Long-term survival after acute myocardial infarction is lower in more deprived neighborhoods.
ABSTRACT As part of the Worcester Heart Attack Study, a community-wide study examining changes over time in the incidence and long-term case-fatality rates of greater Worcester, Mass, residents hospitalized with confirmed acute myocardial infarction (AMI), we investigated the hypothesis that census tract-level socioeconomic position is an important predictor of survival after hospital discharge for AMI, after adjusting for demographic and clinical characteristics.
Data were available for 3423 confirmed cases of AMI among metropolitan Worcester residents during the 4 study years of 1995, 1997, 1999, and 2001 who were followed up through the end of 2002. The mean age among patients was 69 years, and 58% were men. Using a multilevel Cox proportional hazards regression model, we estimated a 30% higher death rate after AMI for patients living in census tracts with the most residents living below the poverty line compared with patients living in the wealthiest census tracts (relative risk=1.30; 95% CI, 1.08 to 1.56). Similarly, patients living in census tracts with the highest proportion of residents with less than a high school education experienced a 47% higher death rate than patients living in census tracts with the lowest proportion of residents with less than a high school education (relative risk=1.47; 95% CI, 1.15 to 1.88).
Within a medium-sized urban area, there are important variations in survival after hospital discharge for AMI that are associated with socioeconomic position. These associations persist after adjustment for demographic and clinical characteristics. Reasons for these differences warrant further investigation.
Article: Long-term exposure to air pollution is associated with survival following acute coronary syndrome.[show abstract] [hide abstract]
ABSTRACT: AimsThe aim of this study was to determine (i) whether long-term exposure to air pollution was associated with all-cause mortality using the Myocardial Ischaemia National Audit Project (MINAP) data for England and Wales, and (ii) the extent to which exposure to air pollution contributed to socioeconomic inequalities in prognosis.Methods and resultsRecords of patients admitted to hospital with acute coronary syndrome (ACS) in MINAP collected under the National Institute for Cardiovascular Outcomes Research were linked to modelled annual average air pollution concentrations for 2004-10. Hazard ratios for mortality starting 28 days after admission were estimated using Cox proportional hazards models. Among the 154 204 patients included in the cohort, the average follow-up was 3.7 years and there were 39 863 deaths. Mortality rates were higher for individuals exposed to higher levels of particles with a diameter of ≤2.5 µm (PM(2.5); PM, particulate matter): the fully adjusted hazard ratio for a 10 µg/m(3) increase in PM(2.5) was 1.20 (95% CI 1.04-1.38). No associations were observed for larger particles or oxides of nitrogen. Air pollution explained socioeconomic inequalities in survival to only a small extent.Conclusion Mortality from all causes was higher among individuals with greater exposure to PM(2.5) in survivors of hospital admission for ACS in England and Wales. Despite higher exposure to PM(2.5) among those from more deprived areas, such exposure was a minor contribution to the socioeconomic inequalities in prognosis following ACS. Our findings add to the evidence of mortality associated with long-term exposure to fine particles.European Heart Journal 02/2013; · 10.48 Impact Factor
Article: Identifying unique neighborhood characteristics to guide health planning for stroke and heart attack: fuzzy cluster and discriminant analyses approaches.[show abstract] [hide abstract]
ABSTRACT: Socioeconomic, demographic, and geographic factors are known determinants of stroke and myocardial infarction (MI) risk. Clustering of these factors in neighborhoods needs to be taken into consideration during planning, prioritization and implementation of health programs intended to reduce disparities. Given the complex and multidimensional nature of these factors, multivariate methods are needed to identify neighborhood clusters of these determinants so as to better understand the unique neighborhood profiles. This information is critical for evidence-based health planning and service provision. Therefore, this study used a robust multivariate approach to classify neighborhoods and identify their socio-demographic characteristics so as to provide information for evidence-based neighborhood health planning for stroke and MI. The study was performed in East Tennessee Appalachia, an area with one of the highest stroke and MI risks in USA. Robust principal component analysis was performed on neighborhood (census tract) socioeconomic and demographic characteristics, obtained from the US Census, to reduce the dimensionality and influence of outliers in the data. Fuzzy cluster analysis was used to classify neighborhoods into Peer Neighborhoods (PNs) based on their socioeconomic and demographic characteristics. Nearest neighbor discriminant analysis and decision trees were used to validate PNs and determine the characteristics important for discrimination. Stroke and MI mortality risks were compared across PNs. Four distinct PNs were identified and their unique characteristics and potential health needs described. The highest risk of stroke and MI mortality tended to occur in less affluent PNs located in urban areas, while the suburban most affluent PNs had the lowest risk. Implementation of this multivariate strategy provides health planners useful information to better understand and effectively plan for the unique neighborhood health needs and is important in guiding resource allocation, service provision, and policy decisions to address neighborhood health disparities and improve population health.PLoS ONE 01/2011; 6(7):e22693. · 4.09 Impact Factor
Article: Five-year prognosis in an incident cohort of people presenting with acute myocardial infarction.[show abstract] [hide abstract]
ABSTRACT: Following an AMI, it is important for patients and their physicians to appreciate the subsequent risk of death, and the potential benefits of invasive cardiac procedures and secondary preventive therapy. Studies, to-date, have focused largely on high-risk populations. We wished to determine the risk of death in a population-derived cohort of 2,887 patients after a first acute myocardial infarction (AMI). Logistic regression and survival analysis were conducted to investigate the effect of different baseline characteristics, pharmacological therapies and revascularization procedures on coronary heart disease (CHD) and all-cause mortality outcomes. Within five years 44.4% of patients died (27.1% short-term [<30 days] and 23.7% longer-term [≥30 days]). Percutaneous transluminal coronary angioplasty (Adjusted Hazards Ratio (AHR) = 0.49, 95% Confidence Interval (CI) 0.26-0.93), β-blockers (AHR = 0.58, 95%CI 0.46-0.74) and statins (AHR = 0.60, 95%CI 0.47-0.77) were all associated with significant reductions in longer-term CHD-related mortality. However, not all patients received secondary preventive therapy (8.7%). Diabetes (AHR = 1.83, 95%CI 1.43-2.34), stroke (AHR = 1.73, 95%CI 1.35-2.22), heart failure (AHR = 1.69, 95%CI 1.28-2.22), smoking (AHR = 1.72, 95%CI 1.18-2.51) and obesity (>30 kg/m2; AHR = 1.39, 95%CI 1.01-1.90) increased the risk of longer-term mortality independent of other risk factors. It is encouraging that the coronary procedure PTCA and pharmacological secondary prevention therapies were found to be strongly associated with an important reduced risk of subsequent death, although not all patients received these interventions. Smoking, being obese and having cardiovascular related disease at baseline were also associated with an increased likelihood of longer-term mortality, independent of other baseline characteristics. Thus, the provision of smoking cessation, advice on diet (for obese patients) and optimal treatment is likely to be crucial for reducing mortality in all patients after AMI.PLoS ONE 01/2011; 6(10):e26573. · 4.09 Impact Factor