Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Background And Objectives: Prevalence of prediabetes and undiagnosed diabetes are different in rural and urban dwellings, with varying driving factors. This study aimed to determine the differences in risk factors of prediabetes and undiagnosed diabetes among Yoruba speaking adult dwellers in selected rural and urban communities in Nigeria using haemoglobin A1c.
Methods: A cross-sectional study was conducted in five selected states in Southwestern Nigeria. Using a multistage sampling technique, 2,537 participants with no prior diagnosis of prediabetes or diabetes mellitus (DM) were enrolled and their glycated haemoglobin (HbA1c) determined. Descriptive statistics, univariate and multiple logistic regression analysis was used to determine the prevalence and risk factors of prediabetes and diabetes at 5% level of significance.
Results: Increased age, sex, family history of diabetes, being married, participants' history of hypertension, cardiovascular disease and Gestational Diabetes Mellitus (GDM) or delivery of big babies, BMI, systolic and diastolic blood pressure were significantly associated with prediabetes and diabetes in both urban and rural areas. However, adjusted odds ratio showed that family history of diabetes (2.14, 95% CI: 1.26-3.61 versus 1.36, 95% CI: 1.00-1.85) and past GDM among women (2.67, 95% CI: 0.62, 11.39 versus 1.32, 95% CI: 0.61, 2.89) clearly predict dysglycaemia in the rural compared to urban participants, respectively.
Conclusions: Family history of diabetes and past GDM disproportionately predict dysglycaemia in rural compared to urban participants. Periodic screening for dysglycaemia and public health education, especially in child-bearing women, are necessary measures to reduce the burden of dysglycaemia in Nigeria.
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