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ZENODO
Article . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
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A Binary Logistic Regression Model for Assessing the Risk Factors Associated with Diabetes Mellitus among Farmers in Benue State, Nigeria

Authors: Sewuese Abutu, Angela; Adugh Kuhe, David;

A Binary Logistic Regression Model for Assessing the Risk Factors Associated with Diabetes Mellitus among Farmers in Benue State, Nigeria

Abstract

The aim of this study is to assess the predisposing factors of diabetes mellitus among farmers in Benue state, using binary logistic regression model. A convenience sampling technique was employed to collect data from 254 patients attending Federal Medical Centre Makurdi (FMC) through case folder reviews and structured interviews. Statistical analyses included summary statistics, proportions, percentages, and binary logistic regression. The socio-demographic profile of respondents revealed a female predominance (135; 53.1%) in the study area, with the largest age group (87; 34.2%) being 45-54 years and an average age of approximately 53 years with a standard deviation of approximately 13 years (SD ≈ 13). The majority of the respondents had attained secondary education (131; 51.6%), were employed (137; 53.9%), and were married (192; 75.6%). Regarding diabetic status, 224 respondents (88.2%) were diabetic.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average