In this study, we propose a hyper-simplified indicator of health and well-being for data visualization purposes in large datasets and apply it to SHARE survey data, the largest macro survey on health, ageing and retirement for 18 European countries. The indicator is based on four thematic sub-indicators, each focussing on a particular issue, which are obtained from more than twenty mixed variables measured on more than 60,000 respondents; Next, PCA is used to summarize their information in order to find and visualize profiles of “healthy ageing” across Europe. As a result, EU countries are classified in three groups, that segment the database into the least to the most individuals at risk of health and well-being. The methodology we propose is wide enough to be extended to other surveys or disciplines.

在这项研究中，我们为大型数据集中的数据可视化目的，提出了一种超级简化的健康和幸福指标，并将其应用于SHARE调查数据，这是18个欧洲国家最大的有关健康，衰老和退休的宏观调查。该指标基于四个主题子指标，每个子指标着重于一个特定的问题，这些指标是从对60,000多名受访者进行衡量的二十多个混合变量中获得的；接下来，使用PCA汇总他们的信息，以查找和可视化整个欧洲“健康老龄化”的概况。结果，欧盟国家被分为三类，将数据库划分为对健康和福祉风险最大的个人最少。我们建议的方法足够广泛，可以扩展到其他调查或学科。