Several specific population interventions that achieved a Class I or IIa recommendation with grade A or B evidence were identified , providing a set of specific evidence -based strategies that deserve close attention and prioritization for wider implementation .
Effective interventions included specific approaches in all 6 domains evaluated for improving diet , increasing activity , and reducing tobacco use .
The writing group also identified several specific interventions in each of these domains for which current evidence was less robust , as well as other inconsistencies and evidence gaps , informing the need for further rigorous and interdisciplinary approaches to evaluate population programs and policies .
This systematic review identified and grade d the evidence for a range of population -based strategies to promote lifestyle change .
BACKGROUND Poor lifestyle behaviors , including suboptimal diet , physical inactivity , and tobacco use , are leading causes of preventable diseases globally .
Although even modest population shifts in risk substantially alter health outcomes , the optimal population -level approaches to improve lifestyle are not well established .
Dissociation between hospital performance of the smoking cessation counseling quality metric and cessation outcomes after myocardial infarction.
BACKGROUND Recognizing the importance of smoking cessation after acute myocardial infa rct ion ( AMI ) , the Centers for Medicare & Medicaid Services and the Joint Commission on Accreditation of Healthcare Organizations currently uses documentation of smoking cessation counseling ( SCC ) as a metric of hospitals ' quality of AMI care . Yet , the association between hospitals ' performance of this quality measure and subsequent tobacco cessation rates has not been established . METHODS We analyzed 889 consecutive smokers treated for AMI at 19 hospitals in PREMIER ( Prospect i ve Registry Evaluating Myocardial Infa rct ion : Events and Recovery ) between January 1 , 2003 , and June 28 , 2004 . Patients were followed up for 1 year after hospitalization . Multivariate regression modeling was performed to determine the association between hospital-level documented SCC rates and tobacco cessation rates after discharge . RESULTS On a hospital level , the median medical record-documented SCC rate was 72.0 % ( interquartile range , 59.6%-90.1 % ) . At 1 year , the median smoking cessation rate was 55.6 % ( interquartile range , 37.5%-61.9 % ) . Although patients with documented SCC were more likely to recall receiving SCC at 1 month ( 86.1 % vs 70.8 % , P < .001 ) , their rate of quitting at 1 year was lower than that of patients without documented SCC ( 50.1 % vs 60.7 % , P = .02 ; relative risk , 0.76 ; 95 % confidence interval , 0.61 - 0.94 ) . At the hospital level , there was no correlation between SCC documentation and successful quitting at 6 months ( r = -0.19 , P = .11 ) or 1 year ( r = -0.13 , P = .45 ) . CONCLUSIONS The performance metric for SCC , as it is currently structured , does not correlate with actual smoking cessation at 6 months or 1 year . Revision of this performance measure should be considered to more effectively reflect the goal of promoting smoking cessation
Several specific population interventions that achieved a Class I or IIa recommendation with grade A or B evidence were identified , providing a set of specific evidence -based strategies that deserve close attention and prioritization for wider implementation .
Effective interventions included specific approaches in all 6 domains evaluated for improving diet , increasing activity , and reducing tobacco use .
The writing group also identified several specific interventions in each of these domains for which current evidence was less robust , as well as other inconsistencies and evidence gaps , informing the need for further rigorous and interdisciplinary approaches to evaluate population programs and policies .
This systematic review identified and grade d the evidence for a range of population -based strategies to promote lifestyle change .
BACKGROUND Poor lifestyle behaviors , including suboptimal diet , physical inactivity , and tobacco use , are leading causes of preventable diseases globally .
Although even modest population shifts in risk substantially alter health outcomes , the optimal population -level approaches to improve lifestyle are not well established .