METHODS: This secondary cross-sectional analysis used data from a door-to-door survey of 2,196 residents in a low-income, urban, and African-American community. The measures of social integration included 1) frequency of church attendance and 2) duration of residence in that community. Health care seeking measures were 1) Pap smear, 2) mammogram and, 3) dental visit all within 2 years, and 4) blood pressure measurement within 1 year, 5) having a regular source of care, and 6) not seeking care when needed. In multivariate analyses, we controlled for socioeconomic factors (age, gender, education, employment, marital status, and health insurance) and number of chronic diseases. Interactions were examined between measures of social integration and other covariates. RESULTS: The study population had a mean age of 44 years, 37% male, 63% completed high school, 21% married, 74% had health insurance, and 25% had > =2 chronic diseases. Eight hundred and eighteen (37%) went to church at least once a month and 1116 (51%) resided in that community for 10 or more years. In multivariate analyses, regular church attendance increased dental visits (OR heath care seeking behaviors is unclear. The objective of the study was to evaluate the relationship between social integration and positive health care seeking behaviors in a lowincome African-American community. METHODS: This secondary cross-sectional analysis used data from a door-to-door survey of 2,196 residents in a low-income, urban, and African-American community. The measures of social integration included 1) frequency of church attendance and 2) duration of residence in that community. Health care seeking measures were 1) Pap smear, 2) mammogram and, 3) dental visit all within 2 years, and 4) blood pressure measurement within 1 year, 5) having a regular source of care, and 6) not seeking care when needed. In multivariate analyses, we controlled for socioeconomic factors (age, gender, education, employment, marital status, and health insurance) and number of chronic diseases. Interactions were examined between measures of social integration and other covariates. RESULTS: The study population had a mean age of 44 years, 37% male, 63% completed high school, 21% married, 74% had health insurance, and 25% had > = 2 chronic diseases. Eight hundred and eighteen (37%) went to church at least once a month and 1116 (51%) resided in that community for 10 or more years. In multivariate analyses, regular church attendance increased dental visits (OR PURPOSE: Airline passengers are particularly vulnerable to the effects of cardiac arrest due to a lack of access to emergency medical services. To offset this relative isolation, airlines are installing automated external defibrillators (AEDs) on commercial aircraft. Our objective was to measure the cost-effectiveness of airline AED programs and estimate their value to the flying public. METHODS: A decision analytic model was constructed to estimate the clinical and economic effects of airline AEDs. Inputs were obtained from published data and the FAA. Utility estimates were derived from cardiac arrest survivors. The medical event rate was .0004 per flight in the base case; 15% of medical events were cardiac arrest. Of these cardiac arrests, 48% were ventricular fibrillation or tachycardia. Cardiac arrest survival with an AED on-board was 40%, compared to 8% without AED access. The AED cost (including training) was $2.51 per flight. Sensitivity analyses evaluated changes in AED cost, probability of cardiac arrest (and arrest survival), and the likelihood of airplane diversion. Since AEDs may provide utility gains through`p eace of mind'' for passengers not experiencing a medical event, the impact of this added passenger confidence was also evaluated. RESULTS: AEDs on commercial aircraft cost an incremental $5.16 per flight (approximately $.05 per passenger). AED deployment resulted in an estimated additional $162,000 per QALY gained (16 quality-adjusted minutes per flight). Sensitivity analysis of event probabilities and cost inputs did not substantially change the results. However, the cost effectiveness of AEDs was significantly enhanced by the inclusion of utility gain experienced by passengers from increased peace of mind. While the magnitude of this benefit is unknown, an incremental increase of .003 in utility over the flight duration would reduce the incremental cost-effectiveness of AEDs to less than $50,000 per QALY gained. CONCLUSION: Our model estimated that when the benefits of on-board AEDs are limited to patients experiencing a medical event, the incremental cost-effectiveness is inferior to most recommended medical interventions. However, if passengers gain utility from knowing an AED is on the aircraft, then these incremental expenditures may be justified. Utility gains from``peace of mind'' may have significant implications in determining the value of health care interventions. Thus, further research should be conducted into this potentially important area.