Understanding the variability in the effectiveness of community heart health programs: A meta-analysis

Abstract

Over the past 25 years, community interventions to reduce cardiovascular disease (CVD) have been conducted around the world with very mixed results. This study uses meta-analysis to assess whether the variation in the observed effectiveness of community heart health programs (CHHP) is related to characteristics of the intervention program, the population under study, or the evaluation methods. A CHHP is defined as any primary prevention program that attempted to reduce the population burden of CVD by shifting the distribution of risk factors in a general population. To be included in the meta-analysis, a study must have utilized a reference group in the evaluation, employed a repeated independent cross-sectional measurement design, and reported sufficient outcome information for at least one of four major risk factors: smoking, total cholesterol, blood pressure, and body weight. Results of these studies are summarized with the effect size measure (( Y ̄ i1 − Y ̄ i2) − ( Y ̄ r1 − Y ̄ r2))s r1 where Y = outcome measure, S = standard deviation of the outcome measure, 1 = baseline, 2 = follow-up, i = intervention, and r = reference community. This measure, which reports the net change in the intervention group in terms of the variability in the reference population before the start of the intervention, permits comparison across different outcome measures and facilitates the aggregation of effects across studies. Generalized least squares regression, which permits the incorporation of multiple, dependent effect sizes from a single study, was used to assess the impact of characteristics of the intervention (prevention strategy, type of mass communication, community organization, and environmental change), the population (setting, gender, year of follow-up measurement), and the evaluation design and implementation (the number of communities, matching of communities, the follow-up time, the response rate, and covariate adjustment in the analysis) on the effect sizes. The results of this analysis suggest that the characteristics of the evaluation method account for much of the heterogeneity in the outcome of CHHPs, though some intervention characteristics also play a role.