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<title>School of Public Health</title>
<link href="http://ir.mu.ac.ke:8080/jspui/handle/123456789/47" rel="alternate"/>
<subtitle/>
<id>http://ir.mu.ac.ke:8080/jspui/handle/123456789/47</id>
<updated>2026-10-04T17:41:00Z</updated>
<dc:date>2026-10-04T17:41:00Z</dc:date>
<entry>
<title>Prevalence and determinants of undiagnosed diabetes mellitus among patients presenting for elective surgery at Moi Teaching and Referral Hospital, Eldoret Kenya</title>
<link href="http://ir.mu.ac.ke:8080/jspui/handle/123456789/10515" rel="alternate"/>
<author>
<name>Kimetto, Joan</name>
</author>
<id>http://ir.mu.ac.ke:8080/jspui/handle/123456789/10515</id>
<updated>2026-09-22T09:25:04Z</updated>
<published>2026-01-01T00:00:00Z</published>
<summary type="text">Prevalence and determinants of undiagnosed diabetes mellitus among patients presenting for elective surgery at Moi Teaching and Referral Hospital, Eldoret Kenya
Kimetto, Joan
Background: Diabetes mellitus (DM) is a group of metabolic disorders characterized by chronic hyperglycemia due to defects in insulin secretion, action, or both. The International Diabetes Federation estimates that over 10.5% of adults aged 20–79 years globally have diabetes, with half undiagnosed. In Kenya, the true prevalence is unclear, and the reported 3% likely underestimates the burden. Routine diabetes screening is uncommon, particularly among elective surgical patients. Known risk factors include age, overweight/obesity, physical inactivity, poor diet, family history, and comorbidities such as hypertension and dyslipidaemia. However, local evidence on these determinants remains limited, underscoring the need to assess undiagnosed diabetes among elective surgical patients.&#13;
Objective: To determine the prevalence of undiagnosed DM and describe the social, demographic, economic, lifestyle and clinical factors associated with undiagnosed DM among patients presenting for elective surgery at Moi Teaching and Referral Hospital (MTRH).&#13;
Methods: This was a descriptive cross-sectional study conducted in four surgical wards of MTRH (Kilimanjaro, Longonot, Rehema, and Sergoit). A total of 540 adult patients (≥18 years) admitted for elective surgery with unknown diabetes status were recruited through consecutive sampling. Data was collected using a structured questionnaire and clinical measurements, including fasting plasma glucose. Undiagnosed diabetes mellitus was defined as fasting plasma glucose ≥7.0 mmol/L with no prior history of diabetes.&#13;
Ethical approval was obtained from the Institutional Research and Ethics Committee (IREC) of Moi University/MTRH, and permission to undertake the study was granted by hospital management. Written informed consent was obtained from all participants.&#13;
Data were analyzed using SPSS version 20. Descriptive statistics were used to summarize variables as frequencies and percentages (n, %). Associations were assessed using binary logistic regression, with results presented as odds ratios (OR) and 95% confidence intervals (CI). Statistical significance was set at p&lt;0.05.&#13;
Results: The prevalence of undiagnosed DM among patients presenting for elective surgery in MTRH was 3.5%. The highest prevalence was found in the age group 36-55 years, with a rate of 6.3%. Single individuals exhibited a significantly higher likelihood of undiagnosed DM (p-value of 0.029). Additionally, business persons and those employed portrayed a higher likelihood of undiagnosed DM with statistically significant associations (p-values of 0.04, 0.01 and 0.02 respectively). Although clinical, lifestyle and dietary factors were found to be associated with the undiagnosed DM, these relationships were not statistically significant.&#13;
Conclusion: There is a higher proportion of persons with undiagnosed diabetes among those presenting for elective surgery at MTRH compared to the general population. Among those presenting for elective surgery, the middle-aged, and employed are at a higher risk of undiagnosed diabetes. &#13;
Recommendations: Routine screening is recommended in all adults undergoing elective surgery at the Moi Teaching and Referral Hospital and similar healthcare facilities to enable early detection and appropriate management of undiagnosed diabetes. The Ministry of Health Kenya should incorporate opportunistic diabetes screening into national guidelines and strengthen implementation across hospital settings
</summary>
<dc:date>2026-01-01T00:00:00Z</dc:date>
</entry>
<entry>
<title>Prevalence and factors associated with modern contraceptive use among female adolescents aged 15-19 years in Kenya</title>
<link href="http://ir.mu.ac.ke:8080/jspui/handle/123456789/10218" rel="alternate"/>
<author>
<name>Salat, Ednah Chepngeno</name>
</author>
<id>http://ir.mu.ac.ke:8080/jspui/handle/123456789/10218</id>
<updated>2026-06-17T07:37:32Z</updated>
<published>2025-01-01T00:00:00Z</published>
<summary type="text">Prevalence and factors associated with modern contraceptive use among female adolescents aged 15-19 years in Kenya
Salat, Ednah Chepngeno
Adolescent sexual and reproductive health (ASRH) contributes to the global burden of &#13;
sexual ill health, with unmet needs persisting worldwide. Kenya's government &#13;
reaffirms its commitment to increasing the contraceptive prevalence among adolescents &#13;
aged 15-19 to 55% by 2025 from the current 10%. Only 43.8% of married and 36.9% &#13;
of sexually active unmarried adolescents (15-19) used any method of contraception as &#13;
of 2022 in Kenya. The objectives were; to determine the demographic and social &#13;
characteristics (Age, education, marital status, parity, economic status), and prevalence &#13;
of modern contraceptive use among female adolescents and to identify associated &#13;
factors. The study utilized secondary data from Kenya's 2021 Performance Monitoring &#13;
for Action (PMA) survey. The data extraction process focused on identifying and &#13;
filtering female adolescents aged 15-19 who met specific inclusion criteria: sexually &#13;
active, married or unmarried, and present during the survey period. After applying these &#13;
criteria, the final weighted sample consisted of 344 respondents. Descriptive analyses &#13;
were conducted to calculate the mean values and proportions for the relevant variables. &#13;
Bivariate analysis was carried out to determine the association between outcome &#13;
(modern contraceptive use) and exposure variables. All variables with a p-value&gt;0.2 at &#13;
the bivariate level were subjected to a multivariable binary logistic regression model. &#13;
Stepwise backward elimination unconditional logistic regression was used to develop &#13;
the final model. All variables with p-values &gt;0.05 at a multivariable level were regarded &#13;
as independently associated with modern contraceptives. According to the results of &#13;
the 344 sexually active girls, 169 were using modern contraceptives, giving a &#13;
prevalence of 49.1% (95% CI: 43.8- 54.4). The mean age was 17.8 years (SD+/-1.7), &#13;
with the age group 18-19 years contributing 64.8% of the respondents, with a &#13;
prevalence of 57.4%. Those who reported being married or staying with a partner as if &#13;
married had 46.3% using modern contraceptives, while those with secondary and &#13;
higher education had 51.9% using modern contraceptives. The odds of modern &#13;
contraceptive use were 2.0 times higher among those adolescents aged 18-19 years &#13;
(AOR 2.0, 95% CI, 1.21-3.45, p&lt;0.005) compared to adolescents aged 15- 17 years. &#13;
Those who reported having one child had 2.2 odds of using modern contraceptives &#13;
compared to those who had never had a child before (AOR 2.2, 95% CI, 1.17-4.24, &#13;
p&lt;0.05). Other factors that were independently associated with modern contraceptive &#13;
use include household wealth quantiles (AOR 4.9 CI 95%, 2.08-11.29, p&lt;0.05) and the &#13;
perception that the community’s view a few adolescents using modern contraceptives &#13;
were promiscuous (AOR 0.4. 95% CI, 0.2-0.78, p&lt;0.05). In conclusion Age, education, &#13;
and economic resources have a positive impact on modern contraceptive use, while &#13;
community perceptions have a negative influence. These factors are key in shaping the &#13;
contraceptive behavior of adolescents in Kenya.  Recommending this a targeted &#13;
comprehensive approach encompassing education on sexual reproductive health, &#13;
awareness-raising, and community engagement is paramount in empowering &#13;
adolescents to make informed decisions about their reproductive health
</summary>
<dc:date>2025-01-01T00:00:00Z</dc:date>
</entry>
<entry>
<title>Factors associated with mortality among severely ill covid-19 patients, Nairobi metropolis, Kenya</title>
<link href="http://ir.mu.ac.ke:8080/jspui/handle/123456789/10211" rel="alternate"/>
<author>
<name>Muendo, Charles Mulwa</name>
</author>
<id>http://ir.mu.ac.ke:8080/jspui/handle/123456789/10211</id>
<updated>2026-06-16T06:39:05Z</updated>
<published>2025-01-01T00:00:00Z</published>
<summary type="text">Factors associated with mortality among severely ill covid-19 patients, Nairobi metropolis, Kenya
Muendo, Charles Mulwa
Background: Severe Coronavirus Disease 2019 (COVID-19) occurs in about 20% of&#13;
hospitalized patients. Many of these patients have comorbidities and are the main&#13;
contributors for COVID-19 mortality. The most common underlying conditions include&#13;
hypertension, diabetes, and chronic lung disease.&#13;
Objectives: To describe socio-demographic factors of severe COVID-19 patients;&#13;
determine the clinical, laboratory, and radiological characteristics and outcomes of&#13;
severe COVID-19 disease; and evaluate the predictors of mortality for severely ill&#13;
COVID-19 patients.&#13;
Methods: A cross-sectional study in Nairobi Metropolis was conducted between&#13;
September and December 2021. Patient information was collected from the inpatient&#13;
registers of selected hospitals with COVID-19 isolation centers. This included&#13;
demographic and clinical information, presenting signs and symptoms, laboratory and&#13;
radiological findings during hospitalization, and case management. A severe COVID-&#13;
19 patient was defined as any COVID-19 patient with any of the following: oxygen&#13;
saturation &lt;94% in room air, respiratory rate &gt;30 breaths/minute, and any signs of&#13;
respiratory distress such as difficulty in breathing, or rapid breathing, confusion,&#13;
reduced blood pressure, low blood oxygen, and tiredness. Mortality (case) was defined&#13;
as any patient with severe COVID-19 infection who died, as recorded and reported by&#13;
the hospital. Non-case was defined as any patient who survived a severe COVID-19&#13;
infection. Means and medians were calculated for continuous variables, and&#13;
frequencies and proportions for categorical variables. Chi-square and multivariable&#13;
binary logistic regression compared exposure factors with disease outcome. The study&#13;
proposal was approved by Moi University Institutional Research Ethics Committee&#13;
(IREC).&#13;
Results: Total abstracted records were for 818 patients; 500 (61%) severe patients (153&#13;
non-survivors, 347 survivors). The analysis involved 150 non-survivors and 150&#13;
survivors. Males were 66.8%, and a mean age of 53.29 years ± 17.7. Sixty-four (64.3)&#13;
percent presented with difficulty breathing, cough 63.7%, while 33.3% had a fever.&#13;
Patients with Peripheral Oxygen Saturation (SPO2) of ≤94% were 39.9% at admission,&#13;
rising to 90.0% during isolation. Patients with underlying diabetes were 29.3%, while&#13;
hypertension/heart disease was 28.3%. Patients that developed acute respiratory&#13;
distress syndrome (ARDS) were 26.0%. Patients put on oxygen therapy were 28.3%,&#13;
mechanical ventilation 19.3%, and ICU admissions were 3.7%. Factors significantly&#13;
associated with death were: hypertension (OR-3.5, 95% CI- 1.34–9.45, p-value- 0.011);&#13;
ARDS (OR- 8.9, 95% CI- 3.05–26.14, p-value- &lt;0.001); severe disease at admission&#13;
(OR- 18.7, 95% CI- 5.24–67.15, p-value &lt;0.001); and failure to receive oxygen&#13;
treatment (OR- 17.5, 95% CI- 5.54–55.32, p-value &lt;0.001).&#13;
Conclusion: The results highlighted that advanced age, hypertension, hypoxia at&#13;
admission, and lack of oxygen therapy were independently associated with increased&#13;
risk of death. These findings are consistent with international evidence, yet they also&#13;
reflect unique health system challenges within the Kenyan context.&#13;
Recommendation: We recommend that the government of Kenya, through the&#13;
Ministry of Health, should: enhance early risk stratification and triage, scale up&#13;
oxygen supply and infrastructure, expand intensive care capacity, and improve&#13;
management of non-communicable diseases, among others.
</summary>
<dc:date>2025-01-01T00:00:00Z</dc:date>
</entry>
<entry>
<title>The factors associated with the uptake of intermittent preventive treatment of Malaria in pregnancy in Nambale Sub-County Hospital, Kenya</title>
<link href="http://ir.mu.ac.ke:8080/jspui/handle/123456789/10205" rel="alternate"/>
<author>
<name>Angute, Collins Omondi</name>
</author>
<id>http://ir.mu.ac.ke:8080/jspui/handle/123456789/10205</id>
<updated>2026-06-15T07:22:43Z</updated>
<published>2026-01-01T00:00:00Z</published>
<summary type="text">The factors associated with the uptake of intermittent preventive treatment of Malaria in pregnancy in Nambale Sub-County Hospital, Kenya
Angute, Collins Omondi
Background: Malaria remains a significant public health problem globally, with highest &#13;
morbidity and mortality reported in sub Saharan Africa. In 2022, there were 12.7 million &#13;
(36%) cases of Malaria in Pregnancy (MiP) in Sub Saharan Africa and 27% were reported &#13;
from East Africa. In Kenya, there were a total of 4,080,441 malaria cases and 5% MiP &#13;
cases. Busia County in Western Kenya reported 341,886 malaria cases and 22% MiP &#13;
cases. WHO recommends administering intermittent preventive treatment of malaria in &#13;
pregnancy using sulfadoxine-pyrimethamine (IPTp-SP) as preventive   treatment for &#13;
malaria in pregnancy (MIP) in malaria-endemic zones to prevent MiP.  &#13;
Objectives: To determine proportion of pregnant women of nine months’ pregnancy &#13;
utilizing IPTp-SP 3 and to describe sociodemographic, health facility and individual &#13;
factors influencing utilization of IPTp-SP 3 among pregnant women of nine months’ &#13;
pregnancy attending antenatal care at Nambale Sub-County Hospital in Busia County. &#13;
Methods: This was a cross-sectional study that employed consecutive sampling &#13;
whereby, pregnant women of nine months, aged between 14-49 years were interviewed, &#13;
using the interviewer- administered questionnaires on Kobo-collect. The dependent &#13;
variable was the uptake of three doses of IPTp-SP, with sociodemographic, health facility &#13;
and individual factors as the independent variables. A Descriptive of factors was done, &#13;
Chi square test was used in bivariate analysis to determine association between &#13;
independent variables and dependable variables, variable with p value of ≤0.2, were &#13;
subjected to multivariable logistic regression analysis to identify variables with p value &#13;
of ≤0.05 associated with utilization of IPTp-SP among pregnant women.  &#13;
Results: A total of 384 pregnant women were interviewed. Their median age was 25 years &#13;
(range of 14 – 49 years), 68% (262/384) were married and 90% (348/384) of all the participants &#13;
resided in rural areas. More than half of the participants, 60% (232/384) utilized IPTp&#13;
SP3. Awareness of use and the benefits of IPTp was reported by 93% (256/384) of &#13;
participants. Majority of the respondents, 67% (258/384) were unemployed, and 47% &#13;
(182/384) had secondary education as their highest level of education. In the bivariate &#13;
analysis, participant age 21-30 years {cOR=2.34, 95% CI=1.4–3.7}, belief that &gt;3 doses &#13;
of IPTp prevented MiP {cOR=3.09, 95% CI=1.5–6.2}and participant having attained &#13;
tertiary education {cOR=2.71, 95% CI=1.4–5.1} were associated with uptake of three or &#13;
more doses of IPTp by the participants. On multivariable logistics regression analysis, &#13;
attendance of ANC at least 4 times {aOR=8.42, 95% CI=4.4–16.0} and participants &#13;
taking IPTp-SP for the first time at 14-17 gestation weeks {aOR=7.79, 95% CI=3.2&#13;
18.7} were factors independently associated with optimal utilization of IPTp (IPTp-SP3). &#13;
Conclusion: A sub-optimal IPTp-SP 3 utilization (60%) way below WHO target &#13;
recommendation of 80%. More than four ANC attendance with the first IPTp-SP uptake &#13;
beginning 14-17 gestation weeks were independently associated with optimal utilization &#13;
of IPTp (IPTp-SP3). &#13;
Recommendation: Pregnant women attending ANC at the facility should ensure that &#13;
they attend ANC at least four times and take at least three doses of IPTp for maximum &#13;
protection against malaria in pregnancy. Enhanced risk communication and community &#13;
engagement by the community health volunteers on IPTp-SP awareness and importance. &#13;
Key Words: FELTP, IPTp-SP, Kenya, Malaria, Pregnancy, WHO
</summary>
<dc:date>2026-01-01T00:00:00Z</dc:date>
</entry>
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