A semi-parametric mixed models for longitudinally measured fasting blood sugar level of adult diabetic patients

Abstract Background At the diabetic clinic of Jimma University Specialized Hospital, health professionals provide regular follow-up to help people with diabetes live long and relatively healthy lives. Based on patient condition, they also provide interventions in the form of counselling to promote a healthy diet and physical activity and prescribing medicines. The main purpose of this study is to estimate the rate of change of fasting blood sugar (FBS) profile experienced by patients over time. The change may help to assess the effectiveness of interventions taken by the clinic to regulate FBS level, where rates of change close to zero over time may indicate the interventions are good regulating the level. Methods In the analysis of longitudinal data, the mean profile is often estimated by parametric linear mixed effects model. However, the individual and mean profile plots of FBS level for diabetic patients are nonlinear and imposing parametric models may be too restrictive and yield unsatisfactory results. We propose a semi-parametric mixed model, in particular using spline smoothing to efficiently analyze a longitudinal measured fasting blood sugar level of adult diabetic patients accounting for correlation between observations through random effects. Results The semi-parametric mixed models had better fit than the linear mixed models for various variance structures of subject-specific random effects. The study revealed that the rate of change in FBS level in diabetic patients, due to the clinic interventions, does not continue as a steady pace but changes with time and weight of patients. Conclusions The proposed method can help a physician in clinical monitoring of diabetic patients and to assess the effect of intervention packages, such as healthy diet, physical activity and prescribed medicines, because individualized curve may be obtained to follow patient-specific FBS level trends

Family Planning Knowledge, Attitude and Practice among Married Couples in Jimma Zone, Ethiopia

Background: Understanding why people do not use family planning is critical to address unmet needs and to increase contraceptive use. According to the Ethiopian Demographic and Health Survey 2011, most women and men had knowledge on some family planning methods but only about 29% of married women were using contraceptives. 20% women had an unmet need for family planning. We examined knowledge, attitudes and contraceptive practice as well as factors related to contraceptive use in Jimma zone, Ethiopia. Methods: Data were collected from March to May 2010 among 854 married couples using a multi-stage sampling design. Quantitative data based on semi-structured questionnaires was triangulated with qualitative data collected during focus group discussions. We compared proportions and performed logistic regression analysis. Result: The concept of family planning was well known in the studied population. Sex-stratified analysis showed pills and injectables were commonly known by both sexes, while long-term contraceptive methods were better known by women, and traditional methods as well as emergency contraception by men. Formal education was the most important factor associated with better knowledge about contraceptive methods (aOR = 2.07, p\u3c0.001), in particular among women (aOR(women )= 2.77 vs. aOR(men) = 1.49; p\u3c0.001). In general only 4 out of 811 men ever used contraception, while 64% and 43% females ever used and were currently using contraception respectively. Conclusion: The high knowledge on contraceptives did not match with the high contraceptive practice in the study area. The study demonstrates that mere physical access (proximity to clinics for family planning) and awareness of contraceptives are not sufficient to ensure that contraceptive needs are met. Thus, projects aiming at increasing contraceptive use should contemplate and establish better counseling about contraceptive side effects and method switch. Furthermore in all family planning activities both wives\u27 and husbands\u27 participation should be considered

Joint Modeling of Longitudinal Systolic and Diastolic Blood Pressure Measurements of Hypertensive Patients Receiving Treatment

Hypertension is a chronic disease that has a major health problem over thecenturies due to its signicant contribution to the global health burden. Itis also called high blood pressure, described by two numbers Systolic bloodpressure (SBP) and diastolic blood pressure (DBP). Hence, joint longitudinalmodel was used to address how the evolution of SBP is associated with theevolution of DBP. The objective was to investigate the joint evolution andassociation of SBP and DBP measurements of hypertensive patients andidentify the potential risk factors aecting the two end points. In this thisstudy 354 hypertensive patients with age greater than or equal to 18 years,who were on treatment, and who had measured at least three times wereincluded. For a close examination of the separate and joint models, rst, eachof the outcomes was analyzed separately using linear mixed model. Then,a joint model was considered to study the joint evolution and identify thepotential risk factors aecting the two end points. Fit statistics showed thatthe joint model resulted in better t to the data than the separate models.Based on the joint model, sex, baseline age, and place of residence were thesignicant factors for the progression of blood pressure, while family historyand all the interaction term except age by time did not appear signicant.The result from the joint model suggested a strong association between theevolutions and a slowly increasing evolution of the association between SBPand DBP

Marginalized multilevel hurdle and zero-inflated models for overdispersed and correlated count data with excess zeros

Count data are collected repeatedly over time in many applications, such as biology, epidemiology, and public health. Such data are often characterized by the following three features. First, correlation due to the repeated measures is usually accounted for using subject-specific random effects, which are assumed to be normally distributed. Second, the sample variance may exceed the mean, and hence, the theoretical mean-variance relationship is violated, leading to overdispersion. This is usually allowed for based on a hierarchical approach, combining a Poisson model with gamma distributed random effects. Third, an excess of zeros beyond what standard count distributions can predict is often handled by either the hurdle or the zero-inflated model. A zero-inflated model assumes two processes as sources of zeros and combines a count distribution with a discrete point mass as a mixture, while the hurdle model separately handles zero observations and positive counts, where then a truncated-at-zero count distribution is used for the non-zero state. In practice, however, all these three features can appear simultaneously. Hence, a modeling framework that incorporates all three is necessary, and this presents challenges for the data analysis. Such models, when conditionally specified, will naturally have a subject-specific interpretation. However, adopting their purposefully modified marginalized versions leads to a direct marginal or population-averaged interpretation for parameter estimates of covariate effects, which is the primary interest in many applications. In this paper, we present a marginalized hurdle model and a marginalized zero-inflated model for correlated and overdispersed count data with excess zero observations and then illustrate these further with two case studies. The first dataset focuses on the Anopheles mosquito density around a hydroelectric dam, while adolescents' involvement in work, to earn money and support their families or themselves, is studied in the second example. Sub-models, which result from omitting zero-inflation and/or overdispersion features, are also considered for comparison's purpose. Analysis of the two datasets showed that accounting for the correlation, overdispersion, and excess zeros simultaneously resulted in a better fit to the data and, more importantly, that omission of any of them leads to incorrect marginal inference and erroneous conclusions about covariate effects.status: publishe

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Intervention pathways towards improving the resilience of pastoralists: A study from Borana communities, southern Ethiopia

Building resilient communities towards recurrent droughts is increasingly becoming an important element in development endeavours, particularly among communities vulnerable to shocks and stresses. Despite decades of remarkable efforts made by governmental and non-governmental organization, the resilience capacity of pastoralists in Ethiopia remains poor. The aim of this study is to test the statistical relationships among the resilience dimensions that emerged through community consultations, and to identify the intervention pathways for effective resilience building efforts. Data were collected from 1058 randomly sampled households in Arero and Dhas districts of Borana Zone, Southern Ethiopia. The data were collected through interviewer administered structured questionnaire and observational checklist. Principal component analyses were done to develop composite scores of the different resilience dimensions. Structural equation model (SEM) verified the theoretical model. The SEM also revealed that resilience towards impact of recurrent droughts was multi-dimensional and showed statistically significant (p < 0.05) relationships. Consequently, household food insecurity manifested as ultimate outcome of poor resilience. Infrastructure and social services (β = −0.24), livestock dimension (β = −0.21), human capital (β = −0.12), psychosocial distress (β = −0.1) dimensions significantly (p < 0.05) affected the status of household food insecurity. Furthermore, livestock and wealth (β = 0.16), wealth and infrastructure (β = 0.06), infrastructure and human capital (β = 0.18), livestock and psychosocial distress (β = −0.09) dimensions have structural relationships and significantly influence each other. Environment, and peace and security are found to be major underlying resilience factors and significantly associated with pastoralists’ resilience which affect other resilience dimensions. The intervention pathway indicated that intervention on the livestock and infrastructure dimensions could help to improve the resilience of these communities

No association between perinatal mood disorders and hypertensive pregnancies

Mental health disorders such as anxiety and/or depression are the most common mental health disorders seen among reproductive aged women and can increase during pregnancy. Many sociodemographic risk factors have been associated with anxiety and/or depression in pregnancy, which can lead to adverse maternal and infant outcomes including the risk of a hypertensive pregnancy. The current study prospectively examined self-reported anxiety, depression and stress in pregnant women without a history of fetal loss or mood disorders beginning at 20–26 weeks. At each study visit, circulating immune factors associated with perinatal mood disorders were measured in blood samples that were collected. A total of 65 women were eligible for data analysis, 26 of which had hypertensive pregnancies. There was not a significant difference in self-reported depression, anxiety or stress between hypertensive disorders of pregnancy and normotensive women. Black women were more likely to have a hypertensive pregnancy and develop a perinatal mood disorder compared to non-black women. Both the inflammatory cytokines interleukin-17 and tumor necrosis factor-alpha were increased in patients with perinatal mood disorders. However, additional research is needed in a larger sample to truly understand the relationship between these factors along with the underlying etiologies and the associated outcomes

Fertility preference.

<p>Percent distribution of Sex preference for next child depending on the number of boys and girls from all marriages living in the family of respondents in Jimma zone, Ethiopia 2013.</p