Mekonnen Fenta Haile, Lakew Workie Demeke, Tesfaye Zike Dereje, Swain Prafulla Kumar
Department of Statistics, College of Science, Bahir Dar University, Bahir Dar- Ethiopia.
Department of Statistics, Utkal University, Bhubaneswar-751004, India.
Afr Health Sci. 2019 Sep;19(3):2555-2564. doi: 10.4314/ahs.v19i3.31.
Chronic non-communicable diseases:- such as epilepsy, are increasingly recognized as public health problems in developing and African countries. This study aimed at finding determinants of the number of epileptic seizure attacks using different count data modeling techniques.
Four common fixed-effects Poisson family models were reviewed to analyze the count data with a high proportion of zeros in longitudinal outcome, i.e., the number of seizure attacks in epilepsy patients. This is because, in addition to the problem of extra zeros, the correlation between measurements upon the same patient at different occasions needs to be taken into consideration.
The investigation remarkably identified some important factors associated with epileptic seizure attacks. As people grow old, the number of seizure attacks increased and male patients had more seizures than their female counterparts. In general, a patient's age, sex, monthly income, family history of epilepsy andservice satisfaction were some of the significant factors responsible for the frequency of seizure attacks (P value<0.05).
This study suggests that zero-inflated negative binomial is the best model for predicting and describing the number of seizure attacks as well as identifying the potential risk factors. Addressing these risk factors will definitely contain the progression of seizure attack.
慢性非传染性疾病，如癫痫，在发展中国家和非洲国家日益被视为公共卫生问题。本研究旨在使用不同的计数数据建模技术找出癫痫发作次数的决定因素。
回顾了四种常见的固定效应泊松族模型，以分析纵向结果中零值比例较高的计数数据，即癫痫患者的发作次数。这是因为，除了额外零值的问题外，还需要考虑同一患者在不同时间测量值之间的相关性。
该调查显著确定了一些与癫痫发作相关的重要因素。随着年龄增长，发作次数增加，男性患者比女性患者发作更多。一般来说，患者的年龄、性别、月收入、癫痫家族史和服务满意度是导致发作频率的一些重要因素（P值<0.05）。
本研究表明，零膨胀负二项式是预测和描述发作次数以及识别潜在风险因素的最佳模型。解决这些风险因素肯定会遏制发作的进展。
