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The role country of birth plays in receiving disability pensions in relation to patterns of health care utilisation and socioeconomic differences: a multilevel analysis of Malmo, Sweden

BMC Public Health volume 6, Article number: 71 (2006) Cite this article

Abstract

Background

People of low socioeconomic status have worse health and a higher probability of being granted a disability pension than people of high socioeconomic status. It is also known that public and private general physicians and public and private specialists have varying practices for issuing sick leave certificates (which, if longstanding, may become the basis of disability pensions). However, few studies have investigated the influence of a patient's country of birth in this context.

Methods

We used multilevel logistic regression analysis with individuals (first level) nested within countries of birth (second level). We analysed the entire population between the ages of 40 and 64 years (n = 80 212) in the city of Malmo, Sweden, in 2003, and identified 73% of that population who had visited a physician at least once during that year. We studied the associations between individuals and country of birth socioeconomic characteristics, as well as individual utilisation of different kinds of physicians in relation to having been granted a disability pension.

Results

Living alone (ORwomen = 1.72, 95% CI: 1.62–1.82; ORmen = 2.64, 95% CI: 2.46–2.83) and having limited educational achievement (ORwomen = 2.14, 95% CI: 2.00–2.29; ORmen = 2.12, 95% CI: 1.98–2.28) were positively associated with having a disability pension. Utilisation of public specialists was associated with a higher probability (ORwomen = 2.11, 95% CI: 1.98–2.25; ORmen = 2.16, 95% CI: 2.01–2.32) and utilisation of private GPs with a lower probability (ORmen = 0.76, 95% CI: 0.69–0.83) of having a disability pension. However, these associations differed by countries of birth. Over and above individual socioeconomic status, men from middle income countries had a higher probability of having a disability pension (ORmen = 1.61, 95% CI: 1.06–2.44).

Conclusion

The country of one's birth appears to play a significant role in understanding how individual socioeconomic differences bear on the likelihood of receiving a disability pension and on associated patterns of health care utilisation.

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Background

Sweden has a general welfare policy that guarantees financial security and social rights to all citizens [1]. Included in this system is the provision of a disability pension for those between the ages of 30 and 64 who, for medical reasons, are incapable of working or supporting themselves financially [2].

A number of studies have investigated the association between different measures of health status [3, 4], medical conditions [5], and receiving disability pensions. Studies of health care utilisation after being granted a disability pension have also been made, with varying results [5–7]. It is known that people of low socioeconomic status have worse health and higher health care requirements than people of high socioeconomic status [8–11]. Therefore, they have a higher probability of eventually being in need of a disability pension [3]. The area where one resides [12] and its socioeconomic characteristics [13] also seem to affect an individual's likelihood of receiving a disability pension.

Even if disability pensions were granted solely on objective medical grounds, the probability of obtaining a disability pension may depend on other types of factors, operating on different levels [12, 14]. It is known that a patient's ability to communicate information and articulate needs influence the provision of health care [15] and disability pensions [16]. Based on an analysis of sick leave certifications, it has also been observed that different types of physicians assign different periods of sick leave for the same diseases [17, 18]. Few studies, however, have investigated the influence of ethnicity in this context [19–22].

Members of a given ethnic group tend to identify themselves and be identified by others on the basis of specific characteristics differentiating them from other groups. People who are born in the same country and who share a number of economic, social, and cultural characteristics in addition to a common geographic origin and language, may exhibit a related probability of receiving disability pensions. In a life-course approach, it is possible that global social circumstances related to the economy of the country of one's birth act to condition individual experiences while growing up. These experiences may, in turn, affect individual health, behaviour, and attitudes, and may find expression years later, after immigration to a new country. The original country of birth may, therefore, bring about patterns of health care utilisation [23], including the likelihood of receiving a disability pension, that are common to those individuals born there.

Sweden offers an ideal scenario for investigating cultural determinants of health care utilisation. Equitable access to health care is ensured by law [24]. Ninety-four percent of the health care system originates from state and county finances that support providers in both the public and private sectors. This universal health insurance seeks to allocate resources on the basis of need, rather than such factors as gender, socioeconomic position, or country of birth [25]. This societal funding of both public and private health care sectors removes fees for services as a major contributing factor by making costs similar between sectors. Also, a direct access to health care, with no gatekeeper function exercised by general practitioners, makes individual choice of provider possible. Patterns of utilisation of specific health care services that may be influenced by country related factors (e.g., learned patterns and expectations) or by an immigrant's interaction with Swedish society can then be studied without being confounded by economical or administrative barriers.

In the presence of this intra-country correlation, multilevel regression analysis (MLRA), for both statistical and epidemiological reasons, appears to be an appropriate methodological approach for investigating the influence country of birth may have exercised on those currently holding disability pensions. MLRA allows us to quantify the role that country of birth plays for understanding individual differences among disability pension recipients [26, 27] and also correctly assess the association between country of birth characteristics (e.g., the economy of that country) and the probability that someone born there will one day receive a disability pension in Sweden [28].

Studying the total population of the city of Malmo, Sweden, we sought to assess the role of the country of one's birth in relation to the probability of having a disability pension. Our intention was to investigate possible associations between individual socioeconomic characteristics (i.e., living alone and level of educational achievement) and being granted a disability pension. In addition, by focusing on those individuals who had had some contact with the Swedish health care system, we wished to determine if an association existed between the kind of physician consulted (i.e., public and private general practitioners, and public and private specialists) and being granted a disability pension.

Methods

Study population

Our study population consisted of all 80 212 individuals aged 40 to 64 years (from 146 different countries) who resided in Malmo, Sweden, during 2003. (Malmo is the largest city in the County of Scania, in southern Sweden, with 257 455 inhabitants as of January 1, 1999.) Of the 80212 people studied, 33% were foreign-born men (n = 40 471) and 31% foreign-born women (n = 39 748). We also identified 73% of the population (58 848/80 212) who had visited a physician at least once in 2003. Of this group, 32% were foreign-born men (n = 26 599) and 31% foreign-born women (n = 32 249).

The present analysis is based on the 2003 County of Scania Register for Resource Allocation, which includes, among other variables, age, gender, marital status, education, income, disability pension, and country of birth, as well as detailed information on health care utilisation for each individual in the county. The Regional Ethics Review Board in Lund, and the Data Safety Committee at Statistics Sweden, approved the use of this database. The information was handled in such a way as to preserve the anonymity of the subjects. Analyses were performed at the individual level, but results always presented in the aggregate.

Outcome variable

A disability pension may be granted for medical reasons to a person who has lost 25% to 100% of their working capacity. For our purposes, the beneficiary of a disability pension is any individual who has been granted such a pension, irrespective of their degree of disability.

Individual characteristics

We considered those people who were single, separated, or widowed as "living alone". This definition did not take into account unmarried couples or people sharing the same household – a factor that might produce misclassification and lead to underestimating the association between living alone and having a disability pension. Formal schooling of nine years or less was categorised as "low educational achievement". Those with further schooling were labelled as having "high educational achievement". Age was considered a contiguous variable and centred on the median. Since the association between age and having a disability pension may not be linear, age-squared was also included in the models. Utilisation of health care (in the form of visits to doctors, irrespective of the type of provider, but excluding hospitalisations) was classified as either "yes" or "no". Those who visited a physician at least once were categorized according to the type of provider they consulted: public general practitioner, public specialist, private general practitioner, or private specialist. An individual who visited different types of physicians during 2003 received multiple classifications.

Country of birth (i.e., contextual) variables

The socioeconomic characteristics of one's country of origin, over and above those of the individual, may have conditioned the likelihood of receiving a disability pension. We tested this hypothesis by using the World Bank Classification of Country Economies as a contextual variable [29] in which countries are classified according their gross national income (GNI) per capita, using the World Bank Atlas method. The GNI categories employed are low, lower middle, upper middle, and high income. We merged the first two into a single category designated "low income country", and used the high income country category as a reference in the comparisons.

Statistical and epidemiological methods

In order to account for a possible modification of effects due to gender, we stratified the study population into males and females.

Due to the hierarchical structure of the data, with individuals nested within countries of birth, and the possibility of intra-country correlation regarding the likelihood of having a disability pension, we applied multilevel logistic regression [26, 30, 31]. Of the 146 different countries of birth that made up our study population, 66 countries were represented by fewer than ten individuals. However, this disproportion can be satisfactorily handled by multilevel regression analysis [31].

We investigated disability pensions for the entire population and separately for those who had contact with physicians. We then established four consecutive multilevel models. In the first or empty model (A), the probability of having a disability pension was only a function of an individual's country of birth and was modelled by a random intercept. Our second model (B) included the individual variables of age, education, and marital status. The third model (C) considered an individual variable for utilisation of health care. Finally, the fourth model (D) expanded the third model to include the contextual variable "World Bank Classification of Country Economies". Models B and C also allowed us to study the interaction between country of birth and individual variables (educational achievement, marital status, and the variable for utilisation of health care) by allowing the regression coefficients of the individual level variables to be random at the level of country of birth. Such models indicate whether the bearing of individual variables on disability pensions differ by country of birth (i.e., for individuals from some countries, living alone or consulting a public general practitioner may be associated with a higher probability of having a disability pension, whereas in other countries the reverse may be true).

By this general strategy we were able to quantify differences between various countries of birth (model A) and estimate the role played by individual characteristics of people from each nation, as well as quantify possible cross-level interactions between marital status, education, and country of birth (model B). The third model (C) assessed the relationship between consulting different providers and having a disability pension, and also indicated possible cross-level interactions between individual patterns of visiting different types of physicians and one's country of birth. Finally, the last model (D) indicated whether the economic circumstances in one's country of birth, over and above individual conditions, were associated with being granted a disability pension in Sweden.

We appraised the association of the variables studied and having a disability pension by odds ratios (OR) with a 95% confidence interval (CI), as obtained from the regression coefficients (standard error).

In order to quantify the influence of country of birth for having a disability pension, we computed the median odds ratio (MOR) [32]. With this method, the variance at the second level (country of birth) is translated into the well-known OR scale. The MOR could represent how much (in median) the likelihood of having a disability pension would increase if an individual had been born in a country whose inhabitants had a greater probability of receiving disability pensions. If the MOR is equal to one, country of birth does not condition an individual's likelihood of having such a pension.

In the presence of slope variance for marital status or level of education (model B), or the variable for utilisation of health care (model C), the country of birth variance becomes a function of individual marital status, education, or physician utilisation (e.g., disability pension differences between countries of birth may be much greater for married individuals than for those living alone, or lower for those who visit a private general practitioner than for those who visit other physicians). Therefore, we calculated the variance between countries of birth as a function of individual variables [33–35], and expressed this variance on the OR scale by means of the MOR [36].

MLwiN software, version 2.0 [34], was used for the analyses. Parameters were estimated using the Markov Chain Monte Carlo (MCMC) procedure. The Deviance Information Criterion (DIC) was used as a measure of how well our different models fit the data. A lower value on the DIC indicated a better fit of the model [37].

Results

Table 1 indicates that 11% of the men and 16% of the women between the ages of 40 and 64 who lived in Malmo in 2003 were granted disability pensions. However, this figure was somewhat higher (14% for men and 18% for women) among those who had had at least one contact with a health care provider in 2003. Individuals from middle income countries had the highest likelihood of having disability pensions. Low educational achievement was less common among individuals from countries with a flourishing economy, but the percentage of people living alone increased as a country's economy improved. A greater number of women than men (81% vs. 66%) had seen a physician one or more times in 2003. Public GPs were more frequently consulted by people from countries with poorer economies. Women from wealthier countries preferred private specialists to a greater extent than men from the same countries.

Table 1 Country of birth economic characteristics of individuals 40 to 64 living in Malmo, Sweden 2003 Country economies according to World Bank classification. Values in parentheses are percentages.
Full size table

Compared to the entire population (Table 1), individuals who had disability pensions (Table 2) more frequently lived alone, had less education, and were in greater contact with health care providers. In general, such individuals tended to use public physicians.

Table 2 Country of birth economic characteristics of disability pension recipients 40 to 64 in Malmo, Sweden, 2003 Country economies according to World Bank classification. Values in parentheses are percentages.
Full size table

Measures of association (fixed effects)

As seen in Table 3, model B, living alone and having low educational achievement were clearly associated with having disability pensions for both men and women. Compared with married and individuals with high educational achievement, those living alone and having low educational achievement had a higher probability of being granted a disability pension. However, marital status seemed a more relevant factor for men and educational level for women.

Table 3 Multilevel logistic regression analysis, entire population. Probability of receiving disability pensions, individual and contextual effects.
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In Table 3, model C, we also note that the OR of receiving disability pensions was high among those who had paid at least one visit to a physician in 2003, both in the case of women (OR 2.45, 95% CI: 2.21–2.71) and men (OR 2.09, 95% CI: 1.93–2.27).

We observed (Table 3, model D) that over and above individual age, educational level, or marital status, men from middle income countries had a higher probability of having a disability pension, and this association was lower and not conclusive for women (ORmen = 1.61, 95% CI: 1.06–2.44; ORwomen = 1.34, 95% CI: 0.82–2.19).

Table 4 represents a similar analysis as Table 3, but this population is restricted to those who have had at least one contact with a physician in 2003. The pattern of association between marital status, education, and country economy in relation to holding a disability pension was similar to that observed in the analysis of the whole population. The association between utilisation of different physicians and having a disability pension was rather heterogeneous. In the case of both genders, using public specialists was clearly associated with a higher probability of having a disability pension (OR approximately 2). We found a slightly higher prevalence of disability pension recipients among women who had visited public GPs, but not in men (ORwomen = 1.23, 95% CI: 1.15–1.32; ORmen = 1.09, 95% CI: 1.01–1.18). However, having a disability pension seemed to be less frequent among individuals visiting private GPs than among those consulting other physicians, especially for men (OR = 0.76, 95% CI: 0.70–0.83). Disability pensions were not associated with the utilisation of private specialists in either women or men (ORwomen = 1.04, 95% CI: 0.96–1.09; ORmen = 1.04, 95% CI: 0.96–1.12).

Table 4 Multilevel logistic regression analysis, population who sought health care. Probability of receiving disability pensions, individual and contextual effects for those who sought health care.
Full size table

Over and above the individual characteristics considered in the analysis, being born in a middle income country (Table 4, model D) increased the probability that a man would receive a disability pension (OR = 1.58, 95% CI: 1.08–2.33).

Measures of variation (random effects)

Tables 5 and 6 show the country of birth variance obtained in the models presented in Tables 3 and 4. Overall, country of birth variance in disability pensions (Table 5, model A) was higher for women than for men (MOR = 2.17 and 1.84, respectively), and this pattern persisted when the analyses were restricted to individuals who sought health care (Table 6, model A).

Table 5 Multilevel logistic regression analysis, random effects, entire population.
Full size table
Table 6 Multilevel logistic regression analysis, random effects, population who sought health care.
Full size table

In model B, Table 5, consideration of the individual composition of countries with regard to marital status and educational achievement improved the fit of the model (as seen by the reduction in the DIC value).

In model C, Table 5, allowing for slope variance for the variables of marital status and educational level also improved the fit. Furthermore, because of the existence of slope variance, country of birth differences in disability pensions became a function of individual marital status; the same was true for the education variable. Country of birth variance appeared to be greater (i.e., a higher MOR) among married individuals than among those living alone, especially for women (MORwomen 2.08 vs. 1.64; MORmen 1.81 vs. 1.50). We also observed greater discrepancies by countries of birth (i.e., a higher MOR) among those with less schooling than for individuals with more education.

When country of birth variance in disability pensions became a function of visiting a physician, we observed a higher MOR for those who had not sought health care than for individuals who had consulted a physician at least once, a fact that was more conspicuous in men than women.

Table 6, model C, indicates that when country of birth variance in disability pensions became a function of utilisation of different providers, the country of birth differences for those who had visited a public specialist (MORwomen 1.76) were lower than for those who had not (MOR 2.10). An opposite pattern was seen for individuals who had utilised private specialists, i.e., their MOR was higher than those who had not.

Discussion

We sought to quantify the role of country of one's birth in understanding the individual probability of being granted a disability pension in the current country of residence (i.e., Sweden). We also examined the association between individual marital status, educational level, and utilisation of health care on the one hand, and disability pensions on the other, weighing whether this association was modified by country of birth. Moreover, we considered whether the economic circumstances of one's country of birth influences the likelihood of receiving a disability pension in the present country of residence (i.e., Sweden), independent of individual socioeconomic characteristics. The simultaneous analysis of these essential research questions represented a methodological challenge that was resolved by applying multilevel regression analysis.

Analogous to what we previously found regarding socioeconomic factors and the utilisation of specific health care providers [23], we observed a clear association between having less education and living alone, on the one hand, and receiving a disability pension, on the other. These associations were expected since it is know that people with low socioeconomic status who live alone have worse health than their high socioeconomic status counterparts and, therefore, have a higher likelihood of being granted a disability pension. However, it was striking to find that these associations were modified by the country of one's birth.

Using the information provided by the MOR as a measure of country of birth variance, we found that country of birth played a greater role than other individual variables when it came to understanding individual differences in the probability of having a disability pension. For example, the individual odds ratio for women living alone to receive a disability pension was 1.62 (Table 4, model B). However, the influence of country of birth was a MOR of 1.90 (Table 5, model B). This contextual effect was more pronounced for women than for men (Table 5). These gender specific effects may express different gender roles and expectations in different countries. An aspect that need more (qualitative) investigation in order to tailor effective public health intervention directed to reduce inappropriate granting of disability pensions [38].

Random slope analysis significantly contributed to understanding the part played by country of birth in the association between socioeconomic position and disability pensions. From a statistical point of view, the inclusion of a random slope parameter increased the fit of the models, as indicated by a lower DIC value. From an epidemiological perspective, the existence of slope variances indicates that socioeconomic gradients were steeper for some countries of birth than for others. Because of this phenomenon, country of birth played a different role for understanding individual differences in the probability of having disability pensions among married people and those with minimal education. It is possible that individuals with greater education and those living alone share values and circumstances that are independent of their country of birth, which would explain the lower MOR for these groups. One might speculate that cultural aspects in some countries dissuade married people from seeking disability pensions, while in other cultures the opposite may be true. We need further qualitative studies in order to comprehend these reasons. In any case, conventional measures of association between socioeconomic factors and disability pensions may be misleading if contextual elements related to country of birth are not considered. This consideration would be of substantial importance in the analysis of health care [39].

We also found that, especially for men, the economic characteristics of one's country of birth influenced the probability of having a disability pension in the new country of residence, i.e., individuals from middle income countries had a greater chance of being granted a disability pension than individuals from more affluent countries (Table 3). However, this contextual effect proved to be not very relevant since the residual country of birth variance was high [36] and the fit of the model did not improve when including this variable.

It is known that having a disability pension is associated with health care utilisation [5, 6] – a fact confirmed by our study. Unexpectedly, however, we noted that the OR for having a disability pension was twice as great for those who had consulted public specialists (generally through hospital out-patients clinics) than for those who had utilised other types of physicians. The opposite, i.e., a lower OR for having disability pensions, was true of those who had visited private GPs. The apparent association between utilisation of public specialists and disability pensions might be attributable to patients with more severe diseases seeking out public specialists, since these physicians have closer affiliations with hospitals. Alternatively, it may be that the Social Insurance Agency that grants disability pensions insists on medical certificates issued by public specialists. However, as our study was cross-sectional, we do not know whether utilisation of public specialists starts before or after disability pensions are granted.

Being outside the workforce might have a direct negative effect on an individual's health [40] and result in higher utilisation of specialised care. The negative association between utilisation of private GPs and disability pensions may have an analogous explanation in this context, i.e., the demand for hospital resources and/or stipulations by the Social Insurance Agency. However, if the above were true, the same phenomenon would also be seen among private specialists and public GPs, which was not the case. Rather, the answer might partly lie in differences between public and private providers regarding incentives for certain actions. Some authors have found significant differences in the length of sick leave certificates and the extent of cooperation with the Social Insurance Agency by private or public providers [17]. Although our study cannot answer these questions, it may point out a direction for future investigation.

Limitations of the study

The present study is based on data that has been gathered for administrative purposes and, therefore, its validity might be questioned. However, Sweden has a long tradition of maintaining population and health care registers, and well-developed systems are in place for recording, storing, and managing this information. The database we studied is used for resource allocation analysis, has been checked for registration errors, and has consistently been handled with professional expertise by the Scania County Council and Statistics Sweden. In this context, country of birth, education, disability pension, and marital status are not self-reported, but are based on official statistics maintained by Swedish authorities, thus increasing the validity of this data. Information on visits to different kinds of physicians is recorded by the county patient administrative system that covers all health care facilities in the Scania region.

We did not use personal income as a proxy for socioeconomic position, since our study was cross-sectional and disability pensions reduce income levels. Moreover, the information available to us on income reflects personal rather than household income, limiting the validity of income as a measure of socioeconomic status: people with low personal incomes may reside in households whose total income is high. This phenomenon is more pronounced for women, whom we were especially interested in studying since they receive a higher percentage of disability pensions than men [41].

Education as a proxy for socioeconomic position has the advantage of being independent of disability pensions, since an individual's level of education is achieved early in life, making the risk of reverse causation less likely. Our database was assembled in 2002 and 2003. Since the year 2000 the education register of Statistics Sweden has implemented quality enhancements that reduce the underestimation of advanced educational levels, while increasing the amount of data available on educational achievement among immigrants.

Because the present database was cross-sectional and we lacked information on how long individuals had been living in Sweden, it is possible that after many years immigrants have a history of disability pension awards and health care utilisation similar to Swedish-born individuals. Therefore, some of the differences between countries of birth could partly reflect disparities in the length of the time immigrants have resided in Sweden.

We had no information on reasons for immigration to Sweden among those we studied, and it is possible that differing reasons might affect the probability of being granted a disability pension. Previous studies have found more sick days and a higher probability of receiving a disability pension recorded for immigrants from countries that traditionally have sent migrant labourers to work in Sweden than from refugee countries [19, 20], which could reflect differences in work strain.

Conclusion

The present investigation has found that the country of one's birth plays a relevant role in understanding individual socioeconomic differences related to being granted a disability pension. As expected, we found that men and women with low educational achievement and those who live alone had a higher probability of having a disability pension, but these associations were modified by one's country of birth. We also found qualitative differences in the relationship of health care utilisation to disability pensions, i.e., a higher probability of having a disability pension among individuals who consulted public specialists and a lower probability for those who visited private GPs.

We believe our investigation presents an innovative methodology for studying socioeconomic and ethnic differences in the distribution of disability pensions. By using a multilevel analytical approach that considered country of birth as a higher level in which people are culturally nested, we applied a statistical and conceptual design that we find more appropriate than classical single-level analysis. Classical analyses usually operate with simple ethnic or geographic categorisations that may be unsuitable for studying the impact of socioeconomic or cultural influences on disability pensions [42]. Conversely, employing a way of classifying individuals within a city according to their country of birth (by incorporating a contextual socioeconomic taxonomy that relies on World Bank criteria for a country's economy) provides a simple approach to analysing factors that may contribute to inequalities in health care determinations among a diverse urban population.

References

  1. Socialtjänstlag. 2001

  2. Lag om allmän försäkring. 1962

  3. Krokstad S, Johnsen R, Westin S: Social determinants of disability pension: a 10-year follow-up of 62 000 people in a Norwegian county population. Int J Epidemiol. 2002, 31 (6): 1183-1191. 10.1093/ije/31.6.1183.

    Article  PubMed  Google Scholar 

  4. Mansson NO, Rastam L: Self-rated health as a predictor of disability pension and death--a prospective study of middle-aged men. Scand J Public Health. 2001, 29 (2): 151-158. 10.1080/14034940152393426.

    CAS  Article  PubMed  Google Scholar 

  5. Wallman T, Burel G, Kullman S, Svardsudd K: Health care utilisation before and after retirement due to illness. A 13-year population-based follow-up study of prematurely retired men and referents from the general population. Scand J Prim Health Care. 2004, 22 (2): 95-100. 10.1080/02813430410005126.

    Article  PubMed  Google Scholar 

  6. Eden L, Ejlertsson G, Leden I: Health and health care utilization among early retirement pensioners with musculoskeletal disorders. Scand J Prim Health Care. 1995, 13 (3): 211-216.

    CAS  Article  PubMed  Google Scholar 

  7. Hojsted J, Alban A, Hagild K, Eriksen J: Utilisation of health care system by chronic pain patients who applied for disability pensions. Pain. 1999, 82 (3): 275-282. 10.1016/S0304-3959(99)00055-X.

    CAS  Article  PubMed  Google Scholar 

  8. Berkman LF, Glass T, Brissette I, Seeman TE: From social integration to health: Durkheim in the new millennium. Soc Sci Med. 2000, 51 (6): 843-857. 10.1016/S0277-9536(00)00065-4.

    CAS  Article  PubMed  Google Scholar 

  9. Lynch JW, Kaplan GA, Shema SJ: Cumulative impact of sustained economic hardship on physical, cognitive, psycological, and social functioning. N Engl J Med. 1997, 337:

    Google Scholar 

  10. Lynch JW, Smith GD, Kaplan GA, House JS: Income inequality and mortality: importance to health of individual income, psychosocial environment, or material conditions. BMJ. 2000, 320: 1200-1204. 10.1136/bmj.320.7243.1200.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  11. Wilkinson RG, Marmot M: Social determinants of health: the solid facts. 2003, Copenhagen , WHO, 31-2:nd

    Google Scholar 

  12. Johnell K, Månsson NO, Sundquist J, Melander A, Blennow G, Merlo J: Neighborhood social participation, use of anxiolytic-hypnotic drugs and women’s propensity for disability pension: a multilevel analysis. Scand J Public Health. 2005, preview article:

    Google Scholar 

  13. Krokstad S, Magnus P, Skrondal A, Westin S: The importance of social characteristics of communities for the medically based disability pension. Eur J Public Health. 2004, 14 (4): 406-412. 10.1093/eurpub/14.4.406.

    Article  PubMed  Google Scholar 

  14. Suominen S, Gould R, Ahvenainen J, Vahtera J, Uutela A, Koskenvuo M: Sense of coherence and disability pensions. A nationwide, register based prospective population study of 2196 adult Finns. J Epidemiol Community Health. 2005, 59 (6): 455-459. 10.1136/jech.2003.019414.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Andersen RM: Revisiting the behavioral model and access to medical care: does it matter?. J Health Soc Behav. 1995, 36 (1): 1-10.

    CAS  Article  PubMed  Google Scholar 

  16. Ostlund GM, Borg KE, Wide P, Hensing GK, Alexanderson KA: Clients' perceptions of contact with professionals within healthcare and social insurance offices. Scand J Public Health. 2003, 31 (4): 275-282. 10.1080/14034940210165037.

    Article  PubMed  Google Scholar 

  17. Arrelöv B: Towards Understanding of Determinants of Physicians Sick-listing Practice and their Interrelations: A Population-based Epidemiological Study. Department of Public Health and Caring Sciences. 2003, Uppsala , Department of Public Health and Caring Sciences, 57-

    Google Scholar 

  18. Hetzler A, Melén D, Bjerstedt D: Sjuk-Sverige. Försäkringskassan, rehabilitering och utslagning från arbetsmarknaden. 2005, Stockholm , Brutus Östlings Bokförlag Symposion, 256-

    Google Scholar 

  19. Bengtsson T, Scott K: Immigrant consumption of sickness benefits in Sweden, 1981-1991. 2002, Lund , Lund university, 23-

    Google Scholar 

  20. Eden L, Ejlertsson G, Lamberger B, Leden I, Nordbeck B, Sundgren P: Immigration and socio-economy as predictors of early retirement pensions. Scand J Soc Med. 1994, 22 (3): 187-193.

    CAS  PubMed  Google Scholar 

  21. Elders LA, Burdorf A, Ory FG: Ethnic differences in disability risk between Dutch and Turkish scaffolders. J Occup Health. 2004, 46 (5): 391-397. 10.1539/joh.46.391.

    CAS  Article  PubMed  Google Scholar 

  22. Hyyppa MT, Maki J: Why do Swedish-speaking Finns have longer active life? An area for social capital research. Health Promot Int. 2001, 16 (1): 55-64. 10.1093/heapro/16.1.55.

    CAS  Article  PubMed  Google Scholar 

  23. Beckman A, Håkansson A, Råstam L, Chaix B, Gerdtham UG, Merlo J: Country of birth economic characteristics and individual inequities in health care utilisation—a multilevel analysis of the choice of providers in the city of Malmö, Sweden. Submitted, availiable on request. 2005

    Google Scholar 

  24. Hälso- och sjukvårdslag. 1982

  25. Health on equal terms--national goals for public health. Scand J Public Health Suppl. 2001, 57: 1-68.

  26. Goldstein H, Browne W, Rasbash J: Multilevel modelling of medical data. Stat Med. 2002, 21 (21): 3291-3315. 10.1002/sim.1264.

    Article  PubMed  Google Scholar 

  27. Merlo J: Multilevel analytical approaches in social epidemiology: measures of health variation compared with traditional measures of association. J Epidemiol Community Health. 2003, 57 (8): 550-552. 10.1136/jech.57.8.550.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  28. Merlo J, Chaix B, Yang M, Lynch J, Råstam L: A brief conceptual tutorial on multilevel analysis in social epidemiology - interpreting neighbourhood differences and the effect of neighbourhood characteristics on individual health. J Epidemiol Community Health. 2005, In press:

    Google Scholar 

  29. World Bank T: Country Classification. [http://www.worldbank.org/data/countryclass/countryclass.html]

  30. Leyland AH, Goldstein H: Multilevel modelling of health statistics. 2001, Chichester , Wiley

    Google Scholar 

  31. Snijders T, Bosker R: Multilevel analysis - An introduction to basic and advanced multilevel modeling. 1999, Wiltshire , SAGE Publications

    Google Scholar 

  32. Larsen K, Merlo J: Appropriate assessment of neighborhood effects on individual health: integrating random and fixed effects in multilevel logistic regression. Am J Epidemiol. 2005, 161 (1): 81-88. 10.1093/aje/kwi017.

    Article  PubMed  Google Scholar 

  33. Merlo J, Asplund K, Lynch J, Rastam L, Dobson A: Population effects on individual systolic blood pressure: a multilevel analysis of the World Health Organization MONICA Project. Am J Epidemiol. 2004, 159 (12): 1168-1179. 10.1093/aje/kwh160.

    Article  PubMed  Google Scholar 

  34. Rasbash J, Browne W, Goldstein H, Yang M, Plewis I, Healy M, Woodhouse G, Draper D, Langford IH, Lewis T: A user´s guide to MLwiN. 2000, London , University of London

    Google Scholar 

  35. Subramanian SV, Jones K, Duncan K: Multilevel methods for public health research. Neighbourhoods and health. Edited by: Kawachi I. 2003, Oxford , Oxford University Press

    Google Scholar 

  36. Merlo J, Chaix B, Ohlsson H, Beckman A, Johnell K, Hjerpe P, Råstam L, Larsen K: A brief conceptual tutorial of multilevel analysis in social epidemiology - using measures of clustering in multilevel logistic regression to investigate contextual phenomena. J Epidemiol Community Health. 2005, In press:

    Google Scholar 

  37. Browne WJ: MCMC estimation in MLwiN. Edited by: Edmond SW Ng. 2004, London , Centre for Multilevel Modelling, Institute of Education, University of London, 299-2.0

    Google Scholar 

  38. Wamala S, Agren G: Gender inequity and public health. Getting down to real issues. Eur J Public Health. 2002, 12 (3): 163-165. 10.1093/eurpub/12.3.163.

    Article  PubMed  Google Scholar 

  39. Krieger N: Counting accountably: implications of the new approaches to classifying race/ethnicity in the 2000 census. Am J Public Health. 2000, 90 (11): 1687-1689.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  40. Hansson BS, Andersson C, Isacsson SO, Lindström M, Nilsson J, Rosvall M: Hur mår Malmö? Folkhälsorapport 1996. 1996, Malmö , Samhällsmedicinska institutionen

    Google Scholar 

  41. Försäkringskassan: Sjukersättning och aktivitetsersättning utbetalade i december 2003 och 2004. Edited by: Försäkringskassan . 2005, Försäkringskassan, 2005:5: 7-

    Google Scholar 

  42. Beckman A, Merlo J, Lynch JW, Gerdtham UG, Lindstrom M, Lithman T: Country of birth, socioeconomic position, and healthcare expenditure: a multilevel analysis of Malmö, Sweden. J Epidemiol Community Health. 2004, 58 (2): 145-149. 10.1136/jech.58.2.145.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

This study was financed by grants from the Swedish Council for Working Life and Social Research (Principal investigator JM, # 2003–0580), the Swedish Medical Research Council (Principal investigator JM, # 2004–6155), Scania Region's Health Care Research Funds, and from the Regional Council for Health Care Research (HSF # 263).

This study is a part of the Scania Region's project on "Distribution and determinants of disability pension in Scania"

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Authors and Affiliations

  1. Department of Clinical Sciences, Lund University, University Hospital, S-205 02, Malmo, Sweden

    Anders Beckman, Anders Hakansson, Lennart Rastam & Juan Merlo

  2. Regional Office, Scania County Council, Lund, Sweden

    Thor Lithman

Authors
  1. Anders Beckman
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  2. Anders Hakansson
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  3. Lennart Rastam
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  4. Thor Lithman
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  5. Juan Merlo
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Correspondence to Anders Beckman.

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The author(s) declare that they have no competing interests.

Authors' contributions

AB performed the statistical analysis and AB and JM conceived of the study, participated in the design, analysis, and drafted the manuscript. AH, LR and TL have revised the manuscript critically for intellectual content. All authors have given final approval of the submitted version

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Beckman, A., Hakansson, A., Rastam, L. et al. The role country of birth plays in receiving disability pensions in relation to patterns of health care utilisation and socioeconomic differences: a multilevel analysis of Malmo, Sweden. BMC Public Health 6, 71 (2006). https://doi.org/10.1186/1471-2458-6-71

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Keywords

  • Health Care Utilisation
  • Disability Pension
  • Deviance Information Criterion
  • Gross National Income
  • Private Specialist

BMC Public Health

ISSN: 1471-2458

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