Geographic Variation in Heart Failure Mortality and Its Association With Hypertension, Diabetes, and Behavioral-Related Risk Factors in 1,723 Counties of the United States.

Longjian Liu,Xiaoyan Yin,Albert Hofman,Ming Chen,Howard J Eisen,Hong Jia

doi:10.3389/fpubh.2018.00132

Abstract

Studies that examined geographic variation in heart failure (HF) and its association with risk factors at county and state levels were limited. This study aimed to test a hypothesis that HF mortality is disproportionately distributed across the United States, and this variation is significantly associated with the county- and state-level prevalence of high blood pressure (HBP), diabetes, obesity and physical inactivity. Data from 1,723 counties in 51 states (including District of Columbia as a state) on the age-adjusted prevalence of obesity, physical inactivity, HBP and diabetes in 2010, and age-adjusted HF mortality in 2013-2015 are examined. Geographic variations in risk factors and HF mortality are analyzed using spatial autocorrelation analysis and mapped using Geographic Information System techniques. The associations between county-level HF mortality and risk factors (level 1) are examined using multilevel hierarchical regression models, taking into consideration of their variations accounted for by states (level 2). There are significant variations in HF mortality, ranging from the lowest 11.7 (the state of Vermont) to highest 85.0 (Mississippi) per 100,000 population among the 51 states. Age-adjusted prevalence of obesity, physical inactivity, HBP, and diabetes are positively and significantly associated with HF mortality. Multilevel analysis indicates that county-level HF mortality rates remain significantly associated with diabetes (β = 2.7, 95% CI: 1.7-3.7, p < 0.0001), HBP (β = 3.6, 2.1-5.0, p < 0.0001), obesity (β = 0.9, 0.6-1.3, p < 0.0001), and physical inactivity (β = 1.2, 0.8-1.5, p < 0.0001) after controlling for gender, race/ethnicity, and poverty index. After further controlling obesity and physical inactivity in diabetes and HBP models, the effects of diabetes (β = 1.0, -0.3 to 2.3, p = 0.12) and HBP (β = 2.4, 0.9-3.9, p = 0.003) on HF mortality had a considerable reduction. HF mortality disproportionately affects the counties and states across the nation. The geographic variations in HF morality are significantly explained by the variations in the prevalence of obesity, physical inactivity, diabetes, and HBP.

Highlights

Heart failure (HF), one of the major forms of cardiovascular diseases, is a complex clinical syndrome that results in the impairment of heart’s ability to fill or to pump out blood [1, 2]
This study aimed to test a hypothesis that HF mortality is disproportionately distributed across the United States, and this variation is significantly associated with the countyand state-level prevalence of high blood pressure (HBP), diabetes, obesity and physical inactivity
On the basis of a temporal causal-effect association between exposures and outcomes, we examined the association for risk factors that were measured in 2010, and outcomes (i.e., HF mortality) that were measured in 2013–2015

Summary

Introduction

Heart failure (HF), one of the major forms of cardiovascular diseases, is a complex clinical syndrome that results in the impairment of heart’s ability to fill or to pump out blood [1, 2]. We aimed to test a hypothesis that a significant geographic disparity in HF mortality exists across the nation, and this geographic disparity is significantly associated with four preventable behavior- and disease-related risk factors. To test this hypothesis, we used data from three nationally representative data sources to examine the geographic variations in HF mortality and to examine the associations between the risk of HF mortality and the prevalence of obesity, physical inactivity, diabetes and HBP at the county- and state levels. This study aimed to test a hypothesis that HF mortality is disproportionately distributed across the United States, and this variation is significantly associated with the countyand state-level prevalence of high blood pressure (HBP), diabetes, obesity and physical inactivity

Objectives

Methods

Results

Conclusion