Background: Elder abuse is a critical and under-measured global public health issue, with growing concern about changing patterns following the COVID-19 pandemic. Variability in measurement approaches and the absence of standardized global surveillance systems have limited comparability across studies and regions.
Aim: To estimate the global prevalence and subtype distribution of elder abuse across pre-, during-, and post-COVID-19 contexts.
Methods: We conducted a systematic review and random-effects meta-analysis following PRISMA guidelines. Inclusion criteria were cross-sectional studies reporting quantitative overall elder-abuse prevalence with an extractable numerator and denominator within the defined COVID-19 windows. Studies reporting a single abuse subtype only, relative change rather than prevalence, or falling outside the cross-sectional design or time windows were excluded. Nine studies (N = 17,159) from Asia, North America, and Oceania were included; one large Chinese study (Du et al.; N = 10,362) was excluded for reporting relative change. Retrieved European and African records were excluded under the criteria above. Included studies relied predominantly on older-adult self-report and did not stratify by cognitive status.
Results: Pooled prevalence was 19.1% (approximately 1 in 5 older adults), with substantial and statistically significant between-study heterogeneity. Estimates ranged from 10.0% to 75.4%, the upper bound derived from a study using a broad definition and an inclusive self-report instrument capturing psychological abuse and neglect. Psychological abuse, emotional neglect, and financial exploitation were most frequently reported. Higher estimates during or after the pandemic than pre-pandemic reflect measurement and design heterogeneity rather than confirmed temporal causation.
Conclusion: Elder abuse represents a persistent, heterogeneous global burden. Reliance on self-report likely under-captures adults unable to report, including those with dementia. Strengthening surveillance harmonization, standardizing definitions, and incorporating proxy and third-party ascertainment are essential to improving detection and prevention.