Lifestyle Effects on the Risk of Transmission of COVID-19 in the United States: Evaluation of Market Segmentation Systems.

Esra Ozdenerol,Jacob Seboly

doi:10.3390/ijerph18094826

Abstract

The aim of this study was to associate lifestyle characteristics with COVID-19 infection and mortality rates at the U.S. county level and sequentially map the impact of COVID-19 on different lifestyle segments. We used analysis of variance (ANOVA) statistical testing to determine whether there is any correlation between COVID-19 infection and mortality rates and lifestyles. We used ESRI Tapestry LifeModes data that are collected at the U.S. household level through geodemographic segmentation typically used for marketing purposes to identify consumers’ lifestyles and preferences. According to the ANOVA analysis, a significant association between COVID-19 deaths and LifeModes emerged on 1 April 2020 and was sustained until 30 June 2020. Analysis of means (ANOM) was also performed to determine which LifeModes have incidence rates that are significantly above/below the overall mean incidence rate. We sequentially mapped and graphically illustrated when and where each LifeMode had above/below average risk for COVID-19 infection/death on specific dates. A strong northwest-to-south and northeast-to-south gradient of COVID-19 incidence was identified, facilitating an empirical classification of the United States into several epidemic subregions based on household lifestyle characteristics. Our approach correlating lifestyle characteristics to COVID-19 infection and mortality rate at the U.S. county level provided unique insights into where and when COVID-19 impacted different households. The results suggest that prevention and control policies can be implemented to those specific households exhibiting spatial and temporal pattern of high risk.

Highlights

As the U.S healthcare system moves closer to a value-based approach, there is a constantly growing need for market intelligence that provides healthcare providers, health plan providers, major employers and policy-makers with insights into their constituents and positions them to anticipate their needs and behaviors
This study demonstrates the use of market intelligence tools to identify a population, determine its lifestyle clusters, and estimate their propensity for various diseases
This paper offers a unique spatial and temporal approach proving indispensable for timely and effective ways of analyzing the impact of COVID-19 on American households by their lifestyle characteristics which are summarized as LifeMode groups based on lifestyle and lifestage

Summary

Introduction

As the U.S healthcare system moves closer to a value-based approach, there is a constantly growing need for market intelligence that provides healthcare providers, health plan providers, major employers and policy-makers with insights into their constituents and positions them to anticipate their needs and behaviors. This study demonstrates the use of market intelligence tools (i.e., lifestyle segments, market segmentation, geodemographic segmentation) to identify a population, determine its lifestyle clusters, and estimate their propensity for various diseases. Throughout this paper, we will use the terms lifestyle segments, lifestyle segmentation, market segmentation, and geodemographic segmentation interchangeably, but they convey the same meaning. This paper offers a unique spatial and temporal approach proving indispensable for timely and effective ways of analyzing the impact of COVID-19 on American households by their lifestyle characteristics which are summarized as LifeMode groups based on lifestyle and lifestage. We tested two hypotheses: “Is there a difference in average COVID-19 rate among different

Objectives

Methods

Results

Conclusion