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Workplace
ORIGINAL ARTICLE
Unemployment and coronary heart disease among middle-aged men in Sweden: 39 243 men followed for 8 years Andreas Lundin,1 Daniel Falkstedt,2 Ingvar Lundberg,1 Tomas Hemmingsson1,3 1
Division of Occupational Medicine, Karolinska institutet, Institute of Environmental Medicine, Stockholm, Sweden 2 Department of Public Health Sciences, Karolinska institutet, Stockholm, Sweden 3 Centre for Social Research on Alcohol and Drugs, Stockholm University, Stockholm, Sweden Corresponding to Dr Andreas Lundin, Division of Occupational Medicine, Karolinska institutet, Institute of Environmental Medicine, SE-17176 Stockholm, Sweden; [email protected] Received 9 July 2013 Revised 11 November 2013 Accepted 17 December 2013 Published Online First 8 January 2014
ABSTRACT Background Although unemployment may be a stressful life event, its association with coronary heart disease (CHD) remains unclear. This study examines the association between unemployment and later hospitalisation due to CHD. Methods The study was based on a Swedish military conscription cohort of 18 to 20-year-old men from 1969/1970 (n=49 321) with information provided on health status and health behaviours. Information on unemployment in middle age was obtained from national registers. CHD information was obtained from hospital registers and the cause of death register. Cox proportional hazard analyses were run on the 39 243 individuals who were in paid employment in 1996 and 1997. Results It was found that ≥90 days of unemployment was associated with subsequent CHD during 8 years follow-up (crude HR=1.47, 95% CI 1.23 to 1.75). Controlling for known risk factors for CHD reduced the association but a significant association remained (HR=1.24, 95% CI 1.04 to 1.48); ≥90 days of unemployment was significantly associated with CHD during the first 4 years (HR adjusted for known risk factors=1.31, 95% CI 1.01 to 1.71). Conclusions Unemployment was associated with increased risk of CHD after adjustment for confounders. We interpret the increased risk of CHD associated with unemployment as potentially the somatic result of a process started by stress.
INTRODUCTION
To cite: Lundin A, Falkstedt D, Lundberg I, et al. Occup Environ Med 2014;71:183–188.
Unemployment is a stressful life event1 shown to be associated with mental health outcomes such as suicide, depression, anxiety and alcohol use disorders.2–4 It has been mentioned as potentially contributing to the socioeconomic gradient in mortality and morbidity,5 6 hypothetically also through coronary heart disease (CHD).7 8 The link to somatic disease is suggested to go through both material hardship and psychosocial stress, mediated by pathophysiological responses, as well as negative change in health behaviours.9 The status of unemployment as an independent cardiovascular risk factor is not settled,10 and while unemployment has been linked to changes in cardiovascular risk factors for example, body mass index (BMI)11 and smoking,12–15 current studies on associations between unemployment and CHD, stroke, myocardial infarction (MI) and cardiovascular disease (CVD) show no clear pattern.16–20
Lundin A, et al. Occup Environ Med 2014;71:183–188. doi:10.1136/oemed-2013-101721
What this study adds ▸ Despite being a stressful life event, unemployment has an unclear association with coronary heart disease (CHD) ▸ Previous studies have had limited possibility to control for risk factors for CHD existing before unemployment. ▸ This study on middle-aged men shows that unemployment is associated with CHD even after controlling for known important risk factors for CHD.
In one Swedish job closure study of 17 008 displaced and 188 000 non-displaced workers followed for 12 years, there was no increased risk of either MI or stroke hospitalisation associated with displacement.16 However, in a similar Danish study of 33 065 displaced workers and 1 161 222 controls, displacement was associated with increased risk for MI/stroke mortality.20 In one recent Swedish study, based on register linkage of 3.4 million individuals, unemployment was found to be significantly associated with mortality from circulatory diseases, ischaemic heart disease and stroke during 6 years of follow-up. Only health measured as previous hospitalisation could be controlled for as potential confounding, which had little reducing effect.19 Three studies, 6-, 10- and 18 year follow-ups of the US Health and Retirement Study, have also examined MI and stroke following job loss (layoff or plant closure) in workers 50 years or older. In these studies, job loss was found to be associated with stroke17 18 and MI.18 21 Unlike the large register-based studies mentioned above, these studies had information on known risk factors for CHD, smoking, hypertension, obesity and diabetes, and although those in the first two studies had little reducing effect on the risk estimates, they substantially reduced association between unemployment and MI in the 18-year follow-up. We have previously examined unemployment and CVD mortality in the same cohort as the present study is based upon. Although a crude association between unemployment of less than 90 days and subsequent CVD mortality during 8 years was found, the increased risk was diluted towards null and nonsignificant when controlling for confounding variables related to health and socioeconomic position (SEP).22 183
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Workplace Both layoffs and re-employment after layoff are selection processes in which workers’ individual characteristics are scrutinised by employers. While age, education, cognitive ability and SEP are well-known determinants of unemployment,23 less is known about health and health behaviour as risk factors for unemployment.24 Sickness absence has been shown to be a strong risk factor for unemployment in Sweden and elsewhere.25–28 Also, a few studies have shown that major risk factors for CHD, such as smoking, BMI and high blood pressure,29–32 are more prevalent among those who later become unemployed,13 33–36 and in a previous Swedish study on 800 unemployed individuals those with circulatory problems had lower probability of becoming employed the following year.37 Furthermore, life-course studies have shown that indicators of poor circumstances in childhood, for example, SEP and crowded housing, are associated with adult unemployment.13 33 We have previously shown the importance of risk factors measured before adulthood in relation to CHD mortality later in life.38–40 The aim of the present study was to examine if becoming unemployed is associated with subsequently increased risk of CHD, adjusted for CHD risk factors measured across the life course prior to unemployment. The following research questions were posed: (i) Is exposure to unemployment associated with an excess risk of CHD? (ii) If so, to what extent is the association between unemployment and CHD confounded by risk factors preceding unemployment?
METHODS Study design The study population consisted of the Swedish Conscription cohort of 1969/1970, originally including 50 465 men. By law at this time, all men were required to undergo 2 days of examination at one of six conscript centres across Sweden, usually during the year of their 18th birthday. A small number of conscripts are older than 18, but this study encompass only those born in 1949 (5%), 1950 (18%) and 1951 (77%); 49 321 individuals. Due to severe handicap or congenital disorder, a small group did not attend conscript examination, estimated to be 2– 3%. Through unique identification numbers, we linked register information on employment, income, education, hospitalisation and mortality to the baseline examination. Included in this study are all those who were in paid employment 1996/1997 (having a work-related income above SEK 36 600/US$8300) and who had no disability pension 1999–2001 (n=40 823). This exclusion criterion was made to ascertain that individuals were in the labour force, that is, had worked and were under risk of unemployment. Of these, 40 071 had never had any CHD at the start of follow-up and 39 243 had information on all variables. All analyses are based on these individuals.
Unemployment Information on yearly accumulated days registered as unemployed was obtained from the Longitudinal Integration Database for Health Insurance and Labour Market Studies (LISA), based on administrative records reported by the Public Employment Service. This is a national government agency, which is the largest placement service in Sweden and also the controlling function for any benefits from the unemployment insurance funds and Cash Labour Market Assistance. Conditions to be fulfilled are stipulated in the Unemployment Insurance Act section 9, which agrees with the International Labour Organization definition of unemployment as (1) lacking work, (2) being available for employment and (3) looking for work. The studied exposure, unemployment, was formed from 184
persons with short-term unemployment (1–89 days of accumulated registered unemployment) and long-term unemployment (90 or more days of accumulated registered unemployment) 1998–2000. This division was based on the theoretical assumption of duration dependence; that the probability of leaving unemployment for work declines with the duration of unemployment. That is, short-term unemployment is more likely to be completed spells with exit to employment, while long-term unemployment is more likely to be ongoing spells and/or exits to labour market programmes.
Coronary heart disease Information on CHD between 2001 and 2008 was obtained from record linkage with the National Patient Register and the Cause of Death Register, administered by the National Board of Health and Welfare. Codes of CHD according to the 10th revision of International Classification of Disease (ICD-10) were I20–I25.
Confounders Parent SEP was based on the SEP of the individuals’ parents (with priority of father’s SEP) or other head of household where applicable. Categories were (i) unskilled worker, (ii) skilled worker, (iii) assistant non-manual employee, (iv) nonmanual employee at intermediate level, (v) non-manual employee at higher level, (vi) farmer and (vii) not classifiable in SEP. Crowded housing was categorised as >2 persons/room— kitchen not included. The Information on childhood social circumstances was collected from the National Population and Housing Census of 1960 of the individuals’ parents—matched through the Multigenerational Register at Statistics Sweden. From the conscription examination, we got information on BMI, systolic and diastolic blood pressure, cognitive test results, as well as questionnaire answers concerning smoking. BMI was calculated as body weight (kg) divided by height (m) squared. Systolic and diastolic blood pressures were measured in mm Hg after 5–10 min test. Smoking was self-reported as 1= >20 cigarettes/day, 2=11–20 cigarettes/day, 3=5–10 cigarettes/day, 4=1– 5 cigarettes/day and 5=non-smokers. General cognitive ability was based on the combined results from four cognitive tests, SEB67, normalised into a standard-nine scale.41 Information on SEP, sickness absence and level of education in adulthood was obtained from LISA. SEP was categorised in the same way as for parents (described above). Education in 1990 was classified as completion of 9 years or less, 11, 12 or more than 12 years of education. Sickness absence 1996–1997 was information on registered benefits from spells from national health insurance lasting longer than 14 days, dichotomised as present or not. An illustration of the collected data is provided in table 1.
Statistical analysis The association between exposure to unemployment in 1998– 2000 and CHD 2001–2008 (and subperiods 2001–2004 and 2005–2008) was investigated by means of crude and multivariate Cox proportional-hazard models using the PHREG procedure in the SAS statistical package (V.9.1; SAS Institute Inc, Cary, North Carolina). Splitting of the time band was performed to check for non-proportional hazards. Individuals were censored at the time of CHD hospitalisation or death. Confounding variables were grouped and included stepwise as (i) childhood social circumstances, (ii) measures from late adolescence, (iii) adult socioeconomic measures and (iv) sickness absence.
Lundin A, et al. Occup Environ Med 2014;71:183–188. doi:10.1136/oemed-2013-101721
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Workplace Table 1
Data collection 1960–2008
Data
Calendar year
Age
Information
Parents’ census Conscription Longitudinal Register of Education and Labour Market Statistics Longitudinal Register of Education and Labour Market Statistics Longitudinal Register of Education and Labour Market Statistics The National Patient Register and the Cause of Death Register
1960 1969 1990 1996–1997 1998–2000 2001–2008
9–11 18–20 39–41 45–48 47–51 50–59
Socioeconomic position, crowded housing BMI, blood pressure, smoking, cognitive ability Socioeconomic position, education Long-term sickness absence, income from work Unemployment CHD
BMI, body mass index; CHD, coronary heart disease.
RESULTS Among the 39 243 men included in the final analysis, 11% experienced unemployment during 1998 to 2000 (n=4 359). Most of these, 8% experienced long-term unemployment, that is, 90 days or more (n=3119). Despite having labour market connection as an inclusion criteria, the bulk of unemployment is in the first year of exposure (n=2969), and incident cases in the following 2 years are fewer (n=803 in 1999 and n=587 in 2000).
Prevalence of confounding risk factors among the employed and unemployed Table 2 shows the prevalence of potential confounding factors among those employed, short-term unemployed and long-term unemployed 1998–2000. With the exception of BMI and systolic and diastolic blood pressures, the unemployed have more risk factors than the employed. Table 3 shows the associations between the same factors and CHD 1992–2008. All of the factors are associated with CHD.
Unemployment and CHD
Table 2 Prevalence of risk factors in categories of unemployment 1998–2000 (%) Risk factor group Childhood
Adolescence
Adulthood
Adult absence
Risk factor name SEP—Unskilled worker SEP—Skilled worker SEP—Assistant non-manual employee SEP—Non-manual employee intermediate SEP—Non-manual employee, high SEP—farmers SEP—not classified Crowded housing BMI (mean kg/m2) Diastolic blood pressure (mean mm Hg) Systolic blood pressure (mean mm Hg) Cognitive ability (mean stanine) Smoker >20 cig/day Smoker 11–20 cig/day Smoker 6–10 cig/day Smoker 1–5 cig/day Smoker 0 cig/day SEP—unskilled worker SEP—skilled worker SEP—assistant non-manual employee SEP—non-manual, intermediate SEP—non-manual employee, high SEP—farmers SEP—not classified Education (mean years) Sickness absence, long term
Employed
Short
Long
31.9 21.2 10.7
40.6 22.7 8.9
37.5 23.6 7.6
17.3
12.8
14.9
5.5
3.5
3.3
11.7 1.8 18.8 20.9 72.8
8.4 3.2 23.3 21.0 72.1
9.9 3.1 26.3 21.0 73.2
126.0
126.0
126.4
5.6
4.9
4.8
2.7 21.0 20.3 11.3 44.7 22.0 18.0 12.2
4.1 23.9 22.7 13.5 35.9 24.6 28.8 11.5
4.5 27.3 22.4 12.0 33.9 26.3 29.1 9.3
27.0
16.5
14.9
11.7
5.0
4.3
2.5 6.7 11.7 11.71
1.4 11.2 11.1 17.7
1.2 15.0 10.8 18.8
There were a total of 1277 cases of CHD, of which 34 occurred among the short-term unemployed and 142 among the longterm unemployed. Table 4 shows the associations between short term and long term unemployment 1998–2000 and CHD 2001–2008 as HRs. In the crude analysis, those unemployed for 20 cig/day** SEP—unskilled worker†† Education, 9 years‡‡ Sickness absence§§, high
1.41 1.19 2.29 1.01 1.01 0.92 2.50 1.31 1.50 1.76
Adolescence
Adult SEP Adult absence
(1.21 to 1.65) (1.04 to 1.36) (1.46 to 3.61) (1.01 to 1.01) (1.00 to 1.02) (0.90 to 0.95) (1.93 to 3.22) 1.14 to 1.52 (1.29 to 1.75) (1.45 to 2.15)
n=39 243. Crude HRs with 95% CI. *Father’s socioeconomic position is unskilled worker. Reference category is intermediate and high employees. †Reference category is living in a non-crowded household. ‡Reference category is BMI 20–25. §Per mm Hg. ¶Per stanine decrease. **Reference is non-smokers. ††Reference category is intermediate and high employees. ‡‡Reference category is >12 years education. §§Reference category is no long-term sickness absence. BMI, body mass index; CHD, coronary heart disease; SEP, socioeconomic position.
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Workplace Table 4 Associations between unemployment 1–89 and >89 days, and coronary heart disease (CHD), crude and adjusted HRs with 95% CIs) Follow-up period 2001–2008 (n=39 243)
2001–2004 (n=39 243)
2005–2008 (n=38 699)
Unemployment
Unemployed 0–89 days HR (95% CI)
Unemployed ≥90 days HR (95% CI)
Unemployed 0–89 days HR (95% CI)
Unemployed ≥90 days HR (95% CI)
Unemployed 0–89 days HR (95% CI)
Unemployed ≥90 days HR (95% CI)
CHD (crude) Fully adjusted*
0.87 (0.62 to 1.23) 0.77 (0.54 to 1.08)
1.47 (1.23 to 1.75) 1.24 (1.04 to 1.48)
1.11 (0.69 to 1.77) 0.94 (0.59 to 1.51)
1.62 (1.25 to 2.10) 1.31 (1.01 to 1.71)
0.71 (0.43 to 1.16) 0.63 (0.38 to 1.04)
1.35 (1.06 to 1.71) 1.18 (0.93 to 1.51)
*Adjusted for childhood factors: SEP, crowded housing, cognitive ability, smoking, BMI, diastolic blood pressure, socioeconomic position, education and long-term sickness absence. BMI, body mass index; SEP, socioeconomic position.
Table 4 also shows the associations between short-term and long-term unemployment and CHD for two consecutive periods of follow-up. There are 544 cases of CHD in the first follow-up period and 733 in the second. Long-term unemployment is significantly associated with long-term unemployment in the crude analysis in both periods. These increased HRs of CHD in the first period are attenuated when controlling for confounders but remain significantly elevated.
DISCUSSION Key results The main finding of this study was that those who became unemployed with duration of at least 90 days had an elevated HR of CHD during 8 years of follow-up. After controlling for potential confounders, including childhood social circumstances, late adolescent BMI, smoking, diastolic blood pressure, cognitive ability, adult socioeconomic measures and sickness absence, a weak increased risk remained, but additionally controlling for a previous career of unemployment diluted the association to the null. The relative risks were stronger during the first 4 years of follow-up.
Comparison with previous studies Our finding of a significant association between unemployment and CHD is in concert with those found during 6 years of follow-up by Garcy and Vågerö.19 Like them we found a small significant association between unemployment and CHD, but we had the possibility to control for potential health-related confounders. Our study confirms their finding and extends it by showing that additional control for health-related confounders diluted the increased risk towards null. Much stronger associations between job loss and self-reports of MI (HR of 2.48) were reported by Gallo et al.18 These differences are most likely due to methodological differences; while we follow mortality for a group defined as exposed/unexposed at baseline, Gallo et al treat unemployment as a time-dependent variable within follow-up. In a more recent follow-up of the same data used in that study, Dupre et al21 lagged unemployment 1 year and found a relative risk closer to ours (HR of 1.35). Our results also contrast those in a previous Swedish study by Eliason and Storrie,16 who found no difference in MI between displaced and non-displaced workers during 12 years follow-up. While Eliason and Storrie studied displacement rather than unemployment, and in a period of overall low unemployment, our study focuses on a period of high unemployment, which might explain the contrasting findings.
Interpretation Unemployment is often mentioned in association with other major life events and is as such regarded as a ‘psychological 186
stressor’.42 43 The stress model, which links psychological stress to behavioural changes and activation of the sympathetic nervous system and the hypothalamic–pituitary–adrenal axis, bases much of its evidence on the association with CVD outcomes. The associations between unemployment and symptoms of anxiety and depression,1 known outcomes of psychosocial stress as well as hypothetical risk factors for CVD,44 strengthen the conceptual link between unemployment and the stress model. It has been suggested that unemployment may affect organic disease through chronically increased levels of stress or health-damaging behaviours.45 We interpret our findings of an association between long-term unemployment and subsequent CHD as potentially the somatic result of a process started by stress. In our models, we consider the case that the event of unemployment alters the future risk of CHD and put to the side that duration affects the future risk of CHD, although we separate approximations of short-term events from long term. The expected duration of unemployment, as estimated in the Swedish Labour Force Surveys, ranged between 25 and 20 weeks 1988–2001, but mean days of unemployment ranged between 40 and 30 weeks during the same period.46 That is, while most unemployed leave after a shorter spell, those with low employability stay for very long. Since we lacked date of entry and exit, we could not calculate the number of spells, duration of completed spells or assess if spells were completed or not. In one previous study with more detailed information on unemployment, the number of spells rather than the duration increased the risk of acute myocardial infarction,21 supporting the idea that stress is more acute than chronic.
Strengths and limitations A main strength of the current study is that it is a large population representative of middle-aged men in the working population. Atherosclerosis is a cumulative process, beginning at younger ages, and CHD incidence in men starts to increase first in middle age. Second, in the current study, we had information on several important risk factors for CHD, blood pressure, smoking and BMI, lacking in register-based studies. Third, information on unemployment came from administrative registers, which are both complete and based on objective criteria including being a job seeker. Self-reported labour market status might be subject to bias.47 There are also some limitations to our study. Several of our risk factors for CHD were measured at ages 18–19, which may not reflect circumstances of the time of exposure, age 41–45. Smoking decreased in Sweden during the 1970s and 1980s.48 We know from a small subsample of our cohort that 52% of those smoking at ages 18–19 were persistent smokers, while only 6% had started smoking (n=694).49 As for BMI, cohorts similar to
Lundin A, et al. Occup Environ Med 2014;71:183–188. doi:10.1136/oemed-2013-101721
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Workplace ours50 have shown that the mean BMI measured at age ∼20 increased from about 21 kg/m2 to about 26 kg/m2 at ages ∼40–50. That is, more individuals will be obese in adulthood relative to our measure at age 18. Most of those obese in adolescence will however remain obese in adulthood.51 The strength of systolic and diastolic blood pressure tracking has been shown to decrease with longer follow-up periods,52 but measures in late adolescence have been shown to be correlated with measures at ages 30 and 5053 and at age 39.54 More recent measures of blood pressure may have provided more accurate confounder adjustment. Any adjustment for a confounder measured less than perfect will result in incomplete adjustment and hence residual confounding.55
20 21 22
23 24 25
26
CONCLUSION
27
Unemployment was associated with increased risk of CHD after adjustment for confounders. We interpret the increased risk of CHD associated with unemployment as potentially the somatic result of a process started by stress.
28
29
Correction The section head of this paper has been updated since it was published Online First.
30
Contributors AL was the main investigator. AL, DF and TH were responsible for the design and analysis of the data. All authors contributed to the final writings.
31
Competing interests None. Provenance and peer review Not commissioned; externally peer reviewed.
32
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Chen X, Wang Y. Tracking of blood pressure from childhood to adulthood: a systematic review and meta-regression analysis. Circulation 2008;117:3171–80. Nelson MJ, Ragland DR, Syme SL. Longitudinal prediction of adult-blood pressure from Juvenile blood-pressure levels. Am J Epidemiol 1992;136:633–45. Kivimaki M, Lawlor DA, Smith GD, et al. Early socioeconomic position and blood pressure in childhood and adulthood—the Cardiovascular Risk in Young Finns Study. Hypertension 2006;47:39–44. Greenland S. The effect of misclassification in the presence of covariates. Am J Epidemiol 1980;112:564–9.
Lundin A, et al. Occup Environ Med 2014;71:183–188. doi:10.1136/oemed-2013-101721
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Unemployment and coronary heart disease among middle-aged men in Sweden: 39 243 men followed for 8 years Andreas Lundin, Daniel Falkstedt, Ingvar Lundberg and Tomas Hemmingsson Occup Environ Med 2014 71: 183-188 originally published online January 8, 2014
doi: 10.1136/oemed-2013-101721 Updated information and services can be found at: http://oem.bmj.com/content/71/3/183
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Workplace
ORIGINAL ARTICLE
Unemployment and coronary heart disease among middle-aged men in Sweden: 39 243 men followed for 8 years Andreas Lundin,1 Daniel Falkstedt,2 Ingvar Lundberg,1 Tomas Hemmingsson1,3 1
Division of Occupational Medicine, Karolinska institutet, Institute of Environmental Medicine, Stockholm, Sweden 2 Department of Public Health Sciences, Karolinska institutet, Stockholm, Sweden 3 Centre for Social Research on Alcohol and Drugs, Stockholm University, Stockholm, Sweden Corresponding to Dr Andreas Lundin, Division of Occupational Medicine, Karolinska institutet, Institute of Environmental Medicine, SE-17176 Stockholm, Sweden; [email protected] Received 9 July 2013 Revised 11 November 2013 Accepted 17 December 2013 Published Online First 8 January 2014
ABSTRACT Background Although unemployment may be a stressful life event, its association with coronary heart disease (CHD) remains unclear. This study examines the association between unemployment and later hospitalisation due to CHD. Methods The study was based on a Swedish military conscription cohort of 18 to 20-year-old men from 1969/1970 (n=49 321) with information provided on health status and health behaviours. Information on unemployment in middle age was obtained from national registers. CHD information was obtained from hospital registers and the cause of death register. Cox proportional hazard analyses were run on the 39 243 individuals who were in paid employment in 1996 and 1997. Results It was found that ≥90 days of unemployment was associated with subsequent CHD during 8 years follow-up (crude HR=1.47, 95% CI 1.23 to 1.75). Controlling for known risk factors for CHD reduced the association but a significant association remained (HR=1.24, 95% CI 1.04 to 1.48); ≥90 days of unemployment was significantly associated with CHD during the first 4 years (HR adjusted for known risk factors=1.31, 95% CI 1.01 to 1.71). Conclusions Unemployment was associated with increased risk of CHD after adjustment for confounders. We interpret the increased risk of CHD associated with unemployment as potentially the somatic result of a process started by stress.
INTRODUCTION
To cite: Lundin A, Falkstedt D, Lundberg I, et al. Occup Environ Med 2014;71:183–188.
Unemployment is a stressful life event1 shown to be associated with mental health outcomes such as suicide, depression, anxiety and alcohol use disorders.2–4 It has been mentioned as potentially contributing to the socioeconomic gradient in mortality and morbidity,5 6 hypothetically also through coronary heart disease (CHD).7 8 The link to somatic disease is suggested to go through both material hardship and psychosocial stress, mediated by pathophysiological responses, as well as negative change in health behaviours.9 The status of unemployment as an independent cardiovascular risk factor is not settled,10 and while unemployment has been linked to changes in cardiovascular risk factors for example, body mass index (BMI)11 and smoking,12–15 current studies on associations between unemployment and CHD, stroke, myocardial infarction (MI) and cardiovascular disease (CVD) show no clear pattern.16–20
Lundin A, et al. Occup Environ Med 2014;71:183–188. doi:10.1136/oemed-2013-101721
What this study adds ▸ Despite being a stressful life event, unemployment has an unclear association with coronary heart disease (CHD) ▸ Previous studies have had limited possibility to control for risk factors for CHD existing before unemployment. ▸ This study on middle-aged men shows that unemployment is associated with CHD even after controlling for known important risk factors for CHD.
In one Swedish job closure study of 17 008 displaced and 188 000 non-displaced workers followed for 12 years, there was no increased risk of either MI or stroke hospitalisation associated with displacement.16 However, in a similar Danish study of 33 065 displaced workers and 1 161 222 controls, displacement was associated with increased risk for MI/stroke mortality.20 In one recent Swedish study, based on register linkage of 3.4 million individuals, unemployment was found to be significantly associated with mortality from circulatory diseases, ischaemic heart disease and stroke during 6 years of follow-up. Only health measured as previous hospitalisation could be controlled for as potential confounding, which had little reducing effect.19 Three studies, 6-, 10- and 18 year follow-ups of the US Health and Retirement Study, have also examined MI and stroke following job loss (layoff or plant closure) in workers 50 years or older. In these studies, job loss was found to be associated with stroke17 18 and MI.18 21 Unlike the large register-based studies mentioned above, these studies had information on known risk factors for CHD, smoking, hypertension, obesity and diabetes, and although those in the first two studies had little reducing effect on the risk estimates, they substantially reduced association between unemployment and MI in the 18-year follow-up. We have previously examined unemployment and CVD mortality in the same cohort as the present study is based upon. Although a crude association between unemployment of less than 90 days and subsequent CVD mortality during 8 years was found, the increased risk was diluted towards null and nonsignificant when controlling for confounding variables related to health and socioeconomic position (SEP).22 183
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Workplace Both layoffs and re-employment after layoff are selection processes in which workers’ individual characteristics are scrutinised by employers. While age, education, cognitive ability and SEP are well-known determinants of unemployment,23 less is known about health and health behaviour as risk factors for unemployment.24 Sickness absence has been shown to be a strong risk factor for unemployment in Sweden and elsewhere.25–28 Also, a few studies have shown that major risk factors for CHD, such as smoking, BMI and high blood pressure,29–32 are more prevalent among those who later become unemployed,13 33–36 and in a previous Swedish study on 800 unemployed individuals those with circulatory problems had lower probability of becoming employed the following year.37 Furthermore, life-course studies have shown that indicators of poor circumstances in childhood, for example, SEP and crowded housing, are associated with adult unemployment.13 33 We have previously shown the importance of risk factors measured before adulthood in relation to CHD mortality later in life.38–40 The aim of the present study was to examine if becoming unemployed is associated with subsequently increased risk of CHD, adjusted for CHD risk factors measured across the life course prior to unemployment. The following research questions were posed: (i) Is exposure to unemployment associated with an excess risk of CHD? (ii) If so, to what extent is the association between unemployment and CHD confounded by risk factors preceding unemployment?
METHODS Study design The study population consisted of the Swedish Conscription cohort of 1969/1970, originally including 50 465 men. By law at this time, all men were required to undergo 2 days of examination at one of six conscript centres across Sweden, usually during the year of their 18th birthday. A small number of conscripts are older than 18, but this study encompass only those born in 1949 (5%), 1950 (18%) and 1951 (77%); 49 321 individuals. Due to severe handicap or congenital disorder, a small group did not attend conscript examination, estimated to be 2– 3%. Through unique identification numbers, we linked register information on employment, income, education, hospitalisation and mortality to the baseline examination. Included in this study are all those who were in paid employment 1996/1997 (having a work-related income above SEK 36 600/US$8300) and who had no disability pension 1999–2001 (n=40 823). This exclusion criterion was made to ascertain that individuals were in the labour force, that is, had worked and were under risk of unemployment. Of these, 40 071 had never had any CHD at the start of follow-up and 39 243 had information on all variables. All analyses are based on these individuals.
Unemployment Information on yearly accumulated days registered as unemployed was obtained from the Longitudinal Integration Database for Health Insurance and Labour Market Studies (LISA), based on administrative records reported by the Public Employment Service. This is a national government agency, which is the largest placement service in Sweden and also the controlling function for any benefits from the unemployment insurance funds and Cash Labour Market Assistance. Conditions to be fulfilled are stipulated in the Unemployment Insurance Act section 9, which agrees with the International Labour Organization definition of unemployment as (1) lacking work, (2) being available for employment and (3) looking for work. The studied exposure, unemployment, was formed from 184
persons with short-term unemployment (1–89 days of accumulated registered unemployment) and long-term unemployment (90 or more days of accumulated registered unemployment) 1998–2000. This division was based on the theoretical assumption of duration dependence; that the probability of leaving unemployment for work declines with the duration of unemployment. That is, short-term unemployment is more likely to be completed spells with exit to employment, while long-term unemployment is more likely to be ongoing spells and/or exits to labour market programmes.
Coronary heart disease Information on CHD between 2001 and 2008 was obtained from record linkage with the National Patient Register and the Cause of Death Register, administered by the National Board of Health and Welfare. Codes of CHD according to the 10th revision of International Classification of Disease (ICD-10) were I20–I25.
Confounders Parent SEP was based on the SEP of the individuals’ parents (with priority of father’s SEP) or other head of household where applicable. Categories were (i) unskilled worker, (ii) skilled worker, (iii) assistant non-manual employee, (iv) nonmanual employee at intermediate level, (v) non-manual employee at higher level, (vi) farmer and (vii) not classifiable in SEP. Crowded housing was categorised as >2 persons/room— kitchen not included. The Information on childhood social circumstances was collected from the National Population and Housing Census of 1960 of the individuals’ parents—matched through the Multigenerational Register at Statistics Sweden. From the conscription examination, we got information on BMI, systolic and diastolic blood pressure, cognitive test results, as well as questionnaire answers concerning smoking. BMI was calculated as body weight (kg) divided by height (m) squared. Systolic and diastolic blood pressures were measured in mm Hg after 5–10 min test. Smoking was self-reported as 1= >20 cigarettes/day, 2=11–20 cigarettes/day, 3=5–10 cigarettes/day, 4=1– 5 cigarettes/day and 5=non-smokers. General cognitive ability was based on the combined results from four cognitive tests, SEB67, normalised into a standard-nine scale.41 Information on SEP, sickness absence and level of education in adulthood was obtained from LISA. SEP was categorised in the same way as for parents (described above). Education in 1990 was classified as completion of 9 years or less, 11, 12 or more than 12 years of education. Sickness absence 1996–1997 was information on registered benefits from spells from national health insurance lasting longer than 14 days, dichotomised as present or not. An illustration of the collected data is provided in table 1.
Statistical analysis The association between exposure to unemployment in 1998– 2000 and CHD 2001–2008 (and subperiods 2001–2004 and 2005–2008) was investigated by means of crude and multivariate Cox proportional-hazard models using the PHREG procedure in the SAS statistical package (V.9.1; SAS Institute Inc, Cary, North Carolina). Splitting of the time band was performed to check for non-proportional hazards. Individuals were censored at the time of CHD hospitalisation or death. Confounding variables were grouped and included stepwise as (i) childhood social circumstances, (ii) measures from late adolescence, (iii) adult socioeconomic measures and (iv) sickness absence.
Lundin A, et al. Occup Environ Med 2014;71:183–188. doi:10.1136/oemed-2013-101721
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Workplace Table 1
Data collection 1960–2008
Data
Calendar year
Age
Information
Parents’ census Conscription Longitudinal Register of Education and Labour Market Statistics Longitudinal Register of Education and Labour Market Statistics Longitudinal Register of Education and Labour Market Statistics The National Patient Register and the Cause of Death Register
1960 1969 1990 1996–1997 1998–2000 2001–2008
9–11 18–20 39–41 45–48 47–51 50–59
Socioeconomic position, crowded housing BMI, blood pressure, smoking, cognitive ability Socioeconomic position, education Long-term sickness absence, income from work Unemployment CHD
BMI, body mass index; CHD, coronary heart disease.
RESULTS Among the 39 243 men included in the final analysis, 11% experienced unemployment during 1998 to 2000 (n=4 359). Most of these, 8% experienced long-term unemployment, that is, 90 days or more (n=3119). Despite having labour market connection as an inclusion criteria, the bulk of unemployment is in the first year of exposure (n=2969), and incident cases in the following 2 years are fewer (n=803 in 1999 and n=587 in 2000).
Prevalence of confounding risk factors among the employed and unemployed Table 2 shows the prevalence of potential confounding factors among those employed, short-term unemployed and long-term unemployed 1998–2000. With the exception of BMI and systolic and diastolic blood pressures, the unemployed have more risk factors than the employed. Table 3 shows the associations between the same factors and CHD 1992–2008. All of the factors are associated with CHD.
Unemployment and CHD
Table 2 Prevalence of risk factors in categories of unemployment 1998–2000 (%) Risk factor group Childhood
Adolescence
Adulthood
Adult absence
Risk factor name SEP—Unskilled worker SEP—Skilled worker SEP—Assistant non-manual employee SEP—Non-manual employee intermediate SEP—Non-manual employee, high SEP—farmers SEP—not classified Crowded housing BMI (mean kg/m2) Diastolic blood pressure (mean mm Hg) Systolic blood pressure (mean mm Hg) Cognitive ability (mean stanine) Smoker >20 cig/day Smoker 11–20 cig/day Smoker 6–10 cig/day Smoker 1–5 cig/day Smoker 0 cig/day SEP—unskilled worker SEP—skilled worker SEP—assistant non-manual employee SEP—non-manual, intermediate SEP—non-manual employee, high SEP—farmers SEP—not classified Education (mean years) Sickness absence, long term
Employed
Short
Long
31.9 21.2 10.7
40.6 22.7 8.9
37.5 23.6 7.6
17.3
12.8
14.9
5.5
3.5
3.3
11.7 1.8 18.8 20.9 72.8
8.4 3.2 23.3 21.0 72.1
9.9 3.1 26.3 21.0 73.2
126.0
126.0
126.4
5.6
4.9
4.8
2.7 21.0 20.3 11.3 44.7 22.0 18.0 12.2
4.1 23.9 22.7 13.5 35.9 24.6 28.8 11.5
4.5 27.3 22.4 12.0 33.9 26.3 29.1 9.3
27.0
16.5
14.9
11.7
5.0
4.3
2.5 6.7 11.7 11.71
1.4 11.2 11.1 17.7
1.2 15.0 10.8 18.8
There were a total of 1277 cases of CHD, of which 34 occurred among the short-term unemployed and 142 among the longterm unemployed. Table 4 shows the associations between short term and long term unemployment 1998–2000 and CHD 2001–2008 as HRs. In the crude analysis, those unemployed for 20 cig/day** SEP—unskilled worker†† Education, 9 years‡‡ Sickness absence§§, high
1.41 1.19 2.29 1.01 1.01 0.92 2.50 1.31 1.50 1.76
Adolescence
Adult SEP Adult absence
(1.21 to 1.65) (1.04 to 1.36) (1.46 to 3.61) (1.01 to 1.01) (1.00 to 1.02) (0.90 to 0.95) (1.93 to 3.22) 1.14 to 1.52 (1.29 to 1.75) (1.45 to 2.15)
n=39 243. Crude HRs with 95% CI. *Father’s socioeconomic position is unskilled worker. Reference category is intermediate and high employees. †Reference category is living in a non-crowded household. ‡Reference category is BMI 20–25. §Per mm Hg. ¶Per stanine decrease. **Reference is non-smokers. ††Reference category is intermediate and high employees. ‡‡Reference category is >12 years education. §§Reference category is no long-term sickness absence. BMI, body mass index; CHD, coronary heart disease; SEP, socioeconomic position.
185
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Workplace Table 4 Associations between unemployment 1–89 and >89 days, and coronary heart disease (CHD), crude and adjusted HRs with 95% CIs) Follow-up period 2001–2008 (n=39 243)
2001–2004 (n=39 243)
2005–2008 (n=38 699)
Unemployment
Unemployed 0–89 days HR (95% CI)
Unemployed ≥90 days HR (95% CI)
Unemployed 0–89 days HR (95% CI)
Unemployed ≥90 days HR (95% CI)
Unemployed 0–89 days HR (95% CI)
Unemployed ≥90 days HR (95% CI)
CHD (crude) Fully adjusted*
0.87 (0.62 to 1.23) 0.77 (0.54 to 1.08)
1.47 (1.23 to 1.75) 1.24 (1.04 to 1.48)
1.11 (0.69 to 1.77) 0.94 (0.59 to 1.51)
1.62 (1.25 to 2.10) 1.31 (1.01 to 1.71)
0.71 (0.43 to 1.16) 0.63 (0.38 to 1.04)
1.35 (1.06 to 1.71) 1.18 (0.93 to 1.51)
*Adjusted for childhood factors: SEP, crowded housing, cognitive ability, smoking, BMI, diastolic blood pressure, socioeconomic position, education and long-term sickness absence. BMI, body mass index; SEP, socioeconomic position.
Table 4 also shows the associations between short-term and long-term unemployment and CHD for two consecutive periods of follow-up. There are 544 cases of CHD in the first follow-up period and 733 in the second. Long-term unemployment is significantly associated with long-term unemployment in the crude analysis in both periods. These increased HRs of CHD in the first period are attenuated when controlling for confounders but remain significantly elevated.
DISCUSSION Key results The main finding of this study was that those who became unemployed with duration of at least 90 days had an elevated HR of CHD during 8 years of follow-up. After controlling for potential confounders, including childhood social circumstances, late adolescent BMI, smoking, diastolic blood pressure, cognitive ability, adult socioeconomic measures and sickness absence, a weak increased risk remained, but additionally controlling for a previous career of unemployment diluted the association to the null. The relative risks were stronger during the first 4 years of follow-up.
Comparison with previous studies Our finding of a significant association between unemployment and CHD is in concert with those found during 6 years of follow-up by Garcy and Vågerö.19 Like them we found a small significant association between unemployment and CHD, but we had the possibility to control for potential health-related confounders. Our study confirms their finding and extends it by showing that additional control for health-related confounders diluted the increased risk towards null. Much stronger associations between job loss and self-reports of MI (HR of 2.48) were reported by Gallo et al.18 These differences are most likely due to methodological differences; while we follow mortality for a group defined as exposed/unexposed at baseline, Gallo et al treat unemployment as a time-dependent variable within follow-up. In a more recent follow-up of the same data used in that study, Dupre et al21 lagged unemployment 1 year and found a relative risk closer to ours (HR of 1.35). Our results also contrast those in a previous Swedish study by Eliason and Storrie,16 who found no difference in MI between displaced and non-displaced workers during 12 years follow-up. While Eliason and Storrie studied displacement rather than unemployment, and in a period of overall low unemployment, our study focuses on a period of high unemployment, which might explain the contrasting findings.
Interpretation Unemployment is often mentioned in association with other major life events and is as such regarded as a ‘psychological 186
stressor’.42 43 The stress model, which links psychological stress to behavioural changes and activation of the sympathetic nervous system and the hypothalamic–pituitary–adrenal axis, bases much of its evidence on the association with CVD outcomes. The associations between unemployment and symptoms of anxiety and depression,1 known outcomes of psychosocial stress as well as hypothetical risk factors for CVD,44 strengthen the conceptual link between unemployment and the stress model. It has been suggested that unemployment may affect organic disease through chronically increased levels of stress or health-damaging behaviours.45 We interpret our findings of an association between long-term unemployment and subsequent CHD as potentially the somatic result of a process started by stress. In our models, we consider the case that the event of unemployment alters the future risk of CHD and put to the side that duration affects the future risk of CHD, although we separate approximations of short-term events from long term. The expected duration of unemployment, as estimated in the Swedish Labour Force Surveys, ranged between 25 and 20 weeks 1988–2001, but mean days of unemployment ranged between 40 and 30 weeks during the same period.46 That is, while most unemployed leave after a shorter spell, those with low employability stay for very long. Since we lacked date of entry and exit, we could not calculate the number of spells, duration of completed spells or assess if spells were completed or not. In one previous study with more detailed information on unemployment, the number of spells rather than the duration increased the risk of acute myocardial infarction,21 supporting the idea that stress is more acute than chronic.
Strengths and limitations A main strength of the current study is that it is a large population representative of middle-aged men in the working population. Atherosclerosis is a cumulative process, beginning at younger ages, and CHD incidence in men starts to increase first in middle age. Second, in the current study, we had information on several important risk factors for CHD, blood pressure, smoking and BMI, lacking in register-based studies. Third, information on unemployment came from administrative registers, which are both complete and based on objective criteria including being a job seeker. Self-reported labour market status might be subject to bias.47 There are also some limitations to our study. Several of our risk factors for CHD were measured at ages 18–19, which may not reflect circumstances of the time of exposure, age 41–45. Smoking decreased in Sweden during the 1970s and 1980s.48 We know from a small subsample of our cohort that 52% of those smoking at ages 18–19 were persistent smokers, while only 6% had started smoking (n=694).49 As for BMI, cohorts similar to
Lundin A, et al. Occup Environ Med 2014;71:183–188. doi:10.1136/oemed-2013-101721
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Workplace ours50 have shown that the mean BMI measured at age ∼20 increased from about 21 kg/m2 to about 26 kg/m2 at ages ∼40–50. That is, more individuals will be obese in adulthood relative to our measure at age 18. Most of those obese in adolescence will however remain obese in adulthood.51 The strength of systolic and diastolic blood pressure tracking has been shown to decrease with longer follow-up periods,52 but measures in late adolescence have been shown to be correlated with measures at ages 30 and 5053 and at age 39.54 More recent measures of blood pressure may have provided more accurate confounder adjustment. Any adjustment for a confounder measured less than perfect will result in incomplete adjustment and hence residual confounding.55
20 21 22
23 24 25
26
CONCLUSION
27
Unemployment was associated with increased risk of CHD after adjustment for confounders. We interpret the increased risk of CHD associated with unemployment as potentially the somatic result of a process started by stress.
28
29
Correction The section head of this paper has been updated since it was published Online First.
30
Contributors AL was the main investigator. AL, DF and TH were responsible for the design and analysis of the data. All authors contributed to the final writings.
31
Competing interests None. Provenance and peer review Not commissioned; externally peer reviewed.
32
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Lundin A, et al. Occup Environ Med 2014;71:183–188. doi:10.1136/oemed-2013-101721
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Unemployment and coronary heart disease among middle-aged men in Sweden: 39 243 men followed for 8 years Andreas Lundin, Daniel Falkstedt, Ingvar Lundberg and Tomas Hemmingsson Occup Environ Med 2014 71: 183-188 originally published online January 8, 2014
doi: 10.1136/oemed-2013-101721 Updated information and services can be found at: http://oem.bmj.com/content/71/3/183
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