Kontaris Emily, Wakeling Ian, Brooker Helen, Corbett Anne, Ballard Clive, Aarsland Dag, Churchill Anne
Health and Well-being Centre of Excellence, Givaudan UK Limited, Ashford, United Kingdom.
Qi Statistics Limited, West Malling, United Kingdom.
Front Public Health. 2025 Jul 18;13:1528952. doi: 10.3389/fpubh.2025.1528952. eCollection 2025.
The proportion of older people in the world is increasing and evidence suggests that older adults interact differently with products. Understanding this change is necessary to develop products that satisfy this cohort's needs. Chronological age is typically used to segment older consumers however, given the diversity of ageing, a multi-dimensional approach considering other factors contributing to this behavior change is important. Using data from the PROTECT study in the UK, this research aimed to identify clusters of older people with distinct characteristics and investigate whether chronological age was fundamental in defining these groups.
Twelve variables, covering measures related to physical capabilities, mental health and lifestyle choices, were derived from the baseline questionnaire data from the PROTECT study and subjected to a k-means cluster analysis. Subsequent analyses investigated the association between participants' cluster membership and other key variables.
Cluster analysis identified 8 unique clusters of older adults differentiated on factors such as physical health (physical activity, pain, BMI and sleep quality), mental health (cognitive decline, depression and anxiety) and lifestyle (social events, puzzle and technology use and vitamin intake). Age was considered to be an important contributory factor to some clusters however did not explain all differences observed between the groups.
Our findings indicate that in addition to chronological age, health and lifestyle variables are important in defining the unique characteristics of different clusters of those in the 50+ cohort. Future research should consider the multi-dimensional nature of ageing when conducting research with older consumers.
世界上老年人的比例正在增加，有证据表明老年人与产品的互动方式有所不同。了解这种变化对于开发满足这一群体需求的产品至关重要。按年龄划分通常用于对老年消费者进行细分，然而，鉴于老龄化的多样性，采用考虑导致这种行为变化的其他因素的多维度方法很重要。本研究利用英国PROTECT研究的数据，旨在识别具有不同特征的老年人群体，并调查按年龄划分在定义这些群体时是否至关重要。
从PROTECT研究的基线问卷数据中得出12个变量，涵盖与身体能力、心理健康和生活方式选择相关的指标，并进行k均值聚类分析。随后的分析调查了参与者的聚类成员身份与其他关键变量之间的关联。
聚类分析确定了8个独特的老年人群体，这些群体在身体健康（身体活动、疼痛、体重指数和睡眠质量）、心理健康（认知能力下降、抑郁和焦虑）和生活方式（社交活动、拼图和技术使用以及维生素摄入）等因素方面存在差异。年龄被认为是某些群体的一个重要促成因素，但并不能解释各群体之间观察到的所有差异。
我们的研究结果表明，除了按年龄划分外，健康和生活方式变量在定义50岁及以上人群中不同群体的独特特征方面也很重要。未来的研究在对老年消费者进行研究时应考虑老龄化的多维度性质。
