Determinants of hypertension among diabetes patients attending selected comprehensive specialized hospitals of the Amhara Region, Ethiopia: An unmatched case-control study.

BACKGROUND: The coexistence of diabetes mellitus and hypertension is a worldwide public health problem causing significant morbidity, mortality, and decreased quality of life. Despite the increasing burden of hypertension among patients with DM, data on determinants of hypertension among patients with DM in the Amhara region of Ethiopia is scarce. Hence, this study identified determinants of hypertension among people with diabetes attending chronic disease follow-up clinics in the Amhara region of comprehensive specialized hospitals in Ethiopia. METHOD AND MATERIALS: An institutional-based unmatched case-control study was conducted among 470 individuals with diabetes in the Amhara region's comprehensive specialized hospitals (Debre Berhan, Felege Hiwot, and Dessie Comprehensive specialized hospital). A multistage sampling technique was used to select participants for this study. We collected the data using standard questionnaires (short form of international physical activity questionnaire, Morisky medication adherence scale, patient health questionnaire, perceived dietary adherence scale, Oslo social support questionnaire, and alcohol use disorder identification test), physical measurements, and data extraction checklists. A multivariable binary logistic regression was fitted to identify determinants of hypertension, and we presented the findings using an adjusted odds ratio (AOR) with a 95% confidence interval (CI). RESULTS: 235 cases and 235 controls participated in this study. The median (IQR) age for the cases was 60 (52-66 = 14), and the mean age (± SD) for the controls was 51.72 (± 12.51). The significant determinants of hypertension with AOR [95% CI] were a lower level of physical activity: 1.82 [1.00, 3.31], depression: 2.00 [1.24, 3.21], family history of hypertension: 2.13 [1.34, 3.37], not having diabetic health education: 1.87 [1.18, 2.96], a longer duration of diabetes: 1.99 [1.05, 3.79], and poor glycemic control: 1.57 [1.01, 2.45]. CONCLUSION: In this study, determinants that increase the risk of hypertension among people with diabetes mellitus were older age, physical inactivity, depression, family history of hypertension, not having diabetic health education, a longer duration of diabetes, and poor glycemic control.

Application of quantile mixed-effects model in modeling CD4 count from HIV-infected patients in KwaZulu-Natal South Africa.

BACKGROUND: The CD4 cell count signifies the health of an individual's immune system. The use of data-driven models enables clinicians to accurately interpret potential information, examine the progression of CD4 count, and deal with patient heterogeneity due to patient-specific effects. Quantile-based regression models can be used to illustrate the entire conditional distribution of an outcome and identify various covariates effects at the respective location. METHODS: This study uses the quantile mixed-effects model that assumes an asymmetric Laplace distribution for the error term. The model also incorporated multiple random effects to consider the correlation among observations. The exact maximum likelihood estimation was implemented using the Stochastic Approximation of the Expectation-Maximization algorithm to estimate the parameters. This study used the Centre of the AIDS Programme of Research in South Africa (CAPRISA) 002 Acute Infection Study data. In this study, the response variable is the longitudinal CD4 count from HIV-infected patients who were initiated on Highly Active Antiretroviral Therapy (HAART), and the explanatory variables are relevant baseline characteristics of the patients. RESULTS: The analysis obtained robust parameters estimates at various locations of the conditional distribution. For instance, our result showed that baseline BMI (at [Formula: see text] 0.05: [Formula: see text]), baseline viral load (at [Formula: see text] 0.05: [Formula: see text] [Formula: see text]), and post-HAART initiation (at [Formula: see text] 0.05: [Formula: see text]) were major significant factors of CD4 count across fitted quantiles. CONCLUSIONS: CD4 cell recovery in response to post-HAART initiation across all fitted quantile levels was observed. Compared to HIV-infected patients with low viral load levels at baseline, HIV-infected patients enrolled in the treatment with a high viral load level at baseline showed a significant negative effect on CD4 cell counts at upper quantiles. HIV-infected patients registered with high BMI at baseline had improved CD4 cell count after treatment, but physicians should not ignore this group of patients clinically. It is also crucial for physicians to closely monitor patients with a low BMI before and after starting HAART.

Determinants of the type of health care sought for symptoms of Acute respiratory infection in children: analysis of Ghana demographic and health surveys.

BACKGROUND: Globally, acute respiratory infection (ARI) is a leading cause of infant and childhood morbidity and mortality. Currently, it is estimated that 50 million cases of childhood ARI are untreated. In this study, we identified determinants of the type of treatment sought for symptoms of childhood acute respiratory infection (ARI), including non-treatment, amongst a nationally representative sample of children under five years in Ghana. METHODS: In total, 1 544 children were studied by a secondary analysis of pooled survey data from the 1993, 1998, 2003, 2008, and 2014 Ghana Demographic and Health Surveys (GDHS). Cross-tabulations, chi-square, multinomial logistic regression, and Bayesian hierarchical spatial logistic regression analyses were used to identify relationships between the type of treatment sought and maternal socio-economic and household characteristics. RESULTS: Seeking medical care was significantly associated with child age (RRR= 1.928, 95 % CI 1.276 - 2.915), maternal employment status (RRR = 1.815, 95 % CI 1.202 - 2.740), maternal health insurance status, (RRR = 2.618, 95 % CI 1.801 - 3.989), children belonging to middle (RRR = 2.186, 95 % CI 1.473 - 3.243), richer (RRR = 1.908, 95 % CI 1.145 - 3.180) and richest households (RRR = 2.456, 95 % CI 1.363 - 4.424) and the 1998 survey period (RRR = 0.426, 95 % CI 0.240 - 7.58). Seeking self-care or visiting a traditional healer was significantly associated with maternal educational status (RRR = 0.000, 95 % CI 0.000 - 0.000), and the 1998 (RRR= 0.330, 95 % CI 0.142 - 0.765), 2003 (RRR= 0.195, 95 % CI 0.071 - 0.535), 2008 (RRR= 0.216, 95 % CI 0.068 - 0.685) and 2014 (RRR= 0.230, 95 % CI 0.081 - 0.657) GDHS periods. The probability that the odds ratio of using medical care exceeded 1 was higher for mothers/caregivers in the Western, Ashanti, Upper West, and Volta regions. CONCLUSIONS: Government policies that are aimed at encouraging medical care-seeking for children with ARI may yield positive results by focusing on improving maternal incomes, maternal NHIS enrolment, and maternal household characteristics. Improving maternal education could be a positive step towards addressing challenges with self-care or traditional healing amongst children with ARI.

Additive quantile mixed effects modelling with application to longitudinal CD4 count data.

Quantile regression offers an invaluable tool to discern effects that would be missed by other conventional regression models, which are solely based on modeling conditional mean. Quantile regression for mixed-effects models has become practical for longitudinal data analysis due to the recent computational advances and the ready availability of efficient linear programming algorithms. Recently, quantile regression has also been extended to additive mixed-effects models, providing an efficient and flexible framework for nonparametric as well as parametric longitudinal forms of data analysis focused on features of the outcome beyond its central tendency. This study applies the additive quantile mixed model to analyze the longitudinal CD4 count of HIV-infected patients enrolled in a follow-up study at the Centre of the AIDS Programme of Research in South Africa. The objective of the study is to justify how the procedure developed can obtain robust nonlinear and linear effects at different conditional distribution locations. With respect to time and baseline BMI effect, the study shows a significant nonlinear effect on CD4 count across all fitted quantiles. Furthermore, across all fitted quantiles, the effect of the parametric covariates of baseline viral load, place of residence, and the number of sexual partners was found to be major significant factors on the progression of patients' CD4 count who had been initiated on the Highly Active Antiretroviral Therapy study.

Determinants of Under-Five Children Body Mass Index in Sudan; Application of Quantile Regression: A Systematic Review.

BACKGROUND: One of the health challenges in Sub-Saharan countries is child malnutrition. Body Mass Index (BMI) can be defined as a measure of nutritional status. Examining the determinants of under-five children's BMI is a significant subject that needs to be studied. For this study, quantile regression was used to identify the determinants of under-five children's BMI in Sudan. METHODS: We used the 2014 Sudan Multiple Indicator Cluster Survey (MICS) conducted by the Central Bureau of Statistics. Quantile regression was used. RESULTS: Place of residence, state, mother's educational level, gender, age of the child, and wealth index were an important effect significantly affecting under-five children's BMI at different quantile levels. CONCLUSION: Taking measures on the nutritional status of mothers will accordingly resolve the nutritional status of their children. Therefore, the focus of policymakers should be on the influential significant factors which were found across all quantile levels to plan and develop strategies to enhance the normal or healthy weight status of under-five children in Sudan.

Negative binomial mixed models for analyzing longitudinal CD4 count data.

It is of great interest for a biomedical analyst or an investigator to correctly model the CD4 cell count or disease biomarkers of a patient in the presence of covariates or factors determining the disease progression over time. The Poisson mixed-effects models (PMM) can be an appropriate choice for repeated count data. However, this model is not realistic because of the restriction that the mean and variance are equal. Therefore, the PMM is replaced by the negative binomial mixed-effects model (NBMM). The later model effectively manages the over-dispersion of the longitudinal data. We evaluate and compare the proposed models and their application to the number of CD4 cells of HIV-Infected patients recruited in the CAPRISA 002 Acute Infection Study. The results display that the NBMM has appropriate properties and outperforms the PMM in terms of handling over-dispersion of the data. Multiple imputation techniques are also used to handle missing values in the dataset to get valid inferences for parameter estimates. In addition, the results imply that the effect of baseline BMI, HAART initiation, baseline viral load, and the number of sexual partners were significantly associated with the patient's CD4 count in both fitted models. Comparison, discussion, and conclusion of the results of the fitted models complete the study.

Modelling CD4 counts before and after HAART for HIV infected patients in KwaZulu-Natal South Africa.

BACKGROUND: This study aims to make use of a longitudinal data modelling approach to analyze data on the number of CD4+cell counts measured repeatedly in HIV-1 Subtype C infected women enrolled in the Acute Infection Study of the Centre for the AIDS Programme of Research in South Africa. METHODOLOGY: This study uses data from the CAPRISA 002 Acute Infection Study, which was conducted in South Africa. This cohort study observed N=235 incident HIV-1 positive women whose disease biomarkers were measured repeatedly at least four times on each participant. RESULTS: From the findings of this study, post-HAART initiation, baseline viral load, and the prevalence of obese nutrition status were found to be major significant factors on the prognosis CD4+ count of HIV-infected patients. CONCLUSION: Effective HAART initiation immediately after HIV exposure is necessary to suppress the increase of viral loads to induce potential ART benefits that accrue over time. The data showed evidence of strong individual-specific effects on the evolution of CD4+ counts. Effective monitoring and modelling of disease biomarkers are essential to help inform methods that can be put in place to suppress viral loads for maximum ART benefits that can be accrued over time at an individual level.

Factors affecting child malnutrition in Ethiopia.

BACKGROUND: One of the public health problems in developing countries is child malnutrition. An important factor for children's well-being is good nutrition. Therefore, the malnutrition status of children under the age of five is an important outcome measure for children's health. This study uses the proportional odds model to identify risk factors associated with child malnutrition in Ethiopia using the 2016 Ethiopian Demographic and Health Survey data. METHODS: This study uses the 2016 Ethiopian Demographic and Health Survey results. Based on weight-for-height anthropometric index (Z-score) child nutrition status is categorized into four levels namely- underweight, normal, overweight and obese. Since this leads to an ordinal variable for nutrition status, an ordinal logistic regression (OLR)proportional odds model (POM) is an obvious choice for analysis. RESULTS: The findings and comparison of results using the cumulative logit model with and without complex survey design are presented. The study results revealed that to produce the appropriate estimates and standard errors for data that were obtained from complex survey design, model fitting based on taking the survey sampling design into account is better. It has also been found that for children under the age of five, weight of a child at birth, mother's age, mother's Body Mass Index (BMI), marital status of mother and region (Affar, Dire Dawa, Gambela, Harari and Somali) were influential variables significantly associated with underfive children's nutritional status in Ethiopia. CONCLUSION: This child's age of a child, sex, weight of child at birth, mother's BMI and region of residence were significant determinants of malnutrition of children under five years in Ethiopia. The effect of these determinants can be used to develop strategies for reducing child malnutrition in Ethiopia. Moreover, these findings show that OLR proportional odds model is appropriate assessing thedeterminants of malnutrition for ordinal nutritional status of underfive children in Ethiopia.

Survival analysis of under-five mortality using Cox and frailty models in Ethiopia.

BACKGROUND: The risk of a child dying before reaching 5 years of age is highest in sub-Saharan African countries. But in Ethiopia, under-five mortality rates have shown a substantial decline. METHODS: For this study, the Cox regression model for fixed and time-dependent explanatory variables was studied for under-five mortality in Ethiopia. We adapted survival analysis using the Cox regression model with 2011 Ethiopian Demographic and Health Survey data. RESULTS: From the results, it was found that under-five children who live in Addis Ababa had a lower hazard (risk) of death (p value = 0.048). This could be as a result of higher health facilities and living standards in Addis Ababa, compared to other regions. Under-five children who lived in rural areas had a higher hazard (risk) of death compared to those living in urban areas. In addition, under-five children who lived in rural areas had 18% (p value = 0.01) more hazard (risk) of death than those living in urban areas. Furthermore, with older mothers, the chance of a child dying before reaching the age of 5 is lower. CONCLUSION: The chances of a child dying before reaching the age of 5 are less if the mother does not become pregnant again before the child reaches the age of 5. Therefore, giving birth when older and not becoming pregnant again before the child reaches the age of 5 is one means of reducing under-five mortality.

Comparison of under-five mortality for 2000, 2005 and 2011 surveys in Ethiopia.

BACKGROUND: Though the socio-economic situation of the Ethiopian household is improving along with the decrease in under-five child mortality. But, under-five mortality is still one of the major problems. Identification of the risk factors change over time which mismatches with the diminishing rate of under-five mortality is important to address the problems. METHODS: The survey data used for this research was taken from three different Ethiopian Demographic and Health Surveys (2000, 2005 and 2011). This data was used to identify the effect of time varying under-five mortality risk factors. The Cox proportional hazard model was adapted for the analysis. RESULTS: The effect of respondent's current age, age at first birth and educational level on the under-five mortality rate significantly diminishes in the recent surveys. On the other hand, the effect of the number of births in the last 5 years increases more in 2011 than in the earlier two surveys. Similarly, number of household members in the house and the number of under-five children in the house demonstrated a difference through years. Regarding total children ever born, child death is more for the year 2000 followed by 2005 and 2011. CONCLUSION: Based on the study, our findings confirmed that under-five mortality is a serious problem in the country. The analysis displayed that the hazard of under-five mortality has a decreasing pattern in years. The result for regions showed that there was an increase in years for some of the regions. This research work gives necessary information to device improved teaching for family planning and children health care to change the child mortality circumstance in the country. Our study suggests that the impact of demographic characteristics and socio-economic factors on child mortality should account for their integral changes over time.

Prevalence of rheumatic heart disease among school children in Ethiopia: A multisite echocardiography-based screening.

BACKGROUND: Auscultation-based surveys in Ethiopia conducted in the late 1990's reported a rural prevalence of 4.6/1000 and an urban prevalence of 6.4/1000 of rheumatic heart disease (RHD). With echo-based screening, we aimed to estimate the national prevalence of RHD in school children by taking school-based samples from six regions across the country using the 2012 World Heart Federation echocardiographic criteria. PATIENTS AND METHODS: We conducted a cross-sectional echocardiographic screening of RHD in school children aged 6-18years from 28 randomly selected primary and secondary schools found in six different geographic regions of Ethiopia. We used the standardized WHF echocardiographic criteria. RESULTS: A total of 3238 children (48.5% females) were screened. The mean age was 13.2±3.2years. Of these, 44 patients (1.4%) met the WHF criteria for definite RHD, while 15 (0.5%) met the criteria for borderline disease, yielding a prevalence of 19 [13.9-23.4, 95% CI] cases per 1000 school children between the ages of 6-18years. The majority of those who tested positive were girls (26/44). The prevalence was lowest in children aged 6-9years and otherwise uniformly distributed across ages 10-18years. Definite RHD involved the mitral valve in 42 subjects, 39 of whom had mitral regurgitation and 3 with mitral stenosis. The aortic valve was affected in 6 children. The ratio of definite to borderline cases was 2.9. CONCLUSION: This study demonstrated a consistent pattern of high prevalence of asymptomatic RHD with definite disease predominating over borderline involvement across six regions of Ethiopia.

Indirect child mortality estimation technique to identify trends of under-five mortality in Ethiopia.

BACKGROUND: In sub-Saharan African countries, the chance of a child dying before the age of five years is high. The problem is similar in Ethiopia, but it shows a decrease over years. METHODS: The 2000; 2005 and 2011 Ethiopian Demographic and Health Survey results were used for this work. The purpose of the study is to detect the pattern of under-five child mortality overtime. Indirect child mortality estimation technique is adapted to examine the under-five child mortality trend in Ethiopia. RESULTS: From the result, it was possible to see the trend of under-five child mortality in Ethiopia. The under-five child mortality shows a decline in Ethiopia. CONCLUSION: From the study, it can be seen that there is a positive correlation between mother and child survival which is almost certain in any population. Therefore, this study shows the trend of under-five mortality in Ethiopia and decline over time.

Determinants of fertility in Ethiopia.

BACKGROUND: The most important elements to determine the rate of population growth is fertility. Fertility is the main element to affect the welfare of mother. The survival of a child can be affected by high fertility and shorter birth intervals. METHODS: For this study, the linear mixed model was used to determine factors affecting fertility status of women in Ethiopia. The 2011 Ethiopian demographic and health survey data was used for this study. RESULTS: From the result, materials used for roof, wall and floor were found to have a significant relation to fertility level of women in the last five years. Moreover, family size and births in the last five years were found to have a significant relationship. CONCLUSION: Significant variation in fertility level was observed among rural and urban residents of Ethiopia. To reduce the gap of fertility between rural and urban population, it is important to modernize different factors. These factors could be access to education, media, and providing employment opportunities in the modern economic sector. Besides this, it is important to develop and maintain the access of family planning services.

Structured additive regression models with spatial correlation to estimate under-five mortality risk factors in Ethiopia.

BACKGROUND: The risk of a child dying before reaching five years of age is highest in Sub-Saharan African countries. But Child mortality rates have shown substantial decline in Ethiopia. It is important to identify factors affecting under-five mortality. METHODS: A structured additive logistic regression model which accounts the spatial correlation was adopted to estimate under-five mortality risk factors. The 2011 Ethiopian Demographic and Health Survey data was used for this study. RESULTS: The analysis showed that the risk of under-five mortality increases as the family size approaches seven and keeps increasing. With respect to socio-economic factors, the greater the household wealth, the lower the mortality. Moreover, for older mothers, the chance of their child to dying before reaching five is diminishes. CONCLUSION: The model enables simultaneous modeling of possible nonlinear effects of covariates, spatial correlation and heterogeneity. Our findings are relevant because the identified risk factors can be used to provide priority areas for intervention activities by the government to combat under-five mortality in Ethiopia.

Using Rasch modeling to re-evaluate rapid malaria diagnosis test analyses.

The objective of this study was to demonstrate the use of the Rasch model by assessing the appropriateness of the demographic, social-economic and geographic factors in providing a total score in malaria RDT in accordance with the model's expectations. The baseline malaria indicator survey was conducted in Amhara, Oromiya and Southern Nation Nationalities and People (SNNP) regions of Ethiopia by The Carter Center in 2007. The result shows high reliability and little disordering of thresholds with no evidence of differential item functioning.

Semiparametric models for malaria rapid diagnosis test result.

BACKGROUND: More than 75% of the total of Ethiopia is malarious. Therefore, malaria is a leading public health problem in Ethiopia. This study aims to identify socio-economic, geographic and demographic factors contributing to the spread of malaria and is based on the results of a malaria Rapid Diagnosis Test survey. METHODS: The data used in this study originates from the baseline malaria indicator survey, conducted in the Amhara, Oromiya and Southern Nation Nationalities and People (SNNP) regions of Ethiopia from December 2006 to January 2007. The study applies the method of generalized additive mixed model (GAMM) to analyse data. The response variable is the presence or absence of malaria, using the malaria Rapid Diagnosis Test (RDT). RESULTS: The results provide an improved insight into the distribution of malaria in relation to the age of affected people, the altitude, the total number of rooms, the total number of mosquito nets, family size, and the number of months that their rooms have been sprayed. The results confirm that positive malaria RDT test results are high for children under 15 years and for older persons. Gender, source of drinking water, time needed to fetch water, toilet facilities, main materials used for the construction of walls, floors and roofs, and use of mosquito nets were all found to have a significant impact on the results of the malaria rapid diagnosis test. CONCLUSION: The result of the analysis identifies poor socio-economic conditions as a major contributing factor or determinant for the spread of malaria. With the correct use of mosquito nets, indoor residual spraying with insecticide and other preventative measures, the incidence of malaria could be decreased. In addition, improving housing conditions is a means to reduce the risk of malaria. Other measures such as creating awareness of the use of mosquito nets, indoor residual spraying with insecticide, and malaria transmission, can lead to a further reduction in the number of malaria cases.

Multiple correspondence analysis as a tool for analysis of large health surveys in African settings.

BACKGROUND: More than two thirds of the total population of Ethiopia is estimated to be at risk of malaria. Therefore, malaria is the leading public health problem in Ethiopia. OBJECTIVE: To investigate the determinants of malaria Rapid Diagnosis Test (RDT) result and the association between socio-economic, demographic and geographic factors. METHOD: The study used data from household cluster malaria survey which was conducted from December 2006 to January 2007. A total of 224 clusters of about 25 households each were selected from the Amhara, Oromiya and Southern Nation Nationalities and People (SNNP) regions of Ethiopia. A multiple correspondence analysis was used to jointly analyse malaria RDT result, socio-economic, demographic and geographic factors. RESULTS: The result from multiple correspondence analysis shows that there is association between malaria RDT result and different socio-economic, demographic and geographic variables. CONCLUSION: There is an indication that some socio-economic, demographic and geographic factors have joint effects. It is important to confirm the association between socio-economic, demographic and geographic factors using advanced statistical techniques.

Spatial distribution of malaria problem in three regions of Ethiopia.

BACKGROUND: The transmission of malaria is the leading public health problem in Ethiopia. From the total area of Ethiopia, more than 75% is malarious. The aim of this study was to identify socio-economic, geographic and demographic risk factors of malaria based on the rapid diagnosis test (RDT) survey results and produce the prevalence map of the area illustrating variation in malaria risk. METHODS: This study accounts for spatial correlation in assessing the effects of socio- economic, demographic and geographic factors on the prevalence of malaria in Ethiopia. A total of 224 clusters of about 25 households each were selected from the Amhara, Oromiya and Southern Nation Nationalities and People's (SNNP) regions of Ethiopia. A generalized linear mixed model with spatial covariance structure was used to analyse the data where the response variable was the presence or absence of malaria using the RDT. RESULTS: The results showed that households in the SNNP region were found to be at more risk than Amhara and Oromiya regions. Moreover, households which have toilet facilities clean drinking water, and a greater number of rooms and mosquito nets in the rooms, have less chance of having household members testing positive for RDT. Moreover, from this study, it can be suggested that incorporating spatial variability is necessary for understanding and devising the most appropriate strategies to reduce the risk of malaria.

Prevalence and risk factors of malaria in Ethiopia.

BACKGROUND: More than 75% of the total area of Ethiopia is malarious, making malaria the leading public health problem in Ethiopia. The aim of this study was to investigate the prevalence rate and the associated socio-economic, geographic and demographic factors of malaria based on the rapid diagnosis test (RDT) survey results. METHODS: From December 2006 to January 2007, a baseline malaria indicator survey in Amhara, Oromiya and Southern Nation Nationalities and People (SNNP) regions of Ethiopia was conducted by The Carter Center. This study uses this data. The method of generalized linear model was used to analyse the data and the response variable was the presence or absence of malaria using the rapid diagnosis test (RDT). RESULTS: The analyses show that the RDT result was significantly associated with age and gender. Other significant covariates confounding variables are source of water, trip to obtain water, toilet facility, total number of rooms, material used for walls, and material used for roofing. The prevalence of malaria for households with clean water found to be less. Malaria rapid diagnosis found to be higher for thatch and stick/mud roof and earth/local dung plaster floor. Moreover, spraying anti-malaria to the house was found to be one means of reducing the risk of malaria. Furthermore, the housing condition, source of water and its distance, gender, and ages in the households were identified in order to have two-way interaction effects. CONCLUSION: Individuals with poor socio-economic conditions are positively associated with malaria infection. Improving the housing condition of the household is one of the means of reducing the risk of malaria. Children and female household members are the most vulnerable to the risk of malaria. Such information is essential to design improved strategic intervention for the reduction of malaria epidemic in Ethiopia.