Diagnosis-specific sickness absence as a predictor of mortality: the Whitehall II prospective cohort study.
Diagnosis-specific sickness absence as a predictor of mortality: the Whitehall II prospective cohort study.
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诊断特定的疾病缺乏作为死亡率的预测指标:Whitehall II前瞻性队列研究。
DOI:
10.1136/bmj.a1469
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发表时间:
2008-10-02
期刊:
影响因子:
--
通讯作者:
Whitehall II prospective cohort study
中科院分区:
文献类型:
--
作者:
Head J;Ferrie JE;Alexanderson K;Westerlund H;Vahtera J;Kivimäki M;Whitehall II prospective cohort study
Objective To investigate whether knowing the diagnosis for sickness absence improves prediction of mortality. Design Prospective cohort study established in 1985-8. Sickness absence records including diagnoses were obtained from computerised registers. Setting 20 civil service departments in London. Participants 6478 civil servants aged 35-55 years. Main outcome measures All cause, cardiovascular, and cancer mortality until 2004, average follow-up 13 years. Results After adjustment for age, sex, and employment grade, employees who had one or more medically certified spells of sickness absence (>7 days) in a three year period had a mortality 1.7 (95% CI 1.3 to 2.1) times greater than those with no medically certified spells. Inclusion of diagnoses improved the prediction of all cause mortality (P=0.03). The hazard ratio for mortality was 4.7 (2.6 to 8.5) for absences with circulatory disease diagnoses, 2.2 (1.4 to 3.3) for surgical operations, and 1.9 (1.2 to 3.1) for psychiatric diagnoses. Psychiatric absences were also predictive of cancer mortality (2.5 (1.3 to 4.7)). Associations of infectious, respiratory, and injury absences with overall mortality were less marked (hazard ratios from 1.5 to 1.7), and there was no association between musculoskeletal absences and mortality. Conclusions Major diagnoses for medically certified absences were associated with increased mortality, with the exception of musculoskeletal disease. Data on sickness absence diagnoses may provide useful information to identify groups with increased health risk and a need for targeted interventions.
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影响因子:
7.4
作者:
Falagas, Matthew E.;Zarkadoulia, Effie A.;Ioannidou, Eleni N.;Peppas, George;Christodoulou, Christos;Rafailidis, Petros I.
通讯作者:
Rafailidis, Petros I.
影响因子:
5
作者:
EAKER, ED;PINSKY, J;CASTELLI, WP
通讯作者:
CASTELLI, WP
影响因子:
4.9
作者:
Feeney, A;North, F;Marmot, M
通讯作者:
Marmot, M
影响因子:
168.9
作者:
MARMOT, MG;SMITH, GD;FEENEY, A
通讯作者:
FEENEY, A
影响因子:
3.1
作者:
Goodwin, Renee D.;Cox, Brian J.;Clara, Ian
通讯作者:
Clara, Ian