Heart failure beliefs and self-care adherence while being treated in an emergency department.

BACKGROUND: Heart failure (HF) emergency department (ED) visits are commonly due to HF self-care nonadherence. OBJECTIVE: Our objective was to assess the accuracy of HF beliefs and adherence to self care in patients using an ED for acute HF. METHODS: A cross-sectional, correlational study using validated surveys of HF beliefs and self-care adherence was conducted. A multivariable regression model was used to control for significant baseline factors. RESULTS: In 195 adults, mean HF beliefs score was 2.8 ± 0.3, significantly below the accurate cutoff score of 3.0 (p < 0.001). Mean HF self-care adherence score was 5.1 (10 reflects best adherence). Of HF-related self-care behaviors, adherence was highest for taking medications without skipping or missing doses (7.8 ± 3.3) and lowest for daily weight monitoring (3.5 ± 3.5). Higher accuracy in HF beliefs was associated with higher education level (p = 0.01), younger age (p < 0.001), and choosing low-sodium restaurant foods (p = 0.04), but not with adherence to other self-care behaviors. Self-care adherence was associated with the belief that the HF care plan must be followed forever (p = 0.04), but not with other HF beliefs; and there was a trend toward lower HF self-care adherence when HF belief scores were more accurate. After controlling for significant baseline factors, HF beliefs were not associated with self-care adherence (p = 0.15). CONCLUSIONS: Patients seeking ED care for decompensated HF had inaccurate HF beliefs and poor self-care adherence. Lack of association between HF beliefs and self care (and trend of an inverse relationship) reflects a need for predischarge HF education, including an explanation of what HF means and how it can be better controlled through self-care behaviors.

Statistical methods for linking health, exposure, and hazards.

The Environmental Public Health Tracking Network (EPHTN) proposes to link environmental hazards and exposures to health outcomes. Statistical methods used in case-control and cohort studies to link health outcomes to individual exposure estimates are well developed. However, reliable exposure estimates for many contaminants are not available at the individual level. In these cases, exposure/hazard data are often aggregated over a geographic area, and ecologic models are used to relate health outcome and exposure/hazard. Ecologic models are not without limitations in interpretation. EPHTN data are characteristic of much information currently being collected--they are multivariate, with many predictors and response variables, often aggregated over geographic regions (small and large) and correlated in space and/or time. The methods to model trends in space and time, handle correlation structures in the data, estimate effects, test hypotheses, and predict future outcomes are relatively new and without extensive application in environmental public health. In this article we outline a tiered approach to data analysis for EPHTN and review the use of standard methods for relating exposure/hazards, disease mapping and clustering techniques, Bayesian approaches, Markov chain Monte Carlo methods for estimation of posterior parameters, and geostatistical methods. The advantages and limitations of these methods are discussed.