Browsing by Author "Wesonga, Ronald"
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Item Alcohol consumption, hypertension and obesity: Relationship patterns along different age groups in Uganda(Preventive Medicine Reports, 2020) Mbona Tumwesigye, Nazarius; Mutungi, Gerald; Bahendeka, Silver; Wesonga, Ronald; Katureebe, Agaba; Biribawa, Claire; Guwatudde, DavidThe prevalence of non-communicable diseases including hypertension and obesity is rising and alcohol consumption is a predisposing factor. This study explored the effect of alcohol consumption patterns on the hypertension-age group and obesity-age group relationships. The data were extracted from the 2014 National NCD Survey of adults aged 18–69 years. Hypertension was defined as a condition of having systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg while obesity was defined as having a body mass index ≥30 kg/m2 . Frequent alcohol consumption was measured as alcohol use ≥3 times a week. Multivariable log binomial regression analysis was used to assess independent relationship between the outcomes and alcohol consumption. The prevalences of hypertension, frequent alcohol consumption and obesity increased across age groups but were divergent towards last age group. Hypertension prevalence ratios were higher with higher age groups among moderate and nondrinkers but not among frequent drinkers. Alcohol drinking pattern modified the age hypertension relationship in a model with ungrouped age. The drinking pattern did not modify obesity-age relationship. Alcohol consumption pattern appeared to modify the hypertension-age group relationship. However, more research is needed to explain why prevalence ratios are higher with higher age groups among moderate drinkers and abstainers while they stagnate among the frequent drinkers. There was no evidence to show the effect of alcohol consumption on obesity-age group relationshipItem Alcohol use among adults in Uganda: findings from the countrywide non-communicable diseases risk factor cross-sectional survey(Global Health Action, 2016) Ndugwa Kabwama, Steven; Ndyanabangi, Sheila; Mutungi, Gerald; Wesonga, Ronald; Bahendeka, Silver K.; Guwatudde, DavidThere are limited data on levels of alcohol use in most sub-Saharan African countries. Objective: We analyzed data from Uganda’s non-communicable diseases risk factor survey conducted in 2014, to identify alcohol use prevalence and associated factors. Design: The survey used the World Health Organization STEPS tool to collect data, including the history of alcohol use. Alcohol users were categorized into low-, medium-, and high-end users. Participants were also classified as having an alcohol-use-related disorder if, over the past 12 months, they were unable to stop drinking alcohol once they had started drinking, and/or failed to do what was normally expected of them because of drinking alcohol, and/or needed an alcoholic drink first in the morning to get going after a heavy drinking session the night before. Weighted logistic regression analysis was used to identify factors associated with medium- to high-end alcohol use. Results: Of the 3,956 participants, 1,062 (26.8%) were current alcohol users, including 314 (7.9%) low-end, 246 (6.2%) medium-end, and 502 (12.7%) high-end users. A total of 386 (9.8%) were classified as having an alcohol-use-related disorder. Male participants were more likely to be medium- to high-end alcohol users compared to females; adjusted odds ratio (AOR)2.34 [95% confidence interval (CI)1.882.91]. Compared to residents in eastern Uganda, participants in central and western Uganda were more likely to be mediumto high-end users; AOR1.47 (95% CI1.012.12) and AOR1.89 (95% CI1.312.72), respectively. Participants aged 3049 years and those aged 5069 years were more likely to be medium- to high-end alcohol users, compared to those aged 1829 years, AOR1.49 (95% CI1.161.91) and AOR2.08 (95% CI1.522.84), respectively. Conclusions: The level of alcohol use among adults in Uganda is high, and 9.8% of the adult population has an alcohol-use-related disorder.Item Assessing Aircraft Timeliness Variations By Major Airlines: Passenger Travel Practice In Uganda(International Journal of Sciences: Basic and Applied Research (IJSBAR), 2013) Wesonga, Ronald; Nabugoomu, Fabianb; Masimbi, BrianFlight delays do not only affect passenger satisfaction but also carry along costly consequences to airlines. The overall objective of the study was to assess aircraft timeliness variations by major airlines so as to determine passenger travel practice in Uganda. The study hypotheses were tested using a two-way ANOVA F-test and further measures of associations. The study found out that the number of schedules of each airline per day had a positive effect on the delay duration, whereby an additional schedule increased the average delay by a proportion of 11%. Whereas the day of the week F(16, 1129) = 1.36, p >0.01 had no significant difference in the delays amongst the airlines, the month of the year F(33, 1107) = 1.88, p < 0.001 showed a significant difference. However, the total variance of the delays was attributed to the airline (29%). It was also demonstrated from the analysis that Eagle Air (EA), Kenya Airways (KA) and South African Airways (SAA) experienced more delays than the British Airways (BAW) by 33%, 62% and 55% respectively. Other than Wednesday, flights were delayed more on all the days of the week and less delayed in the months of October and November than in June by 26% and 3% respectively. On Saturdays and Sundays, flights were found to have longer periods of delay (p<0.05) that averaged 14 and 13 minutes respectively. The flights in January and March had longer delays (15 and 14 minutes) than that recorded in the other months. Therefore, it can be concluded that the passengers who use BAW are less likely to delay than the other (EA, KA and SAA) airlines and travelling in the months of October and November is highly recommended. Given that airline delay is positively correlated with the number of scheduled flights, a policy framework could be developed to optimise schedules and airline delays during departure at the airport. The template is used to format your paper and style the text. All margins, column widths, line spaces, and text fonts are prescribed; please do not alter them. The template is used to format your paper and style the text. All margins, column widths, line spaces, and text fonts are prescribed; please do not alter them.Item Associations between environmental covariates and malaria incidence in high transmission settings of Uganda: A distributed non-linear lagged ecological analysis(Research Square, 2021) Okiring, Jaffer; Routledge, Isobel; Esptein, Adrienne; Namuganga, Jane F.; Kamya, Emmanuel V.; Odei Obeng-Amoako, Gloria; Maiteki-Sebuguzi, Catherine; Rutazaana, Damian; Kalyango, Joan N.; Kamya, Moses R.; Dorsey, Grant; Wesonga, Ronald; Kiwuwa, Steven M.; Nankabirwa, Joaniter I.Environmental factors such as temperature, rainfall, and vegetation cover play a critical role in malaria transmission. However, quantifying the relationships between environmental factors and measures of disease burden relevant for public health can be complex as effects are often non-linear and subject to temporal lags between when changes in environmental factors lead to changes in the incidence of symptomatic malaria. The study aim was to investigate the associations between environmental covariates and malaria incidence in high transmission settings of Uganda. Methods This study leveraged data from seven malaria reference centres (MRCs) located in high transmission settings of Uganda over a 24-month period (January 2019 - December 2020). Estimates of monthly malaria incidence (MI) were derived from MRCs’ catchment areas. Environmental data including monthy average measures of temperature, rainfall, and normalized difference vegetation index (NDVI) were obtained from remote sensing sources. A distributed non-linear lagged model was used to investigate the quantitative relationship between environmental covariates and malaria incidence. Results Overall, the median (range) monthly temperature was 30oC (26-47), rainfall 133.0 mm (3.0-247), NDVI 0.66 (0.24-0.80) and MI was 790 per 1000 person-years (73-3973). A non-linear relationship between environmental covariates and malaria incidence was observed. An average monthly temperature of 35oC was associated with significant increases in malaria incidence compared to the median observed temperature (30oC) at month lag 2 (IRR: 2.00, 95% CI: 1.42-2.83) and the cumulative increases in MI significantly at month lags 1-4, with the highest cumulative IRR of 8.16 (95% CI: 3.41-20.26) at lag month 4. An average monthly rainfall of 200mm was associated with significant increases in malaria incidence compared to the median observed rainfall (133mm) at lag month 0 (IRR: 1.24, 95% CI: 1.01-1.52) and the cumulative IRR increases of malaria at month lags 1-4, with the highest cumulative IRR of 1.99(95% CI: 1.22-2.27) at lag month 4. An average NVDI of 0.72 was associated with significant cumulative increases in IRR of malaria as compared to the median observed NDVI (0.66) at month lag 2-4, with the highest cumulative IRR of 1.57(95% CI: 1.09-2.25) at lag month 4. The rate of increase in cumulative IRR of malaria was highest within lag months 1-2 as compared to lag months 3-4 for all the environmental covariates. Conclusions In high-malaria transmission settings, high values of environmental covariates were associated with cumulative increases in the incidence of malaria, with peak associations occurring after variable lag times. The complex associations identified are valuable for designing strategies for early warning, prevention, and control of seasonal malaria surges and epidemics.Item Burden of cumulative risk factors associated with non-communicable diseases among adults in Uganda: evidence from a national baseline survey(International Journal for Equity in Health, 2016) Wesonga, Ronald; Guwatudde, David; Bahendeka, Silver K.; Mutungi, Gerald; Nabugoomu, Fabian; Muwonge, JamesModification of known risk factors has been the most tested strategy for dealing with noncommunicable diseases (NCDs). The cumulative number of NCD risk factors exhibited by an individual depicts a disease burden. However, understanding the risk factors associated with increased NCD burden has been constrained by scarcity of nationally representative data, especially in the developing countries and not well explored in the developed countries as well. Methods: Assessment of key risk factors for NCDs using population data drawn from 3987 participants in a nationally representative baseline survey in Uganda was made. Five key risk factors considered for the indicator variable included: high frequency of tobacco smoking, less than five servings of fruit and vegetables per day, low physical activity levels, high body mass index and raised blood pressure. We developed a composite indicator dependent variable with counts of number of risk factors associated with NCDs per participant. A statistical modeling framework was developed and a multinomial logistic regression model was fitted. The endogenous and exogenous predictors of NCD cumulative risk factors were assessed. Results: A novel model framework for cumulative number of NCD risk factors was developed. Most respondents, 38 · 6% exhibited one or two NCD risk factors each. Of the total sample, 56 · 4% had at least two risk factors whereas only 5.3% showed no risk factor at all. Body mass index, systolic blood pressure, diastolic blood pressure, consumption of fruit and vegetables, age, region, residence, type of residence and land tenure system were statistically significant predictors of number of NCD risk factors (p < 0 · 05). With exception to diastolic blood pressure, increase in age, body mass index, systolic blood pressure and reduction in daily fruit and vegetable servings were found to significantly increase the relative risks of exhibiting cumulative NCD risk factors. Compared to the urban residence status, the relative risk of living in a rural area significantly increased the risk of having 1 or 2 risk factors by a multiple of 1.55.Item Determining Factors that Influence Household Food Insecurity in Uganda: A Case Study of Tororo and Busia Districts(International Journal of Sciences: Basic and Applied Research, 2014) Owino, Abraham Y.; Atuhaire, Leonard K.; Wesonga, Ronald; Nabugoomu, Fabian; Muwanga-Zaake, Elijah S.K.Addressing the national food insecurity problem requires an understanding and measurement of food insecurity at micro-level using a wide range of explanatory variables. Measurement of food insecurity is a challenge because it is a multi-faceted latent and continuous phenomenon explained by many variables. This paper examines these variables and applies exploratory factor analysis to identify variables which significantly influence household food insecurity and how they uniquely associate with specific food insecurity factors. Primary data on food availability, access, utilization and coping strategies were collected from 1175 randomly selected rural households in Tororo and Busia Districts of Uganda. Feasibility of exploratory factor analysis was analyzed using Pearson’s correlation coefficient.Item Determining Food Insecurity: An Application of the Rasch Model with Household Survey Data in Uganda(International journal of food science, 2014) Owino, Abraham; Wesonga, Ronald; Nabugoomu, FabianThe inexplicable nature of food insecurity in parts of Uganda and worldwide necessitated an investigation into the nature, extent, and differentials of household food security.Themain objective of this study was to examine the food security dynamics and model household food insecurity.The Raschmodelling approach was employed on a dataset froma sample of 1175 (Tororo = 577; Busia = 598) randomly selected households in the year 2010. All households provided responses to the food security questions and none was omitted from the analysis. At 5 percent level of significance the analysis indicated that Tororo district average food security assessment (0.137 ± 0.181) was lower than that for Busia district (0.768 ± 0.177). All the mean square fit statistics were in the range of 0.5 to 1.5, and none of them showed any signs of distortion, degradation, or less productivity formeasurement.This confirmed that items used in this study were very productive for measurement of food security in the study area.The study recommends further analysis where item responses are ordered polytomous rather than the dichotomous item response functions used. Furthermore, consideration should be given to fit models that allow for different latent distributions for households with children and those without children and possibly other subgroups of respondents.Item Effectiveness of a nurse-led management intervention on systolic blood pressure among type 2 diabetes patients in Uganda: a cluster randomized trial(BioMed Central Ltd, 2024-05) Lumu, William; Bahendeka, Silver; Kibirige, Davis; Wesonga, Ronald; Mutebi, Ronald KasomaAbstract Hypertension (HT) is an orchestrator of atherosclerotic cardiovascular disease (ASCVD) in people living with type 2 diabetes (T2D). Control of systolic blood pressure (SBP) and HT as a whole is suboptimal in diabetes, partly due to the scarcity of doctors. While nurse-led interventions are pragmatic and cost-effective in the control of HT in primary health care, their effectiveness on SBP control among patients with T2D in Uganda is scantly known. We evaluated the effectiveness of a nurse-led management intervention on SBP among T2D patients with a high ASCVD risk in Uganda. A two-armed cluster randomized controlled trial compared the nurse-led management intervention with usual doctor-led care. The intervention involved training nurses to provide structured health education, protocol-based HT/CVD management, 24-h phone calls, and 2-monthly text messages for 6 months. The primary outcome was the mean difference in SBP change among patients with T2D with a high ASCVD risk in the intervention and control groups after 6 months. The secondary outcome was the absolute difference in the number of patients at target for SBP, total cholesterol (TC), fasting blood glucose (FBG), glycated hemoglobin (HbA1C), low-density lipoprotein (LDL), triglycerides (TG), and body mass index (BMI) after the intervention. The study was analyzed according to the intention-to-treat principle. Generalized estimating equations were used to assess intra-cluster effect modifiers. Statistical significance was set at 0.05 for all analyses. Eight clinics (n = 388 patients) were included (intervention 4 clinics; n = 192; control 4 clinics; n = 196). A nurse-led intervention reduced SBP by -11.21 [+ or -] 16.02 mmHg with a mean difference between the groups of -13.75 mmHg (95% CI -16.48 to -11.02, p < 0.001). An increase in SBP of 2.54 [+ or -] 10.95 mmHg was observed in the control group. Diastolic blood pressure was reduced by -6.80 [+ or -] 9.48 mmHg with a mean difference between groups of -7.20 mmHg (95% C1 -8.87 to -5.48, p < 0.001). The mean differences in the change in ASCVD score and glycated hemoglobin were -4.73% (95% CI -5.95 to -3.51, p = 0.006) and -0.82% (95% CI -1.30 to -0.35, p = 0.001), respectively. There were significant absolute differences in the number of patients at target in SBP (p = 0.001), DBP (p = 0.003), and TC (p = 0.008). A nurse-led management intervention reduces SBP and ASCVD risk among patients with T2D. Such an intervention may be pragmatic in the screening and management of HT/ASCVD in Uganda.Item The Epidemiology of Hypertension in Uganda: Findings from the National Non- Communicable Diseases Risk Factor Survey(PLoS ONE, 2015) Guwatudde, David; Mutungi, Gerald; Wesonga, Ronald; Kajjura, Richard; Kasule, Hafisa; Muwonge, James; Ssenono, Vincent; Bahendeka, Silver K.Hypertension is an important contributor to global burden of disease and mortality, and is a growing public health problem in sub-Saharan Africa. However, most sub-Saharan African countries lack detailed countrywide data on hypertension and other non-communicable diseases (NCD) risk factors that would provide benchmark information for design of appropriate interventions.We analyzed blood pressure data from Uganda’s nationwide NCD risk factor survey conducted in 2014, to describe the prevalence and distribution of hypertension in the Ugandan population, and to identify the associated factors.Item Framework for determining airport daily departure and arrival delay thresholds: statistical modelling approach(SpringerPlus, 2016) Wesonga, Ronald; Nabugoomu, FabianThe study derives a framework for assessing airport efficiency through evaluating optimal arrival and departure delay thresholds. Assumptions of airport efficiency measurements, though based upon minimum numeric values such as 15 min of turnaround time, cannot be extrapolated to determine proportions of delay-days of an airport. This study explored the concept of delay threshold to determine the proportion of delay-days as an expansion of the theory of delay and our previous work. Data-driven approach using statistical modelling was employed to a limited set of determinants of daily delay at an airport. For the purpose of testing the efficacy of the threshold levels, operational data for Entebbe International Airport were used as a case study. Findings show differences in the proportions of delay at departure (μ = 0.499; 95 % CI = 0.023) and arrival (μ = 0.363; 95 % CI = 0.022). Multivariate logistic model confirmed an optimal daily departure and arrival delay threshold of 60 % for the airport given the four probable thresholds {50, 60, 70, 80}. The decision for the threshold value was based on the number of significant determinants, the goodness of fit statistics based on the Wald test and the area under the receiver operating curves. These findings propose a modelling framework to generate relevant information for the Air Traffic Management relevant in planning and measurement of airport operational efficiencyItem Logit models for household food insecurity classification(American Journal of Theoretical and Applied Statistics, 2014) Owino, Abraham; Kiboijana Atuhaire, Leonard; Wesonga, Ronald; Nabugoomu, Fabian; Muwanga-Zaake, ElijahMicro-level measurement of food insecurity is a necessary approach towards a more feasible solution to the global problem for proper classification of households by food insecurity status. Measurement of food insecurity is a challenge because it is a multi-faceted latent and continuous phenomenon explained by a wide range of both quantitative and qualitative variables. In this paper, we examined the quantitative variables and applied exploratory factor analysis to identify which of them significantly influence household food insecurity. Logit models were then developed using the variables identified. Further, empirical data obtained from Tororo and Busia rural households in Uganda were used to fit the models. Four logit models based on four scenarios were developed and compared. The key findings pointed to the fact that if households were to be correctly analyzed and classified into the right food security category, a hybrid dependent variable that represents as many aspects of food insecurity as possible should be used. The model correctly classified 90 % of the combined households for two districts. However, when fitted for separate districts, it was established that 99% of households in Busia and 96% in Tororo district respectively, were found to be food insecure.Item Low consumption of fruits and vegetables among adults in Uganda: findings from a countrywide cross-sectional survey(Archives of Public Health, 2019) Ndugwa Kabwama, Steven; Bahendeka, Silver K.; Wesonga, Ronald; Mutungi, Gerald; Guwatudde, DavidAdequate consumption of fruits and vegetables has protective benefits against development of coronary heart disease, hypertension and chronic obstructive pulmonary disease. However, approximately 2.7 million deaths annually can be attributed to inadequate fruit and vegetable consumption. We analyzed data from a countrywide survey in Uganda, to estimate the prevalence of adequate fruit and/ or vegetable consumption, and identify associated factors. Methods: Data were collected using the World Health Organization STEPwise approach to surveillance, a standard approach to surveillance of risk factors for Non Communicable Diseases. Fruit and vegetable consumption was assessed by asking participants the number of days in a typical week they eat fruits or vegetables and the number of servings eaten in one of those days. Adequate fruit and/ or vegetable consumption was defined as consuming 5 or more servings of fruits and/ or vegetables per day in a typical week. We used modified Poisson regression analysis to estimate prevalence risk ratios (PRRs) and identify factors associated with eating 5 or more servings of fruits and/ or vegetables per day, per week. Results: Of 3962 participants, 484 (12.2%) consumed 5 or more servings of fruits and/ or vegetables per day in a typical week. Participants who were married or cohabiting were more likely to consume at least 5 servings of fruits and/ or vegetables per day in a typical week compared with those who had never been married PRR = 1.51 [95% CI 1.07–2.14]. Compared with participants from Western region, those from Central region were more likely to consume 5 or more servings of fruits and/ or vegetables per day in a typical week, PRR = 3.54 [95% CI 2.46–5.10] as were those from Northern, PRR = 2.90 [95% CI 2.00–4.23] and Eastern regions PRR = 1.60 [95% CI 1.04–2.47]. Conclusions: Fruit and vegetable consumption in Uganda is low and does not differ significantly across social and demographic characteristics, except marital status and geographical region of residence. There is a need to develop and strengthen policies that promote adequate consumption of fruits and vegetables in the Ugandan population.Item Modelling Airport Efficiency With Distributions Of The Inefficient Error Term: An Application Of Time Series Data For Aircraft Departure Delay(International Journal of Sciences: Basic and Applied Research, 2013) Wesonga, Ronald; Nabugoomu, Fabian; Jehopio, Peter; Mugisha, XavierThe study employs determinants of the aircraft departure delay to estimate airport efficiency. Two main parameters were applied to fit the stochastic frontier model using transcendental logarithmic function where both frontier and inefficiency models were generated. The estimated airport efficiencies over a period of 1827 days applying the half-normal and exponential distributions for the inefficiency error terms were (0.7498; δ=0.1417, n=1827) and (0.8181; δ=0.1224, n=1827) respectively. The correlation coefficient for the efficiency estimates (ρ=0.9791, n=1827, p<0.05) between the half-normal and exponential distributions showed no significant statistical difference. Further analysis showed that airport inefficiency was significantly associated with higher number of persons on board, lower visibility level, lower air pressure tendency, higher wind speed and a higher proportion of arrival aircraft delays. The study offers a contribution towards assessing the dynamics for the distribution of inefficient error term to estimate airport efficiency by employing both meteorological and aviation parameters. The study recommends that although either half-normal or exponential distributions could be used; the exponential distribution for the error term was found more suitable when estimating the efficiency score for the airport.Item On the Goodness of Fit of Parametric and Non‑Parametric Data Mining Techniques: The Case of Malaria Incidence Thresholds in Uganda(Health and Technology, 2021) Bbosa, Francis Fuller; Nabukenya, Josephine; Nabende, Peter; Wesonga, RonaldTo identify which data mining technique (parametric or non-parametric) best fits the predictions on imbalanced malaria incidence dataset. The researchers compared parametric techniques in form of naïve Bayes and logistic regression against non-parametric techniques in form of support vector machines and artificial neural networks and their goodness of fit and prediction was assessed using 10-fold and 5-fold cross-validation on an independent validation dataset set to determine which model best fits the predictions on imbalanced malaria incidence dataset. The 10-fold cross-validation outperformed the 5-fold cross-validation in all performance metrics with the naïve Bayes classifier attaining accuracy of 69% with a sensitivity of 90.9%, a specificity of 55.6%, a precision of 55.6% and F-measure score of 69.0%, the logistic regression achieved an accuracy of 65.5% with a sensitivity of 83.3%, a specificity of 52.9%, a precision of 55.6% and F-measure score of 66.7%, the support vector machines achieved an accuracy of 82.8% with a sensitivity of 88.2%, a specificity of 75.0%, a precision of 83.3%, and F-measure score of 85.7% whereas the artificial neural networks registered an accuracy of 89.7% with a sensitivity of 94.1%, a specificity of 83.3%, a precision of 88.9%, and F-measure score of 91.4%. Non-parametric data mining techniques in form of artificial neural networks and support vector machines outperformed the parametric data mining technique in form of naïve Bayes in making predictions emanating from imbalanced malaria incidence dataset on account of registering higher F-measure values of 91.4% and 85.7% respectively.Item Parameterized framework for the analysis of probabilities of aircraft delay at an airport(Journal of Air Transport Management, 2012) Wesonga, Ronald; Nabugoomu, Fabian; Jehopio, PeterThe study analyses ground delays and air holding at Entebbe International Airport over five years. Daily probabilities for aircraft departure and arrival delays at are generated for each. The mean probabilities of delay for ground delays and air holding at 50% delay threshold levels are 0.94 and 0.82 that fall to 0.49 and 0.36 when 60% delay threshold levels are used. Simulations are performance for delay threshold levels to monitor for the trends of the daily probabilities for the study period. The general conclusion is that a parameter-based framework is best suited to determine the probability of aircraft delay at an airport.Item Physical Activity Levels Among Adults in Uganda: Findings From a Countrywide Cross-Sectional Survey(Journal of Physical Activity and Health, 2016) Guwatudde, David; Kirunda, Barbara E.; Wesonga, Ronald; Mutungi, Gerald; Kajjura, Richard; Kasule, Hafisa; Muwonge, James; Bahendeka, Silver K.Being physically active is associated with lower risk of many noncommunicable diseases (NCDs). We analyzed physical activity (PA) data collected as part of Uganda’s countrywide NCD risk factor survey conducted in 2014, to describe PA levels in Uganda. Methods: PA data were collected on the domains of work, travel and leisure. We calculated the percentage of participants meeting the World Health Organization (WHO) PA recommendations, and the types of intense-specific duration of PA. Prevalence ratios (PR) were used to identify factors associated with meeting WHO PA recommendations. Results: Of the 3987 participants, 3758 (94.3%) met the WHO PA recommendations. Work-related PA of moderate intensity, and travel-related PA contributed most to participants’ overall weekly duration of PA, each contributing 49.6% and 25.2% respectively. The median weekly duration of all moderate-intensity PA was 1470 minutes (interquartile range [IQR] = 540 to 2460). Weekly duration of all vigorous-intensity PA was low with a median of 0 minutes (IQR = 0 to 1080). The median daily sedentary time was 120 minutes (IQR = 60 to 240). Factors significantly associated with meeting WHO PA recommendations were body mass index and level of education. Conclusions: PA levels in Uganda are high, mostly achieved through travel and work-related activities of moderate intensity.Item Prevalence and correlates of abdominal obesity among adults in Uganda: findings from a national cross-sectional, population based survey 2014(BMC obesity, 2018) Ndugwa Kabwama, Steven; Kirunda, Barbara; Mutungi, Gerald; Wesonga, Ronald; Bahendeka, Silver K.; Guwatudde, DavidOverweight and obesity are associated with health complications the gravity of which, vary with the regional deposition of the excess fat. The Body Mass Index (BMI) is often used to measure obesity although is an inferior predictor of cardiovascular disease risk mortality and morbidity compared with measures of abdominal obesity. We analyzed data from Uganda’s 2014 World Health Organization (WHO) STEPwise approach to surveillance of Non-communicable diseases (NCDs) survey to estimate the prevalence of abdominal obesity and associated factors to provide information on the prevention and control of overweight and obesity. Methods: Data were collected using the WHO STEPS protocol. Waist measurement was taken using a non-stretchable standard tape measure mid-way between the lowest rib and iliac crest with the subject standing at the end of gentle expiration. Participants with waist circumference > 102 cm for men and 88 cm for women were classified as abdominally obese. We used weighted modified Poisson regression with robust error variance to estimate the prevalence of abdominal obesity and associated factors. Results: Of the 3676 participants, 432 (11.8%) were abdominally obese; with the prevalence higher among females 412 (19.5%) compared with males 20 (1.3%). Compared with males, female participants were more likely to be abdominally obese Adjusted Prevalence Rate Ratio (APRR) 7.59 [5.58–10.33]. Participants who were married or cohabiting APRR 1.82 [1. 29–2.57] and participants who were separated or divorced APRR 1.69 [1.17–2.46] were more likely to be abdominally obese compared with those who had never married before. Compared with rural dwellers, participants from urban areas were more likely to be abdominally obese APRR 1.29 [1.09–1.53]. Compared with participants with normal blood pressure, those with elevated blood pressure were more likely to be abdominally obese APRR 1.83 [1.57–2.14]. Compared with participants without any education, those with secondary education were more likely to be abdominally obese APRR 1.42 [1.12–1.78]. Conclusions: There is a high prevalence of abdominal obesity among adults in Uganda which puts many at risk of developing associated metabolic complications. These data provide useful information for developing interventions and formulation of policies for the control and prevention of abdominal obesity in Uganda.Item Prevalence and correlates of diabetes mellitus in Uganda: a population-based national survey(Tropical Medicine & International Health, 2016) Bahendeka, Silver; Wesonga, Ronald; Mutungi, Gerald; Muwonge, James; Neema, Stella; Guwatudde, DavidWe analysed fasting blood glucose (FBG) and other data collected as part of a population-based nationwide non-communicable disease risk factor survey, to estimate the prevalence of impaired fasting glycaemia (IFG) and diabetes mellitus and to identify associated factors in Uganda. methods The nationwide cross-sectional survey was conducted between April and July 2014. Participants were adults aged 18–69 years. A multistage stratified sample design was used to produce a national representative sample. Fasting capillary glucose was measured to estimate glycaemia. Data were managed with WHO e-STEPs software and Epi Info. Stata survey procedures were used to account for the sampling design, and sampling weights were used to account for differential probability of selection between strata. results Of the 3689 participants, 1467 (39.8%) were males, and 2713 (73.5%) resided in the rural areas. The mean age was 35.1 years (standard deviation = 12.6) for males and 35.8 years (13.2) for females. The overall prevalence of IFG was 2.0% (95% confidence interval (CI) = 1.5–2.5%), whereas that of diabetes mellitus was 1.4% (95% CI 0.9–1.9%). The prevalence of IFG was 2.1% (95% CI 1.3–2.9%) among males and 1.9% (95% CI 1.3–2.6%) among females, whereas that of diabetes mellitus was 1.6% (95% CI 0.8–2.6%) and 1.1% (95% CI 0.6–1.7%), respectively. The prevalence of IFG was 2.6% (95% CI 1.4–3.8%) among urban and 1.9% (95% CI 1.3–2.4%) among rural residents, whereas that of diabetes mellitus was 2.7% (95% CI 1.4–4.1) and 1.0% (95% 0.5–1.6%), respectively. The majority of participants identified with hyperglycaemia (90.5% IFG and 48.9% diabetes) were not aware of their hyperglycaemic status. Factors associated with IFG were region of residence, body mass index and total cholesterol; factors associated with diabetes mellitus were age, sex, household floor finish and abdominal obesity. conclusion The prevalence of IFG and of diabetes mellitus is low in the Ugandan population, providing an opportunity for the prevention of diabetes. The majority of persons with hyperglycaemia were not aware of their hyperglycaemic status, which implies a likelihood of presenting late with complications.Item Simulation of time series wind speed at an international airport(Simulation, 2019) Wesonga, Ronald; Nabugoomu, Fabian; Ababneh, Faisal; Owino, AbrahamThe sporadic and unstable nature of wind speed renders it very difficult to predict accurately to serve various decisions, such as safety in the air traffic flow and reliable power generation system. In this study we assessed the autoregressive integrated moving average (ARIMA) and artificial neural network (ANN) models on the wind speed time series problem. Data on wind speed and minimum and maximum temperatures were evaluated. Wind speed was established to follow a time series that fluctuated around ARIMA (0,1,1) and ARIMA (1,1,1). The optimal ANN model was established at 10 hidden neurons. The performance indices considered all indicated that the ANN wind speed model was superior to the ARIMA model. Wind speed prediction accuracy can be improved to secure the safety of air traffic flow as well support the implementation of a reliable and secure power generation system at the airportItem Stochastic Optimisation Models for Air Traffic Flow Management(Makerere University, 2010) Wesonga, RonaldAir traffic delay is not only a source of inconvenience to the aviation passenger, but also a major deterrent to the optimisation of airport utility. Many developing countries do less to abate this otherwise seemingly invisible constraint to development. The overall objective of this study was to investigate the dynamics of air traffic delays and to develop stochastic optimisation models that mitigate delays and facilitate efficient air traffic flow management. Aviation and meteorological data sources at Entebbe International Airport for the period 2004 to 2008 on daily basis were used for exploratory data analysis, modelling and simulation purposes. Exploratory data analysis involved logistic modeling for which post-logistic model analysis estimated the average probability of departure delay to be 49 percent while that for arrival delay was 36 percent. These computations were based on a delay threshold level at 60 percent which presented more significant predicators of nine and ten for departure and arrival respectively. The proportion of aircrafts that delay was established to follow an autoregressive integrated moving average, ARIMA (1,1,1) time series.