Effect of Asthma Call-back Survey methodology changes on work-related asthma estimates, 19 states, 2007-2012

Prevalence of COPD among workers with work-related asthma

Objective: Concurrent asthma and chronic obstructive pulmonary disease (COPD) diagnoses occur in 15%-20% of patients, and have been associated with worse health outcomes than asthma or COPD alone. Work-related asthma (WRA), asthma that is caused or made worse by exposures in the workplace, is characterized by poorly controlled asthma. The objective of this study was to assess the proportion of ever-employed adults (≥18 years) with current asthma who have been diagnosed with COPD, by WRA status.Methods: Data from 23 137 respondents to the 2012-2014 Behavioral Risk Factor Surveillance System Asthma Call-back Survey from 31 states and the District of Columbia were examined. Logistic regression was used to calculate adjusted prevalence ratios (PRs), examining six disjoint categories of WRA-COPD overlap with non-WRA/no COPD as the referent category.Results: An estimated 51.9% of adults with WRA and 25.6% of adults with non-WRA had ever been diagnosed with COPD. Adults with WRA/COPD were more likely than those with non-WRA/no COPD to have an asthma attack (PR = 1.77), urgent treatment for worsening asthma (PR = 2.85), an asthma-related emergency room visit (PR = 4.21), overnight stay in a hospital because of asthma (PR = 6.57), an activity limitation on 1-13 days (PR = 2.01) or ≥14 days (PR = 5.02), and very poorly controlled asthma (PR = 3.22).Conclusions: COPD was more frequently diagnosed among adults with WRA than those with non-WRA, and adults diagnosed with both WRA and COPD appear to have more severe adverse asthma outcomes than those with non-WRA and no COPD.

Predictive validation and forecasts of short-term changes in healthcare expenditure associated with changes in smoking behavior in the United States

Objectives

Out-of-sample forecasts are used to evaluate the predictive adequacy of a previously published national model of the relationship between smoking behavior and real per capita health care expenditure using state level aggregate data. In the previously published analysis, the elasticities between changes in state adult current smoking prevalence and mean cigarette consumption per adult current smoker and healthcare expenditures were 0.118 and 0.108 This new analysis provides evidence that the model forecasts out-of-sample well.

Methods

Out-of-sample predictive performance was used to find the best specification of trend variables and the best model to bridge a break in survey data used in the analysis. Monte-Carlo simulation was used to calculate forecast intervals for the effect of changes in smoking behavior on expected real per capita healthcare expenditures.

Results

The model specification produced good-out-of-sample forecasts and stable recursive regression parameter estimates spanning the break in survey methodology. In 2014, a 1% relative reduction in adult current smoking prevalence and mean cigarette consumption per adult current smoker decreased real per capita healthcare expenditure by 0.104% and 0.113% the following year, respectively (elasticity). A permanent relative reduction of 5% reduces expected real per capita healthcare expenditures $99 (95% CI $44, $154) in the next year and $31.5 billion for the entire US (in 2014 dollars), holding other factors constant. The reductions accumulate linearly for at least five years following annual permanent decreases of 5% each year. Given the limitations of time series modelling in a relatively short time series, the effect of changes in smoking behavior may occur over several years, even though the model contains only one lag for the explanatory variables.

Conclusion

Reductions in smoking produce substantial savings in real per capita healthcare expenditure in short to medium term. A 5% relative drop in smoking prevalence (about a 0.87% reduction in absolute prevalence) combined with a 5% drop in consumption per remaining smoker (about 16 packs/year) would be followed by a $31.5 billion reduction in healthcare expenditure (in 2014 dollars).