Distribution and determinants of unintentional injuries among older adults population in Tamil Nadu, India: a community-based injury prediction model.

Abstract

Background: Unintentional injuries among older adults represent a significant public health challenge, particularly in low-resource settings. This study aimed to estimate the prevalence of unintentional injuries among older adults in Tamil Nadu, identify associated risk factors and develop a prediction model for unintentional injuries.

Methods: A cross-sectional study was conducted among older adults in Tamil Nadu, India, and used probability proportional to size sampling. Data were collected via a semistructured questionnaire. The receiver-operating characteristic curve was created to show the probability of the occurrence of unintentional injuries among older adults.

Results: Among 995 older adults, 13.9% reported having unintentional injuries. Among those injured, about 49% of all injuries were due to falls. The best cut-off point for predicted probability was found to be 0.88 for a sensitivity of 81% and a specificity of 61%, from receiver-operating characteristic curve. The regression analysis showed that fear of falling (4.5 times higher risk), being tribal (3.15 times higher risk), female gender (1.98 times higher risk) and alcohol consumption (1.95 times higher risk) significantly increased chance of unintentional injury.

Conclusions: The study highlighted the critical need to prioritise the prevention of unintentional injuries among older adults, particularly focusing on high-risk populations such as those from low socioeconomic and tribal communities. The use of receiver-operating characteristic curve in this study provides a robust and reliable method for predicting unintentional injuries in older adults in India, offering actionable insights for healthcare professionals and public health planners, if validated in future studies.