Factors Associated with Cesarean Section in Tehran, Iran using Multilevel Logistic Regression Model

In this paper, multilevel logistic regression models are developed for examining the hierarchical effects of contraceptive use and its selected determinants in Oman using the 2008 Oman National Reproductive Health Survey (ONRHS). Comparison between single level and multilevel logistic regression models has been made to examine the plausibility of multilevel effects of contraceptive use. From the multilevel logistic regression model analysis, it was found that there is real multilevel variation among contraceptive users in Oman. The results indicate that a multilevel logistic regression model is the best fit over ordinary multiple logistic regression models. Generally, this study revealed that women’s age, education, number of living children and region of residence are important factors that affect contraceptive use in Oman. The effect of regional variation for age of women, education of women and number of living children further implies that there exists considerable differences in modern contraceptive use among regions, and a model with a random coefficient or slope is more appropriate to explain the regional variation than a model with fixed coefficients or without random effects. The study suggests that researchers should use multilevel models rather than traditional regression methods when their data structure is hierarchal.

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Determinants of Wasting Among Under-Five Children in Ethiopia: (A Multilevel Logistic Regression Model Approach)

International Journal of Statistics in Medical Research ◽

10.6000/1929-6029.2014.03.04.5 ◽

2014 ◽

Vol 3 (4) ◽

pp. 368-377 ◽

Cited By ~ 5

Author(s):

Gutu Dabale ◽

◽

M.K Sharma

Keyword(s):

Logistic Regression ◽

Regression Model ◽

Logistic Regression Model ◽

Multilevel Logistic Regression ◽

Under Five ◽

Under Five Children ◽

Multilevel Logistic Regression Model ◽

Model Approach

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Response to the Comment on: Factors Associated with Increased Pain in Primary Dysmenorrhea: Analysis Using a Multivariate Ordered Logistic Regression Model

Journal of Pediatric and Adolescent Gynecology ◽

10.1016/j.jpag.2018.03.009 ◽

2018 ◽

Vol 31 (4) ◽

pp. 433

Author(s):

Antonio Palazón-Bru ◽

María Isabel Tomás-Rodríguez ◽

José Vicente Toledo-Marhuenda ◽

Vicente Francisco Gil-Guillén

Keyword(s):

Logistic Regression ◽

Regression Model ◽

Logistic Regression Model ◽

Primary Dysmenorrhea ◽

Factors Associated ◽

Ordered Logistic Regression

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Household means of transportation and place of child delivery in Nigeria

10.21203/rs.3.rs-17304/v1 ◽

2020 ◽

Author(s):

Lukman Bola Solanke ◽

Omolayo Bukola Oluwatope ◽

Yinusa Rasheed Adebayo ◽

Olaoye James Oyeleye ◽

Benjamin Bukky Ilesanmi ◽

...

Keyword(s):

Logistic Regression ◽

Pregnant Women ◽

Logistic Regression Model ◽

Institutional Delivery ◽

Multilevel Logistic Regression ◽

Place Of Delivery ◽

Pooled Data ◽

Support Programme ◽

Mode Of Transport ◽

Multilevel Logistic Regression Model

Abstract Background The means of transportation available to pregnant women in households may serve either as a driver or deterrent of institutional delivery. However, how household means of transportation associates with place of delivery has been less explored in Nigeria. Methods This study was based on pooled data of 2008-2013 Nigeria Demographic and Health Survey. The study analysed a weighted sample size of 6,540 women. The multilevel logistic regression model was applied using STATA 14. Results The study revealed 37% institutional delivery among women in Nigeria. Women whose household mode of transport were cars were twice more likely to have institutional delivery compared to women who had no viable household means of transportation (AOR=2.044, p<0.01; CI=1.781-2.345). Women who live in communities with high proportions of households with no means of transportation were 12.8% less likely to have institutional delivery (AOR=0.872, p=0.01; CI: 0.788-0.967). Women who live in communities with high proportions of household who owned motorcycle compared to those in communities with low proportion were 31.9% more likely to have institutional delivery (AOR=1.319, p<0.05; CI: 1.071-1.625). Women who live in communities with high proportions of households who owned cars compared to those in communities with low proportion were more than three times more likely to have institutional delivery (AOR=3.146, p<0.01; CI: 2.621-3.777).Conclusion Means of transportation significantly explains choice of place of child delivery in urban Nigeria. A public-private transport support programme to reduce transportation burden among pregnant women is imperative in the country.

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Individual and community level factors associated with anemia among children 6—59 months of age in Ethiopia: A further analysis of 2016 Ethiopia demographic and health survey

PLoS ONE ◽

10.1371/journal.pone.0241720 ◽

2020 ◽

Vol 15 (11) ◽

pp. e0241720

Author(s):

Menaseb Gebrehaweria Gebremeskel ◽

Afework Mulugeta ◽

Abate Bekele ◽

Lire Lemma ◽

Muzey Gebremichael ◽

...

Keyword(s):

Health Survey ◽

Logistic Regression Model ◽

Demographic And Health Survey ◽

Community Level ◽

Multilevel Logistic Regression ◽

Factors Associated ◽

Dire Dawa ◽

Poverty Status ◽

The Individual ◽

Multilevel Logistic Regression Model

Background Anemia is a global public health problem; but its burden is disproportionately borne among children in the African Regions. The 2016 Ethiopia Demographic and Health Survey report showed that the prevalence of anemia among children 6–59 months of age was 57%; far exceeding the national target of 25% set for 2015. Although studies have been conducted in Ethiopia, multilevel analysis has rarely been used to identify factors associated with anemia among children. Therefore, this study aimed to identify individual and community-level factors associated with anemia among children 6–59 months of age by fitting a multilevel logistic regression model. Methods The data was obtained from the 2016 Ethiopia Demographic and Health Survey, conducted from January to June 2016, and downloaded from the website http://www.DHSprogram.com. The sample was taken using two-stage stratified sampling. In stage one, 645 Enumeration Areas and in stage two 28 households per Enumeration Area were selected. A sample of 7790 children 6–59 months of age was included. Data were analyzed using STATA version 14. A multilevel logistic regression model was fitted and an adjusted odds ratio with a 95% confidence interval was obtained. Result From the individual-level factors, anemia was associated most strongly with child age, wealth index, maternal anemia and child stunting followed by child underweight, child fever and birth order whereas from the community-level, the strongest odds of anemia occurred among children from Somali, Harari, Dire Dawa and Afar region followed by Oromia and Addis Ababa. Low community-poverty is a protective factor for anemia. The odds of anemia were 0.81 (95% CI: 0.66, 0.99) times lower for children who were living in communities of lower poverty status than children who were living in communities of higher poverty status. Children from Somali and Dire Dawa had 3.38 (95% CI: 3.25, 5.07) and 2.22 (95% CI: 1.42, 3.48) times higher odds of anemia, respectively than children from the Tigray region. Conclusions This study shows that anemia among children 6–59 months of age is affected both by the individual and community level factors. It is better to strengthen the strategies of early detection and management of stunted and underweight children. At the same time, interventions should be strengthened to address maternal anemia, child fever and poverty, specifically targeting regions identified to have a high risk of anemia.

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Association of maternal obesity with fetal and neonatal death: Evidence from South and South-East Asian countries

PLoS ONE ◽

10.1371/journal.pone.0256725 ◽

2021 ◽

Vol 16 (9) ◽

pp. e0256725

Author(s):

Rezwanul Haque ◽

Syed Afroz Keramat ◽

Syed Mahbubur Rahman ◽

Maimun Ur Rashid Mustafa ◽

Khorshed Alam

Keyword(s):

Logistic Regression ◽

Risk Factor ◽

Regression Model ◽

Neonatal Death ◽

Logistic Regression Model ◽

Maternal Obesity ◽

East Asian ◽

Multilevel Logistic Regression ◽

Asian Countries ◽

Neonatal Deaths

Background Obesity prevalence is increasing in many countries in the world, including Asia. Maternal obesity is highly associated with fetal and neonatal deaths. This study investigated whether maternal obesity is a risk factor of fetal death (measured in terms of miscarriage and stillbirth) and neonatal mortality in South and South-East Asian countries. Methods This cross-sectional study pooled the most recent Demographic and Health Surveys (DHS) from eight South and South-East Asian countries (2014–2018). Multivariate logistic regression was deployed to check the relationships between maternal obesity with fetal and neonatal deaths. Finally, multilevel logistic regression model was employed since the DHS data has a hierarchical structure. Results The pooled logistic regression model illustrated that maternal obesity is associated with higher odds of miscarriage (adjusted odds ratio [aOR]: 1.26, 95% CI: 1.20–1.33) and stillbirths (aOR: 1.46, 95% CI: 1.27–1.67) after adjustment of confounders. Children of obese mothers were at 1.18 (aOR: 1.18, 95% CI: 1.08–1.28) times greater risk of dying during the early neonatal period than mothers with a healthy weight. However, whether maternal obesity is statistically a significant risk factor for the offspring’s late neonatal deaths was not confirmed. The significant association between maternal obesity with miscarriage, stillbirth and early neonatal mortality was further confirmed by multilevel logistic regression results. Conclusion Maternal obesity in South and South-East Asian countries is associated with a greater risk of fetal and early neonatal deaths. This finding has substantial public health implications. Strategies to prevent and reduce obesity should be developed before planning pregnancy to reduce the fetal and neonatal death burden. Obese women need to deliver at the institutional facility centre that can offer obstetrics and early neonatal care.

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A One Health perspective to identify environmental factors that affect Rift Valley fever transmission in Gezira state, Central Sudan

Tropical Medicine and Health ◽

10.1186/s41182-019-0178-1 ◽

2019 ◽

Vol 47 (1) ◽

Author(s):

Rania Salah Eldien Bashir ◽

Osama Ahmed Hassan

Keyword(s):

Remote Sensing ◽

Logistic Regression ◽

Environmental Factors ◽

Soil Type ◽

Rift Valley ◽

Rift Valley Fever ◽

Logistic Regression Model ◽

Multilevel Logistic Regression ◽

Valley Fever ◽

Multilevel Logistic Regression Model

Abstract Background Rift Valley fever (RVF) is a zoonotic viral vector-borne disease that affects both animals and humans and leads to severe economic consequences. RVF outbreaks are triggered by a favorable environment and flooding, which enable mosquitoes to proliferate and spread the virus further. RVF is endemic to Africa and has spread to Saudi Arabia and Yemen. There is great concern that RVF may spread to previously unaffected geographic regions due to climate change. We aimed to better understand the spatiotemporal pattern of the 2007 RVF outbreak at the human–animal–environment interface and to determine environmental factors that may have effects on RVF occurrence in Gezira state, Sudan. Materials and methods We compiled epidemiological, environmental, and spatiotemporal data across time and space using remote sensing and a geographical information system (GIS). The epidemiological data included 430 RVF human cases as well as human and animal population demographic data for each locality. The cases were collected from 41 locations in Gezira state. The environmental data represent classified land cover during 2007, the year of the RVF outbreak, and the average of the Normalized Difference Vegetation Index (NDVI) for 6 months of 2007 is compared with those of 2010 and 2014, when there was no RVF outbreak. To determine the effect of the environmental factors such as NDVI, soil type, and RVF case’s location on the Blue Nile riverbank on RVF incidence in Gezira state, a multilevel logistic regression model was carried out. Results We found that the outbreak in Gezira state occurred as a result of interaction among animals, humans, and the environment. The multilevel logistic regression model (F = 43,858, df = 3, p = 0.000) explained 23% of the variance in RVF incidence due to the explanatory variables. Notably, soil type (β = 0.613, t = 11.284, p = 0.000) and NDVI (β = − 0.165, t = − 3.254, p = 0.001) were the explanatory environmental factors that had significant effects on RVF incidence in 2007 in Gezira state, Sudan. Conclusions Precise remote sensing and the GIS technique, which rely on environmental indices such as NDVI and soil type that are satellite-derived, can contribute to establishing an early warning system for RVF in Sudan. Future preparedness and strengthening the capacity of regional laboratories are necessary for early notification of outbreaks in animals and humans.

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294. Hepatitis C Virologic Response in Hepatitis B and C Coinfected Persons Treated with Directly Acting Antiviral Agents: Results from ERCHIVES

Open Forum Infectious Diseases ◽

10.1093/ofid/ofz360.369 ◽

2019 ◽

Vol 6 (Supplement_2) ◽

pp. S159-S160

Author(s):

Adeel A Butt ◽

Peng Yan ◽

Samia Aslam ◽

Kenneth Sherman ◽

Dawd Siraj ◽

...

Keyword(s):

Logistic Regression ◽

Hepatitis C ◽

Liver Fibrosis ◽

Hepatitis B ◽

Regression Model ◽

Logistic Regression Model ◽

Antiviral Agents ◽

Virologic Response ◽

Hbv Infection ◽

Factors Associated

Abstract Background There are scant data regarding hepatitis C (HCV) virologic response to directly acting antiviral agents (DAAs) in chronic hepatitis B (HBV) and HCV coinfected persons. HCV treatment response in those with spontaneously cleared HBV infection is unknown. Methods All HCV-infected persons treated with a DAA regimen in ERCHIVES were identified and categorized into HBV/HCV-coinfected (HBsAg, HBV DNA or both positive), HCV-monoinfected, and resolved HBV (isolated HBcAb+). SVR rates were determined and compared for all groups. A logistic regression model was used to determine factors associated with SVR. Results Among 115 HCV/HBV-coinfected, 38,570 HCV-monoinfected persons, and 13,096 persons with resolved HBV, 31.6% of HCV/HBV-coinfected, 24.6% of HCV-monoinfected and 26.4% with resolved HBV had cirrhosis at baseline. SVR was achieved in 90.4% of HCV/HBV-coinfected, 83.4% of HCV-monoinfected and 84.5% of those with resolved HBV infection (P = 0.04 HCV/HBV vs. HCV monoinfected). In a logistic regression model, those with HCV/HBV were more likely to achieve SVR compared with HCV monoinfected (OR 2.25, 95% CI 1.17, 4.31). For HCV/HBV coinfected, the SVR rates dropped numerically with increasing severity of liver fibrosis (P-value non-significant). Factors associated with a lower likelihood of attaining SVR included cirrhosis at baseline (OR 0.85, 95% CI 0.80, 0.92), diabetes (OR 0.93, 95% CI 0.87, 0.99) and higher pretreatment HCV RNA (OR 0.86, 95% CI 0.84, 0.87). Conclusion HBV/HCV-coinfected persons have higher overall SVR rates with newer DAA regimens. The virologic response is graded, with decreasing SVR rates with increasing degree of liver fibrosis as determined by the FIB-4 scores. Disclosures All authors: No reported disclosures.

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