Published May 17, 2023 | Version v1
Dataset Open

Assessment of non-communicable diseases screening practices among university lecturers in Ghana – a cross sectional single centre study

Description

Data Collection Tool

Data were collected using structured questionnaires. The questionnaires covered dietary intake, alcohol intake, issues with physical inactivity, and tobacco use. Aside from these four main risk factors of NCDs, the questionnaire also captured the frequency of blood pressure checks, blood pressure outcome anytime it is checked (systolic and diastolic), frequency of general body check-ups, frequency of anthropometric measurement checks (weight and height), an assessment of impressions about the outcome of weight and height checks, an assessment of intended measures to be taken depending on the outcomes of weight and health checked. Again, the general observation of the nature of the job as a lecturer and health status especially the outcome of blood pressure monitoring were also assessed. The questionnaire also captured the socio-demographic status of Lecturers,

 

Data Management

Only the Research Team had access to data. Data was kept confidential. The researchers had planned of disposing data from the storage 5 years after the publication of this research. Collected data was entered and cleaned using Microsoft Excel spread sheet, and then imported into STATA version 14.0 (Stata Corp LP, College Station, Texas, USA) for statistical analysis and results.

 

Data Analysis

Descriptive statistics were used to summarize the characteristics of the study population by employing frequencies and percentages for categorical data. In addition, the degree of relatedness (association) was evaluated using Chi-square (χ2) or Fisher’s exact tests where appropriate with a p ≤0.05 assumed to be statistically significant. Both bivariate and multivariate logistic regression analyses were performed and adjusted for colleges' effect to identify associations among the variables of interest. Variables having significant association in the logistic regression models were set at p≤0.05 with 95% confidence interval (95% CI) for both unadjusted and adjusted odds ratios (OR, AOR).

 

Variables

BP was selected as the dependent variable, and in turn define as Normal: ≤ 120/80 mmHg; Elevated: Systolic between 120-129 and diastolic ≤ 80; Hypertension: Systolic ≥ 130 or diastolic ≥ 80. Then dichotomized into Normal blood pressure: ≤ 120/80 mmHg and high blood pressure (Hypertension): ≥ 130/90 mmHg for logistic regression analyses. Independent variables were socio-demographics; gender, age, marital status, staff rank, and lecturer’s colleges (categorized into binary variables; Colleges, family history of NCDs, and health check status. In this study, the variable “very often” denotes (doing the activity in question more than 4 times a month), “often” denotes (doing the activity in question at least twice a month), and “not often” denotes (doing the activity in question once a month).

 

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Data_Predictors of Non-communicable Diseases among University Lecturers.csv

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Additional details

References

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