Relation between sickness absence and socio-demographic characteristics，well-being，and health care utilisation—a primary care based study
-
首席医学网
2009年06月02日 11:25:48 Tuesday
-
作者：Ahmad Al-Windi1，2，Holger Theobald1，Sven-Erik Johansson1 作者单位：Centre for Family and Community Medicine，Stockholm，Karolinska Institute，Huddinge，Sweden
PDF下载
加入收藏夹
【摘要】 Objective This study aims to explore the pattern of sickness absence（SA）at a multiethnic health care practice.Methods Data from a questionnaire and medical records were collected during 4 months 2002 at Jordbro Health Centre，Stockholm，Sweden.Logistic regression analysis was performed adjusting for sociodemographic characteristics.Of 1,089 patients，861（79%）completed the questionnaire and 50% were on SA during the past year.Results Men had less SA，OR 0.44（95% CI 0.26~0.76），than women.Poor working situation was associated with SA，OR 2.99（95% CI 1.54~5.81）.Perceived poor health was associated with long-term SA>28 days，OR 3.16（95% CI 1.75~5.73）which dropped to 1.77（95% CI 0.89~3.49）when adjusted for sociodemographic characteristics.Conclusion Gender and poor work situation predict SA and need particular attention.Effort should be focused on improving the working situation in general and for these patients in particular.
【关键词】 sickness absence；health care practice；work situation；economic situation；physical fitness；perceived health；questionnaire
Correspondence to Ahmad Al-Windi，MD，PhD，Associate professor，Family Medicine,Stockholm，Karolinska Institute，Alfred Nobels allé 12，SE-141 83 Huddinge，Sweden
E-mail: ahmad.alwindi@gmail.com
INTRODUCTION
In Sweden long-term sickness absence is more widespread than in any other EC country［1］.About 40% of individuals with long-term sickness absence have psychiatric diagnosis［1］.Atroshi and associates reported that long-term sickness absence was common among primary care patients with musculoskeletal pain［2］，while Feeney,et al. reported that respiratory disorders and gastroenteritis accounted for over half of all spells of absence，with headaches and migraine，musculoskeletal disorders，injury and neurosis accounting for a further 20%~30% of absences［3］.Shiels,et al. reported that mild mental disorder accounted for nearly 40% of certified sickness and risk factors for longer-term incapacity included increasing age，social deprivation，mild and severe mental disorder，neoplasm and congenital illness［4］.
The costs and the length of sickness absence have increased dramatically during the last decade and there is an urgent need to find methods to stop this negative development［5-7］.Many epidemiological studies have shown that sickness absence is determined by health conditions，the labour market，work conditions，socio-economic conditions and individual characteristics［8］.However，there are no easy methods for detecting risk patients at an early stage in primary health care.North and associates identified several risk factors related to sickness absence，including health related behaviours，work characteristics，low levels of job satisfaction and adverse social circumstances outside work［9］.Psychosocial factors at work，especially decision latitude，have also been reported to predict sickness absence［10］.However，Hornquist,et al. found that the poorer the situation of well-being，the greater the subsequent sickness absence［11］.Marmot and associates found that there was a strong association between ill health andsickness absence，particularly for longer spells，and proposed that sickness absence be used as an integrated measure of physical，psychological and social functioning in studies of working populations［12］.It has been reported that patients appear to have a strong influence on sick-listing practice［13］.Sickness certification is one of the most common tasks performed in general practice and further studies regarding the characteristics of patients on sickness absence are needed.It therefore seems reasonable to study the simultaneous impact of all these variables on sickness absence［14］.
The present study is part of a comprehensive programme entitled “Improving Health Care in Jordbro”designed to assess the influence of socio-demographic characteristics，including country of birth and morbidity，on health care and drug utilisation among patients residing in Jordbro，a small multi-ethnic sub-community in Stockholm，Sweden.This present study has explored the impact that work and economic situation as well as health status measured as physical fitness and perceived health have on sickness absence.
The main aim of the study was to explore the pattern of sickness absence in a Swedish multiethnic care health practice，using a patient questionnaire and medical records.Another aim was to study the relation between sickness absence，work and economic situation，physical fitness，perceived health，health care and drug utilisation after taking socio-demographic characteristics into consideration.
The Committee on Research Ethics at Karolinska Institutet approved the study.
METHODS
Study Population
Data were collected during four months between 14 January and 10 May，2002，concerning adult patients（between 16 and 64 years）who attended Jordbro health centre in Haninge municipality，Stockholm，Sweden.This health care centre with 5 full-time positions for family physicians has a catchment area of 9，500 patients.
Every patient who attended the Jordbro health centre during the study period received upon admission a questionnaire and letter explaining the purpose of the study.Patients were informed that they were free to take part or refuse to participate in the study and that they could answer the questionnaire at the xxx if they wished.Translation services would be made available if needed.
A total of 1，089 questionnaires were distributed.Patients who had not responded within two weeks of the end of the study period were sent a reminder.The total response rate was 79% and altogether 861 answers were received.The mean age of the respondents was 41.3 years and of the non-respondents 42.1 years.The median age for both groups was 41.3（95% CI 40.1~42.1）and 42.1（95% CI 40.6~43.5）years，and the range was 16~64 years and 17~64 years，respectively.The gender distribution was also similar，with 36.4% of the respondents and 40.1% of the non-respondents being men.
Postal Questionnaire
The questionnaire contained questions on socio-demographic characteristics in addition to age and gender，current marital status，educational level，occupation and country of birth.The respondents well-being was measured in terms of their work and economic situation，while physical fitness and perceived health was assessed using part of the “Gothenburg quality-of-life instrument”［15］.
Patients were also asked to indicate whether they had consulted a physician，i.e.a specialist or general practitioner（GP），during the past year（2001）;if they had consulted a physician，they were asked to give the number of consultations.The medicines concerned included the use of prescribed medicines，if any，and the number of medicines used during the past year.The participants were also asked to indicate if they had been on sickness absence during the past year，and if so，for how many days.
Medical Records
The patients medical records were studied and information was collected about the respondents with respect to consultations with the GP and prescriptions.If a respondent had been given a prescription during that year，data about the prescription were collected.Both the number of prescriptions and medicines were recorded.The findings were matched with information from the questionnaire survey.
Outcome Variables
Based on the number of sickness absence days three outcome variables were defined:Sickness absence 0，Sickness absence 1~28（short-term），and Sickness absence>28 days（long-term）.
Explanatory Variables
Socio-demographic variables
Age was categorised into the following groups:16~24，25~44 and 45~64.
Gender:man or woman.
Marital status comprised two groups:married/cohabiting or single.
Education was divided into 2 groups，“High level”=more than 11 years of education，or“Low level”=less than 12 years.
Employment status comprised 3 groups:employed，on sick-leave & disability pension，or other（old-age pension，students and others）.
Country of birth was grouped into the following groups:Sweden，other Nordic countries，other European countries or other parts of the world.
Well-being variables
Work and economic situation，physical fitness and perceived health were defined on a seven-point scale，ranging from score 1 “very bad”，to score 7 “excellent，could not be better”.The variables were dichotomised to“Good scores” score 3~7 and “Bad or poor scores” score 1~2.
Utilisation variable
Means were calculated for consultations with the GP or any physician，all contacts with the Jordbro health centre，number of prescriptions，number of medicines prescribed and medicines used.
Statistical Methods
The data were analysed using the SAS and JMP software package［16，17］.Standard methods were used to obtain summary statistics，such as means and measures of dispersion.An analysis was made of the relationships between sickness absence days and work and economic situation，physical fitness and perceived health，using the unconditional logistic regression in successive models，adjusted for socio-demographic variables.In the final analysis（model 5），all well-being variables were adjusted for.The results are shown as odds ratios（OR）with 95% confidence intervals（CI:s）.We also used a regression procedure，available in the JMP program package，based on the standard least square method to calculate the crude and the adjusted means for health care utilisation and medicine use in the stepwise model.The means with 95% confidence intervals（CI）were calculated，adjusted for socio-demographic characteristics.The fit of the models were judged by the Hosmer-Lemeshow goodness-of-fit test.The models were considered as acceptable if P>0.05 and all models met this demand.
RESULTS
Socio-demographic Characteristics and Sickness Absence
Approximately 50% of all socio-demographic groups were on sickness absence during the past year.About 20%~39% were on short-term sickness absence，i.e.less than 29 days.This was most obvious among persons aged 25~44 years，married/cohabited，employed，and persons born in Sweden or other Nordic countries.A higher percentage of women and persons born outside the Nordic countries were on long-term sickness absence compared with men and persons born in Nordic countries（Table 1）.
It is obvious from Table 1 that the pattern of sickness absence among the occupation category differs from other studied variables.For example，17.3% and 37.2% of the respondents on sickness absence and disability pension have short-term and long-term sickness absence，respectively.This is because some respondents have both partial disability pension and sickness absence concurrently.
Work and Economic Situation，Physical Fitness and Perceived Health，and Sickness Absence
Table 2 shows the OR and 95% CI for being on short-term sickness absence（1~28 vs.0 day）by poor well-being variables and socio-demographic characteristics in logistic regression analyses.
Respondents with short-term sickness absence had about the same odds ratios of having a poor work and economic situation，physical fitness and perceived health in the crude and adjusted models as the reference group.In models 3，4 and 6，when adjusted for the effect of the confounders，the only variable related to lower short-term sickness absence was being born in other Nordic countries.For example，these respondents had a 60%~70% lower risk of being on short-term sickness absence compared with persons born outside Europe.None of the studied well-being variables was related to short-term sickness absence.
Table 3 shows the OR and 95% CI for being on long-term sickness absence（>28 vs.0 day）by poor well-being variables and socio-demographic characteristics in logistic regression analyses.Respondents on long-term sickness absence had significantly higher crude and adjusted ORs for poor work situation，poor physical fitness and poor perceived health than did respondents with no sickness absence except for poor economic situation（Models 1 to 4）.However，the OR was 1.74 and the 95% CI was 0.99~3.05.In addition，in models 2 and 3 some variables were related to long-term sickness absence，such as female gender and being single.
Table 1 Sociodemographic background and sickness absence
Note:*Some respondents have half-part disability pension and sickness absence simultaneously
Table 2 Odds ratios（OR）and 95% Confidence Intervals（CI）for being on short-term sick-leave（1~28 days vs.0 day）by poor well-being variables and socio-demographic characteristics in logistic regression analyses Note:*Other refers outside Europe
Table 3 Odds ratios（OR）and 95% Confidence Intervals（CI）for being on long-term sick-leave（>28 days vs.0 day）by poor well-being variables and socio-demographic characteristics in logistic regression analyses
Note:*Other refers to outside Europe
It is interesting to note that when the well-being variables were included in the analysis（Model 5），the only variables that remained significant were gender and poor work situation，with OR 0.44（0.26~0.76）for the men compared with the women.The OR and 95% CI for poor work situation was 2.99（1.54~5.81）.The OR for poor perceived health was 3.16（1.75~5.73）in model 4（Table 3），dropping to 1.77（0.89~3.49）when other well-being variables were included in the analysis（Model 5）.
Health Service Utilisation and Sickness Absence
Respondents on short-term sickness absence had slightly higher consultation and prescription rates than did respondents who were not on sickness absence.However，long-term sickness absence was related to higher consultations with a physician and with the GPs.These respondents also had higher prescription rates and used a greater number of medicines.This was also true in the adjusted and non-adjusted models（Table 4）.
Table 4 Regression analysis of health care and drug utilisation by sickness absence in various models
Note:Model 1 adjusted for age，gender,Model 2（+ marital status，education）,Model 3（+ occupational status and country of birth）.1refers to the questionnaire survey,2 refers to the medical record study.Jorbro Health Care=JHC.
Diagnoses and Sickness Absence
The most frequent diagnoses related to short-term sickness absence were musculoskeletal and circulatory disorders and symptoms，signs and abnormal clinical and laboratory findings，not elsewhere classified（Table 5）.For long-term sickness absence，the common diagnoses were musculoskeletal，mental and behavioural disorders，and symptoms，signs and abnormal clinical and laboratory findings，not elsewhere classified.
Table 5 Diagnosis by short and long-term sickness absence
Note:Some patients had more than one diagnosis.
DISCUSSION
The main finding of this primary care study is that gender and poor work situation were the only variables that remained significantly and independently related to long-term sickness absence when adjusted for the influence of all confounders.However，other well-being variables such as economic situation，physical fitness and poor perceived health，and some socio-demographic characteristics were also found to be related to sickness absence.This study also shows that long-term sickness absence is related to higher rates of physician consultations，prescriptions and medicine use.
Self-rated health，ill health and sickness absence have been reported to be associated with one another，particularly for long spells，a finding that is in line with the present study［12］ Also in agreement with the present study is the finding that the work-related environment is a predictor of sickness absence［18~20］.There are only a few studies in which factors such as the patients'work situation，economic circumstances，physical fitness and perceived health have been analysed to ascertain if they are related to sickness absence in primary care patients.The present study confirms the impact of many of these variables on sickness absence regardless of variation in population and methodology［9，12，19，21］.
Poor physical fitness and poor perceived health were associated with long-term sickness absence in model 4;however，poor economic situation was not a significant factor in the logistic models 2 and 5（Table 2）.North and associates reported that adverse social circumstances such as financial difficulties and negative support were risk factors for sickness absence in contrast to the result of the present study regarding economic situation［9］.An explanation for this divergent finding could be that long-term sickness absence depends more on patients' beliefs concerning their physical fitness and health rather than on economic benefits of sickness absence.Another explanation is that the Swedish sickness benefit and social insurance system differs from many other countries.Musculoskeletal and mental disorders were the most common diagnoses among patients on long-term sickness absence（Table 4），findings that are in accordance with the studies by other authors［2，4］.
It could be argued that some objective measures of health，work situation and economic situation would have strengthened the results.Although the present study contains no such objective measures，self-reported health status has been shown to be a strong predictor of mortality［22，23］.
In the present investigation，the response rate was 79%，which is acceptable and is higher than that reported in other，similar studies［24，25］.The mean age and gender distribution of the non-respondents did not differ significantly from that of the respondents.However，the non-response rate probably did have some impact on the results.In addition to the response rate，the multi-ethnic population and multi-language background of our population should be considered when interpreting the results.To reduce any linguistic difficulties in responding to the questionnaire，an interpreter was provided when needed.
About 50% of all patients aged 16~64 years who visited the practice were on sickness absence during the year in question.About half of the individuals were on long-term sickness absence（SA>28 days）.The patients in our study had a high rate of sickness absence compared with other studies［26~29］.This could be explained by the fact that the present study is patient-based and the main intention was to analyse the relations between sickness absence and the determinants of sickness absence rather than studying its prevalence，which could be higher among patients in comparison with，for example，the general population.
The socio-demographic characteristics of the area served by the general practice may influence the sickness absence rate and the fact that this study reflects is concerned with patients who consulted the health care centre may play a significant role in the detected differences.Country of birth was an importance factor for long-time sickness absence.Both patients born in Sweden and patients born outside the Nordic countries had about the same total sickness absence rate，but the long-term sickness absence rate was bout 40% higher among patients born outside the Nordic countries compared with the Swedish-born patients（Table 1）.This finding is，however，in agreement with the results of the study reported by Grossi,et al. who found that those patients who had been on sickness absence for>30 days were significantly more often divorced，immigrants，blue-collar workers and less educated than the other patients in their sample［30］.They also reported that their patients used more pain medication and tranquillizers［30］.Gender and marital status were other social factors that seem to be associated with long-term sickness absence.These findings are in accordance with the findings of other studies［19，31-33］.
It is apparent that work situation is an important predicator of sickness absence at the same level as perceived health and physical fitness.Poor work situation was one important determinant of long-term sickness absence（Table 3）.As found in the study by Hemingway, et al.，a poor work situation could make it more difficult for the person to return to work，and with reduced fitness it would be much more difficult to adapt to the work［34］.The magnitude of dissatisfaction with the work situation plays a substantial role.It appears that this factor measures many aspects of work-related factors and could be used in clinical practice.Efforts should be focused on improving the work situation and should be an important issue for occupational health care and GPs.Measures of health status combined with an easy tool for to enable respondents to evaluate their work situation could provide valuable information.
In conclusion，this primary care study has shown that gender and poor work situation are associated with periods of long-term sickness absence.Persons on long-term sickness absence have higher consultation rates with physicians and GPs.They also have higher prescription rates and use a greater number of medicines.Our findings suggest that respondents on sickness absence are in fact sicker or perceive their health status poorer than others do and that they have higher health care utilisation and dissatisfaction with their work conditions.Gender and poor work situation also predicted sickness absence，a finding that calls for special measures.Efforts should be focused on improving the work situation for people in general and for these patients in particular.This information is essential and should be taken into account in rehabilitation programmes that aim to return people to work.
【参考文献】
1. Anderberg UM.Stress-related syndromes-contemporary illnesses.Lakartidningen，2001，98:5860-5863.
2. Atroshi I，Andersson IH，Gummesson C，Leden I，Odenbring S，Ornstein E.Care patients with musculoskeletal pain.Value of health-status and sense-of-coherence measures in predicting long-term work disability.Scandinavian Journal of Rheumatology，2002，31:239-244.
3. Feeney A，North F，Head J，Canner R，Marmot M.Socioeconomic and sex differentials in reason for sickness absence from the Whitehall II Study.Occupational and Environmental Medicine，1998，55:91-98.
4. Shiels C，Gabbay MB，Ford FM.Patient factors associated with dura-tion of certified sickness absence and transition to long-term incapacity.British Journal of General Practice，2004，54:86-91.
5. Alexandersson K，Nordlind.A Sickness absence-causes，conse-quences，and physicians'sickness certification practice.A systematic literature review by the Swedish Council on Technology Assessment in Health Care.Chapter 1.Scandinavian Journal of Public Health，2004，Suppl 63:12-30.
6. The National Social Insurance Board.Vad kostar sjukskrivningarna inom olika yrken?［How much does sickness absence cost in different occupations］.Vol.5.RFV 2003，Stockholm，Sweden.（In Swedish）.
7. Utredningen om den arbetslivsinriktade rehabiliteringen.［Investigation on work-related rehabilitation］.SOU 78，2000，Stockholm，Fritzes.（In Swedish）.
8. Voss M.Work and health:Epidemiological studies of sickness absence and mortality with special reference to work environment，factors outside work and unemployment.（thesis）.Division of Environmental Medicine，2002，Karolinska Institute，Stockholm.
9. North F，Syme SL，Feeney A，Head J，Shipley MJ，Marmot MG.Explaining socioeconomic differences in sickness absence:the Whitehall II Study.British Medical Journal，1993，306:361-366.
10. Niedhammer I，Bugel I，Goldberg M，Leclerc A，Gueguen A.Psychosocial factors at work and sickness absence in the Gazel cohort:a prospective study.Occupational and Environmental Medicine，1998，55:735-741.
11. Hornquist JO，Zar M，Hansson B.Precursors of repeated short-term sick-leave:an empirical review of some background，job and well-being characteristics.Scandinavian Journal of Social Medicine，1993，21:164-170.
12. Marmot M，Feeney A，Shipley M，North F，Syme SL.Sickness absence as a measure of health status and functioning:from the UK Whitehall II study.Journal of Epidemiology and Community Health，1995，49:124-130.
13. Englund L，Svardsudd K.Sick-listing habits among general practitioners in a Swedish county.Scandinavian Journal of Primary Health Care，2000，18:81-86.
14. Tellnes G.Sickness certification in general practice.A review.Family Practice，1992，6:58-65.
15. Tibblin G，Peciva S，Kullman S，Svardsudd K.'The Goteborg quality of life instrument'-an assessment of well-being and symptoms among men born 1913 and 1923.Methods and validity.Scandinavian Journal of Primary Health Care，1990，Suppl 8:33-38.
16. JMP-program:The Statistical Discovery Software.Introductory guide.5th ed.2002，SAS Institue，Cary，NC.
17. SAS:The SAS System.8th edition.1999，Inc.，Cary，NC，USA，Cary，NC，SAS Institute.
18. Eshoj P，Jepsen JR，Nielsen CV.Long-term sickness absence -risk indicators among occupationally active residents of a Danish county.Occupational Medicine（Oxford），2001，51:347-353.
19. Melchior M，Niedhammer I，Berkman LF，Goldberg M.Do psychosocial work factors and social relations exert independent effects on sickness absence? A six year prospective study of the GAZEL cohort.Journal of Epidemiology and Community Health，2003，57:285-293.
20. North FM，Syme SL，Feeney A，Shipley M，Marmot M.Psychosocial work environment and sickness absence among British civil servants:the Whitehall II study.American Journal of Public Health，1996，86:332-340.
21. Virtanen M，Kivimaki M，Elovainio M，Vahtera J，Cooper CL.Contingent employment，health and sickness absence.Scandinavian Journal of Work，Environment and Health，2001，27:365-372.
22. Heidrich J，Liese AD，Lowel H，Keil，U.Self-rated health and its relation to all-cause and cardiovascular mortality in southern Germany.Results from the MONICA Augsburg cohort study 1984-1995.Annals of epidemiology，2002，12:338-345.
23. Benjamins MR，Hummer RA，Eberstein IW，Nam CB.Self-reported health and adult mortality risk:an analysis of cause-specific mortality.Social Science and Medicine，2004，59:1297-1306.
24. Asplund R，Aberg H.Nocturnal micturition，sleep and well-being in women of ages 40~64 years.Maturitas，1996，24:73-81.
25. Isacsson A，Hanson BS，Janzon L，Kugelberg G.The epidemiology of sick leave in an urban population in Malmo，Sweden.Scandinavian Journal of Social Medicine，1992，220:234-239.
26. Krasnik A，Hansen E，Keiding N，Sawits A.Determinants of general practice utilisation in Denmark.Danish Medical Bulletin，1997，44:542-546.
27. Tellnes G，Mathisen S，Skau I，Thune O，Ulsberg S，Berg JE.Hvem er langtidssykmeldt i Norge?［Who is long-term sick-listed in Norway? From the project Evaluation of the follow-up of long-term sick-listed］.Tidsskrift for Den norske laegeforening，1992，112:2773-2778.
28. Gjesdal S，Bratberg E.The role of gender in long-term sickness absence and transition to permanent disability benefits.Results from a multiregister based，prospective study in Norway 1990-1995.European Journal of Public Health，2002，12:180-186.
29. Knutsson A，Goine H.Occupation and unemployment rates as predictors of long-term sickness absence in two Swedish counties.Social Science and Medicine，1998，47:25-31.
30. Grossi G，Soares JJ，Angesleva J，Perski A.Psychosocial correlates of long-term sick-leave among patients with musculoskeletal pain.Pain，1999，80:607-619.
31. Aronsson G，Gustafsson K，Dallner M.Sick but yet at work.An empirical study of sickness presenteeism.Journal of Epidemiology and Community Health，2000，54:502-509.
32. Leijon M，Hensing G，Alexanderson K.Gender trends in sick-listing with musculoskeletal symptoms in a Swedish county during a period of rapid increase in sickness absence.Scandinavian Journal of Social Medicine，1998，226:204-213.
33. Sandanger I，Nygard JF，Brage S，Tellnes G.Relation between health problems and sickness absence:gender and age differences-a comparison of low-back pain，psychiatric disorders，and injuries.Scandinavian Journal of Public Health，2000，28:244-252.
34. Hemingway H，Shipley MJ，Stansfeld S，Marmot M.Sickness absence from back pain，psychosocial work characteristics and employment grade among office workers.Scandinavian Journal of Work，Environment and Health，1997，23:121-129.
（Editor Yolanda）
订阅登记：
请您在下面输入常用的Email地址、职业以便我们定期通过邮箱发送给您最新的相关医学信息，感谢您浏览首席医学网！