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Health Promotion by Social Cognitive Means

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Health Promotion by Social Cognitive Means

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Using Cognitive Theory to Facilitate Medical Education

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Using Cognitive Theory to Facilitate Medical Education

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Background

Medical education has changed significantly over time. The changes are linked not only to changes in educational technology and the advancement of medical knowledge, but also in educational concepts and curricula. From the 1940s, key principles and practices of the discipline-based model were questioned by educators. In 1944, Goodenough advocated for a reduction in basic science detail which seemed to "clutter up the student's mind and deaden interest" [ 1]. Sinclair [ 2] noted that medical students are often attracted to medicine by a sense of idealism, but the premedical, preclinical and clinical sequence of instruction discourages them.

An early wave of innovation saw a revised curriculum which focused on organ systems. This may be one of the earliest examples of an attempt to better integrate the curriculum. Two different models followed which then catalyzed significant changes in medical curricula. One is problem based learning (PBL), which has been in use since 1971 and still remains popular in many medical schools. The other is the clinical presentation (CP) based model, which has been used since 1991.

Educators continue to search for better strategies for medical education. Papa et al. [ 3] detail the unifying theme of reforms: increasing interest in, attention to, and understanding of the knowledge base structures and cognitive processes that characterize and distinguish medical experts and novices. There are three main aspects to this theme: (1) more attractive courses; (2) well organized knowledge; and (3) proper guidance for different students. Although these aspects are relatively independent, they are often confused by educators. Attractive courses are not necessarily effective, and effective training is not always interesting. It is difficult to achieve all these aspects via a single type of instruction.

In this paper, we aim to answer several questions: (1) What is the basic step in medical learning, to think or to memorize? (2) Why do some curricula seem attractive, but prove not to be effective? (3) What are the differences between novices and experts? (4) How can novices become experts, and how best can novices be given instruction? Answers to these questions are complex and widely debated. However, we argue that cognitive load theory proposed by Sweller et al. [ 4- 8] holds answers to these questions. Cognitive load theory is based on human cognitive architecture and assumes a limited working memory capacity. We argue that when designing instruction, it must be taken into more explicit consideration.

Methods

PBL has been shown to be less effective than expected in teaching of internal medicine [ 9]. We aimed to determine the reasons for this. As a first step, key words linked to medical education were selected and used in a literature search. These included 'medical education', 'curriculum', 'problem based learning', and 'clinical reasoning.' 'Advantage', 'disadvantage' or 'limit' were also used when needed. For the second step, we added several other key words, closely related to cognitive load theory. They included 'cognitive load', 'schema', 'worked examples' and 'working memory.' We used these key words to search in Google Scholar ( http://scholar.google.com) and Pubmed ( http://www.ncbi.nlm.nih.gov/pubmed/). Related search results on this topic were selected for discussion. The full text of articles was acquired from the open internet proxy service of Shanghai Jiao Tong University and the library of the School of Medicine, Shanghai Jiao Tong University. The research protocol was approved by the Ethics Committee of Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University.

Results and discussion

Memorizing: a basic step in learning

What is the most basic step in medical learning? To make students "thinkers" rather than "memorizers" was the hallmark of the discipline-based curricular movement, which dates back to the late 19 th century. In 1898, Sternberg echoed the importance of thinking in his American Medical Association (AMA) presidential address [ 3]. Over the next hundred years, educators continually made efforts to support this view and the importance of thinking over memorizing. However, we contend that to be a thinker, one first needs to be a memorizer. Although it may not follow that a good thinker should be a good memorizer, a good thinker most likely needs to draw on a wide and deep reservoir of memorized knowledge. In Sweller's words, the more sophisticated and knowledgeable the learner, the more complex will be the elements he or she is dealing with [ 10]. An element is defined here as material to be learned.

The definitions of short-term memory (STM) and long-term memory (LTM) indicate the different time spans of the information retention associated with each. STM retains information for just a few seconds. LTM can hold information for several days or decades. Working memory (WM) stores task-relevant information and involves "the temporary storage of information that is being processed in any of a range of cognitive tasks" [ 11, 12]. Because of temporary storage, WM was once considered as a function of STM. Now, many researchers believe STM is in fact a component of WM, and there are other mechanisms based on skilled use of storage in LTM. Ericsson and Delaney used the term "long-term working memory (LTWM)" to refer to information that is stored in stable form, but could be retrieved temporarily by means of cues in STM [ 13]. Baddeley considered this as an interactive mode between LTM and WM rather than a new type of WM per se [ 14].

As LTM has been demonstrated as an important source of WM, knowledge in LTM should not be neglected. In medical education, acquisition of declarative knowledge depends on memory, especially LTM, and LTM can also directly affect actions [ 14]. Procedural or skills based knowledge should be retrieved from LTM when needed [ 15]. Problem-solving performance is dependent on knowledge of specific areas, so clinical reasoning ability cannot be separated from LTM. As Clark et al. [ 16] described, novices can attend the problem-solving process, but they may learn almost nothing. Memorizing should be regarded as a first basic step in learning as it gives a firm foundation for further learning and practice. However, promoting memorizing remains a challenging task.

Cognitive load theory: a framework for proper instruction

In medical learning, considering only the large volume of information, the challenges associated with learning can be very high. For clinical reasoning education, the cognitive load becomes higher because of the high interactivity of elements. The large amount of information and high intrinsic cognitive load can explain why medical learning is most often a challenge. Learning processes could be affected when the cognitive load exceeds the limit of WMC [ 26]. Medical students have to take considerable time in memorizing and understanding the unrelated learning materials. One solution is to decrease the extraneous cognitive load in learning materials [ 26].

Moving to our second question: Why do some curricula seem attractive, but not effective? High intrinsic cognitive load causes difficulties when studying medicine because of the large volume of information. When inappropriate teaching methods are used (e.g., guidance integrated with different disciplines or problem based exploration) this will serve to even further increase the extraneous cognitive load without decreasing the burden of intrinsic load.

Although cognitive load theory has not always been explicitly considered, there is evidence for its effectiveness. In the 1950s, the Western Reserve School of Medicine initiated the first organ-system curriculum [ 27]. Educators aimed to help students integrate knowledge of system-oriented functions and malfunctions. This reform failed because while it appeared to integrate basic science with clinical knowledge, learners struggled to achieve this integration. As the amount of information was not reduced and interacting elements were added to the curriculum, extraneous cognitive load became untenably high, especially for junior medical students. Students in the early years of their degree programs have limited background knowledge of medicine, and are not able to effectively chunk the large number of elements into schemata. The cognitive load of the organ-system framework most likely exceeded the students' WMC. The demands of that process may be viewed as analogous to expecting novice foreign language learners to readily master grammar.

PBL focuses on clinical cases and is widely used in medical education. There has been considerable debate about PBL, and attitudes towards the approach vary considerably. Literature suggests that it can be used as an effective approach, but this is not always the case. Patel et al. found that PBL students were less accurate in diagnosis and made more conceptual errors than their more traditionally trained counterparts [ 28]. Albanese et al. carried out a meta-analysis focusing on PBL and its effectiveness [ 29]. They found that PBL students spent more time studying, but that their basic science exam scores were lower than students who were being trained using other methods. Although PBL students achieved better scores for their clinical performance, they were found to order significantly more unnecessary tests for their patient, which means a higher cost with less benefit. In Berkson's meta-analysis, similar conclusions were reached [ 30]. Colliver reviewed PBL literature and noted no convincing evidence that PBL improves students' knowledge base and clinical performance [ 31]. While Kirschner debates the effect of PBL [ 9], Sanson-Fisher et al. highlight a lack of evidence supporting the superiority of PBL over traditional methods [ 32]. PBL is innovative, but has yet to meet the requirements of evidence-based practice. Sweller et al. emphasize that PBL may teach students how to find information, but it does not reduce the relevant information that is ultimately required to be assimilated [ 33]. A more recent meta-analysis suggests that unassisted discovery does not benefit learners [ 34]. Conversely, feedback, worked examples, scaffolding, and elicited explanations might work.

PBL aims to improve the hypothetico-deductive reasoning (HDR) of students. However, HDR brings with it a high cognitive load, which needs some degree of prior background knowledge and some basic skills. Students may face the same challenges in PBL as in the organ-system curriculum. Before acquiring basic knowledge, the cognitive load is high and materials might be hard for students to understand. This can explain why PBL students spend more study hours and make more conceptual errors. Haeri et al. did not recommend widespread use of HDR [ 35]. Although the full use of PBL is not advocated for medical curricula, it should be noted that this does not mean that PBL is totally outdated or inappropriate. It does have some uses in medical education, especially if understood in light of the cognitive load theory, a point to which we return later.

Schemata: distinguishing experts from novices

Inappropriate instruction cannot promote learning, especially in novices. Before giving proper instruction, we consider the differences between novices and experts. While a person may have the capability to memorize Shakespeare's dramas, it does not mean that s/he would then have the writing skills of Shakespeare! Could one learn more when memorizing more? Although this seems logical, it may not be accurate. A study of physicians has shown a positive relationship between memory for numerical laboratory data and expertise [ 36]. However, when participants were informed at the outset that a memory test would be given, the difference between experts and students was no longer reliable. This retrieval task showed that there is no significant memory difference between experts and students, but experts can memorize related information simultaneously. While storing information in LTM is the basic step of learning, Paas et al. suggested two other critical mechanisms: schemata acquisition and the transfer of learned procedures from controlled to automatic processing [ 37]. Evidence showed that domain specific knowledge in the form of schemata is the primary factor distinguishing experts from novices in learning and problem-solving skill [ 21].

Schemata consist of highly organized knowledge and information. According to Elstein, knowledge organization and schemata acquisition are important in developing expertise [ 38]. For example, experiments suggest that chess experts can remember 50,000 game positions. This superior memory is thought to be mediated by the familiar and meaningful configurations of the chess pieces [ 39]. A chess master stores a large amount of information regarding the specific patterns of chess pieces in LTM, and memory representations allow for the rapid recognition of patterns in a presented chess position. Cooke et al. contended that skilled chess players encode chess positions in terms of high-level descriptions of their structure [ 40].

The research on chess players suggests two aspects of organized knowledge in LTM: (1) Using organized knowledge can increase the speed of retrieval from LTM; (2) After a training period, a large amount of organized knowledge relating to a specific area can be stored in LTM. New information can be organized more quickly by experts in a specific field. A schema is a cognitive construct that organizes the elements of information according to how they will be processed [ 21]. In Sweller's cognitive load theory, schemata could reduce elements' interactivity, and thereby reduce the intrinsic cognitive load. According to Ericsson et al., the bottleneck for retrieval from LTM is the lack of retrieval cues that relate to the desired item stored in LTM [ 13]. Schemata represent a higher level of organized knowledge than a simple collection of lower-level components [ 41]. Although organized knowledge cannot increase the retrieval cues, it can reduce the need for such cues. Schemata that contain automated procedural knowledge, can be considered as a whole to be retrieved together. Learners with higher levels of knowledge can retrieve appropriate schemata and generate more appropriate solutions.

Now we can also explain why senior doctors are better at clinical reasoning than novices. Clinical reasoning is complex and requires breadth of knowledge, knowledge organization and retrieval ability, and that each of these aspects work together. Doctors will always require a broad perspective of organized knowledge for their reasoning. Schmidt describes how experts may have access to extensive case knowledge, but this knowledge remains 'encapsulated' until needed [ 42]. Rikers et al. showed that encapsulated knowledge plays a very important role in specialists' clinical reasoning [ 43] and that this is very different from the clinical reasoning of senior medical students. While senior medical students could use basic scientific knowledge to explain a phenomenon, specialists made more accurate diagnoses even in areas beyond their own specialty.

Proper instruction helps novices become experts

In 1998, educators from UCFM carried out an analysis of the use of CPC. They found that it generated less stress than other curricula, despite an equivalent workload [ 51]. In 2009, a comparison of a 3- and 4-year curriculum was made by Lockyer et al. [ 52]. CPC was applied in a 3-year curriculum at UCFM. The results showed no significant difference between students from UCFM and those following a 4-year curriculum. Students from UCFM were saving about 3 months of medical study time to meet the same standard. Although UCFM have provided the only data based evidence of CPC to date, other researchers have given their support to CPC. Tsai introduced CPC and supported its use in Taiwan [ 53]. Haeri et al. also recommended CPC as a more appropriate choice than PBL. CPC may offer a preferable way of training, but its focus is on clinical education rather than on preclinical work or basic sciences [ 35]. Worked examples can foster diagnostic knowledge [ 54]. van den Berge et al. showed that novices who studied worked examples of electrocardiograms (ECG) performed better on a retention test [ 55]. Worked examples can also be applied to the acquisition of visual perceptual skills, and have even been used in more complex skills training, such as bronchoscopy and catheter-based cardiovascular interventions [ 56, 57].

Returning to PBL, we note that this approach has been used in a range of different areas. In medical education, PBL is considered an appropriate way to promote HDR abilities and it has been implemented in many curricula [ 58]. PBL has been widely used as a way to encourage exploration, but many scholars argue that its use in medical education needs reconsideration [ 9]. Today there are still many PBL curricula used in medical schools around the world. A PBL curriculum will typically give simulated scenarios of real clinical work, with minimal guidance given beforehand. It is a student centered active learning activity which strives to promote self-study [ 3]. However, there is no evidence to show that PBL students perform better than students following a traditional curriculum. This may be because of the inappropriate implementation of PBL. As PBL is an HDR process with feedback, it has to be supported by sufficient related knowledge. Novices have yet to acquire this knowledge. They lack the knowledge to complete the process. In early stages of medical education, basic science and preclinical courses are the main components of learning. Memorizing knowledge plays an important role at that stage. There is a large amount of new information in anatomy, pathology, physiology and biochemistry. The task is difficult because of the high volume of information [ 10]. Using PBL at that stage cannot reduce the intrinsic load. HDR with high interactivity of elements might even increase the extraneous cognitive load. This could explain why PBL students achieve lower scores in basic science [ 29]. For senior medical students, the situation is quite different, especially when they begin their internships. Senior students have more relative knowledge than novices, and they will be exposed to more clinical problems than their junior peers. As formation of schemata (increasing expertise) can reduce the intrinsic cognitive load, partially or minimally guided instruction can be effective for senior students and residents under supervision [ 16].

Conclusion

Medical education reform is ongoing. The motivation underpinning this reform has not changed over time. Although different methods have been trialed in medical education, memorizing is still an important step, especially for the basic sciences. According to cognitive load theory, the intrinsic cognitive load of subjects like anatomy or pathology originates mainly from the large volume of new information. Methods to decrease extraneous cognitive load might not be effective in the case of these subjects. To store more information in LTM might be the only feasible solution. Learning challenges will increase when cognitive load is high. Inappropriate use of educational methods can also increase the extraneous cognitive load. When cognitive load exceeds WMC, it will negatively affect the learning processes. The failure of the organ-system curriculum described in this paper gives an example of this negative overloading effect. Similarly, the inappropriate use of PBL will lead to the same outcome. These curricula seem attractive and innovative, but are not effective. Clinical reasoning is a complex process with a high intrinsic cognitive load. Experts are skilled at clinical reasoning when compared with novices. We have emphasized that this is because of their experiences. These experiences are based on the formation of cognitive schemata. We described the application of such schemata where experts have developed worked examples for students to facilitate their study. Ultimately, this may promote clinical reasoning. Although the full use of PBL is not recommended in medical education, it could be effectively used as a supplementary approach with senior students to facilitate their exploration and self-study.

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Using cognitive theory to facilitate medical education

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Medical education has changed significantly over time. The changes are linked not only to changes in educational technology and the advancement of medical knowledge, but also in educational concepts and curricula. From the 1940s, key principles and practices of the discipline-based model were questioned by educators.

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Health Education for Children and Adolescents

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Health Education for Children and Adolescents

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Health education in one form or another has been a traditional part of public education at the primary and secondary school level. Common approaches have attempted to teach sound habits related to, for example, nutrition, safety, hygiene, physical activity, and more recently, smoking and the use of drugs. These approaches have been justified with reference to a generally accepted belief in the "desirability" of such teaching. More recently, additional emphasis has been directed at health education for children as the links between behavior and health have become more obvious and as the rapidly accelerating costs of treating rather than preventing sickness have been experienced. The objective of the paper is to examine the responses of the research community to the apparent need for more effective health education for children.

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Health Education for Children and Adolescents

# data[].attributes.attachment_link.description
Health education in one form or another has been a traditional part of public education at the primary and secondary school level. Common approaches have attempted to teach sound habits related to, for example, nutrition, safety, hygiene, physical activity, and more recently, smoking and the use of drugs.

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Social Determinants of Cardiovascular Disease Outcomes

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Social Determinants of Cardiovascular Disease Outcomes

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Abstract

Cardiovascular diseases (CVD) are the leading cause of death and disability in both developed and developing countries. In developed countries socio-economic mortality differentials have been studied extensively showing that the low socio-economic group suffers the highest mortality. As the epidemiological transition is taking place against a background of economic globalization, CVD risk factors among the urban poor and middle class are rapidly increasing in India. Recent evidences from India also suggest reversal of social gradient with excess burden of CVD morbidity in the low socio-economic group. Understanding the social determinants of environmental and behavioural exposures, in determining the risk factors for cardiovascular disease is an important challenge for public health professionals as well as communities. Socio-economic disadvantage is not simply a proxy for poor cardiovascular risk factor status, but also an indication of the likely trajectory that an individual or a community may follow in the course of their life. The paucity of intervention research seeking to address the role of social determinants in shaping lifestyle practices among individuals in culturally and socially diverse population groups within India is definitely a measure of inadequacy in public health research. This review article provides an overview of the role of social determinants of CVD and its possible conceptual pathways with special focus on acute coronary syndrome (ACS) outcomes among Indians.

Keywords: Acute coronary syndrome, cardiovascular disease, social determinants, social gradient

Introduction

Cardiovascular disease (CVD) is no longer limited to developed countries, it is widespread in developing countries. Additionally, the rate of increase in CVD in developing countries is twice as high as in developed countries. CVD also typically occurs at a younger age in developing countries: for example, about 52 per cent of deaths from such disorders in India occur before 70 yr of age, compared with 23 per cent in established-market economies. In the context of this large and growing disease burden, strategies to improve population health in India require consistent efforts to identify and address the real causes of this rapid rise in CVD.

In developed countries socio-economic mortality differentials have been studied extensively showing that the low socio-economic group suffer the highest mortality ⁻. Such a trend was not observed for CVD in India until the 1990s, and CVD was regarded as a disease of the affluent classes. The epidemic of CVD struck the more affluent sections of India first, but as the epidemic is maturing, we are observing a graded reversal of social gradient, with socio-economically disadvantaged groups becoming increasingly vulnerable to CVD. For example, the social class gradient in cardiovascular event rates among Indians has reversed with evidence for excess CVD events among the lower socio-economic groups ⁻. In a survey conducted in 45 rural villages in India, 32 per cent of all deaths were due to CVD, outranking infectious diseases, which were responsible for 13 per cent giving clear evidence that the epidemic has reached its advanced stage even in rural India. Neglect of this epidemic, particularly ignoring the socio-economic context as they are driven by social and economic changes with lack of an adequate public health response will further fuel the inequities associated with CVD in Indians.

Socio-economic mortality differentials have been demonstrated using several indicators of social position representing occupational, educational, and financial aspects. Commonly used variables for assessing social determinants of health are given in . Although most of the studies have considered each socio-economic variable individually and at single points in time, the mechanisms through which these affect health are often linked and vary over time. It is challenging to quantify the effect of social disadvantage on CVD outcomes because social and economic factors are surrogates for the latent construct of social disadvantage. While the various dimensions of socio-economic position are interrelated, it has been suggested that these represent rather different forces associated with health outcomes. However, education has been proposed as the preferable variable to other socio-economic indicators to describe health outcomes. There is evidence from several countries showing that its association with mortality and morbidity is probably the strongest among other social determinants of health ⁻. This paper provides an overview of the role of social determinants of CVD and its possible conceptual pathways with special focus on acute coronary syndrome (ACS) outcomes among Indians.

Table I

Place of residence

Location of residence or neighbourhood of residence (rural, urban, peri-urban), citizenship, house ownership, etc.

Race/Ethnicity

Race, ethnicity, dissimilarity index*, isolation index**, perceived discrimination, foreign born status, etc.

Gender

Gender, partner violence, perceived role within family, perceived discrimination against males/females, sex selective abortion rates, etc.

Education

Highest educational attainment, years of education, literacy rate, etc.

Socio-economic status

Income, education, occupation, parent's education, parent's occupation, household items, type of house, ownership of land, car and other luxury items, etc.

Social class differences in CVD outcomes: evidence from migrant studies

Among South Asians in the United Kingdom (UK), there is a continuing excess of CVD and in particular ischaemic heart disease (IHD) deaths ⁻. A literature review of all published studies also suggest significantly higher coronary heart disease (CHD) mortality ratio of 1.1-3.8 among migrants from Indian subcontinent when compared to the host country populations. Two decades ago, McKeigue et al linked this excess CHD risk in migrant South Asians in UK to an emerging trend in inverse association between social class and CHD. Later, Bhopal et al demonstrated this relationship in migrants from the Indian sub-continent in UK. In a recent study, Tillin et al present evidence on increased risk of ischaemic heart disease (IHD) when socio-economic disadvantage was measured as fewer years of education among predominantly Indian, South Asian community in UK. While Tillin's study highlights the intimate relationship between CVD outcomes and social class, similar observations on social class differences in perceived health outcomes among Indians in UK have been reported by Chandola. This clearly indicates that social class differences are emerging as important determinants of increased CHD risk in migrants from the Indian sub-continent.

Social determinants of CVD outcomes in India

Case control studies of acute myocardial infarction (AMI) in India showed significantly higher risk of AMI among low socio-economic group compared to high socio-economic group. Similarly, 30 days follow-up data of acute coronary syndrome (ACS) patients from CREATE registry demonstrated significantly higher mortality rate in low socio-economic status (SES) group compared to higher SES group. Further, a clear inverse gradient of SES and ACS related mortality was evident across four different categories of socio-economic position. These differences persist even after adjustment for clinical symptoms and the area of infarct. The SES inequity in risk for ACS mortality is not fully accounted for by socio-economic gradients of classical risk factors in CREATE registry, which suggests additional or alternative pathways underlie the association between SES and cardiovascular diseases. However, the inverse gradient disappeared once it was adjusted for treatment differences across various socio-economic groups. Three quarters of patients in this study were from lower middle socio-economic class and poor backgrounds. They were either less likely to afford the treatments in the hospitals for secondary prevention or the health care personnel were inept in identifying the needs of this group due to various other reasons.

Gradient in CVD risk factors across socio-economic groups

As the epidemiological transition is taking place against a background of economic globalization, CVD risk factors among the urban poor and middle class are rapidly increasing in India. Consequent to the impact of globalization, there is an "aspiration effect" which has behavioural consequences among the upper middle class and rich people in India. The aspiration for to emulate the western society leads to improved awareness of the preventive measures to tackle the raised CVD risk in these groups. By contrast, higher levels of tobacco use, obesity or overweight and hypertension are now associated with lower levels of education and income in India. Since development is socially and regionally uneven in India, the social gradient in CVD risk factors is also expected to be uneven across societies and geographical locations. For example, in more urbanized communities there is higher vulnerability of low educational group to CHD risk factors and related events compared to less urbanized communities in India. It is therefore, important to understand that the socio-economic disadvantage is not simply a proxy for poor cardiovascular risk factor status, but also an indication of the likely trajectory that an individual may follow in the due course of life.

Social gradient in awareness and treatment seeking behaviours related to CVD risk factors

While prevalence of diabetes in India increases as the educational level decreases, the awareness of diabetes was lowest in the low education group. Several urban-rural comparison studies also documented poor awareness of CVD risk factors in socio-economically disadvantaged rural population ⁻. These studies also highlight the inadequate treatment practices for management of risk factors especially diabetes and hypertension among the rural population. Widespread implementation of programmes like hypertension detection and follow up programme in US resulted in increased awareness, treatment and control of hypertension and ultimately eliminated the association of mortality with low socio-economic status. Similar community based programmes will be helpful for reducing the cardiovascular disease burden in Indian population as well.

Conceptual models for social gradient in health outcomes

The latent effect model: The latency model emphasizes the prospect that psychosocial and socio-economic conditions vary early in life will have a strong impact later in life independent of intervening experience. Power & Hertzman describe a latent effects model wherein certain early life events may have strong independent effects on adult health. However, circumstances in early childhood can affect health status later in life independent of intervening experience ( i.e., latent effects), and also through the life pathways that individuals get set on ( i.e., pathway effects).

The pathway model: The pathway model emphasizes the cumulative effect of life events and the reinforcing effect of differing psychosocial and socio-economic circumstances throughout the life cycle. The duration of "exposure" to at-risk living conditions has a dose-response effect on subsequent health and well-being. Hertzman et al propose a developmental process linking early-life psychosocial environments with adult health risk via pathway effects, wherein early experiences place an individual onto a certain "life trajectory," eventually impacting adult health. While a pathway life course model is generally appealing, its operation is difficult to test empirically. Life course studies typically collect information on participants at two or three time points, which do not permit the continuous, lifelong operation of pathway effects to be observed.

The social mobility model: Forsdahl hypothesized that deprivation in early life followed by later affluence combine to produce elevated CVD mortality risk, partly via elevation of adult cholesterol levels. According to this hypothesis, migrants who encounter prosperity in adult life, having experienced relative deprivation during childhood, should face an even greater risk of CVD than long-term residents of the country they migrate to. However, early deprivation may not be the only explanation for high CVD rates in South Asian migrants in UK, since Afro-Caribbean's and others who have migrated from less developed regions have low CVD mortality rates.

The cumulative model: The cumulative SES life course model hypothesizes that psychosocial and physiological experiences and environments during early and later life accumulate to influence adult disease risk. Smith et al suggest that if factors operating at different life stages are combined, large differences in CVD risk will be observed. An additive effect of both childhood and adulthood socio-economic disadvantage on CVD mortality has been reported in the Southall study.

New perspectives on social gradients in health outcomes

The social gradient in health (health status rises with each level of socio-economic status) suggests that health status may be embedded in collective factors in society, not just in individual factors. Since health status follows a gradient pattern, people in poorer socio-economic circumstances are not as healthy as those in the middle-class, and middle-class groups are not as healthy as those at the top. However, a large number at the bottom still develop into healthy and competent adults. In other words, not all children and adults living in low socio-economic circumstances have poor health, they are simply more likely to develop poor physical and emotional outcomes than those living in better circumstances.

The socio-economic gradient in health status is not new in India. In fact, the socio-economic gradient in health status seems to be able to replicate itself on the principal diseases of each era, despite the fact that their pathological basis varies greatly. For instance, till early 1990s the gradient was found for infectious diseases that were the principal cause of death in India at that time. By the beginning of the new century, the socio-economic gradient had replicated itself in heart diseases which are the current major causes of death.

Future research needs

Possible study designs to understand the social gradient in CVD morbidity and mortality are given in the . Longer prospective studies or series of cross-sectional studies that evaluate associations between early-life experiences and risk factor levels at several time points may provide the opportunity to observe the operation of pathway life course effects. Life course SES studies have generally failed to consider the length of exposure to the various socio-economic conditions measured. As this may influence the impact of negative SES experiences on adult health, future cumulative life course studies may benefit from evaluating the effect of length of exposure into their indices. The paucity of intervention research seeking to address the role of social determinants in shaping lifestyle practices among individuals in culturally and socially diverse population groups within India is definitely a measure of inadequacy in public health research. A large opportunity for pioneering evaluation research models that will demonstrate the effectiveness of social determinant interventions in reducing and ultimately eliminating health disparities is therefore possible in countries like India.

Table II

Policy implications of socio-economic gradient in CVD outcomes in Indians

Socio-economic determinants are strongly linked to CVD risk factors, related morbidity and mortality. Failure to acknowledge, and more importantly, to understand the role of social determinants in health and access to health and social services will hamper any effort to improve the health of the population. A paradigm shift away from the biomedical model is therefore required in the perspective of the existing health care system while responding to the rapidly increasing burden of CVD morbidity and mortality in India. A population perspective, that considers social and ethnic differences in health status, needs to be highlighted and the action plan should involve institutions outside the health sector, based on an appreciation of the economic and social causes of disease. Persistence and an open attitude to learning without receding to previous paradigms and ways of intervening, can lead us to uncover contemporary ways to address the issues that underlie and perpetuate socio-economic disparities in CVD outcomes. Identifying and addressing disparities based on socio-economic position will surely move India closer to the Millennium Development Goals (MDGs).

References

1. [ The World Health Report, 2002: reducing risks, promoting healthy life. Geneva: World Health Organization; 2002. WHO. [ PubMed] Google Scholar]

8. Marmot M, Wilkinson RG. [ Social determinants of health. Oxford: Oxford University Press; 1999. Google Scholar]

18. Valkonen T. Adult mortality and level of education: A comparison of six countries. In: Fox J, editor. [ Health inequalities in European countries. London: Gower; 1989. pp. 142-62. Google Scholar]

22. Jeemon P, Neogi S, Prabhakaran D, Bhatnagar D, Cruickshank JK. The impact of migration on CVD and its risk factors among Indians. [ Google Scholar]

41. Smith GD, Ben-Shlomo Y, Lynch J. Life course approaches to inequalities in coronary heart disease risk. In: Stansfeld SA, Marmot MG, editors. [ Stress and the heart: psychosocial pathways to coronary heart disease. London: BMJ Books; 2002. pp. 21-49. Google Scholar]

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Social determinants of cardiovascular disease outcomes in Indians

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