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Visualizing Inequality in Health and Socioeconomic Wellbeing in the EU: Findings from the SHARE Survey

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  • Aurea Grané

    (Statistics Department, Universidad Carlos III de Madrid, 28903 Getafe, Spain)

  • Irene Albarrán

    (Statistics Department, Universidad Carlos III de Madrid, 28903 Getafe, Spain)

  • Roger Lumley

    (Statistics Department, Universidad Carlos III de Madrid, 28903 Getafe, Spain)

Abstract

The main objective of this paper is to visualize profiles of older Europeans to better understand differing levels of dependency across Europe. Data comes from wave 6 of the Survey of Health, Ageing and Retirement in Europe (SHARE), carried out in 18 countries and representing over 124 million aged individuals in Europe. Using the information of around 30 mixed-type variables, we design four composite indices of wellbeing for each respondent: self-perception of health, physical health and nutrition, mental agility, and level of dependency. Next, by implementing the k -prototypes clustering algorithm, profiles are created by combining those indices with a collection of socio-economic and demographic variables about the respondents. Five profiles are established that segment the dataset into the least to the most individuals at risk of health and socio-economic wellbeing. The methodology we propose is wide enough to be extended to other surveys or disciplines.

Suggested Citation

  • Aurea Grané & Irene Albarrán & Roger Lumley, 2020. "Visualizing Inequality in Health and Socioeconomic Wellbeing in the EU: Findings from the SHARE Survey," IJERPH, MDPI, vol. 17(21), pages 1-18, October.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:21:p:7747-:d:433508
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    2. Yingxue Wang & Jiaheng Du & Jingxing Kuang & Chunxu Chen & Maobiao Li & Jin Wang, 2023. "Two-Scaled Identification of Landscape Character Types and Areas: A Case Study of the Yunnan–Vietnam Railway (Yunnan Section), China," Sustainability, MDPI, vol. 15(7), pages 1-18, April.

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