Socioeconomic Status Factors Associated with Increased Incidence of Community-AssociatedClostridium difficileInfection

作     者：Skrobarcek, Kimberly Mu, Yi Winston, Lisa G Brousseau, Geoff Lyons, Carol Farley, Monica Perlmutter, Rebecca Holzbauer, Stacy Phipps, Erin C Dumyati, Ghinwa Beldavs, Zintars G Kainer, Marion Guh, Alice 

作者机构：Division of Healthcare Quality Promotion Centers for Disease Control and Prevention Atlanta Georgia Medicine University of California San Francisco and Zuckerberg San Francisco General Hospital and Trauma Center San Francisco California Colorado Department of Public Health and Environment Denver Colorado Yale School of Public Health Connecticut Emerging Infections Program New Haven Connecticut Department of Medicine Emory University School of Medicine and Atlanta VA Medical Center Atlanta Georgia Maryland Department of Health and Mental Hygiene Baltimore MD Minnesota Department of Health St. Paul Minnesota University of New Mexico New Mexico Emerging Infections Program Albuquerque New Mexico New York Emerging Infections Program at the University of Rochester Medical Center Rochester New York Oregon Health Authority Portland Oregon Tennessee Department of Health Nashville Tennessee 

出 版 物：《Open Forum Infectious Diseases》 

年 卷 期：2017年第4卷第SUPPL_1期

页      面：S381–S381页

摘      要：Background Traditionally a hospital-acquired pathogen, Clostridium difficile is increasingly recognized as an important cause of diarrhea in community settings. Health disparities in C. difficile infection (CDI) have been reported, but little is known about the social determinants of health that influence community-associated (CA) CDI incidence. We sought to identify socioeconomic status (SES) factors associated with increased CA-CDI incidence. Methods Population-based CDI surveillance is conducted in 35 U.S. counties through the Centers for Disease Control and Prevention’s Emerging Infections Program. A CA-CDI case is defined as a positive C. difficile stool specimen collected as an outpatient or within three days of hospitalization in a person aged ≥ 1 year who did not have a positive test in the prior 8 weeks or an overnight stay in a healthcare facility in the prior 12 weeks. ArcGIS software was used to geocode 2014–2015 CA-CDI case addresses to a 2010 census tract (CT). Incidence rate was calculated using 2010 Census population denominators. CT-level SES factors were obtained from the 2011–2015 American Community Survey 5-year estimates and divided into deciles. To account for CT-level clustering effects, separate generalized linear mixed models with negative binomial distribution were used to evaluate the association between each SES factor and CA-CDI incidence, adjusted by age, sex and race. Results Of 9686 CA-CDI cases, 9417 (97%) had addresses geocoded to a CT; of these, 62% were female, 82% were white, and 35% were aged ≥65 years. Annual CA-CDI incidence was 42.9 per 100,000 persons. After adjusting for age, sex and race, CT-level SES factors significantly associated with increased CA-CDI incidence included living under the poverty level (rate ratio [RR] 1.12; 95% confidence interval [CI] 1.09–1.53), crowding in homes (RR 1.11; 95% CI 1.01–1.21), low education (RR 1.11; 95% CI 1.07–1.15), low income (RR 1.15; 95% CI 1.12–1.17), having public health insuran