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Stratified Diabetes Mellitus Prevalence for the Northwestern Nigerian States, a Data Mining Approach

Author

Listed:
  • Musa Uba Muhammad

    (Department of Information sciences and Technology, Yanshan University, Qinhuangdao 066000, China)

  • Ren Jiadong

    (Department of Information sciences and Technology, Yanshan University, Qinhuangdao 066000, China)

  • Noman Sohail Muhammad

    (Department of Information sciences and Technology, Yanshan University, Qinhuangdao 066000, China)

  • Bilal Nawaz

    (State Key Laboratory of Metastable Materials Science and Technology, Yanshan University, Qinhuangdao 066004, China)

Abstract

An accurate classification for diabetes mellitus (DBM) allows for the adequate treatment and handling of its menace, particularly in developing countries like Nigeria. This study proposes data mining techniques for the classification and identification of the prevalence of diagnosed diabetes cases, stratified by age, gender, diabetic conditions and residential area in the northwestern states of Nigeria, based on the real-life data derived from government-owned hospitals in the region. A K-mean assessment was used to cluster the instances, after 12 iterations the instances classified out of 3022: 2662 (88.09%) non-insulin dependent (NID), 176 (5.82%) insulin-dependent (IND) and 184 (6.09%) gestational diabetes (GTD). The total number of diagnosed diabetes cases was 3022: 1380 males (45.66%) and 1642 females (54.33%). The higher prevalence was found to be in females compared to males, and in cities and towns, rather than in villages (36.5%, 34.2%, and 29.3%, respectively). The highest prevalence among the age groups was in the age group 50–69 years, which constituted 43.9% of the total diagnosed cases. Furthermore, the NID condition had the highest prevalence of cases (88.09%). These were the first findings of the stratified prevalence in the region, and the figures have been of utmost significance to the healthcare authorities, policymakers, clinicians, and non-governmental organizations for the proper planning and management of diabetes mellitus.

Suggested Citation

  • Musa Uba Muhammad & Ren Jiadong & Noman Sohail Muhammad & Bilal Nawaz, 2019. "Stratified Diabetes Mellitus Prevalence for the Northwestern Nigerian States, a Data Mining Approach," IJERPH, MDPI, vol. 16(21), pages 1-11, October.
    • Handle: RePEc:gam:jijerp:v:16:y:2019:i:21:p:4089-:d:279701
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    References listed on IDEAS

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    1. Muhammad Noman Sohail & Jiadong Ren & Musa Uba Muhammad, 2019. "A Euclidean Group Assessment on Semi-Supervised Clustering for Healthcare Clinical Implications Based on Real-Life Data," IJERPH, MDPI, vol. 16(9), pages 1-12, May.
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    Cited by:

    1. Sohail M. Noman & Jehangir Arshad & Muhammad Zeeshan & Ateeq Ur Rehman & Amir Haider & Shahzada Khurram & Omar Cheikhrouhou & Habib Hamam & Muhammad Shafiq, 2021. "An Empirical Study on Diabetes Depression over Distress Evaluation Using Diagnosis Statistical Manual and Chi-Square Method," IJERPH, MDPI, vol. 18(7), pages 1-11, April.

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