| Literature DB >> 31053139 |
Ingeborg Lund1, Inger Synnøve Moan2, Hilde Marie Erøy Edvardsen3.
Abstract
BACKGROUND: It is well documented that tobacco, alcohol and drug use can be detrimental to health. However, little is known about the relative impact of these factors on sickness absence, and whether the association between use of these substances and sickness absence is different for women and men. The aim of this study was to examine the association between tobacco-, alcohol- and drug use, as well as polydrug use, and sickness absence among Norwegian employees.Entities:
Keywords: Alcohol; Illegal and medical drugs; Sickness absence; Tobacco
Mesh:
Year: 2019 PMID: 31053139 PMCID: PMC6499980 DOI: 10.1186/s12889-019-6891-1
Source DB: PubMed Journal: BMC Public Health ISSN: 1471-2458 Impact factor: 3.295
Demographic and sickness absence description of sample
| Health | Industry | Restaurants | Media | Finance | Total | |
|---|---|---|---|---|---|---|
| N | 917 | 254 | 131 | 152 | 457 | 1911 |
| Age | % | % | % | % | % | |
| under 30 | 15.0 | 12.2 | 79.2 | 25.0 | 9.5 | 18.5 |
| 30–39 | 27.2 | 15.4 | 16.9 | 31.6 | 28.5 | 25.6 |
| 40–49 | 27.1 | 31.6 | 3.1 | 15.8 | 25.0 | 24.6 |
| 50–59 | 22.4 | 29.6 | 0.0 | 21.1 | 28.3 | 23.1 |
| 60+ | 8.3 | 11.3 | 0.8 | 6.6 | 8.6 | 8.1 |
| Sex | ||||||
| Male | 18.9 | 80.0 | 51.9 | 48.7 | 50.6 | 60.9 |
| Female | 81.1 | 20.0 | 48.1 | 51.3 | 49.4 | 39.1 |
| Education | ||||||
| Middle school | 2.0 | 9.1 | 8.4 | 4.6 | 0.7 | 3.2 |
| High School | 19.6 | 53.9 | 48.1 | 14.5 | 14.7 | 24.5 |
| College | 71.3 | 28.4 | 40.5 | 74.3 | 80.5 | 65.9 |
| unreported | 7.1 | 8.7 | 3.1 | 6.6 | 4.2 | 6.3 |
| No of sickness absences last 12 months | ||||||
| none | 26.9 | 33.9 | 36.7 | 27.0 | 34.0 | 30.2 |
| 1 or 2 | 51.7 | 56.2 | 49.2 | 57.2 | 51.9 | 52.6 |
| 3 or more | 21.5 | 10.0 | 14.1 | 15.8 | 14.1 | 17.2 |
| No of days last sickness absence | ||||||
| one day or less | 58.4 | 57.6 | 62.2 | 56.6 | 62.6 | 59.4 |
| 2 or 3 days | 25.2 | 26.0 | 24.4 | 35.5 | 26.0 | 26.3 |
| more than three days | 16.4 | 16.4 | 13.4 | 7.9 | 11.4 | 14.3 |
To identify those with a higher occurrence of sickness absences, the variable was recalculated into a dummy variable, with categories representing (0) less than three, and (1) three or more, sickness absences during the last 12 months
Factors associated with having had three or more sickness absences in the past 12 months
| AOR | P | 95% CI for AOR | |
|---|---|---|---|
| Smoking | |||
| Daily | 1.65 | 0.019 | 1.09–2.50 |
| Occasional | 1.19 | 0.432 | 0.77–1.84 |
| Former | 1.08 | 0.617 | 0.79–1.49 |
| Daily snus use | 1.18 | 0.492 | 0.73–1.90 |
| Weekly binge drinking | 1.76 | 0.147 | 0.82–3.78 |
| Illegal drug use | 0.77 | 0.737 | 0.16–3.65 |
| Medical drug use | 2.36 | 0.007 | 1.27–4.37 |
| Poly- and drug use | |||
| Smoking and drug use | 0.88 | 0.807 | 0.33–2.40 |
| Smoking and weekly binge drinking | 1.26 | 0.702 | 0.39–4.05 |
| Drug use and weekly binge drinking | 0.39 | 0.329 | 0.06–2.58 |
| Male | 0.70 | 0.024 | 0.52–0.96 |
| Age (ref = younger than 30 yrs) | |||
| 30–39 yrs | 1.10 | 0.625 | 0.76–1.59 |
| 40–49 yrs | 0.54 | 0.004 | 0.36–0.83 |
| 50–59 yrs | 0.35 | 0.000 | 0.22–0.56 |
| 60+ yrs | 0.36 | 0.002 | 0.19–0.69 |
| Education (ref = middle school) | |||
| High school | 1.84 | 0.225 | 0.69–4.94 |
| University | 1.51 | 0.409 | 0.57–4.03 |
| Constant | 0.14 | 0.000 | 0.05–0.42 |
Multilevel logit regression (mixed effect logistic regression) with sickness absence (dummy variable) as the dependent variable, controlled for random effects of branch and workplace. AOR = Adjusted Odds Ratio
N = 1811, 22 workplaces (var = 0.12, SE = 0.13) within 5 branches (var = 0.14, SE = 0.08), LR-test for sign. Effect of random stratification: p < 0.001
Factorsa associated with high-level sickness absence
| AOR | P | 95% CI for AOR | |
|---|---|---|---|
| Smoking (ref = never) | |||
| Daily | 2.61 | 0.008 | 1.29–5.30 |
| Occasionally | 1.07 | 0.893 | 0.42–2.70 |
| Former | 1.47 | 0.199 | 0.82–2.66 |
| Daily snus use | 1.61 | 0.290 | 0.67–3.88 |
| Weekly binge drinking | 1.01 | 0.991 | 0.19–5.28 |
| Medical drug use | 2.22 | 0.103 | 0.85–5.79 |
| Poly- and dual drug use | |||
| Smoke and drugs | 0.50 | 0.451 | 0.08–3.01 |
| Smoke and drink | 0.62 | 0.714 | 0.05–7.95 |
| Drink and drugs | 1.94 | 0.599 | 0.17–22.73 |
| Male | 0.45 | 0.006 | 0.26–0.79 |
| Constant | 0.02 | 0.000 | 0.00–0.08 |
Binary logistic regression with high-level absence as the dependent variable. N = 1801. No significant effect of random stratification. AOR Adjusted Odds Ratio
a Adjusted also for age and education, which were not significantly associated with the outcome, and removed from table for increased simplicity. Illegal drug use was not included in the analysis as none of the 75 individuals in the high-level absence group had used illegal drugs
Bivariate associations between tobacco, alcohol, and drug use and last year sickness absence (N = 1392–1888)a
| Sickness absence more than twice last 12 months | Last sickness absence more than 3 days duration | High-level absence group | |
|---|---|---|---|
| Sample ( | 17.21 (1888) | 14.33 (1870) | 4.01 (1870) |
| Weekly binge drinking | |||
| Yes | 24.05 | 11.54 | 3.85 |
| No | 17.01 | 14.37 | 4.04 |
| medical drugs | |||
| Yes | 27.55** | 18.75 | 7.29 |
| no | 16.65 | 14.09 | 3.83 |
| Illegal drugs | |||
| Yes | 12.5 | 4.17 | 0.00 |
| No | 17.27 | 14.46 | 4.06 |
| Daily smoking | |||
| Yes | 22.39* | 17.72 | 6.69* |
| No | 16.46 | 13.80 | 3.60 |
Chi Square, *: p < 0.05; **: p < 0.01
a: variation due to item non-response