Article

Neighborhood income, health insurance, and prehospital delay for myocardial infarction - The atherosclerosis risk in communities study

Department of Epidemiology, University of North Carolina at Chapel Hill, 137 E Franklin St, Ste 306, Chapel Hill, NC 27514, USA.
Archives of internal medicine (Impact Factor: 13.25). 10/2008; 168(17):1874-9. DOI: 10.1001/archinte.168.17.1874
Source: PubMed

ABSTRACT Outcomes following an acute myocardial infarction (AMI) are generally more favorable if prehospital delay time is minimized.
We examined the association of neighborhood household income (nINC) and health insurance status with prehospital delay among a weighted sample of 9700 men and women with a validated, definite, or probable AMI in the Atherosclerosis Risk in Communities (ARIC) community surveillance study (1993-2002). Weighted multinomial regression with generalized estimation equations was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) and to account for the clustering of patients within census tracts.
Low nINC was associated with a higher odds of long vs short delay (OR, 1.46; 95% CI, 1.09-1.96) and medium vs short delay (OR, 1.43; 95% CI, 1.12-1.81) compared with high nINC in a model including age, sex, race, diabetes, hypertension, presence of chest pain, arrival at the hospital via emergency medical service, distance from residence to hospital, study community, and year of AMI event. Meanwhile, compared with patients with prepaid insurance or prepaid plus Medicare, patients with Medicaid were more likely to have a long vs short delay (OR, 1.87; 95% CI, 1.10-3.19) and a medium vs short delay (OR, 1.76; 95% CI, 1.13-2.74).
Both low nINC and being a Medicaid recipient are associated with longer prehospital delay. Reducing socioeconomic and insurance disparities in prehospital delay is critical because excess delay time may hinder effective care for AMI.

0 Followers
 · 
49 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The Medicare program provides universal access to hospital care for the elderly; however, mortality disparities may still persist in this population. The association of individual education and area income with survival and recurrence post Myocardial Infarction (MI) was assessed in a national sample.
    BMC Public Health 07/2014; 14(1):705. DOI:10.1186/1471-2458-14-705 · 2.32 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: BACKGROUND: Patients’ treatment-seeking delay remains a significant barrier to timely initiation of reperfusion therapy. Measurement of treatment-seeking delay is central to research that focuses on pre-hospital delay (PHD). Investigators have aimed to quantify PHD and its effects on morbidity and mortality, identify contributing factors, and evaluate interventions to reduce delay. A definite time of symptom onset in acute coronary syndrome (ACS) is essential for determining delay, but difficult to establish. We aimed to explore operational definitions of PHD and symptom onset in published research. METHODS AND RESULTS: We reviewed English-language literature from 1998 to 2013 for definitions of PHD and symptom onset. Of 626 possibly applicable papers, 175 were deemed relevant. Ninety-seven percent reported a delay time and 84% provided an operational definition of PHD. Three definitions predominated: 1) symptom onset to decision to seek help (18%); 2) symptom onset to hospital arrival (67%), 3) total delay, incorporating two or more intervals (11%). Eight percent of those measuring delay provided a definition of which symptoms triggered the start of timing. CONCLUSION: We found few and variable operational definitions of PHD, despite recommendations to report specific intervals. Worryingly, definitions of symptom onset, the most elusive component of PHD to establish, are uncommon. We recommend that researchers 1) report two PHD delay intervals (onset to decision to seek care, and decision to seek care to hospital arrival), and 2) develop, validate and use a definition of symptom onset. This will increase clarity and confidence in conclusions and comparisons within and between studies.
    European Journal of Cardiovascular Nursing 02/2014; · 1.83 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Background:Patients' treatment-seeking delay remains a significant barrier to timely initiation of reperfusion therapy. Measurement of treatment-seeking delay is central to the large body of research that has focused on pre-hospital delay (PHD), which is primarily patient-related. This research has aimed to quantify PHD and its effects on morbidity and mortality, identify contributing factors, and evaluate interventions to reduce such delay. A definite time of symptom onset in acute coronary syndrome (ACS) is essential for determining delay, but difficult to establish. This literature review aimed to explore the variety of operational definitions of both PHD and symptom onset in published research.Methods and results:We reviewed the English-language literature from 1998-2013 for operational definitions of PHD and symptom onset. Of 626 papers of possible interest, 175 were deemed relevant. Ninety-seven percent reported a delay time and 84% provided an operational definition of PHD. Three definitions predominated: (a) symptom onset to decision to seek help (18%); (b) symptom onset to hospital arrival (67%), (c) total delay, incorporating two or more intervals (11%). Of those that measured delay, 8% provided a definition of which symptoms triggered the start of timing.Conclusion:We found few and variable operational definitions of PHD, despite American College of Cardiology/American Heart Association recommendations to report specific intervals. Worryingly, definitions of symptom onset, the most elusive component of PHD to establish, are uncommon. We recommend that researchers (a) report two PHD delay intervals (onset to decision to seek care, and decision to seek care to hospital arrival), and (b) develop, validate and use a definition of symptom onset. This will increase clarity and confidence in the conclusions from, and comparisons within and between studies.
    European Journal of Cardiovascular Nursing 02/2014; DOI:10.1177/1474515114524866 · 1.83 Impact Factor