| Literature DB >> 25608660 |
Ivana T Croghan1,2, Jon O Ebbert3,4,5, J Taylor Hays6, Darrell R Schroeder7, Alanna M Chamberlain8, Véronique L Roger9,10,11, Richard D Hurt12.
Abstract
BACKGROUND: With the goal of reducing exposure to secondhand smoke, the state of Minnesota (MN), enacted a smoke-free law (i.e., Freedom to Breathe Act) in all workplaces, restaurants, and bars in 2007. This retrospective cohort study analyzes emergency department (ED) visits in Olmsted County, MN, for chronic obstructive pulmonary disease (COPD) and asthma over a five-year period to assess changes after enactment of the smoke-free law.Entities:
Mesh:
Substances:
Year: 2015 PMID: 25608660 PMCID: PMC4417313 DOI: 10.1186/1471-2466-15-6
Source DB: PubMed Journal: BMC Pulm Med ISSN: 1471-2466 Impact factor: 3.317
Patient characteristics
| Asthma | ||||
|---|---|---|---|---|
| Characteristic | COPD | Overall | Adults | Children |
| n = 5293 | n = 5906 | n = 4375 | n = 1531 | |
| Age, y, median (25th, 75th) | 75 (64, 82) | 37 (17, 57) | 47 (33, 65) | 6 (3, 11) |
| Sex | ||||
| Female, n (%) | 2551 (48.2) | 3619 (61.3) | 2994 (68.4) | 625 (40.8) |
| Male, n (%) | 2742 (51.8) | 2287 (38.7) | 1381 (31.6) | 906 (59.2) |
Abbreviation: COPD chronic obstructive pulmonary disease.
Segmented poisson regression results
| Monthly trend before law was passed (β 1 ) | Step change when law took effect (β 2 ) | Change in trend after law took effect (β 3 ) | Monthly trend after law took effect (β 1 + β 3 ) | |
|---|---|---|---|---|
| COPD | ||||
| β (SE) | -0.002 (0.002) | -0.091 (0.065) | -0.004 (0.004) | -0.006 (0.003) |
| RR (95% CI) | 0.998 (0.993, 1.002) | 0.913 (0.804, 1.036) | 0.994 (0.989, 0.999) | |
| p value | 0.331 | 0.158 | 0.313 | 0.028 |
| Asthma | ||||
| Overall | ||||
| β (SE) | +0.003 (0.002) | -0.206 (0.061) | -0.002 (0.003) | +0.000 (0.003) |
| RR (95% CI) | 1.003 (0.998, 1.007) | 0.814 (0.722, 0.918) | 1.000 (0.995, 1.005) | |
| p value | 0.236 | <0.001 | 0.502 | 0.876 |
| Adults | ||||
| β (SE) | -0.000 (0.003) | -0.175 (0.072) | +0.002 (0.004) | +0.002 (0.003) |
| RR (95% CI) | 1.000 (0.994, 1.005) | 0.840 (0.729, 0.966) | 1.002 (0.996, 1.008) | |
| p value | 0.922 | 0.015 | 0.611 | 0.552 |
| Children | ||||
| β (SE) | +0.011 (0.004) | -0.287 (0.118) | -0.015 (0.007) | -0.004 (0.005) |
| RR (95% CI) | 1.011 (1.002, 1.020) | 0.751 (0.595, 0.947) | 0.996 (0.986, 1.006) | |
| p value | 0.015 | 0.015 | 0.027 | 0.424 |
*The segmented Poisson regression model adjusted for age and sex provides estimates for the trend in ED visits over time prior to the law being passed (β1), the step change after the law took effect (β2) and the change in trend after the law took effect (β3). The sum of β1 and β3 corresponds to the trend over time after the law took effect.
Abbreviation: COPD chronic obstructive pulmonary disease.
Figure 1ED visit rates for COPD before and after smoke-free law. Visit rates are presented monthly from 1/1/2005 through 12/31/2009. The vertical dashed lines indicate the time period between when the law was passed and when the law took effect. Solid lines represent the predicted rates from segmented Poisson regression.
Figure 2ED visit rates for asthma before and after smoke-free law. Visit rates are presented monthly from 1/1/2005 through 12/31/2009. The vertical dashed lines indicate the time period between when the law was passed and when the law took effect. Solid lines represent the predicted rates from segmented Poisson regression.
Figure 3Adult ED visit rates for asthma before and after smoke-free law. Visit rates are presented monthly from 1/1/2005 through 12/31/2009. The vertical dashed lines indicate the time period between when the law was passed and when the law took effect. Solid lines represent the predicted rates from segmented Poisson regression.
Figure 4Child ED visit rates for asthma before and after smoke-free law. Visit rates are presented monthly from 1/1/2005 through 12/31/2009. The vertical dashed lines indicate the time period between when the law was passed and when the law took effect. Solid lines represent the predicted rates from segmented Poisson regression.