Geographic, racial/ethnic, and socioeconomic inequities in broadband access

Abstract

Introduction: Broadband access is a "super determinant of health." Understanding the spatial distribution and predictors of access may help target government programs and telehealth applications. Our aim was to examine broadband access across geography and sociodemographic characteristics using American Community Survey (ACS) data.

Methods: We used 5-year ACS estimates from 2014 to 2018 to evaluate broadband access across contiguous US census tracts. Rural-Urban Commuting Area (RUCA) codes were categorized as metropolitan, micropolitan, small town, and isolated rural. We performed bivariate analyses to determine differences by RUCA categories and meeting the Healthy People 2020 (HP2020) objective (83.2% broadband access) or not. We conducted spatial statistics and spatial regression analyses to identify clusters of broadband access and sociodemographic factors associated with broadband access.

Results: No RUCA grouping met the HP2020 objective; 80.6% of households had broadband access, including 82.0% of metropolitan, 73.9% of micropolitan, 70.7% of small town, and 70.0% of isolated rural households. Areas with high percentages of Black residents had lower broadband access, particularly in isolated rural tracts (54.9%). Low access was spatially clustered in the Southeast, Southwest, and northern plains. In spatial regression models, poverty and education were most strongly associated with broadband access, while the proportion of American Indian/Alaska Native population was the strongest racial/ethnic factor.

Conclusions: Rural areas had less broadband access with the greatest disparities experienced among geographically isolated areas with larger Black and American Indian/Alaska Native populations, more poverty, and lower educational attainment, following well-known social gradients in health. Resources and initiatives should target these areas of greatest need.

Keywords: COVID-19 pandemic; broadband access; rural health; spatial regression; telehealth.