Eastes Kaytlin, Oyungu Eren, Jerop Carolyne, Ombitsa Ananda Roselyne, Kigen Barnabas, McHenry Megan S
Center for Global Health Equity, Indiana University, Indianapolis, IN, USA.
Department of Medical Physiology, Moi University School of Medicine, Eldoret, Kenya.
SAGE Open Med. 2024 Jun 12;12:20503121241258849. doi: 10.1177/20503121241258849. eCollection 2024.
Existing estimates of rates of childhood disability in Kenya are based on data with important limitations. Individual-level data on childhood disability at the local level is also lacking, leaving critical knowledge gaps for clinical and programmatic development.
We aimed to estimate the rates of children at-risk for disability, examine the external factors related to risk of childhood disability, and gain a better understanding of the challenges experienced by children at-risk for disabilities and their families within western Kenya.
We conducted a small, cross-sectional randomized community survey to assess the rates of childhood disability across six administrative locations in Uasin Gishu County, Kenya, and to understand the experiences of these children and their caretakers.
Rate of childhood disability in Uasin Gishu county was estimated to be 5%, with the most common disabilities being mood disorders. Caretakers reported several barriers to accessing treatment for their children at-risk of having disabilities, including financial concerns and lack of transportation.
Our findings suggest a need for improved access to care in this region, including addressing significant barriers to accessing care such as stigma and socioeconomic challenges. These community-level data will inform the development of future infrastructure and programming for this population.
肯尼亚现有的儿童残疾率估计是基于存在重要局限性的数据。地方层面关于儿童残疾的个体层面数据也很缺乏,这在临床和项目发展方面留下了关键的知识空白。
我们旨在估计有残疾风险的儿童比例,研究与儿童残疾风险相关的外部因素,并更好地了解肯尼亚西部有残疾风险的儿童及其家庭所面临的挑战。
我们开展了一项小型横断面随机社区调查,以评估肯尼亚乌阿辛吉舒县六个行政区的儿童残疾率,并了解这些儿童及其照料者的经历。
据估计,乌阿辛吉舒县的儿童残疾率为5%,最常见的残疾类型是情绪障碍。照料者报告称,他们为有残疾风险的孩子寻求治疗时面临诸多障碍,包括经济担忧和交通不便。
我们的研究结果表明,该地区需要改善医疗服务的可及性,包括消除诸如耻辱感和社会经济挑战等获取医疗服务的重大障碍。这些社区层面的数据将为该人群未来的基础设施建设和项目规划提供参考。