Ageing-fit mobile applications (or ageing-fit mobile apps) are increasingly adopted by ageing people, helping them use mobile apps more conveniently. However, Accessibility issues For agEing people (AFE issues for short) are prevalent in ageingfit apps, significantly impeding their accessibility. Unfortunately, there is an absence of enough attention and in-depth study concerning AFE issues in ageing-fit apps. This paper presents a large-scale, comprehensive empirical study involving 691 realworld AFE issues gathered from 31 popular, commercial mobile ageing-fit mobile apps specifically designed for ageing users. Our study confirms the prevalence and severity of AFE issues in ageing-fit mobile apps. In addition, we found that certain types of AFE issues in aging-fit mobile apps stand out more prominently compared to previous studies conducted on general apps, and there are AFE issues in ageing-fit apps that were not previously recognized as accessibility issues in general apps. Furthermore, existing detectors either overlooked the AFE issues or failed to effectively detect them. Building on the findings, we developed AGEINGDROID, a tool specifically designed for effective AFE issue detection. We evaluated AGEINGDROID with 36 real-world, popular, and commercial ageing-fit apps. The experimental results are encouraging: AGEINGDROID detected 345 previously-unknown AFE issues, of which 333 have been confirmed by ageing people.