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The Effects of Lifestyle on the Risk of Lyme Disease in the United States: Evaluation of Market Segmentation Systems in Prevention and Control Strategies

Author

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  • Esra Ozdenerol

    (Spatial Analysis and Geographic Education Laboratory, Department of Earth Sciences, University of Memphis, Memphis, TN 38152, USA)

  • Rebecca Michelle Bingham-Byrne

    (Spatial Analysis and Geographic Education Laboratory, Department of Earth Sciences, University of Memphis, Memphis, TN 38152, USA)

  • Jacob Daniel Seboly

    (Department of Geosciences, Mississippi State University, Starkville, MS 39762, USA)

Abstract

The aim of this study was to investigate lifestyles at risk of Lyme disease, and to geographically identify target populations/households at risk based on their lifestyle preferences. When coupled with geographically identified patient health information (e.g., incidence, diagnostics), lifestyle data provide a more solid base of information for directing public health objectives in minimizing the risk of Lyme disease and targeting populations with Lyme-disease-associated lifestyles. We used an ESRI Tapestry segmentation system that classifies U.S. neighborhoods into 67 unique segments based on their demographic and socioeconomic characteristics. These 67 segments are grouped within 14 larger “LifeModes” that have commonalities based on lifestyle and life stage. Our dataset contains variables denoting the dominant Tapestry segments within each U.S. county, along with annual Lyme disease incidence rates from 2000 through 2017, and the average incidence over these 18 years. K-means clustering was used to cluster counties based on yearly incidence rates for the years 2000–2017. We used analysis of variance (ANOVA) statistical testing to determine the association between Lyme disease incidence and LifeModes. We further determined that the LifeModes Affluent Estates, Upscale Avenues, GenXurban, and Cozy Country Living were associated with higher Lyme disease risk based on the results of analysis of means (ANOM) and Tukey’s post hoc test, indicating that one of these LifeModes is the LifeMode with the greatest Lyme disease incidence rate. We further conducted trait analysis of the high-risk LifeModes to see which traits were related to higher Lyme disease incidence. Due to the extreme regional nature of Lyme disease incidence, we carried out our national-level analysis at the regional level. Significant differences were detected in incidence rates and LifeModes in individual regions. We mapped Lyme disease incidence with associated LifeModes in the Northeast, Southeast, Midcontinent, Rocky Mountain, and Southwest regions to reflect the location-dependent nature of the relationship between lifestyle and Lyme disease.

Suggested Citation

  • Esra Ozdenerol & Rebecca Michelle Bingham-Byrne & Jacob Daniel Seboly, 2021. "The Effects of Lifestyle on the Risk of Lyme Disease in the United States: Evaluation of Market Segmentation Systems in Prevention and Control Strategies," IJERPH, MDPI, vol. 18(24), pages 1-22, December.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:24:p:12883-:d:696680
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    References listed on IDEAS

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    1. Esra Ozdenerol & Jacob Seboly, 2021. "Lifestyle Effects on the Risk of Transmission of COVID-19 in the United States: Evaluation of Market Segmentation Systems," IJERPH, MDPI, vol. 18(9), pages 1-19, April.
    2. Donohoe, Holly & Pennington-Gray, Lori & Omodior, Oghenekaro, 2015. "Lyme disease: Current issues, implications, and recommendations for tourism management," Tourism Management, Elsevier, vol. 46(C), pages 408-418.
    3. Esra Ozdenerol, 2015. "GIS and Remote Sensing Use in the Exploration of Lyme Disease Epidemiology," IJERPH, MDPI, vol. 12(12), pages 1-22, December.
    4. Schwartz, B.S. & Goldstein, M.D. & Childs, J.E., 1993. "Antibodies to Borrelia burgdorferi and tick salivary gland proteins in New Jersey outdoor workers," American Journal of Public Health, American Public Health Association, vol. 83(12), pages 1746-1748.
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    1. Esra Ozdenerol & Jacob Seboly, 2022. "The Effects of Lifestyle on COVID-19 Vaccine Hesitancy in the United States: An Analysis of Market Segmentation," IJERPH, MDPI, vol. 19(13), pages 1-19, June.

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