The Bone Mineral Density and Vitamin D Status in Children With Moderate to Severe Cerebral Palsy in Kenyatta National Hospital and St Theresa Mission Hospital

Abstract

Cerebral palsy is a common disorder among children with disabilities globally. The local burden is estimated to be 1 in every 300 children. Children with Gross Motor Classification System (GMFCS) III-V are usually immobile and are at high risk of developing low Bone Mineral Density (BMD) and low vitamin D levels. This leads to reduced bone strength and an increase in fracture risk. The life expectancy of children has improved due to advancements in medical care. It is therefore expected that there will be a rise in fracture incidence. There is scarce literature on bone quality in children with cerebral palsy in Kenya. Interventions such as timely supplementation of vitamin D has been found to reduce incidence of fractures. It is therefore important to have an updated baseline data on the level of Vitamin D and BMD in children with moderate to severe cerebral palsy in Kenya. Study Objective: To determine the bone mineral density and vitamin D status of children with moderate to severe cerebral palsy in Kenyatta National Hospital and St Theresa Mission Hospital. study design: descriptive cross-sectional study Study site: Kenyatta National Hospital and St Theresa Mission Hospital, Kiirua. Methodology: 70 patients met the criteria using convenience sampling. A standard questionnaire was used to enter the demographical data, GMFCS level and drug use. A venous non- fasting sample was drawn for analysis of Vitamin D and a calcaneal quantitative ultrasound used to assess bone mineral density. The interpretation of the bone mineral density findings was done according to the International Society of Clinical Densitometry in 2013 and Vitamin D according to the American Academy of paediatricians. Data processing: The collected data was analysed using the Statistical Package for the Social Sciences version 25. RESULTS: Analysis of non- parametric data was done using spearman’s rank. The significant demographic variables was analysed using multiple logistic regression models. Data variables were presented in frequencies and analysed using the chi- squared test and Fischer’s exact test.........................................................................