An institutional based, epidemiological study with cross-sectional design was conducted among 156 teaching and non-teaching staff of Bishop Stuart University from 18^th April-6^th May 2017. Participants were drawn from the three major components of the university staffing i.e., the academic staff, the administration and the non-teaching staff.

Bishop Stuart University had a total of 260 teaching and non-teaching staff by March 2017 according to the Human resource report for the beginning of semester 11 of 2016/2017 academic year. Aware of the target population, Krejcie and Morgan table 1970 [15] for sample sizes was used to determine a representative sample size. Morgan and Krejicie table shows that N represents population size, and n = Sample size: hence from the table N = 260, a corresponding sample size (n) of 156 was extracted and used as the study sample size.

Stratified sampling was used to categories the study population into 3 components i.e. teaching staff, administrative staff, and support staff. Teaching staff members were drawn from all the departments and a total of 85 staffs (teaching Assistants, lecturers, senior lecturers and professors) were by simple random sampling identified. Being a small population, all the administrative staffs (25) in number were incorporated in the study except those on leave. The non-teaching staff included compound working staff, security department staff and drivers, a total of 42 non-teaching staff were randomly selected and incorporated in the study.

In this study, pre-designed and pre-tested, interviewer-administered structured questionnaire with open-ended and closed questions was used. The first part of our study tool focused on respondents’ demographic, socioeconomic, and knowledge while the second part of the tool focused on respondents’ physical body measurements (anthropometry). Three (3) research assistants were trained to administer the questionnaires and take anthropometric measurements. Training was done by the principle investigator for a period of 2 days a laboratory Technician was co-opted on the team to collect and process the collected samples.

Study subjects were interviewed in their work place setting after explaining the academic nature of this research and they were assured that information collected would be kept confidential. Two (2) attempts were made to interview a particular individual if the person could not be accessed the first time or (s)he was suffering from any acute illness on the day of the first visit. Blood pressure was measured on the upper left arm after at least 10 minutes of rest using a mercury sphygmomanometer in millimeters of mercury (mmHg). During the study, individuals with blood pressure level more than or equal to 140/90 mmHg were advised to visit the University Clinic for further treatment.

Weight was measured in kilograms (kg) using calibrated weighing scales with participants lightly clothed. Height was measured in meters using standard height meter by participants standing upright on the height meter, BMI was computed using a Reference Scale BMI: Below 16 = severe malnutrition, 16 - 16.99 = moderate malnutrition, 17 - 18.4 = mild malnutrition, Normal weight = 18.5 - 25, 25 - 29.99 = overweight grade 1.30 - 39.99 = overweight grade 2 (obesity), above 40 = overweight grade 3 (severe obesity).

Random blood sugar sample was drawn from every participant and measured using glucometer strips following the Reference Scale for Normal Random Blood Sugar as equal or less than 200 mg/dl. Any participant without history of diabetes presenting with random blood sugar of >200 mg/dl was identified as having diabetes.

Data were entered, cleaned and edited for inconsistencies in Epi-info version 7. There after a Statistical Package for Social Scientists (SPSS) version 19 was used for analysis. Descriptive and analytical statistics were used to summarize the data. Descriptive statistics involved the use of frequencies, proportions and tables. Analytical statistics through bivariate analysis and multivariate logistic regression were performed to identify factors associated with the occurrence of hypertension, overweight and obesity. The chi square test was used in determining statistically significant associations while factors with p-values < 0.05 were included in the logistic regression model. Adjusted odds ratios (AORs) were determined with 95% confidence interval (CI) to identify independent factors.

Guidance to do research was sought from the Institutional Review Committee that reviewed all the protocols. Informed consent was sought from the respondents before taking their blood pressure, weight, height and getting blood samples from them. Respondents consented to the data collection process. Standard Operating Procedures (SOPs) for checking blood pressure, Weight, Height, blood sugar were considered.

Comparatively, the prevalence of hypertension in the current study is lower than the prevalence of hypertension (26.1%) observed in west Bengal rural community in 2017 [16] . Similarly, recent studies conducted in south western Nigeria also reported a slightly higher prevalence of (31.6%) [17] , 20.8% [18] and 26.4%, similar higher prevalence of hypertension 28.3% [19] was reported in Ethiopia

and 32% in Ghana [20] . Although these studies were done in the general community while ours was done in a university setting, this may not fully explain why there is such a big difference. The observed difference could be due to the fact that three quarters (76.1%) of our study subjects were under forty five years of age. Several studies including ours have demonstrated a rising trend in hypertension affecting adults [21] [22] . Specifically, our study demonstrated a statistically significant relationship between those aged more than 40 years and having hypertension (X² = 5.82, P = 0.015, OR = 4.2). A noted clear sharp contrast to our study findings however, is that observed from Kulandaivelan, (2015) where the overall prevalence of Hypertension among the university employees in India was found to be 37%. [22] , probablythe difference in life styles could explain the sharp difference. According to WHO (2005) [23] , the risk of hypertension is usually higher in the obese and overweight. In this study 32% were overweight (BMI 25 < 30 kg/m² while 28.2% were obese BMI > 30 kg/m². In general, n = 94 (60.2%) a proportion of 0.6 was at risk of developing hypertension and according to WHO 2005 report, this rate is higher than that of USA (50%/0.5 proportion) and Australia 37%/0.37. Whereas this appears to be an alarming risk among university staff to developing hypertension in a rural a setting, this finding concurs with recent global estimated rates of obesity [24] that has tripled in the developing countries as a result of people adopting a western lifestyle that involve decreased physical activity and overconsumption of cheap energy-dense foods. In our study only 48.7% of the University staff were practicing daily exercises to prevent hypertension.

This study established the prevalence of diabetes among university staff as 16.1%, this finding is not much different from 15% prevalence in Nepal among people aged 20 years and above according to Nepal Diabetes Association (NDA) [25] . In contrast however, cross-sectional studies previously done around towns close to Kampala city showed a low prevalence of 8.1% [26] and 9% from studies on foot hills of Rwenzori Mountains in western Uganda [13] . These differences could be as a result of heterogeneity of diabetes across population structures and difference in life styles given the fact that our study focused on the elite group only while the rest were focusing on general population.

Risk factors for Diabetes among the study subjects included, age, sex, obesity, and family History. In this study, lecturers aged 40 years and above were 5.6 times likely to have diabetes compared to those aged less than 40 years (OR = 5.6, X² = 16 , P = 0.0005). The strong association between advancing age and diabetic condition was consistent with other studies [12] [27] . In this study being a male was also statistically associated with diabetes compared to females (OR = 1.86, P = 0.0167 and X² = 1.942).

The overall prevalence of obesity in this study was 28% and overweight at 32.15% (BMI (25 < 30 kg/ m²). This is slightly higher than 25% among Civil Servants in Nepal. In this study 32.7% had practiced physical exercise to prevent future diabetes while majority (67.3%) did not. This finding is in contrast with findings of William K.M (2010) in the Kenyan study where a relatively bigger percent of respondents (72%) had not participated in regular physical exercise. Studies done elsewhere have also demonstrated that physical inactivity is a major risk factor diabetes and Hypertension.