notion of “embodiment” describes how

“we literally incorporate biological influences from the material and social world”

and that “no aspect of our biology can be understood divorced from knowledge of history and individual and societal ways of living”. This notion of “embodiment”

is an extension from “embedding” of Hertzman (1999). “Embedding” is the process by which experiences are programmed into the structure and functioning of biological and behavioural systems (Hertzman, 1999).

Health and developmental science recognise the multidimensionality and complexity of causation, including how environmental, social, psychological, and biological systems interact to influence health and developmental outcomes (Lerner and Benson 2002; Boyce et al. 1998). The mediating mechanisms for the association between different determinants of health and perceived health is divergent (Costa-Font and Hernandez-Quevedo, 2012; Nummela et al., 2007;

Frijters et al., 2005; Laaksonen et al., 2005; Adams et al., 2003 and Wilkinson, 1997 and 1996). Perceived health is not a direct clinical equivalent measure of health condition, but it correlates with more complex, multi-dimensional reflection of individual health status (Rowan, 1994) and predicts future health outcomes, including mortality (Idler and Benyamini, 1997). Perceived (self-assessed) health status is widely used (Adams et al., 2003; Frijters et al., 2003; Benzeval et al., 2001 and Smith, 1999) to analyse the socioeconomic health gradient. The exact mediating mechanisms for different determinants are not well understood (Sacker et al. 2001 and Bartley et al. 1999). Often the influence of these determinants on perceived health is independent of each other (Lahelma et al., 2004; Daly et al.

2002; Sorlie et al., 1995 and Dahl, 1994).

Evidence-based social and health policy recommendations account for both proximal and structural determinants of health inequalities (Berkman, 2009 and George, 2005). Coburn (2000) emphasises the mechanisms linking the determinants of socioeconomic inequalities to health over the determinants of socioeconomic inequalities themselves. Global and national economic arrangements and social policies are critical of people’s living and working conditions and hence to health equity (CSDH: WHO, 2008). Marmot (2010) argues that the concern for health inequalities require action across all the socioeconomic determinants of health.

It is, therefore, important to understand the extent of changes in socioeconomic conditions that is needed for the public policy to be effective.

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Hence, the challenge is establishing a plausible relationship between SES and the health of the population - not merely identifying a correlation between SES and the perceived health status of the individual.

Empirical objectives of this thesis are to

1. identify the determinants of the perceived health status in three countries with differential phases of development;

2. estimate the effect of different determinants of health in the distribution of perceived health differences and also to examine the life course effect of the determinants in health inequalities for a specific group of individuals;

The theoretical objective of this thesis is to discuss the relationship between the determinants and the distribution of perceived health, and the socioeconomic strata (SES).

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2 Theories of the

interactions between

socioeconomic position and health

Extensive literature has documented the link between increasing income inequality and the worsening of health status (Kawachi, 2000; Lynch et al., 2000, 1998, 1997; Wilkinson, 1996; Kaplan, 1996 and Kennedy et al., 1996). People who live in the lowest SES are vulnerable to ill-health (Link and Phelan, 2002 and 1995). A growing amount of the literature has focused on the impact of early life socioeconomic position (SEP) on later life health (Joseph and Kramer, 1996) and on the health consequences of socioeconomic trajectories (Lynch et al., 1997 and Lynch et al., 1994). Lochner et al. (2001) summarised evidence of a high risk of death when living in a high-inequality environment. Both health and SEP in later life are not independent of health experiences, exposures, and economic resources and inequalities from earlier in the life course (Heikkinen, 2011; Lynch and Davey Smith, 2005; Alwin and Wray, 2005; Crystal and Shea, 2002; and Crystal and Shea, 1990). Furthermore, the idea that individuals must take responsibility for own health is also an increasingly discussed topic (Cappelen and Norheim, 2004). Dworkin (1981) presents typology of meanings of responsibility as (1) role responsibility (one’s body belongs to oneself), (2) causal responsibility (one’s health status is largely determined by personal behavioural choices), and (3) responsibility based on liability (cost and other undesirable consequences of one’s illness).

Rodgers (1999) suggests that levels of health serve as a signal of the socioeconomic environment where people live and reflect the level of deprivation of the society.

Inequality can affect health through a variety of social factors, such as access to life opportunities, levels of social cohesion and psychosocial explanations, such as hopelessness, lack of control, isolation, and chronic stress (Kawachi et al., 1999).

Poor health, in turn, further contributes to these social factors, draining social capital and creating conditions where sections of a society become trapped in a cycle of self-reinforcing social exclusion.

The linkages between SEP and the health of the individuals as well as of the population (societies) lies with the answers to the following questions

(1) what makes the difference in the lives and health of those who have

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consistently low incomes or those who have had large income reductions?; (2) how does parental social class influence educational achievement and mobility within the labour force; (3) how does everyday life vary as one moves in different occupational trajectories?; (4) how does inequality in the distribution of income translate into lower social partition and trust?; (5) how does ordinary life differ among groups in which basic material needs are met but that differ by income level? and (6) how do the differences in the texture of everyday life translate into socioeconomic inequalities in health?

Economic processes and political decisions condition the private resources available to individuals and shape the nature of public infrastructure—education, healthcare services, transportation, environmental controls, availability of food, quality of housing, occupational health regulations—that forms the “neomaterial”

matrix of contemporary life. Thus, income inequality per se is but one manifestation of a cluster of material conditions that affect population health. Relative and material poverty are the important determinants of health and their distribution influences health (Poland et al., 1998).

Socioeconomic context (the income distribution, percentage of the adults having twelve and more years of education, the spread and depth of the publicly provided services, density of working population and ownership of the assets) of the geography of residence affects the health of the individual resident regardless of the SEP of the individual living in the geography (Krieger, 1992; Guest et al., 1998; Figueroa and Breen, 1995 and Crombie et al., 1989).

The association between health and absolute level of income at the individual level has been re-emphasised in recent times by Gravelle (1998). Rodger (1979) had argued that such a relationship is concave (non-linear) – each additional dollar of income raises a person’s health but by ever smaller amounts but the preponderance of evidence suggests that the relationship between income inequality and health is either non-existent or too fragile to show up in a robustly estimated panel specification (Lynch et al, 2004a and Deaton, 2003).

Wagstaff and van Doorslaer (2000) hypothesised that the average health of society improves with the increase in the average income of society. Deaton (2006) concludes that unless growth is accompanied by additional education and higher quality public health institutions (which presumably affect both future growth and health), the economic growth alone will not reduce infant and child mortality on a global scale.

Assessing the effects of economic inequality is not the same as assessing the effects of poverty - economic inequality does not affect health, poverty does so (Leigh, Jencks and Smeeding, 2009). There is a strong negative relationship between health and absolute poverty and this may also hold for relative poverty (Eibner and Evans, 2005). Wilkinson (1998) indicated that health depends on the position of the individual within society – the distance of the individual’s income from the population mean affects health. Wilkinson (1997) argued that the degree of deprivation (measured as the gap in the living standard from some critical level) that matters for equitable health in society is not the absolute position of the individual in society. Wilkinson (1996) postulates that the scale of social and

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economic differences amongst the individuals within the population powerfully affects the health of the population.

The income of others affects the health of the individual if the individual evaluates either their income or their lives as a whole by comparing themselves to others. Relative deprivation increases stress and consequently vulnerability to poor health increases - taxation and tax credits, old age pensions, sickness and rehabilitation benefits, maternity and child benefits, unemployment benefits, housing policies, labour market functioning, organisation of care facilities for communities are found to be relevant to exert positive influence in population health (Marmot, 2005).

The better-off enjoys better health (Bartley et al., 2004; Wilkinson and Marmot, 2003; Mackenbach et al., 2002; Smith, 1999 and Marmot, 1999). The distinction between the SEP of the individual and the socioeconomic context of the geography (in-country and between countries) is important policy relevant evidence that shape public health. Intervention for the geography becomes a necessity when the health related contribution attributable to the socioeconomic context of the geography is unique and is independent to the socioeconomic context of the individuals of that geography. On the contrary, if, the association between socioeconomic context of the geography and population health status is a reflection of the aggregated sum of such relationship at the individual level, targeting individuals with lower SEP becomes prudent instead of targeting geography with lower socioeconomic profiles. However, for efficiency reasons, interventions are often targeted for the geography in order to have the better coverage for the individuals even the context of the intervention is driven by the SEP of the individual.

In recent times, research is being pursued to investigate the nature of the causal relationship between SES and health. Such investigation follows a competing hypothesis – (1) does SES primarily affect health (the “social causation hypothesis”)?

or (2) does health primarily affect SES (the “health selection hypothesis”)? The life course perspective seeks to unfold the reciprocity and dynamicity between SES and health i.e. the interplay between the “social causation hypothesis” and the “health selection hypothesis”. More recently, the notion of the causal relationship between responsibility and health (ill-health) is becoming prevalent in international health.

Model 1: Social causation hypothesis

Social causation hypothesis stipulates that SES affects health (Nielsen, Juon and Ensminger, 2004 and Wheaton, 1978). From this perspective, SEP determines health through intermediary factors. Longitudinal studies in which SEP has been examined before health problems are present, and in which the incidence of health problems has been measured during follow-up, show higher risk of developing health problems in the lower SES, and suggest “social causation” as the main explanation for socioeconomic inequalities in health (Marmot et al., 1991). This causal effect of SEP on health is likely to be mainly indirect, through a number of more specific health determinants that are differently distributed across SES.

Socioeconomic health differences occur when the quality of these intermediary

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factors are unevenly distributed between the different SES: SEP determines a person’s behaviour, life conditions, etc., and these determinants induce higher or lower prevalence of health problems. The main groups of factors that have been identified as playing an important part in the explanation of health inequalities are material, psychosocial, and behavioural and/or biological factors.

Material factors are linked to conditions of economic hardship, as well as to health damaging conditions in the physical environment, e.g. housing conditions, physical working environment, etc. Hence, health inequalities result from the differential accumulation of exposures and experiences that have their sources in the material world. Meanwhile, material factors and social (dis) advantages predictably intertwine, such that “people who have more resources in terms of knowledge, money, power, social ranking in a hierarchical society, and social connections are better able to avoid/reduce risk and to adopt the protective strategies that are available at a given time and at a given place” (Link and Norhtridge, 1998).

Psychosocial factors include stressors (e.g. negative life events), stressful living circumstances, lack of social support, etc. Recognition of these factors argues that socioeconomic inequalities in morbidity and mortality cannot be entirely explained by well-known behavioural or material risk factors of disease. For example, in cardiovascular disease outcomes, risk factors such as smoking, high serum cholesterol and blood pressure can explain less than half of the socioeconomic gradient in mortality. Marmot, Shipley and Rose (1984) have argued that the similarity of the risk gradient for a range of diseases could indicate the operation of factors affecting general susceptibility.

Behavioural factors, such as smoking, dietary habits, alcohol consumption and physical exercise, are certainly important determinants of health. Moreover, since they can be unevenly distributed between different SEPs, they may appear to have important roles as determinants of health inequalities. Yet this hypothesis is inconsistent in the light of the available evidence (Shavers, 2007). Patterns differ significantly from one country to another. For example, smoking is globally more prevalent among lower SES; however, in Southern Europe, smoking rates are higher among higher income groups, and in particular among women.

The contribution of one’s diet, alcohol consumption and physical activities to inequalities in health is less clear and not always consistent. However, there is higher prevalence of obesity and excessive alcohol consumption in lower SES, particularly in richer countries (Olson et al., 2007 and Olivares et al., 2007 and Mackenbach and Bakker, 2002).

The health system itself constitutes an additional relevant intermediary factor.

Distributional responsibility is at its maximum when the society guarantees equal access to services for all (Solar, 2005). Diderichsen (2001) suggests that services through which the health system influences health can be of five different dimensions: (1) reducing the inequality level among the poor with respect to the causal factors that mediate the effects of poverty on health in such areas as nutrition, sanitation, housing and working conditions; (2) reinforcing factors that

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might reduce susceptibility to health effects from inequitable exposures, using various means including vaccination, empowerment and social support; (3) treating and rehabilitating the health problems that constitute the socioeconomic gap of burden of disease (the rehabilitation of disabilities, in particular, is often overlooked as a potential contributor to the reduction of health inequalities); (4) strengthening policies that reproduce contextual factors such as social capital that might modify the health effects of poverty; and (5) protecting against social and economic consequences of ill health through health security nets and welfare policies. Benzeval, Judge and Whitehead (1995) argue that the health system has three obligations in confronting uneven distribution of health i.e. (1) to ensure that resources are distributed between areas in proportion to their relative needs; (2) to respond appropriately to the healthcare needs of different social groups; and (3) to take the lead in encouraging a wider and more strategic approach in developing healthy public policies at both the national and local level, to promote equity in health and social justice.

Furthermore, the recognition that structural conditions – social and economic policies determine the daily living conditions (CSDH: WHO, 2008) reinforces the concern of interplay between context of SEP and individual health (Sacker, Worts, and McDonough, 2011; Bambra et al., 2009 and Espelt et al., 2008).

Model 2: Health selection hypothesis

The health selection (or drift) hypothesis stipulates that an individual’s health influences an individual’s ability to attain and/or maintain desirable SEP and resources (Elstad, 2001; Power, Matthews and Manor, 1996; Blane, Davey Smith and Bartley, 1993; West, 1991; Eaton, 1980; Perrot and Collins, 1935). This implies that health determines SEP, instead of SEP influencing health. The basis of this selection is that health exerts a strong effect on the attainment of social position, resulting in a pattern of social mobility through which unhealthy individuals drift down the social gradient and the healthy move up. Social mobility refers to the notion that an individual’s social position can change within a lifetime, compared either with his or her parents’ SEP (intergenerational mobility) or with himself/

herself at an earlier point in time (intra-generational mobility). It is important to distinguish between inter- and intra-generational health selection, although few studies are available that examine selection in both ways.

The literature on health and social mobility suggests that, in general, health status influences subsequent social mobility (West, 1991 and Illsley, 1955), but evidence is patchy and not entirely consistent across different life stages. Also, there has been limited and inconclusive evidence on the effect that this could have on health gradients (Bartley et al., 1994 and Blane et al., 1994 and 1990). Bartley and Plewis (1997) have argued that health-related social mobility does not widen health inequalities.

Thus, people who are downwardly mobile because of their health still have better health than the people in the class of destination, upgrading this class.

Similarly, upwardly mobile people will nonetheless lower the mean health in the

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higher SES into which they become incorporated (Manor et al., 2003 and West, 1991). Again, the evidence for this is inconsistent, with some studies suggesting that health selection acts to reduce the magnitude of inequalities (Power et al., 2002; Blane et al., 1999; Hart et al., 1998 and Davey et al., 1998), whereas others do not (Elstad, 2001). Few studies conclude that health selection cannot be regarded as the predominant explanation for health inequalities (Marmot, 1997 and Davey et al., 1994).

Several approaches have been used to study the role and magnitude of health selection on the social gradient. One approach focuses on the effect of social mobility, that is all social mobility and not just that related to health status, on health or health gradients (Rahkonen et al., 1997 and Power et al., 1996). A second approach focuses on the effect of health status at an earlier life stage in relation to health gradients later on (van de Mheen et al., 1998). Rodgers and Mann (1993) and Lundberg (1991) have suggested a third approach to overcome these difficulties by focusing on both prior health status and social mobility.

It may be suggestive to distinguish between when illness influences the positioning of individuals to SES (“direct selection”) and when ill-health has economic consequences owing to varying eligibility for and coverage by social insurance or similar mechanisms (example of “indirect selection”). Blane et al. (1993) argue that the effect of the “direct selection” mechanism on the social gradient is small, and, therefore, direct social mobility cannot be regarded as a main explanation for inequalities in health. More commonly social mobility is considered selective on determinants of health (hence “indirect selection”), not on health itself.

It is also important to take into account that the health determinants on which indirect selection takes place could themselves arise from living circumstances of earlier stages of life (Case, Fertig and Paxson, 2005; Currie and Stabile, 2004; Case, Lubotsky and Paxson, 2002 and Kuh and Wadsworth, 1993). Indirect selection would then be part of a mechanism of accumulation of disadvantage over the life course. The process of health selection may, therefore, contribute to the cumulative effects of social disadvantage across the lifespan, but, to date, the inclusion of health selection into studies of life course relationships is limited.

While the social causation and health selection differ on the primary direction of causal relationship between SES and health, the indirect selection mechanism reflects that the relationship between SES and health is – at least to some extent – spurious (Warren, 2009) owing to the existence of the factors influencing both SES and health.

The reciprocity and dynamicity between SES and health i.e. the interplay between the

“social causation hypothesis” and the “health selection hypothesis”

Malatu and Schooler (2002) found that both social causation and health selection contribute to socioeconomic inequalities in health. The contexts, processes and mechanisms of health development are organised over the multiple frames and so, the relationship between SES and health unfold dynamically over the life course

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(Graham, 2002). Unlike financial resources which can be equalised over time with the payment of interests, developmental inputs are not necessarily fungible.

Life course perspective explicitly recognises the importance of time and timing in understanding the causal links between exposures and outcomes within an individual life course, across generations, and in population level diseases trends. The life course approach investigates the concepts and pathways linking childhood SEP, mid-life economic resources, lifestyle factors and various measures of health in later life (Kim, 2011; Warren, 2009; Guralnik, Butterworth and Kuh, 2006; and Luo and Waite, 2005). This approach directs attention to how the social determinants of health operate at every level of development—early childhood, childhood, adolescence and adulthood—both to immediately influence health and to provide the basis for health or illness later in life. The life course perspective attempts to understand how such temporal processes across the life course of one cohort are related to previous and subsequent cohorts and are manifested in health status trends observed over time at the population level. Time lags between exposure, disease initiation and clinical recognition (latency period) suggest that exposures early in life are involved in initiating disease processes prior to clinical manifestations; however, the recognition of early-life influences on chronic diseases does not imply deterministic processes that negate the utility of later-life intervention.

Ben-Shlomo and Kuh (2002) explains life course perspective of health in two interconnected dimensions

a) The “critical periods” (latency model/biological programming) model - an exposure acting during a specific period has lasting or lifelong effects on the structure or function of organs, tissues and body systems that are not modified in any dramatic way by later experiences. This conception is the basis of hypotheses on the foetal origins of adult diseases. This approach does recognise the importance of later life effect modifiers e.g. in the linkage of coronary heart disease, high blood pressure and insulin resistance with low birth weight (Frankel S et al., 1996). This concept of social trajectories (or pathways) suggests that early life disadvantages (deprivation) sets individuals on disadvantaged trajectories or pathways over time.

b) The “accumulation of risk (cumulative exposure)” model suggests that factors that raise disease risk or promote good health may accumulate gradually over the life course, although there may be developmental periods when their effects have greater impact on later health than factors operating at other times. This idea is complementary to the notion that as the intensity, number and/or duration of exposures increase, there is increasing cumulative damage to biological systems. Understanding of the health effects of childhood social class by identifying specific aspects of the early physical or psychosocial environment (such as exposure to air pollution or family conflict) or the possible mechanisms (such as nutrition, infection or stress) that are associated with adult disease provides further aetiological insights. Circumstances in

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early life are seen as the initial stage in the pathway to adult health but with an indirect effect, influencing adult health through social trajectories, such as restricting educational opportunities, thus influencing socioeconomic circumstances and health in later life. Risk factors tend to cluster in socially patterned ways, for example, those living in adverse childhood social circumstances are more likely to be of low birth weight, and be exposed to poor diet, childhood infections and passive smoking. These exposures may raise the risk of adult respiratory disease, perhaps through chains of risk or pathways over time where one adverse (or protective) experience will tend to lead to another adverse (protective) experience in a cumulative way. A clear gradient exists in the effect of exposure to disadvantaged socioeconomic circumstances on health – the extent of health risk increases with each additional level of exposure (Wamala et al., 2001).

Thus, the life course approach reiterates the endowment nature of health with both intra- and inter-generational effect for the population.

Ben-Shlomo and Kuh (2002) further argue that the life course approach is not limited to individuals within a single generation but intertwine biological and social transmission of risk across generations, contextualised to both within a hierarchical structure as well as in relation to geographical and secular differences, which may be unique to that cohort of individuals. Recently, the potential for a life course approach to aide understanding of variations in the health and disease of populations over time, across countries and between social groups has been given more attention. Davey and Morris (1994) suggest that explanations for social inequalities in cause specific adult mortality lie in socially-patterned exposures at different stages of the life course. Disadvantaged SEP in childhood are associated with less favourable (lower level of education and income, precarious employment and living conditions often with poorer lifestyle) SES in adulthood (Hamil-luker and O’Rand, 2007). Early life disadvantaged SEP attenuates significantly the effect of association of the later life relatively higher SEP, and better lifestyle or behavioural factors – the pathway linking early life disadvantaged SEP to later life poorer health often remain uninterrupted in single generation (Guralnik et al., 2006 and Luo and Waite, 2005). Others argue that any observed attenuation in the effects of SEP on health in later life is simply an artefact of selection - the population becomes more homogenous with only the better-off and good health population surviving to advanced age (Hoffman, 2011 and Dupre, 2007).

Cumulative exposure model includes both repeated and extended exposures to a single factor, or a series of exposures to different factors (Hertzman and Power, 2006 and Lynch and Davey Smith, 2005).

Individuals define their life course experiences within the constraints and opportunities of social circumstances (Elder et al., 2003 and Marshall and Mueller, 2003). Corna (2013) argues that SES and health relationship is better understood with the investigation of processes and structural factors (welfare state policies and provisions) that give rise to and sustain socioeconomics inequalities of health over the life course.

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Model 3: Responsibility and egalitarianism

The focus on proximal determinants, potentially controllable at the individual level emphasises both the ability of the individual to control the own health status and the importance of doing so. This paradigm applies the norm of equality – whether equality of well-being or equality of distributable resources to that over which individual lacks control. Individual responsibility is “the cost of freedom”

(Roemer, 1993) that allows an individual to act on personal tastes and preferences and so reduces the scope of excuses for those choices should they become harmful.

Here, the question becomes whether the worse-off group’s higher probability of ill- health is determined by the individual choices and preferences (placing emphasis on the proximal determinants) or the broader institutional factors (structural determinants) that are consequential for SEP and health over time (Siddiqi and Hertzman, 2007). Roemer (1993) posits that the degree of personal responsibility is sensitive to SEP and thus provides the answer to differentiate causality between ‘health-damaging’ behaviour if freely chosen (…)’ and ‘health-damaging behaviour where the degree of choice of lifestyle (behaviour) is severely restricted’

(Whitehead, 1992). This distinction in causality is counter-intuitive about letting responsibility attached to SEP (Daniels, 2008). Following Dworkin (1981), two main dimensions of responsibility emerges – (1) responsibility over factors i.e.

the idea that the distribution of burdens and benefits ought to be linked to the individual contributions in yielding such burdens and benefits, example: smoking is attributable to an increased risk of cancer and cardiovascular diseases, people who freely decide to smoke should be held accountable for this choice and (2) control over the consequences i.e. alternatives with (dis)incentives for controlling individual behaviour. Right incentives promote health, example: cancer screening programmes, as well as testing and treatment for sexually transmitted diseases encourage appropriate health enhancing behaviour (Haavi, 2000). The disincentive argument is concerned with the treatment effectiveness – responsibility for the actions (control on the behaviour) affecting treatment effectiveness (NOU, 1987 and 1997; SOU, 1993 and MOH – The Hague, 1992).

Unhealthy behaviour is statistically more likely among worse-off (Cappelen and Norheim, 2005) but also people with lower SEP on average have poor health (Link and Phelan, 1995). This suggests that it can be misleading to view unhealthy behaviour as freely chosen (Roemer, 1998). Although the theories argue that individuals should be held responsible for the individual health, establishing a causal relationship between behaviour and outcomes is difficult for most conditions and it is hard to establish with certainty that a particular type of behaviour is the sole cause of the disease in question (Callahan et al., 2000 and NOU, 1987). A higher SEP enhances both the quantity and quality of income, knowledge, power and beneficial social relationship (Phelan and Link, 2010 and Link and Phelan, 2002) which not only apply to the prevention of diseases but also to the effectiveness of the treatment process should the illness occur.

Individual responsibility is tied to the notion of reciprocity – the idea is that individuals are entitled to healthcare services and, in return, the beneficiaries are

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expected to act responsibly (Buyx, 2008). Such reciprocity-based approach spells out differently on individuals given the effect of SEPs in determining individual contribution. Thus, reciprocity account depends on the ability to contribute for upholding distributive justice (Segall, 2005).

Ending up with a disease is not caused by an instant decision, but is rather a consequence of the lifestyle pursued through a lifespan (Daniel, 2008). The lifestyle is not determined by the choices of individual’s alone. Most of the time, lifestyle is determined by social factors which are beyond individual’s control. Central to the mediating factors that explains relationship between individual responsibility and SEP is the notion of control - the link between unhealthy personal behaviours, poor health, and SES (Syme, 1990). Syme (1997) has suggested that people at progressively lower SES have correspondingly less opportunity to control the circumstances and events that affect their lives. Conversely, for individuals at higher SES, contribute to a more generalised sense of “control over destiny,”

which, in turn, confers enhanced health behaviours and health outcomes.

Loss of control has been defined (Syme, 1990) as a reflection of the constraints on coping ability, diminished authority over decisions, threats to SEP and self- esteem, lessened opportunity to learn new skills and acquire knowledge, and inappropriateness of coping. Environmental demands and supports shape psychological responses (Adler and Ostrove, 1999). Individuals in social environments that are consistently threatening are more likely to develop a sense of distrust and fear of others. Over time, this may develop into a more chronic sense of hostility that can place the individual at increased risk for cardiovascular disease (Helmers et al., 1994)). The environment also shapes health behaviours. Low income neighbourhoods have more liquor stores and afford fewer opportunities for exercise and less access to nutritious foods (Macintyre et al., 1993).

The responsibility and egalitarianism for health is beset with structural determinants and institutional factors. The combination of individual characteristics and the environmental demands and constraints affect the likelihood of enacting health-related behaviours, such as tobacco use, alcohol use, exercise, and diet (Chuang et al., 2005; Chaix et al., 2004; Shohaimi et al., 2003;

Diez Roux et al., 2003a; Frohlich et al., 2002; Tseng et al., 2001; Reijneveld, 1998 and Kleinschmidt et al., 1995). The impact of environmental threats and individual responses are modified by the SEP (McEwen, 1998). Socio-political, cultural and social context affect SES (Rawls, 1972 and 1990). Populations living in areas with greater income inequality have shorter life expectancies, independent of median levels of income (Adler and Ostrove, 1999). Other studies have shown that SES of neighbourhoods predicts health status above and beyond individual SEPs (Tomey et al., 2013; Yen and Kaplan, 1999; Diez-Roux et al., 1997 and Haan et al., 1987).

Healthcare services influence the average levels of, and differentials in, the population health outcomes but the role is limited (Acheson, 1998). Other areas of fiscal and social policy, that impinge upon, for example, incomes, education, housing conditions, and nutrition, are potentially far stronger influences, perhaps in large part because they better tackle the fundamental determinants of health (Oliver and Mossialos, 2004).

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Hence, the theories suggest that the perceived health status is not the reflection of the characteristics of health system, but rather an outcome of a complex interplay amongst various determinants of health. These determinants of health are highly contextualised and historically determined by the economic, political and social milieu of existence.

2.1 POPULATION HEALTH AND THE DISTRIBUTION OF THE DETERMINANTS OF HEALTH

The existence of a socio economic gradient in health is well documented (Wilkinson and Marmot, 2003; Macintyre, 1997; Link and Phelan, 1995; Blaxter, 1990 and Blane, 1985). Eikemo et al. (2008) argue that, although individual factors account for variations in health, welfare state arrangements is an important factor explaining variations in population health between countries. Wilkinson’s (1997) theory postulates that a nation’s health is not determined by economic growth per se but rather by the degree of differentiation in living standards experienced by its population. Marmot et al. (1997) have suggested that different mechanisms operate at the top and bottom of the socioeconomic strata – the higher strata population is more susceptible to psychosocial processes while the lower strata are more affected by the effects of absolute poverty.

Standards of living and income distributions have taken centre stage in the discussion of Murray et al. (1999); Sen (1997); Mackenbach and Kunst (1997); Frijters and van Prag (1995) and Illsley (1991) for measuring the social determinants of population health. Siegrist (1995) suggested considering different dimensions of SEP, such as occupation, perceived societal position, education, and income or access to material resources when examining health inequality by SES.

Gilson (1998), Wilkinson (1997); Manor et al. (1997); Mcisaac and Wilkinson (1997); Kunst and Mackenbach !994); Blaxter (1989) and Jones and Moon (1987) concluded that the in-country distribution of material deprivation reflects the in- country health differences, ceteris paribus. Further, Eikemo (2008a and 2008b) and Bambra (2007) found a relationship between the health outcomes and patterns of health inequalities, and the characteristics of the underlying social welfare.

The WHO Commission on Social Determinants of Health model (2008) uses structural determinants of health, intermediary determinants of health and the health system to explain the health inequalities. Structural determinants include factors related to socioeconomic and political environment, and the intermediary determinants are the material circumstances, psychosocial circumstances, behavioural and/or biological factors. Several studies have produced evidences to establish the fact that it is the material circumstances in conjunction with social conditions, and not inherent predispositions to illness, which make the greatest contributions to unequal health (Goldman, 2001; Gordon et al., 1999; DoH, 1998;

Whitehead, 1997 and Macintyre, 1995). Lokshin and Ravallion (2008) have also found that people living in larger households tend to have better perceived health status.

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Individuals with higher income, education, social position or occupational class tend to report better health, and thus lower mortality, compared to those individuals with lower SEP (Alvarez-Galvez et al., 2013; Costa-Font and Hernandez-Quevedo, 2012; Nummela et al., 2007; Kunst et al., 2005 and Wilkinson, 1996 and1997). Bleakley (2003) demonstrates the effect of education on health.

Soobader and LeClere (1999) found that income inequality at the country level exerts an independent effect on perceived health, over and above country median income, percentage in poverty in the country, and individual socioeconomic factors. Income inequality erodes the social cohesion and consequently lowers the health status; the extent of income inequality, not the national wealth, is the most important determinant of in-country differences in health status (Kawachi, Kennedy, and Wilkinson, 1999; Kawachi, Kennedy, Lochner and Prothrow-Stith, 1997 and Wilkinson, 1997).

A signification association between the subjective and objective dimension of health (illness) as a social construction as well as a subjective experience has been established by McCubbin (1997) and Grayson (1993). Using the datasets from 7 FSU countries, Bobak et al. (2000) found that (1) consistent with mortality rates, the prevalence of poor perceived health is high and (2) education and material deprivation are important predictors of perceived health with large socioeconomic gradients.

The dynamic interactions between multiple social and biological processes accumulate over time and such interaction continuously affects population health (Willson et al., 2007 and Blane, 2006).The life course perspective on health inequalities (Wadsworth, 1997; Rahkonen et. al., 1997b; Lundberg, 1993 and Power et al., 1991) postulates that health inequalities are attributed to the risk associated with the shape of social class pattern of health at different ages and the factors that influence health accumulated over the life course. The evidence suggests that a greater cumulative exposure to disadvantaged socioeconomic circumstances over the life course is associated with poorer health outcomes and greater mortality among middle aged and older adults (Gruenwald et al., 2012; Ahnquist, Fredlund, and Wamala, 2007; Turrell, Lynch, Leite, Raghunathan, and Kaplan, 2007; Melchior, Lert, Martin, and Ville, 2006; and Wamala, Lynch, and Kaplan, 2001).

This life course approach of health inequalities views health risks associated with social class as a dynamic phenomenon over time that necessitates the consideration of the association of health risks both with the generational background and social class mobility in adulthood as well as the relationship between these two classes. Health inequalities are often observed along a social gradient - a stepwise or linear decrease in health that comes with decreasing social position (Marmot, 2004).

Hence, the identification of healthy and unhealthy trajectories offers the potential for intervention at particular key points to address health inequalities.

The research evidence (Power et al., 1991) suggests that the consequences of poor educational achievement and deviant lifestyles for subsequent health inequalities are profound though childhoods are characterised by relative

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equality in health. The life course perspective admits (Power et al., 1997) (1) health inequalities are not the product of a single underlying mechanism but rather that several different mechanisms (or pathways) implicated for different dimensions of health; (2) often the stressors belong to different and potentially competing domains and (3) attention to detailed social processes is a critical necessity to generate the evidences.

2.2 THE SUBJECTIVE PERCEPTION OF HEALTHCARE SERVICES AND THE DISTRIBUTION OF POPULATION HEALTH

Satisfaction with healthcare services is both a consequence (Sherbourne et al., 1992) and a determinant (Hays, Kravitz, et al., 1994) of individual health status.

Dissatisfaction with healthcare services results in the non-adherence/non- concordance to the medical prescriptions (Wartman, 1983 and Sherbourne et al., 1992) which in turn leads to a poorer health status (Hays, Kravitz et al., 1994).

Satisfaction has an independent influence on the effectiveness of care - it is suggested that satisfied patients are more likely to follow planned care and make better use of healthcare services (Fitzpatrick, 1990; Larsen and Rootman, 1976).

Fitzpatrick (1984) maintained that satisfaction as a determinant of healthcare service consumption is a confluence of three independent determinants – (1) socially created expectations for the consumers of the services, (2) resolution of health problems (consumers own perception about changes in health status triggered by the service consumption and (3) affective behaviour (a type of behaviour expressed by the service provider to the consumer that treats consumer as a person not a case – defined by Ben – Sira, 1976) of the service provider.

Hall, Milburn and Epstein (1993) argued that a population with better health tends to report greater satisfaction with the consumed healthcare services. Several studies have found evidence suggesting dissatisfaction with healthcare services, in large part, a manifestation of disgust with other facets in life (Linn, 1975; Roberts, Pascoe and Attkisson, 1983). More than one third of variations in satisfaction with healthcare services are attributable to general life dissatisfaction (Roberts et al., 1983).

A broad body of literature suggests age as the most consistent determinant for satisfaction studies - elderly population tend to be more satisfied with healthcare services (Khayat and Salter, 1994; Hopton et al., 1993; Zahr et al. 1991 and Blanchard et al., 1990). Greater satisfaction is associated with lower level of education (Schutz et al., 1994; Hall and Dornan, 1990). Several studies (Delgado et al., 1993; Hopton et al., 1993; Hall and Dornan, 1990; Khayat and Salter, 1994) have concluded that gender does not affect satisfaction values.

The relationship between satisfaction and social class is not consistent – a problem being that socioeconomic variables are often ignored (Hall and Dornan, 1990). Salvage et al. (1988) reported that people in the higher echelons of the society

Health development : a study of the determinants of health and the distribution of perceived health in Afghanistan, Armenia and the Russian Federation

uef.fi

Dissertations in Social Sciences and Business Studies

PAVITRA PAUL

PAVITRA PAUL

HEALTH DEVELOPMENT: A STUDY OF THE DETERMINANTS

OF HEALTH AND THE DISTRIBUTION OF PERCEIVED HEALTH

IN AFGHANISTAN, ARMENIA AND THE RUSSIAN FEDERATION

Health development: a study of

the determinants of health and the

distribution of perceived health

in Afghanistan, Armenia and the

Russian Federation

Health development:

a study of the determinants of health and the distribution

of perceived health in

Afghanistan, Armenia and the Russian Federation

Preface

Acknowledgements

Contents

1 Introduction

2 Theories of the

interactions between

socioeconomic position and health