DOI: 10.5281/zenodo.7930250
title: Assessment of non-communicable diseases screening practices among university lecturers in Ghana – a cross sectional single centre study

description: This section highlights the various methods used for this study. It covered study setting, study design, study approach, study population, sampling techniques, sample size calculation, inclusion and exclusion criteria, ethical consideration, data collection, data management and data analysis<strong>. </strong> <strong>Study Setting</strong> The study was carried out at Kwame Nkrumah University of Science and Technology (KNUST), Kumasi between February to August, 2022. The study covered all the six (6) Colleges in the University. <strong>Study Design</strong> This was a cross sectional study to ascertain health check practices among university lecturers. <strong>Study Approach</strong> The study employed quantitative approach in which data was collected using questionnaires with both closed- and open-ended questions. <strong>Study Population</strong> The study population involved 838 Lecturers across the six Colleges at Kwame Nkrumah University of Science and Technology (KNUST), Kumasi. A study of the lecturer population per college revealed that Colleges of Health Sciences (highest) and Agric /Natural resources (lowest) were the outliers (Quality Assurance and Planning Office, 2020). <strong>Sampling Technique </strong> Simple probability technique was used to select the name of a college and the day/date to visit. Two sets of papers were folded with names of colleges (set 1) and day/date of visit (set 2). A picker picked one folded paper from each set and the name of the college and the day/date to visit was matched. In this case, the ordering of date and visit gave 1<sup>st</sup> College of Humanities & Social Sciences, 2<sup>nd</sup> College of Agric and Natural Resources, 3<sup>rd</sup> College of Art & Built Environment, 4<sup>th</sup> College of Engineering, 5<sup>th</sup> College of Science and 6<sup>th</sup> College of Health Sciences. We then used the ‘walk in’’ system to select the study participants. Within the days to visit a college, any lecturer we meet in his/ her office was a potential study participant. <strong>Sample Size Calculation</strong> The sample size was obtained using Yamane, 1967 formulae as shown below: Where n= is the population of Lecturers in at KNUST E= is the level of precision Therefore: n= 838 1+838 (0.0025) n = 838 1+ 2.098 838 3.095 n=270 However, due to logistical constrains, 205 participants were contacted across the 6 Colleges at Kwame Nkrumah University of Science and Technology. We then applied simple proportions to get the number of lecturers to be consulted in each college. <strong>Inclusion and Exclusions Criteria</strong> Inclusion criteria was made up of all Lecturers on KNUST campus who are in active service and consented to participate. All other staff not within this category were excluded from this research. <strong>Ethical Considerations</strong> Ethical approval was sought from the CHRPE, KNUST with approval reference no: CHRPE/AP/581/21. The aim of the research was explained to participants. Those who consented to participate in the research were given consent forms to sign and date. Again, participants were assured of confidentiality. Participants were told that, they were free to withdraw from the study in the cause of time. In other words, study participants were not coerced into the study. <strong>Data Collection Tool</strong> Data was collected using structured questionnaires. The questionnaires covered dietary intake, alcohol intake, issues on physical inactivity and tobacco use. Aside these four main risk factors of NCDs, the questionnaire also captured frequency of blood pressure checks, blood pressure outcome anytime it is checked (systolic and diastolic), frequency of general body check-up, 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 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, <strong>Data Management</strong> 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. <strong>Data Analysis</strong> 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 (χ<sup>2</sup>) 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). <strong>Variables</strong> 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 variable; COHS /COS/COE and CABE/CANR/COHSS), 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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