Inequalities in health: a comparative study between ethnic Norwegians and Pakistanis in Oslo, Norway
© Syed et al; licensee BioMed Central Ltd. 2006
Received: 19 May 2005
Accepted: 29 June 2006
Published: 29 June 2006
The objective of the study was to observe the inequality in health from the perspective of socio-economic factors in relation to ethnic Pakistanis and ethnic Norwegians in Oslo, Norway.
Data was collected by using an open and structured questionnaire, as a part of the Oslo Health Study 2000–2001. Accordingly 13581 ethnic Norwegians (45% of the eligible) participated as against 339 ethnic Pakistanis (38% of the eligible).
The ethnic Pakistanis reported a higher prevalence of poor self-rated health 54.7% as opposed to 22.1% (p < 0.001) in ethnic Norwegians, 14% vs. 2.6% (p < 0.001) in diabetes, and 22.0% vs. 9.9% (p < 0.001) in psychological distress. The socio-economic conditions were inversely related to self- rated health, diabetes and distress for the ethnic Norwegians. However, this was surprisingly not the case for the ethnic Pakistanis. Odd ratios did not interfere with the occurrence of diabetes, even after adjusting all the markers of socio-economic status in the multivariate model, while self-reported health and distress showed moderate reduction in the risk estimation.
There is a large diversity of self-rated health, prevalence of diabetes and distress among the ethnic Pakistanis and Norwegians. Socio-economic status may partly explain the observed inequalities in health. Uncontrolled variables like genetics, lifestyle factors and psychosocial factors related to migration such as social support, community participation, discrimination, and integration may have contributed to the observed phenomenon. This may underline the importance of a multidisciplinary approach in future studies.
Health has a social gradient, i.e. people with lower socio-economic status (SES) have more health related problems than people in the other part of the SES hierarchy [1–5]. Further SE inequalities seem to increase in Western European countries [6, 7]. There may be three possible pathways: increased risk of socially patterned unhealthy lifestyle in lower SES groups [8, 9], unequal access to health care [10, 11], and finally various exposure to material deprivation and a stressful psychosocial environment [12–16].
Inequalities in health across ethnic groups, in terms of both morbidity and mortality, have been documented in the United States [17–21] and the United Kingdom [22–27], both across social class and ethnicity. In the United States the mortality rate for black population has been at least 60 percent higher than for the white population, and trend seems to continue [28, 29]. A number of studies have shown that most British ethnic minorities have higher mortality and morbidity rates compared to the majority ethnic British population [22, 23, 30]. The reported mortality in immigrants with South-Asian descent in the UK caused by coronary diseases, is 40 percent higher than that of Europeans . This seems to be linked to the higher prevalence of diabetes in this group [32–34]. In general, mortality from both cardiovascular diseases and diabetes is more common in immigrant communities especially from South Asia [35, 36] and is linked with the poor SE conditions [37–40]. Similar results have been found for South-Asians immigrants in other countries [32, 41, 42].
A SE gradient has been reported for health inequalities in Norway [43–47]. A study on health inequalities by SES among men has suggested an increased gradient in health inequalities for the period of 1980 to 1990. The inequality pattern appeared to be closer to the average in other European countries . Similarly Norwegian women has shown SE gradient in self-reported health .
Inequalities in health among different ethnic groups in Norway are not extensively studied, despite the fact that earlier surveys and official reports had indicated a different morbidity pattern for immigrants in Norway compared to the native population . Further, it has been reported that immigrants from non-Western countries perceive their health as poor and have high morbidity due to psychological distress and diabetes [51–53].
Self-rated health (SRH) is an important element of the clinical investigation and public health surveillance [54, 55]. It is a subjective appraisal of health and a powerful predictor of survival, functional decline, future morbidity, and subsequent health service utilization. It's validity as a measure of health outcome has been explored after controlling for a variety of physical, socio-demographic, and psychosocial health indices . Moreover, its importance in predicting mortality across SE categories even after adjusting for objective disease, has been reported in earlier studies [57, 58]. For that reason, it has been widely used as a health outcome measure in studies investigating SE inequalities in health. Further it has been reported that immigrants in comparison to the native populations in European context often rate their health as poor .
Psychological distress is a measure of mental health, represented by symptoms of anxiety, depression and somatization. Studies from the Western countries have shown a social gradient; higher SES is associated with lower rate of psychological distress. Moreover, it has been suggested that differences in SES may explain differences in psychological distress between certain groups of immigrants and the native population in Western countries .
Self-reported diabetes was another outcome variable included in the study. The association of many vascular diseases and their risk factors with SES has been well described [61, 62]. Certain risk factors implicated in the development of diabetes are also known to be associated with SES. Obesity, low physical activity, smoking, and low birth weight have all been described as risk factors for type 2 diabetes. In Western societies these factors are associated with lower SES. Thus an inverse relationship would be expected between the prevalence of type 2 diabetes and SES . A few ecological studies have also described, an inverse relation between incidence of type 2 diabetes and relative affluence of the towns [63, 64]. In addition to this knowledge, we also know that immigrants from South-Asia have higher prevalence of diabetes type 2 and coronary heart disease than ethnic Europeans [32, 41]. This high prevalence has also been reported for the immigrants from South-Asia in Norway [52, 65].
Because of the already reported poor SRH, high rates of psychological distress and diabetes among non-Western immigrants in Norway, and additionally their possible relation to SES, the aim of the present study is to investigate to which extent differences in these measures of health between Pakistani immigrants in Oslo may be explained by differences in SES.
In Norway, immigrants with Pakistani background constitute the largest non-Western immigrant group. To the best of our knowledge no previous study has particularly explained inequality in health for this ethnic group from the vantage of SE gradient. Therefore, the objective of our study is to investigate the health inequalities with respect to the selected indicators from the vantage of SE factors between ethnic Pakistanis and Norwegians in Oslo, Norway.
Materials and methods
This is a cross-sectional, population based study conducted as a part of a general health survey known as the Oslo Health Study. This survey was jointly organized during 2000–2001 by the University of Oslo, National Health Screening Services of Norway (now the Norwegian Institute of Public Health), and Oslo Municipality.
The study population included all the inhabitants of Oslo born in 1970, 1960, 1955, 1940/41 and 1924/25 (Figure 1). The Norwegian Registry of Vital Statistics provided information concerning the participant's age, gender, country of birth and residential address. Ethnicity was determined on the basis of country of birth from this register. A cross check with Statistics Norway (SSB) registers confirmed that in 99.8% of the cases the country of birth was identical to their 'country of origin'. The overall attendance rate for Norwegian was 45%, and for ethnic Pakistanis it was 38%. However, the weighted prevalence of self-rated health and other analyzed variables differed only slightly between attendees and the target population, and the association measures were found to be less influenced by the self selection. The details on the methodology were described elsewhere .
The Norwegian Data Inspectorate approved the study. The study protocol was also reviewed by the Regional Committee for Medical Research Ethics in Norway and approved.
A questionnaire was introduced in order to collect SE information including education, employment status, occupational class, and household income. Further, a self-reported health scale indicating known state of general health, diabetes and distress was used. Originally the questionnaire was in Norwegian language, but it was translated into 11 different languages including 'Urdu'. The invitation letter and information brochure was also translated into these 11 languages . The participants were allowed to give their response either in Norwegian or in their own native language.
Education was reported by the respondents as number of total school years. It was converted into primary (7–9 years), middle (10–12 years) and higher education (13 +years) categories. From the information provided by SSB, respondents were categorized into two categories with respect to their civil status, i.e. married and others. The married category included all those who were either married or registered partners. Unmarried, separated/divorced/do not live together and one partner alive were placed under the category of others. At the time of survey respondents were asked about their employment, and the response was recorded against a three item categories, i.e. yes, full time, yes, part time and no. The first two categories were combined to categorize participants into employed and unemployed categories.
The reported information about the profession of the respondents was coded according to the classification suggested by Erikson-Goldthrope . This provided us with seven categories of occupation classes for respondents. These categories included higher service class, lower service class, and routine non-manual, self-employed, Technician/supervisors, skilled manual workers and unskilled manual workers. The first four categories were grouped together as white collar and the other three categories were grouped as blue collar category of occupational class. The information on household income includes all sorts of income including pension or social security before tax. It was provided by the respondents in a range from none to more than 500 thousand Norwegian Kroner (NOK). This income was categorized into three levels as low (no income to 150 thousand NOK), medium (150 to 200 thousand NOK), and high income (>200 NOK).
Self-rated health (SRH) was recorded against a four items response (bad, not very good, good, and very good), and it was converted into two categories as poor or good. Known state of diabetes was registered from the self-reported health form. The respondents were not asked to report the type of diabetes.
Distress level was measured by HSCL-10 as they reported their response against the 10 items included in the instrument. Each item was rated on a scale of 1 (not at all) to 4 (extreme) and a mean score was used as a measure of general psychological distress in the subsequent analyses. For respondents who answered at least 5 items included in the HSCL-10, data was computed by using the mean value of the remaining items reported by the respondent. A mean value of 1.85 or more was used as a marker of psychological distress .
Data was analyzed using SPSS package, version 11.0. For categorical variables we used Chi-squared tests to assess the differences in distribution between groups. For continuous variables, mean and ± 2SD were provided and t-test were performed to assess the differences. All the p values reported were two-tailed. Statistical significance was set at 0.05. Both crude and adjusted prevalence of self-reported health with 95% confidence interval was reported across the socio-economic indicators. Logistic regression models were used to control for the potential confounders. The results are presented as odds ratio (OR) to indicate risk with a 95% confidence interval (CI).
Socio-demographic characteristics of the sample population by ethnicity (percentages)
p < 0.0001
p = 0.017
p < 0.0001
p < 0.001
p < 0.001
p < 0.001
p < 0.001
The level of unemployment was four times higher among the Pakistanis compared to the Norwegians. 66% of the ethnic Pakistanis were in the low income category, and 7% were in the high income group compared to 39% in the high income category in the Norwegians. These socio-demographic differences are in accordance with the already existing statistics on Pakistani immigrants in Norway [71, 72].
Unadjusted and adjusted (age/sex) prevalence of poor-self-rated health, diabetes and distress in sample by ethnicity
Poor health (n)
Age and sex adjusted prevalence and 95% confidence interval for poor self-rated health, diabetes and distress in sample by ethnicity across socio-economic indicators
Poor self-rated health
Odds ratios (95% confidence interval) of poor self-rated health, diabetes and distress for ethnic Pakistanis after inclusion of explanatory variables one by one to the adjusted model for age/sex, Norwegians as reference
Our results confirm the overall poor health reported by the ethnic Pakistanis compared to the Norwegians, irrespective of SE status. The economical gradient is less marked for Pakistanis, and even an opposite trend was observed for distress. For example, individuals with a reported higher education and or higher household income have shown an association with good health among the Norwegians, where as inconsistent result was noted for the Pakistanis.
Possible explanations for the disparity in the observed associations of "health" with education and income for the ethnic Pakistanis and the Norwegians may entail that the ethnic Pakistanis at large belong to the low levels of education and income group. Given the small number of participants from Pakistan belonging to predominantly high education and income strata, it is possible that we do not observe any association of the social gradient with health although the relationship exists. The other possible explanation is that individuals with higher education from the ethnic Pakistani families were not successful in obtaining an employment that may correspond with their educational background. Therefore higher education for the Pakistani's did not result in improved economy and thereby health. Moreover underemployment may interfere with self esteem which may result in stress and depression with an obvious consequence on health.
Another factor that could contribute to the lack of positive association between education and health in the Pakistanis is inaccuracy in reporting education. In a recently conducted study in Oslo, the validity of self-reported education by immigrant communities has been discussed . The conclusion was that in studies based on self-reporting, the tendency to over report education due to social desirability could not be ignored.
Among the SE indices, employment appears to have the maximum impact in explaining higher self reported morbidity among the Pakistanis. This may suggest that being employed, though not necessarily with a high income, has a positive impact on health. This is in accordance with numerous studies showing the negative effect of unemployment [74–78]. The observed unemployment in our study is in accordance with the already existing statistics in Norway. For Pakistanis reported employment rate is 44% compared to 69.3% for the total population. Moreover, described employment pattern for this ethnic group indicated that either they were self-employed with a considerable engagement in hotels and restaurants, or they were employed within elementary occupations . In addition, it has been reported that immigrants do not perform as well on the labor market as natives with similar characteristics and a large proportion of immigrants from non-Western countries is characterized as self-employed marginalized, even when controlling for observed and unobserved individual characteristics .
The design of the study was cross-sectional and we know that inherent problems of a cross-sectional design is that the outcome (in this case self-reported health) and the exposure (in this case SE conditions) are collected simultaneously and thereby cannot predict the causality. Moreover, cross-sectional studies pay little attention to the information bias emerging from the dependent error, which means a possible correlation between the degree of error in measured exposure and measured outcome. Hence, it is possible that estimated associations between self-reported health and SE factors is falsely inflated or deflated in our study .
Self-reporting was the mode of data collection for both health and socio-demographic variables in this study. The data collected by self-reporting has often raised the concerns over its validity. However, self-reported health is widely used in European studies [81–83] and in American studies [84, 85]. Self-reported health appeared to be an important independent predictor of all causes of mortality [86, 87]. However, one cannot rule-out the possibility that cultural differences between ethnic groups may imply that they perceive their physical and mental health differently . This could be the reason for the differences observed in the self-reported health measures across SE indicators for the ethnic Pakistanis in this study. In the context of our study, it seemed that while reporting their health ethnic Pakistanis were contextualizing their prevailing social condition in the Norwegian society. It might be due to this reason that constructs of health such as SRH and distress related to integrated personal perceptions and overlapping in their abilities to incorporate multiple domains of health such as psychosocial well-being, social functioning, and positive affects showed more obvious relation to the SES among Pakistanis. The same explanation could be used to describe the results of our study with regards to diabetes. A discrepancy in perception between reported diabetes prevalence and longstanding illness has been described for ethnic Pakistanis in the U.K. It was further reported that this group does not consider any illness as a longstanding illness unless it cause severe functional disability .
Another methodological challenge was related to the low participation rate for both the ethnic Pakistanis and Norwegians in our study. Low participation in epidemiological studies may threaten the validity and generalizability of the results due to the possibility of selective participation . Though in our case, socio-demographic data provided by the central national register showed that the socio-demographic characteristics of participants were nearly the same as those of the non-participants, with slight deviation for ethnic minorities .
In our study, we used HSCL-10 as an investigating tool for psychological distress. Even though, it was translated into Urdu, it was not validated for the ethnic Pakistanis. Therefore, the results based on HSCL-10 for distress will have to be interpreted with caution.
Inequalities in health between the ethnic Norwegians and Pakistanis were reduced, but not eliminated, when a number of socio-demographic factors were adjusted in a multivariate model. The reduction was strongest for SRH and psychological distress, where as it was weaker for diabetes. The reason for this difference could be that diabetes to a lesser degree than the other measures of health is influenced by the stressors related to migration. Unemployment seemed to be the most important explanatory factor for the difference in health. Given the context of a social-welfare state like Norway, public health policies should be developed to cope against the discrimination in employment for ethnic minorities with a view to promote health.
We are thankful to the Norwegian Foundation for Health and Rehabilitation and Norwegian Diabetes Association for their support and understanding for our work. I am also thankful to the Department of General Practice and Community medicine and National Centre for Minority Health Research for providing us with healthy working environment, guidance and support.
- Acheson D: Independent inquiry into inequalities in health. 1998, London, TSOGoogle Scholar
- Davey Smith G, Blane D, Bartley M: Explanations for socioeconomic differentials in mortality: evidence from Britain and elsewhere. European Journal of Public Health. 1994, 131-144.Google Scholar
- Leon D, Walt G: poverty, inequality and health: an international perspective. 2001, Oxford: Oxford University PressGoogle Scholar
- Smith GD, Egger M: Socioeconomic differences in mortality in Britain and the United States. Am J Public Health. 1992, 82: 1079-1081.PubMed CentralView ArticlePubMedGoogle Scholar
- Strickland S, Shetty P: Human biology and social inequality. 1998, Cambridge: Cambridge University PressGoogle Scholar
- Mackenbach JP, Bos V, Andersen O, Cardano M, Costa G, Harding S, et al: Widening socioeconomic inequalities in mortality in six Western European countries. Int J Epidemiol. 2003, 32: 830-837. 10.1093/ije/dyg209.View ArticlePubMedGoogle Scholar
- Mackenbach JP, Kunst AE, Cavelaars AE, Groenhof F, Geurts JJ: Socioeconomic inequalities in morbidity and mortality in western Europe. The EU Working Group on Socioeconomic Inequalities in Health. Lancet. 1997, 349: 1655-1659. 10.1016/S0140-6736(96)07226-1.View ArticlePubMedGoogle Scholar
- Lantz PM, Lynch JW, House JS, Lepkowski JM, Mero RP, Musick MA, et al: Socioeconomic disparities in health change in a longitudinal study of US adults: the role of health-risk behaviors. Soc Sci Med. 2001, 53: 29-40. 10.1016/S0277-9536(00)00319-1.View ArticlePubMedGoogle Scholar
- Lynch JW, Kaplan GA, Cohen RD, Tuomilehto J, Salonen JT: Do cardiovascular risk factors explain the relation between socioeconomic status, risk of all-cause mortality, cardiovascular mortality, and acute myocardial infarction?. Am J Epidemiol. 1996, 144: 934-942.View ArticlePubMedGoogle Scholar
- Feinstein JS: The relationship between socioeconomic status and health: a review of the literature. Milbank Q. 1993, 71: 279-322.View ArticlePubMedGoogle Scholar
- Mackenbach JP, Stronks K, Kunst AE: The contribution of medical care to inequalities in health: differences between socio-economic groups in decline of mortality from conditions amenable to medical intervention. Soc Sci Med. 1989, 29: 369-376. 10.1016/0277-9536(89)90285-2.View ArticlePubMedGoogle Scholar
- Kuh D, Ben-Shlomo : A Lifecourse Approach to chronic Disease epidemiology. 1997, Oxford, England: Oxford University PressGoogle Scholar
- Lynch JW, Kaplan GA, Cohen RD, Kauhanen J, Wilson TW, Smith NL, et al: Childhood and adult socioeconomic status as predictors of mortality in Finland. Lancet. 1994, 343: 524-527. 10.1016/S0140-6736(94)91468-0.View ArticlePubMedGoogle Scholar
- Health and social organisation. 1996, London: Routledge
- Marmot M, Theorell T, Siegrist J: Work and coronory heart disease. Stress and heart. London. 2002, Stansfeld SA, Marmot M, 50-71.Google Scholar
- Shaw M, Dorling D, Davey Smith G: Poverty social exclusion, and minorities. Social determinants of health. Edited by: Marmot M, Wilkinson. 1999, Oxford: Oxford University Press, 211-239.Google Scholar
- Sorlie P, Rogot E, Anderson R, Johnson NJ, Backlund E: Black-white mortality differences by family income. Lancet. 1992, 340: 346-350. 10.1016/0140-6736(92)91413-3.View ArticlePubMedGoogle Scholar
- Rogers RG: Living and dying in the U.S.A.: sociodemographic determinants of death among blacks and whites. Demography. 1992, 29: 287-303.View ArticlePubMedGoogle Scholar
- Davey SG, Neaton JD, Wentworth D, Stamler R, Stamler J: Mortality differences between black and white men in the USA: contribution of income and other risk factors among men screened for the MRFIT. MRFIT Research Group. Multiple Risk Factor Intervention Trial. Lancet. 1998, 351: 934-939.View ArticleGoogle Scholar
- Sorlie PD, Backlund E, Keller JB: US mortality by economic, demographic, and social characteristics: the National Longitudinal Mortality Study. Am J Public Health. 1995, 85: 949-956.PubMed CentralView ArticlePubMedGoogle Scholar
- Health Status of the Disadvantaged. 1990, Wahsington DC: Department of Health and Human Services
- Harding S, Maxwell R: Differences in the mortality of migrants. Health inequalities. Edited by: Drever F, Whitehead M. 1997, London, England, The Stationery Office. Decennial Supplement Series DS No. 15Google Scholar
- Marmot M, Adelstein A, Bulusu L: Immigrant mortality in England and Wales 1970–78: Causes of death by country of birth. 1984, London: HMSOGoogle Scholar
- Nazroo JY: Ethnicity and Mental Health:Findings from a National Community Survey. 1997, London, England: Policy Studies InstituteGoogle Scholar
- Nazroo JY: The Health of Britain's Ethnic Minorities: Findings From a National Survey. 1997, London, England: Policy Studies InstituteGoogle Scholar
- Nazroo JY: Ethnicity, Class and Health. 2001, London, England: Policy Studies InstituteGoogle Scholar
- Rudat K: Balck and Minority Ethnic groups in England: Health and Lifestyles. 1994, London, England: Health Education Authority, 2005-Google Scholar
- Cooper RS: Health and the social status of blacks in the United States. Ann Epidemiol. 1993, 3: 137-144.View ArticlePubMedGoogle Scholar
- Kochanek KD, Maurer JD, Rosenberg HM: Why did black life expectancy decline from 1984 through 1989 in the United States?. Am J Public Health. 1994, 84: 938-944.PubMed CentralView ArticlePubMedGoogle Scholar
- Nazroo JY: Genetic, cultural or socio-economic vulnerability? Explaing ethnic inequalities in health. Sociol Health Illn. 1998, 710-730.Google Scholar
- Balarajan R: Ethnic differences in mortality from ischaemic heart disease and cerebrovascular disease in England and Wales. BMJ. 1991, 302: 560-564.PubMed CentralView ArticlePubMedGoogle Scholar
- Mather HM, Keen H: The Southall Diabetes Survey: prevalence of known diabetes in Asians and Europeans. Br Med J (Clin Res Ed). 1985, 291: 1081-1084.View ArticleGoogle Scholar
- Pais P, Pogue J, Gerstein H, Zachariah E, Savitha D, Jayprakash S, et al: Risk factors for acute myocardial infarction in Indians: a case-control study. Lancet. 1996, 348: 358-363. 10.1016/S0140-6736(96)02507-X.View ArticlePubMedGoogle Scholar
- Ramachandran A, Snehalatha C, Latha E, Vijay V, Viswanathan M: Rising prevalence of NIDDM in an urban population in India. Diabetologia. 1997, 40: 232-237. 10.1007/s001250050668.View ArticlePubMedGoogle Scholar
- Samanta A, Burden AC, Fent B: Comparative prevalence of non-insulin-dependent diabetes mellitus in Asian and white Caucasian adults. Diabetes Res Clin Pract. 1987, 4: 1-6. 10.1016/S0168-8227(87)80026-8.View ArticlePubMedGoogle Scholar
- Mather HM, Chaturvedi N, Fuller JH: Mortality and morbidity from diabetes in South Asians and Europeans: 11-year follow-up of the Southall Diabetes Survey, London, UK. Diabet Med. 1998, 15: 53-59. 10.1002/(SICI)1096-9136(199801)15:1<53::AID-DIA521>3.0.CO;2-V.View ArticlePubMedGoogle Scholar
- Ko GT, Chan JC, Yeung VT, Chow CC, Tsang LW, Cockram CS: A low socio-economic status is an additional risk factor for glucose intolerance in high risk Hong Kong Chinese. Eur J Epidemiol. 2001, 17: 289-295. 10.1023/A:1017935707807.View ArticlePubMedGoogle Scholar
- Misra A, Pandey RM, Devi JR, Sharma R, Vikram NK, Khanna N: High prevalence of diabetes, obesity and dyslipidaemia in urban slum population in northern India. Int J Obes Relat Metab Disord. 2001, 25: 1722-1729. 10.1038/sj.ijo.0801748.View ArticlePubMedGoogle Scholar
- Riste L, Khan F, Cruickshank K: High prevalence of type 2 diabetes in all ethnic groups, including Europeans, in a British inner city: relative poverty, history, inactivity, or 21st century Europe?. Diabetes Care. 2001, 24: 1377-1383.View ArticlePubMedGoogle Scholar
- Robbins JM, Vaccarino V, Zhang H, Kasl SV: Socioeconomic status and type 2 diabetes in African American and non-Hispanic white women and men: evidence from the Third National Health and Nutrition Examination Survey. Am J Public Health. 2001, 91: 76-83.PubMed CentralView ArticlePubMedGoogle Scholar
- McKeigue PM, Miller GJ, Marmot MG: Coronary heart disease in south Asians overseas: a review. J Clin Epidemiol. 1989, 42: 597-609. 10.1016/0895-4356(89)90002-4.View ArticlePubMedGoogle Scholar
- Nicholl CG, Levy JC, Mohan V, Rao PV, Mather HM: Asian diabetes in Britain: a clinical profile. Diabet Med. 1986, 3: 257-260.View ArticlePubMedGoogle Scholar
- Naess O, Claussen B, Davey SG: Relative impact of childhood and adulthood socioeconomic conditions on cause specific mortality in men. J Epidemiol Community Health. 2004, 58: 597-598. 10.1136/jech.2003.012229.PubMed CentralView ArticlePubMedGoogle Scholar
- Naess O, Claussen B, Thelle DS, Davey SG: Cumulative deprivation and cause specific mortality. A census based study of life course influences over three decades. J Epidemiol Community Health. 2004, 58: 599-603. 10.1136/jech.2003.010207.PubMed CentralView ArticlePubMedGoogle Scholar
- Claussen B, Naess O: [Mortality in Oslo by inequalities in occupational class]. Tidsskr Nor Laegeforen. 2002, 122: 1867-1869.PubMedGoogle Scholar
- Claussen B, Davey SG, Thelle D: Impact of childhood and adulthood socioeconomic position on cause specific mortality: the Oslo Mortality Study. J Epidemiol Community Health. 2003, 57: 40-45. 10.1136/jech.57.1.40.PubMed CentralView ArticlePubMedGoogle Scholar
- Krokstad S, Kunst AE, Westin S: Trends in health inequalities by educational level in a Norwegian total population study. J Epidemiol Community Health. 2002, 56: 375-380. 10.1136/jech.56.5.375.PubMed CentralView ArticlePubMedGoogle Scholar
- Krokstad S, Westin S: Health inequalities by socioeconomic status among men in the Nord-Trondelag Health Study, Norway. Scand J Public Health. 2002, 30: 113-124. 10.1080/14034940210133753.PubMedGoogle Scholar
- Lund E: [Socioeconomic status, self-assessed health and morbidity among Norwegian women aged 45–64]. Tidsskr Nor Laegeforen. 2000, 120: 1131-1134.PubMedGoogle Scholar
- Rognerud M, Strand BH, Hesselberg O: The Health of Disadvantaged Groups in Norway : Norwegian Country Report for the EU Project " Social Inequalities and Health in Europe". 2. 2002, Oslo, Norway, National Institute of Public HealthGoogle Scholar
- Dalgard OS, Sandanger I, Sørensen T, Ingebrigsten G: Mental Health Among Immigrants in Oslo, Norway. Social Psychiatry: A Global Perspective. 1998, New Dehli: McMillian India Limited, 107-112.Google Scholar
- Jenum AK, Holme I, Graff-Iversen S, Birkeland KI: Ethnicity and sex are strong determinants of diabetes in an urban Western society: implications for prevention. Diabetologia. 2005, 48: 435-439. 10.1007/s00125-005-1668-8.View ArticlePubMedGoogle Scholar
- Vangen S, Stoltenberg C, Holan S, Moe N, Magnus P, Harris JR, et al: Outcome of pregnancy among immigrant women with diabetes. Diabetes Care. 2003, 26: 327-332.View ArticlePubMedGoogle Scholar
- Detmar SB, Muller MJ, Schornagel JH, Wever LD, Aaronson NK: Health-related quality-of-life assessments and patient-physician communication: a randomized controlled trial. JAMA. 2002, 288: 3027-3034. 10.1001/jama.288.23.3027.View ArticlePubMedGoogle Scholar
- Pfisterer M, Buser P, Osswald S, Allemann U, Amann W, Angehrn W, et al: Outcome of elderly patients with chronic symptomatic coronary artery disease with an invasive vs optimized medical treatment strategy: one-year results of the randomized TIME trial. JAMA. 2003, 289: 1117-1123. 10.1001/jama.289.9.1117.View ArticlePubMedGoogle Scholar
- Goldman N, Glei DA, Chang MC: The role of clinical risk factors in understanding self-rated health. Ann Epidemiol. 2004, 14: 49-57. 10.1016/S1047-2797(03)00077-2.View ArticlePubMedGoogle Scholar
- Heistaro S, Jousilahti P, Lahelma E, Vartiainen E, Puska P: Self rated health and mortality: a long term prospective study in eastern Finland. J Epidemiol Community Health. 2001, 55: 227-232. 10.1136/jech.55.4.227.PubMed CentralView ArticlePubMedGoogle Scholar
- Idler EL, Benyamini Y: Self-rated health and mortality: a review of twenty-seven community studies. J Health Soc Behav. 1997, 38: 21-37. 10.2307/2955359.View ArticlePubMedGoogle Scholar
- Chandola T: Ethnic and class differences in health in relation to British South Asians: using the new National Statistics Socio-Economic Classification. Soc Sci Med. 2001, 52: 1285-1296. 10.1016/S0277-9536(00)00231-8.View ArticlePubMedGoogle Scholar
- Baum A, Garofalo JP, Yali AM: Socioeconomic status and chronic stress. Does stress account for SES effects on health?. Ann N Y Acad Sci. 1999, 896: 131-144. 10.1111/j.1749-6632.1999.tb08111.x.View ArticlePubMedGoogle Scholar
- Rose G, Marmot MG: Social class and coronary heart disease. Br Heart J. 1981, 45: 13-19.PubMed CentralView ArticlePubMedGoogle Scholar
- Winkleby MA, Fortmann SP, Barrett DC: Social class disparities in risk factors for disease: eight-year prevalence patterns by level of education. Prev Med. 1990, 19: 1-12. 10.1016/0091-7435(90)90001-Z.View ArticlePubMedGoogle Scholar
- Connolly V, Unwin N, Sherriff P, Bilous R, Kelly W: Diabetes prevalence and socioeconomic status: a population based study showing increased prevalence of type 2 diabetes mellitus in deprived areas. J Epidemiol Community Health. 2000, 54: 173-177. 10.1136/jech.54.3.173.PubMed CentralView ArticlePubMedGoogle Scholar
- Weng C, Coppini DV, Sonksen PH: Geographic and social factors are related to increased morbidity and mortality rates in diabetic patients. Diabet Med. 2000, 17: 612-617. 10.1046/j.1464-5491.2000.00352.x.View ArticlePubMedGoogle Scholar
- Grøvedt L: Helseprofil for Oslo. 2002, Oslo, Nasjonalt folkehelseinstitutt & Oslo kommuneGoogle Scholar
- Kumar BN, Meyer HE, Wandel M, Dalen I, Holmboe-Ottesen G: Ethnic differences in obesity among immigrants from developing countries, in Oslo, Norway. Int J Obes Relat Metab Disord. 2005Google Scholar
- Sogaard AJ, Selmer R, Bjertness E, Thelle D: The Oslo Health Study: The impact of self-selection in a large, population-based survey. Int J Equity Health. 2004, 3: 3-10.1186/1475-9276-3-3.PubMed CentralView ArticlePubMedGoogle Scholar
- The Oslo Health Study (HUBRO). [http://www.fhi.no]
- Erikson R, Goldthorpe JH: The Constant Flux. 1992, Oxford: Clarendon PressGoogle Scholar
- Strand BH, Dalgard OS, Tambs K, Rognerud M: Measuring the mental health status of the Norwegian population: a comparison of the instruments SCL-25, SCL-10, SCL-5 and MHI-5 (SF-36). Nord J Psychiatry. 2003, 57: 113-118. 10.1080/08039480310000932.View ArticlePubMedGoogle Scholar
- Employment unchanged among immigrants. [http://www.ssb.no]
- Immigrants face low earning. [http://www.eiro.eurofound.eu.int]
- Kumar BN, Holmboe-Ottesen G, Lien N, Wandel M: Ethnic differences in body mass index and associated factors of adolescents from minorities in Oslo, Norway: a cross-sectional study. Public Health Nutr. 2004, 7: 999-1008. 10.1079/PHN2004644.View ArticlePubMedGoogle Scholar
- Dooley D, Fielding J, Levi L: Health and unemployment. Annu Rev Public Health. 1996, 17: 449-465. 10.1146/annurev.pu.17.050196.002313.View ArticlePubMedGoogle Scholar
- Gerdtham UG, Johannesson M: A note on the effect of unemployment on mortality. J Health Econ. 2003, 22: 505-518. 10.1016/S0167-6296(03)00004-3.View ArticlePubMedGoogle Scholar
- Hallsten L, Grossi G, Westerlund H: Unemployment, labour market policy and health in Sweden during years of crisis in the 1990's. Int Arch Occup Environ Health. 1999, 72 (Suppl): S28-S30.PubMedGoogle Scholar
- Jin RL, Shah CP, Svoboda TJ: The impact of unemployment on health: a review of the evidence. CMAJ. 1995, 153: 529-540.PubMed CentralPubMedGoogle Scholar
- Mathers CD, Schofield DJ: The health consequences of unemployment: the evidence. Med J Aust. 1998, 168: 178-182.PubMedGoogle Scholar
- Self-employment among immigrants: A last resort. [http://www.econ.ku.dk]
- Kristensen P: [Bias from dependent errors in observational studies]. Tidsskr Nor Laegeforen. 2005, 125: 173-175.PubMedGoogle Scholar
- Heistaro S, Vartiainen E, Puska P: Trends in self-rated health in Finland 1972–1992. Prev Med. 1996, 25: 625-632. 10.1006/pmed.1996.0098.View ArticlePubMedGoogle Scholar
- Krause NM, Jay GM: What do global self-rated health items measure?. Med Care. 1994, 32: 930-942.View ArticlePubMedGoogle Scholar
- Power C, Matthews S, Manor O: Inequalities in self-rated health: explanations from different stages of life. Lancet. 1998, 351: 1009-1014. 10.1016/S0140-6736(97)11082-0.View ArticlePubMedGoogle Scholar
- Grant MD, Piotrowski ZH, Chappell R: Self-reported health and survival in the Longitudinal Study of Aging, 1984–1986. J Clin Epidemiol. 1995, 48: 375-387. 10.1016/0895-4356(94)00143-E.View ArticlePubMedGoogle Scholar
- Kaplan GA, Camacho T: Perceived health and mortality: a nine-year follow-up of the human population laboratory cohort. Am J Epidemiol. 1983, 117: 292-304.PubMedGoogle Scholar
- Kington R, Lillard L, Rogowski J: Reproductive history, socioeconomic status, and self-reported health status of women aged 50 years or older. Am J Public Health. 1997, 87: 33-37.PubMed CentralView ArticlePubMedGoogle Scholar
- Miilunpalo S, Vuori I, Oja P, Pasanen M, Urponen H: Self-rated health status as a health measure: the predictive value of self-reported health status on the use of physician services and on mortality in the working-age population. J Clin Epidemiol. 1997, 50: 517-528. 10.1016/S0895-4356(97)00045-0.View ArticlePubMedGoogle Scholar
- Shetterly SM, Baxter J, Mason LD, Hamman RF: Self-rated health among Hispanic vs non-Hispanic white adults: the San Luis Valley Health and Aging Study. Am J Public Health. 1996, 86: 1798-1801.PubMed CentralView ArticlePubMedGoogle Scholar
- Pilgrim S, Fenton S, Hughes T, Hine C, TN : The Bristol Black and Ethnic Minorities Health Survey Report. 1993, Bristol: University of BristolGoogle Scholar
- Ness RB, Nelson DB, Kumanyika SK, Grisso JA: Evaluating minority recruitment into clinical studies: how good are the data?. Ann Epidemiol. 1997, 7: 472-478. 10.1016/S1047-2797(97)00080-X.View ArticlePubMedGoogle Scholar
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