You are working for a pollution control company that specializes inPM2.5 removal from homes.Your supervisor shows you the following abstract and does not understand the stuff about regression.The supervisor asks you to look at this abstract and explain it in English without all the statistical jargon.

"In recent years (2000-2007), ambient levels of fine particulate matter (PM2.5) have continued to decline as a result of interventions, but the decline has been at a slower rate than previous years (1980-2000). Whether these more recent and slower declines of PM2.5 levels continue to improve life expectancy and whether they benefit all populations equally is unknown. Methods: We assembled a data set for 545 U.S. counties consisting of yearly county-specific average PM2.5, yearly county-specific life expectancy, and several potentially confounding variables measuring socioeconomic status, smoking prevalence, and demographic characteristics for the years 2000 and 2007. We used regression models to estimate the association between reductions in PM2.5 and changes in life expectancy for the period from 2000 to 2007. Results: A decrease of 10 g/m3 in the concentration of PM2.5 was associated with an increase in mean life expectancy of 0.35 years R square =.38 ( P = 0.033). This association was stronger in more urban and densely populated counties. Conclusions: Reductions in PM2.5 were associated with improvements in life expectancy for the period from 2000 to 2007. Air pollution control in the last decade has continued to have a positive impact on public health."