Predicting type 2 diabetes mellitus among fishermen in Cape Coast: a comparison between the FINDRISC score and the metabolic syndrome

Richard K D Ephraim; Victor Boachie Owusu; Jephthah Asiamah; Arnold Mills; Albert Abaka-Yawson; Godsway Edem Kpene; Precious Kwablah Kwadzokpui; Samuel Adusei

doi:10.1007/s40200-020-00650-w

Predicting type 2 diabetes mellitus among fishermen in Cape Coast: a comparison between the FINDRISC score and the metabolic syndrome

J Diabetes Metab Disord. 2020 Oct 8;19(2):1317-1324. doi: 10.1007/s40200-020-00650-w. eCollection 2020 Dec.

Authors

Richard K D Ephraim¹, Victor Boachie Owusu¹, Jephthah Asiamah¹, Arnold Mills¹, Albert Abaka-Yawson², Godsway Edem Kpene², Precious Kwablah Kwadzokpui², Samuel Adusei³

Affiliations

¹ Department of Medical Laboratory Science, School of Allied Health Sciences, University of Cape Coast, Cape Coast, Ghana.
² Department of Medical Laboratory Science, School of Allied Health Sciences, University of Health and Allied Sciences, PMB 31, Ho, Ghana.
³ Department of Obstetrics and Gynaecology, University of Cape Town, Cape Town, South Africa.

Abstract

Background: Studies over the past decades have observed a sharp rise in the prevalence and incidence of type 2 diabetes mellitus (T2DM). A highly sensitive and specific predictive tool for risky populations is essential. This study assessed two significant diabetes mellitus predictive tools for effectiveness and accuracy among people living in fishing communities in Cape Coast, Ghana.

Method: In April 2019, we recruited one hundred and thirty-five (135) fishermen from three fishing communities in Cape Coast in the Central Region of Ghana. Each participant underwent a standard metabolic procedure including clinical examination as well as taking of anthropometric variables such as weight, height, waist and hip circumference were also measured. The FINDRISC questionnaire was used to gather data from the respective participants. Serum glucose and lipids were estimated with enzymatic techniques, and metabolic syndrome (MetS) screened with the international diabetes federation (IDF) criteria.

Results: Of the 135 participants, 71 (52.6%) were women. The average age of study participants was 52 ± 16 years with females averagely older (56.6 ± 15.0) than the males (47.3 ± 15.0). This study recorded 31.1% and 8.9% prediabetic and diabetic fishermen respectively. Frequency of both prediabetes and diabetes was significantly predominant among females (71.4% vs 83.3%) than males (26.2% vs 25.0%) (p < 0.001) respectively. Prevalence of MetS according to the IDF criteria was 18.5%, significantly higher among females (92.0%) than recorded among the males (18.5%). The discriminatory accuracy of FINDRISC [aROC = 0.76 (95% CI 0.68 to 0.83); sensitivity = 58.3% and specificity = 86.9%; p = 0.003; optimal cut-off point = 13.50] and the MetS [aROC = 0.74 (95% CI 0.66 to 0.81); sensitivity = 75.0% and specificity = 71.5%; p = 0.002] despite demonstrating a significantly good capacity to detect T2DM were statistically comparable [aROC = 0.018 (95% CI -0.152 to 0.189); p = 0.834] in our study.

Conclusion: Our findings indicate that both FINDRISC (with a suitable cut-off value of 13.5) and MetS screening tools possess a good predictive capacity for the detection of T2DM. Additionally, FINDRISC can be employed to detect MetS in a high-risk population.

Keywords: Diabetes; FINDRISC; Fishing communities; Metabolic syndrome.