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1.
Med. j. Zambia ; 49(2): 157-162, 2022. tales, figures
Article in English | AIM | ID: biblio-1402640

ABSTRACT

Objective:The determine the prevalence of stillbirth and identify associated factors among parturients in a faith-based secondary health centre.Method:This was a retrospective audit of two hundred and twenty-five stillbirth deliveries at the Our Lady of Apostle Catholic Hospital at Oluyoro, OkeOffainIbadan, Nigeria,betweenstst1January2010, and 31December, 2015. Data was extractedfromhospitalrecordsforsociodemographiccharacteristics, obstetricfactors,complications, and outcomes of pregnancy. Data analysis was done using SPSS version 20 and the level of statistical significance was set at p < 0.05. Results:The stillbirth rate was 27.75 per 1000 births. More than half (129; 57.4%) were macerated. The ratio of still birth rate among the booked and unbooked parturients was 1:21. The commoncausesofstillbirthswerehypertensivedisordersinpregnancy (24.9%), anaemia in pregnancy (20.4%); while the least were congenital anomalies (1.0%) and gestational diabetes mellitus (1.0%Conclusion: This study confirmed that most of the stillbirths were due to unsupervised or poorly supervised pregnancies. There is need to ensure quality antenatal care services for the early detection and management of risk factors in order to reduce the burden of stillbirths.


Subject(s)
Humans , Delivery of Health Care , Clinical Audit , Child Mortality , Stillbirth
2.
Ghana Medical Journal ; 56(3): 206-214, )2022. Figures, Tables
Article in English | AIM | ID: biblio-1398796

ABSTRACT

Objectives: This study identified the predictors of weight reduction among adult obese patients in a Family Practice Setting and developed a statistical model to predict weight reduction. Design: A prospective cohort design. Setting: The Family Practice Clinic, University College Hospital, Ibadan, Nigeria Participants and study tools: Obese adults were recruited into a three-month weight reduction program. Patient Information Leaflets were used for counselling, while questionnaires were administered to obtain socio-demographic and lifestyle factors. Potential predictors were assessed using the Multidimensional Scale of Perceived Social Support, Zung Depression Scale, Rosenberg Self-Esteem scale, Garner's Eating Attitude Test-26 (EAT-26), 24-hour dietary recall and International Physical Activity Questionnaire-short form. Anthropometric indices, blood pressure and Fasting Lipid Profile were assessed. Descriptive and inferential statistics were used for analysis with a significance set at α0.05. Results: Most 99(76.2%) of the 130 participants achieved weight reduction and had a median weight change of -2.3kg (IQR-4, -0.5), with 66 (66.7%) out of 99 attaining the weight reduction target of 10%. The regression model showed predictors of weight reduction to be Total Cholesterol [TC] (p=0.01) and Low-Density Lipoprotein Cholesterol [LDLC] (p=0.03). The statistical model derived for Weight reduction = 0.0028 (LDL-C) -0.029 (TC)-0.053 (EAT-26) +0.041(High-Density Lipoprotein Cholesterol). The proportion of variance of the model tested was R 2 = 0.3928 (adjusted R2 = 0.2106). Conclusion: Predictors of weight reduction among patients were eating attitude score, Total Cholesterol, Low-Density Lipid and High-Density Lipoprotein Cholesterol levels. A statistical model was developed for managing obesity among patients


Subject(s)
Clinical Laboratory Information Systems , Diet, Reducing , Obesity , Patient Outcome Assessment , Epidemiological Models
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