Lowest Deviance Research Articles

Multilevel analysis of individual and community factors of awareness of obstetric fistula among women of childbearing age in Nepal: analysis of recent Nepal Demographic and Health Survey 2022 data

BackgroundAccording to the WHO, obstetric fistula (OBF) is an abnormal connection between the genital tract and the urinary tract that occurs as the result of obstetric trauma, typically from prolonged...

Spatial distribution and determinants of measles vaccination dropout among under-five children in Ethiopia: A spatial and multilevel analysis of 2019 Ethiopian demographic and health survey.

Each year, vaccine-preventable diseases cost the lives of 8.8 million under-five children. Although vaccination prevents 1-2 million childhood deaths worldwide, measles vaccination dropouts are not well studied in developing countries, particularly in Ethiopia. Therefore, this study aims to assess the spatial distribution of the measles vaccination dropout and its determinants among under-five children in Ethiopia. Data from Ethiopian Demographic and Health Survey 2019 was used for data analysis. The study used a total of 5,753 children. Spatial autocorrelations was used to determine the spatial dependency of measles vaccination dropout. Ordinary interpolation was employed to forecast measles vaccination dropout. Factors associated with measles vaccination dropout were declared significant at p-values <0.05. The data were interpreted using the confidence interval and adjusted odds ratio. A model with the lowest deviance and highest logliklihood ratio was selected as the best-fit model. In Ethiopia, one in three under-five children had measles vaccination dropouts. Factors such as birth interval (AOR = 1.87, 95% CI: 1.30, 2.70), unmarried marital status women (AOR = 3.98, 95% CI: 1.08, 8.45), ≤1 number of under-five children (AOR = 3.86, 95% CI: 2.56, 5.81), rural place of residence (AOR = 2.43, 95% CI: 2.29, 3.11), low community-level ANC utilization (AOR = 3.20, 95% CI: 2.53, 3.56), and residing in Benishangul Gumuz (AOR = 1.80, 95% CI: 1.061, 3.06) had higher odds of measles vaccination dropout. Measles vaccination dropout rates in Ethiopia among under-five children were high compared to the maximum tolerable vaccination dropout level of 10% by the WHO. Both individual and community-level variables were determinants of measles vaccination dropout. The ministry of health in Ethiopia should give attention to those mothers of under-five children who reported underutilization of ANC services and rural residences while designing policies and strategies in areas of high spatial clustering of vaccine dropout in Ethiopia.

Knowledge of fertility period among reproductive age women in Kenya: a multilevel analysis based on 2022 Kenyan demographic and health survey

BackgroundKnowledge of the fertility period aids women in refraining and engaging in sexual intercourse to avoid and to get pregnant, respectively. The effect of community-level factors on knowledge of the fertility period was not yet known in Kenya. Therefore, we aimed to investigate the community- and individual-level determinants of knowledge of fertility period among women of childbearing age in Kenya.MethodsThe 2022 Kenyan Demography and Health Survey data was used for the current study. This study included 16,901 women of reproductive age. To account for the clustering effects of DHS data and the binary nature of the outcome variable, a multilevel binary logistic regression model was applied. An adjusted odds ratio with a 95% confidence interval was reported to declare the statistical significance. In addition, the model that had the lowest deviance was the one that best fit the data.ResultsThe overall prevalence of knowledge of the fertility period among Kenyan women was 38.1% (95%CI = 37.3, 38.9). Women’s age, women’s education status, heard FP, contraceptive use, media exposure, and distance from health facility significant individual factors while place of residence, and community-level education, were all of factors were found to be strongly associated with knowledge of fertility period.ConclusionAs per the findings of our study, Knowledge of the fertility period among reproductive women was low in Kenya. In the era of increasing refusal of hormone-based family planning, fertility-awareness-based family planning methods may be an option. Promoting the correct fertility period through education and media outreach may be helpful strategies for enhancing fertility decision-making.

Individual and community-level determinants of knowledge about fertile periods among adolescent girls and young women (10–24 years) in Sub-Saharan Africa: A multilevel mixed effect analysis of a recent demographic and health survey

BackgroundIdentifying fertility periods accurately will protect teenage girls and young women from unintended pregnancies and related complications. However, in Sub-Saharan Africa, knowledge of the fertile period among adolescent girls and young women is not well studied. Thus, the purpose of this study was to assess adolescents' and young women's knowledge regarding fertility periods and its determinants in Sub-Saharan Africa. MethodsThe most recent demographic and health surveys' data were used. The study had 140,064 participants in all. The data was analyzed using STATA/SE version 14. Using a multilevel logistic regression model, factors associated with knowledge of fertile periods have been determined. P-values <0.05 showed the significance of the factors associated with the outcome variable. The data were interpreted using the adjusted odds ratio and confidence interval. The best-fit model was determined to be the one with the highest logliklihood ratio and the lowest deviance. ResultsOne in five (20%) women between the ages of 10 and 24 had accurate knowledge about the fertile period. Age (AOR = 1.44, 95% CI: 1.40, 1.49), educational level (AOR = 1.68, 95% CI: 1.60, 1.77), knowledge of family planning (AOR = 1.33, 95% CI: 1.27, 1.39), distance (AOR = 2.31, 95% CI: 2.02, 2.98), residence (AOR = 1.06, 95% CI: 1.02, 1.10), and low community poverty (AOR = 3.06, 95% CI: 3.01, 3.12) had higher odds of knowledge about fertile period. ConclusionThis research finds that adolescents and young women in sub-Saharan Africa have low knowledge of the reproductive period. It was discovered that factors at the individual and communal levels influence women's knowledge of the fertile period. While developing policies and strategies, the health ministries of Sub-Saharan African countries had to take into consideration input from women whose experiences indicated that obtaining reproductive health services was hindered by distance.

Individual and community-level determinants of pentavalent vaccination dropouts among under-five children in the sub-Saharan African countries: A multilevel analysis of the recent demographic and health survey

BackgroundGlobally, each year, about 3 million deaths among children are prevented by pentavalent vaccinations. However, in developing countries, particularly in Sub-Saharan Africa, pentavalent vaccination dropout rates are not well reported. Therefore, this study aimed to assess pentavalent vaccination dropout rates and their determinants among under-five children in Sub-Saharan Africa. MethodsData from the recent Demographic and Health Surveys in 33 Sub-Saharan African countries were used for analysis. The study used a total of 358,529 under-five children. The determinants of pentavalent vaccination dropout were determined using a multilevel mixed-effects logistic regression model. Significant factors associated with pentavalent vaccination dropout were declared significant at p-values < 0.05. A model with the lowest deviance and highest logliklihood ratio was selected as the best-fit model. ResultsIn Sub-Saharan Africa, one in five under-five children had pentavalent vaccination dropout rates. Factors such as Age (AOR = 1.61, 95 % CI: 1.51, 1.72), educational level (AOR = 1.30, 95 % CI: 1.22, 1.40), place of delivery (AOR = 1.65, 95 % CI: 1.57, 1.73), ANC visits (AOR = 1.34, 95 % CI: 1.23, 1.45), postnatal check-up (AOR = 1.19, 95 % CI: 1.14, 1.25), wealth status (AOR = 1.09, 95 % CI: 1.04, 1.15), distance to health facility (AOR = 1.08, 95 % CI: 1.03, 1.13), media exposure (AOR = 1.12, 95 % 1.15), and geographical region (AOR = 1.60, 95 % CI: 1.49, 1.72) had higher odds of pentavalent vaccination dropouts. ConclusionsPentavalent vaccination dropout rates in sub-Saharan Africa among under-five children were high. Both individual and community-level variables were determinants of pentavalent vaccination dropout rates. Government and ministry of health in Sub-Saharan Africa should give attention to those mothers of under-five children who reported distance as a big problem in accessing health facilities and to women who do not utilise antenatal and postnatal check-ups while designing policies and strategies in sub-Saharan Africa.

Integrating Statistical Models and Principal Component Analysis to Assess Grasshopper Distribution and Diversity in Matiari District, Sindh, Pakistan

This study offers a comprehensive analysis of grasshopper diversity and distribution across different sites of Matiari district, Sindh, Pakistan during 2021-22 by using advanced statistical and ecological methodologies. This research documented ten grasshopper species, revealing significant spatial and temporal patterns. Acrotylus humertianus and Aiolopus thalassinus were widely distributed, with Acrotylus humertianus showing peak abundance in Mooro Lakho, while Oedaleus rosesense demonstrated the highest overall density, reaching up to 20 individuals per site. Notably, species richness peaked at ten species in Hala during April 2022, indicating substantial temporal variability. Principal Component Analysis (PCA) highlighted distinct ecological niches, with Acrotylus humertianus scoring highly on PC1, suggesting it thrives under specific conditions. The Shannon-Wiener Index revealed Bhit Shah and Mooro Lakho as the most diverse sites, while Simpson's Diversity Index indicated lower diversity in Saedabad. The correlation analysis showed a moderate positive relationship between temperature and grasshopper density (r = 0.452), while humidity and soil type had minimal effects. Generalized Linear Model (GLM) analysis identified Locusta migratoria as the most effective model, with the lowest Deviance, AIC, and BIC values, reflecting its optimal fit. The study emphasizes the complex interplay between environmental factors and grasshopper populations, providing crucial insights for biodiversity conservation and ecological research. These results highlight the dynamic nature of grasshopper ecology and underscore the need for targeted conservation strategies based on environmental and temporal variations.

Determinants of high-risk fertility behavior among women of reproductive age in Kenya: a multilevel analysis based on 2022 Kenyan demographic and health survey

BackgroundWomen’s high-risk fertility behavior (HRFB), which is characterized by narrow birth intervals, high birth order, and younger maternal age at birth, have been scientifically reported to have detrimental effects on the mother and child’s health. To date, there has been limited research into the underlying factors contributing to high-risk fertility behavior in Kenya. Thus, the aim of this study is to identify the factors associated with high-risk fertility behavior among women of reproductive age in Kenya.MethodThe 2022 Kenyan Demography and Health Survey data was used for the current study. This study included 15,483 women of reproductive age. To account for the clustering effects of DHS data and the binary nature of the outcome variable, a multilevel binary logistic regression model was applied. An adjusted odds ratio with a 95% confidence interval was reported to declare the statistical significance. In addition, the model that had the lowest deviance was the one that best fit the data.ResultsThe overall prevalence of HRFB among Kenyan women were 70.86% (95%CI = 69.96, 71.40). Women with primary, secondary, and higher educational levels, Protestant and Muslim religion followers, women whose husbands/partners had secondary and higher educational levels, a high household wealth index, ever had a terminated pregnancy, and rural residence, all of these factors were found to be strongly associated with high-risk fertility behavior.ConclusionAs per the findings of our study, in Kenya a significant proportion of women has experienced HRFB. This is a matter of concern as it poses a significant challenge to the healthcare system. The high prevalence of HRFB indicates that there is an urgent need to take appropriate measures in order to mitigate its impact. The situation calls for a comprehensive and coordinated approach involving all stakeholders to address this issue effectively. It would benefit policymakers to create programs that consider factors like education, wealth, and residence that make women more susceptible to HRFB. Targeting women living in high HRFB-prevalence areas could help address the root causes of the issue. This approach can alleviate negative impacts and ensure effective and sustainable solutions.

An unacceptably high burden of anaemia and it’s predictors among young women (15–24 years) in low and middle income countries; set back to SDG progress

BackgroundAnaemia is a major global public health problem, considerably affects young women in resource limited countries. The available researches on anaemia focused on children, pregnant women, or all women of reproductive age. However, women's biology and life experiences vary dramatically across 15 to 49 years, putting young women bear the higher burden of anaemia, mainly in low and middle income countries (LMICs). Therefore, this study assessed the burden of anaemia among young women (15–24 years) in 24 LMICs which conducted Demographic and Health Surveys (DHS) between 2016 and 2021.MethodData analysis was carried out with STATA version 14. The forest plot was used to explore the pooled prevalence of anaemia. Multilevel binary logistic regression was fitted to accommodate the hierarchical nature of the DHS data. Accordingly, a model with lowest deviance (model III) was the best-fitted model. All variables with a p-value ≤ 0.2 in the bi-variable analysis were fitted in the multi-level multivariable model. Adjusted odds ratio with 95% CI and p < 0.05 were presented to declare statistical significance.ResultThe pooled prevalence of anaemia among young (15–24 years) women in 24 LMICs was 41.58% (95%CI: 34.51, 48.65). Country wise, Mali (62.95%) and Rwanda (14.13%) constitute the highest and lowest prevalence of anaemia. In this study, young women who lived in the poorest wealth status, had no education, were underweight, perceived distance to the health facility a big problem, larger family size, and women who had ever terminated pregnancy were associated with increased odds of anaemia. Whereas, young women who were overweight and not breast feeding had decreased odds of anaemia.ConclusionThe unacceptably high burden of anaemia among young women setbacks the SDG target; to end all forms of malnutrition by 2030. Therefore, it is highly recommended to take relevant interventions to reduce the burden of anaemia targeted the young women who are uneducated, have low socio-economic status, limited access to health facilities, and lived in larger family size.

A practical illustration of spatial smoothing methods for disconnected regions with INLA: spatial survey on overweight and obesity in Malaysia

BackgroundNational prevalence could mask subnational heterogeneity in disease occurrence, and disease mapping is an important tool to illustrate the spatial pattern of disease. However, there is limited information on techniques for the specification of conditional autoregressive models in disease mapping involving disconnected regions. This study explores available techniques for producing district-level prevalence estimates for disconnected regions, using as an example childhood overweight in Malaysia, which consists of the Peninsular and Borneo regions separated by the South China Sea. We used data from Malaysia National Health and Morbidity Survey conducted in 2015. We adopted Bayesian hierarchical modelling using the integrated nested Laplace approximation (INLA) program in R-software to model the spatial distribution of overweight among 6301 children aged 5–17 years across 144 districts located in two disconnected regions. We illustrate different types of spatial models for prevalence mapping across disconnected regions, taking into account the survey design and adjusting for district-level demographic and socioeconomic covariates.ResultsThe spatial model with split random effects and a common intercept has the lowest Deviance and Watanabe Information Criteria. There was evidence of a spatial pattern in the prevalence of childhood overweight across districts. An increasing trend in smoothed prevalence of overweight was observed when moving from the east to the west of the Peninsular and Borneo regions. The proportion of Bumiputera ethnicity in the district had a significant negative association with childhood overweight: the higher the proportion of Bumiputera ethnicity in the district, the lower the prevalence of childhood overweight.ConclusionThis study illustrates different available techniques for mapping prevalence across districts in disconnected regions using survey data. These techniques can be utilized to produce reliable subnational estimates for any areas that comprise of disconnected regions. Through the example, we learned that the best-fit model was the one that considered the separate variations of the individual regions. We discovered that the occurrence of childhood overweight in Malaysia followed a spatial pattern with an east–west gradient trend, and we identified districts with high prevalence of overweight. This information could help policy makers in making informed decisions for targeted public health interventions in high-risk areas.

Determinants of knowledge of the highest conception probability period among reproductive age women in Low-Income African countries: A multilevel analysis based on the recent Demographic and Health Survey.

Adequate knowledge about the highest conception probability period in the reproductive cycle allows individuals and couples to attain or avoid their fertility probabilities. Poor knowledge of conception probability period leads to undesirable outcomes like unwanted pregnancy, miscarriage, and abortion. Determinants of knowledge of highest conception probability period were not well studied on economically disadvantaged countries. Therefore, our study aimed to identify individual and community level factors of knowledge of the highest conception probability period among women of reproductive age in low income African countries. The appended and latest Demographic and Health Survey datasets of 15 low-income African countries was used for analysis. Model fitness was done using the Intraclass correlation coefficient, median odds ratio, and deviance. A model with the lowest deviance (model-III) was selected as the best model. Multilevel logistic regression model was used to identify determinant factors of knowledge of the highest conception probability period. In the final model, adjusted odds ratio with 95% confidence interval was reported and variables with p<0.05 were considered as statistically significant with knowledge of the highest conception probability period. Total weighted sample of 235,574 reproductive aged women with a median age of 27 years were included. The correct knowledge of the highest conception probability period among the study participants was 24.04% (95%CI = 23.87-24.22%). Maternal age groups ((20-24 (AOR = 1.49; 95%CI = 1.44-1.55), 25-29 (AOR = 1.62; 1.56-1.68), 35-39 (AOR = 1.76; 1.68-1.84), 40-44 (AOR = 1.75; 1.67-1.83), and 45-49 (AOR = 1.83; 1.74-1.93)), marital status((currently in union (AOR = 1.75; 1.16; 1.13-1.20), formerly in union (AOR = 1.75; 1.11; 1.06-1.16)), better educational status ((secondary (AOR = 2.08; 2.01-2.14) and higher(AOR = 3.36; 3.18-3.55)), higher wealth index ((middle (AOR = 1.08; 1.04-1.12), richer (AOR = 1.24; 1.20-1.28), and richest (AOR = 1.51; 1.45-1.57)), knowledge of contraceptive methods (AOR = 2.63; 2.49-2.77), current contraceptive use (AOR = 1.14; 1.11-1.16), and urban residency (AOR = 1.26; 1.21-1.29) were statistically significant with knowledge of the highest conception probability period. In this study, knowledge of the highest conception probability period among women of reproductive age in low-income African countries was low. Therefore, improving the fertility awareness through comprehensive reproductive education or counseling could be one of the operational ways to control unintended pregnancy.

Prevalence and associated factors of early sexual initiation among youth female in sub-Saharan Africa: a multilevel analysis of recent demographic and health surveys

BackgroundEarly sexual initiation is a major public health concern globally, specifically in Sub-Saharan African (SSA) countries where reproductive health care services are limited. It is strongly related to increased risk of HIV/AIDS, sexually transmitted diseases, unwanted pregnancy, adverse birth outcomes, and psychosocial problems. However, there is limited evidence on the prevalence and associated factors of early sexual initiation among youth females in SSA.MethodsA secondary data analysis was employed based on the recent DHSs of sub-Saharan African countries. A total weighted sample of 184,942 youth females was considered for analysis. Given the hierarchical nature of DHS data, a multilevel binary logistic regression model was fitted. The Intra-class Correlation Coefficient (ICC), Median Odds Ratio (MOR), and Likelihood Ratio (LR) test were used to assess the presence of clustering. Four nested models were fitted and the model with the lowest deviance (-2LLR0 was selected as the best-fitted model. Variables with p-value < 0.2 in the bivariable multilevel binary logistic regression analysis were considered for the multivariable analysis. In the multivariable multilevel binary logistic regression analysis, the Adjusted Odds Ratio (AOR) with the 95% Confidence Interval (CI) was reported to declare the strength and statistical significance of the association.ResultsThe prevalence of early sexual initiation among youth females in sub-Saharan Africa was 46.39% [95%CI: 41.23%, 51.5%] ranging from 16.66% in Rwanda to 71.70% in Liberia. In the final model, having primary level education [AOR = 0.82, 95% CI; 0.79, 0.85], and [AOR = 0.50, 95%CI; 0.48, 0.52], being rural [AOR = 1.05, 95%CI: 1.03, 1.07], having media exposure [AOR = 0.91, 95%CI: 0.89, 0.94], and belonged to a community with high media exposure [AOR = 0.92, 95%CI: 0.89,0.96] were found significantly associated with early sexual initiation.ConclusionThe prevalence of early sexual initiation among youth females in SSA was high. Educational status, wealth index, residence, media exposure, and community media exposure have a significant association with early sexual initiation. These findings highlight those policymakers and other stakeholders had better give prior attention to empowering women, enhancing household wealth status, and media exposure to increase early sexual in the region.

Incidence of infant mortality and its predictors in East Africa using Gompertz gamma shared frailty model

BackgroundGlobally, infant mortality is a major public health concern and a sensitive indicator of countries' socio-economic and health status. Despite the substantial reduction of under-five mortality in sub-Saharan African countries specifically in East Africa, the infant mortality rate remains highest and too far below to achieve the WHO target. As to our search of the literature is concerned, there is a dearth of evidence on the incidence and predictors of infant mortality in East Africa. Therefore, this study investigated the incidence of infant mortality and its predictors in East Africa.MethodsThe present study has utilized 138,803 weighted samples from Demographic and Health Surveys (DHSs) of 12 East African countries. Considering the hierarchical nature of DHS data shared frailty parametric survival models were fitted and compared based on deviance (-2LLR), AIC, and BIC. Gompertz gamma shared frailty model was the best-fitted model for the data since it had the lowest deviance, AIC, and BIC values. Variables with a p-value < 0.2 in the bi-variable analysis were considered for the multivariable analysis. In the multivariable Gompertz gamma shared analysis, the Adjusted Hazard Ratio (AHR) with 95% Confidence Interval (CI) was reported to declare the significant predictors of infant mortality.ResultsThe infant mortality rate in East Africa was 41.41 per 1000 live births. Mothers aged 25–34 years, wanted birth, health facility delivery, 1–3 ANC visit, being 2nd- 4th birth order, 5th and above, the birth interval of 24–48 months, and birth interval of 49 months and above were significantly associated with lower risk of infant mortality. Whereas women who didn’t have formal education, women who didn't participate in making health care decisions making, being male children, cesarean delivery, small size at birth, and large size at birth were significantly associated with a higher risk of infant mortality.ConclusionDespite the substantial progress in improving maternal and child health, this study showed that infant mortality is still a major public health concern in East Africa. Maternal age, place of delivery, maternal education, birth size, sex of the child, mode of delivery, women's autonomy, birth order, birth interval, and ANC visit were found to be significant predictors of infant mortality. Therefore, public health interventions enhancing health facility delivery, ANC visit, maternal education, birth spacing, and empowering women are crucial for reducing the incidence of infant mortality in East Africa.

Individual and community-level determinants of knowledge of ovulatory cycle among women of childbearing age in Ethiopia: A multilevel analysis based on 2016 Ethiopian Demographic and Health Survey.

Knowledge of the ovulatory cycle (KOC) aids women to refrain and engage in sexual intercourse to avoid and to get pregnancy, respectively. The effect of community-level factors on KOC was not yet known in Ethiopia. Therefore, we aimed to investigate the community- and individual-level determinants of KOC among women of childbearing age. We used the 2016 Ethiopian Demographic and Health Survey, and total weighted samples of 15,683 women were included. Intra-class correlation, median odds ratio, and deviance were executed for model comparison in which a model with the lowest deviance was the best model i.e. model III in this case. A multivariable multilevel logistic regression model was employed to identify community- and individual-level factors of correct KOC. In the ultimate model, an adjusted odds ratio (AOR) with a 95% confidence interval was reported and variables with a p<0.05 were considered as statistically significant. In this study, 3,698 [23.58% (95% CI; 22.92-24.25)] participants had correct KOC. Women's age in years, i.e. 20-24 (AOR = 1.46;1.28-1.68) 25-29 (AOR = 1.72; 1.49-1.99), 30-34 (AOR = 2.21; 1.89-2.58), 35-39 (AOR = 1.78; 1.51-2.09), 40-44 (AOR = 1.97; 1.65-2.37), and 45-49 (AOR = 1.78; 1.44-2.19), knowledge of contraceptive methods (AOR = 3.08; 2.07-4.58), increased women's educational level, i.e. higher (AOR = 4.24; 3.54-5.07), secondary (AOR = 2.89; 2.48-3.36), and primary (AOR = 1.57; 1.39-1.78), higher household's wealth index, i.e. richest (AOR = 1.71; 1.35-2.16), richer (AOR = 1.42; 1.16-1.72), middle (AOR = 1.29; 1.07-1.56), and poorer (AOR = 1.24; 1.03-1.48), current contraceptive use (AOR = 1.26; 1.13-1.39), menstruating in the last six weeks (AOR = 1.13; 1.03-1.24), women's media exposure (AOR = 1.20; 1.07-1.35), and being in the community with a high level of media exposure (AOR = 1.53; 1.24-1.88) were statistically significant with KOC. Knowledge of the ovulatory cycle was low in this study, which demands health education for women of childbearing age. Special attention should be given to teenagers, those with lower educational, and lower economic status. Besides, the strengthening of media campaigns could increase women's KOC, which is crucial for preventing unintended pregnancy.

Incidence of neonatal mortality and its predictors among live births in Ethiopia: Gompertz gamma shared frailty model

BackgroundNeonatal mortality remains a serious public health concern in developing countries including Ethiopia. Ethiopia is one of the countries with the highest neonatal mortality in Africa. However, there is limited evidence on the incidence and predictors of neonatal mortality at the national level. Therefore, this study aimed to investigate the incidence of neonatal mortality and its predictors among live births in Ethiopia. Investigating the incidence and predictors of neonatal mortality is essential to design targeted public health interventions to reduce neonatal mortality.MethodsA secondary data analysis was conducted based on the 2016 Ethiopian Demographic and Health Survey (EDHS) data. A total weighted sample of 11,022 live births was included in the analysis. The shared frailty model was applied since the EDHS data has hierarchical nature, and neonates are nested within-cluster, and this could violate the independent and equal variance assumption. For checking the proportional hazard assumption, Schoenfeld residual test was applied. Akakie Information Criteria (AIC), Cox-Snell residual test, and deviance were used for checking model adequacy and for model comparison. Gompertz gamma shared frailty model was the best-fitted model for this data since it had the lowest deviance, AIC value, and the Cox-Snell residual graph closet to the bisector. Variables with a p-value of less than 0.2 were considered for the multivariable Gompertz gamma shared frailty model. In the multivariable Gompertez gamma shared frailty model, the Adjusted Hazard Ratio (AHR) with a 95% confidence interval (CI) was reported to identify significant predictors of neonatal mortality.ResultsOverall, the neonatal mortality rate in Ethiopia was 29.1 (95% CI: 26.1, 32.4) per 1000 live births. In the multivariable Gompertz gamma shared frailty model; male sex (AHR = 1.92, 95% CI: 1.52, 2.43), twin birth (AHR = 5.22, 95% CI: 3.62, 7.53), preceding birth interval less than 18 months (AHR = 2.07, 95% CI: 1.51, 2.85), small size at birth (AHR = 1.64, 95% CI: 1.24, 2.16), large size at birth (AHR = 1.53, 95% CI: 1.16, 2.01) and did not have Antenatal Care (ANC) visit (AHR = 2.10, 95% CI: 1.44, 3.06) were the significant predictors of neonatal mortality.ConclusionOur study found that neonatal mortality remains a public health problem in Ethiopia. Shorter birth interval, small and large size at birth, ANC visits, male sex, and twin births were significant predictors of neonatal mortality. These results suggest that public health programs that increase antenatal care service utilization should be designed to reduce neonatal mortality and special attention should be given for twin births, large and low birth weight babies. Besides, providing family planning services for mothers to increase birth intervals and improving accessibility and utilization of maternal health care services such as ANC is crucial to improve neonatal survival.

Information maximizing component analysis of left ventricular remodeling due to myocardial infarction.

BackgroundAlthough adverse left ventricular shape changes (remodeling) after myocardial infarction (MI) are predictive of morbidity and mortality, current clinical assessment is limited to simple mass and volume measures, or dimension ratios such as length to width ratio. We hypothesized that information maximizing component analysis (IMCA), a supervised feature extraction method, can provide more efficient and sensitive indices of overall remodeling.MethodsIMCA was compared to linear discriminant analysis (LDA), both supervised methods, to extract the most discriminatory global shape changes associated with remodeling after MI. Finite element shape models from 300 patients with myocardial infarction from the DETERMINE study (age 31–86, mean age 63, 20 % women) were compared with 1991 asymptomatic cases from the MESA study (age 44–84, mean age 62, 52 % women) available from the Cardiac Atlas Project. IMCA and LDA were each used to identify a single mode of global remodeling best discriminating the two groups. Logistic regression was employed to determine the association between the remodeling index and MI. Goodness-of-fit results were compared against a baseline logistic model comprising standard clinical indices.ResultsA single IMCA mode simultaneously describing end-diastolic and end-systolic shapes achieved best results (lowest Deviance, Akaike information criterion and Bayesian information criterion, and the largest area under the receiver-operating-characteristic curve). This mode provided a continuous scale where remodeling can be quantified and visualized, showing that MI patients tend to present larger size and more spherical shape, more bulging of the apex, and thinner wall thickness.ConclusionsIMCA enables better characterization of global remodeling than LDA, and can be used to quantify progression of disease and the effect of treatment. These data and results are available from the Cardiac Atlas Project (http://www.cardiacatlas.org).

Predicting Increased Blood Pressure Using Machine Learning

The present study investigates the prediction of increased blood pressure by body mass index (BMI), waist (WC) and hip circumference (HC), and waist hip ratio (WHR) using a machine learning technique named classification tree. Data were collected from 400 college students (56.3% women) from 16 to 63 years old. Fifteen trees were calculated in the training group for each sex, using different numbers and combinations of predictors. The result shows that for women BMI, WC, and WHR are the combination that produces the best prediction, since it has the lowest deviance (87.42), misclassification (.19), and the higher pseudo R 2 (.43). This model presented a sensitivity of 80.86% and specificity of 81.22% in the training set and, respectively, 45.65% and 65.15% in the test sample. For men BMI, WC, HC, and WHC showed the best prediction with the lowest deviance (57.25), misclassification (.16), and the higher pseudo R 2 (.46). This model had a sensitivity of 72% and specificity of 86.25% in the training set and, respectively, 58.38% and 69.70% in the test set. Finally, the result from the classification tree analysis was compared with traditional logistic regression, indicating that the former outperformed the latter in terms of predictive power.

Gillnet selectivity for Chilean hake (Merluccius gayi gayi Guichenot, 1848) in the bay of Valparaíso

Summary To determine the selectivity of gillnets in the Chilean artisanal fishery for the Chilean hake Merluccius gayi gayi, an experimental net was used with three mesh sizes (5.2, 6.8 and 7.6 cm). A total of 2279 specimens of Chilean hake were caught (24–56 cm total length, TL), mainly via gilling and snagging. The catch proportion below the size of sexual maturity SSM50% (37 cm TL) for each mesh size tested was estimated. Models were fitted separately according to the sex to compensate for differences in size compositions, with the males fitted to a binormal model and females fitted to the normal location model. Analysing both sexes combined, the model with the lowest deviance was lognormal, with estimated modal lengths of 30.9, 40.2 and 43.9 cm TL for meshes of 5.2, 6.8 and 7.6 cm, respectively. The estimated selectivity factor (SF) indicates that the modal size matches the SSM50% with a mesh size of 6.2 cm, while the length of retention of 50% (l50) coincides with the SSM50% with a mesh size of 7.6 cm.

Estimation of Mortality Risk in Chronically Ventilated Infants With Bronchopulmonary Dysplasia

Bronchopulmonary dysplasia is a chronic, sometimes fatal lung disease, which primarily affects premature infants and often leads to a dependence on mechanical ventilation lasting many months. To identify prognostic factors of mortality at 1 and 2 months of age, the authors reviewed the medical records of the 144 neonates admitted to two neonatal intensive care units in Seattle from January 1, 1986, through December 31, 1988, who required mechanical ventilation throughout the first month of life. Likely predictors of mortality were tested by logistic regression analysis. The calculated mean airway pressure at 30 days of age (MAP30) and the diagnosis of bacterial sepsis at any time during the first month of life (Bact 0-30) were statistically significant predictors of mortality (P less than .001 and P = .018, respectively) and had the lowest deviance in the regression model. The probability of mortality was estimated by 1/(1 + e-chi), where chi = -6.510 + 0.4588 (MAP30) + 1.475 (Bact 0-30), and where MAP30 is expressed as centimeters of water pressure (1 cm H2O = 0.0978 kPa) and the presence or absence of bacteremia is 1 and 0, respectively. The records of the 57 infants who still required mechanical ventilation at 60 days of age were reanalyzed with clinical data available during the first 2 months of life. Mean airway pressure (MAP 60) and the fraction of inspired oxygen (F60) at 60 days of age combined to form the best predictors of mortality, where chi = 7.668 + 0.2940 (MAP 60) + 5.935 (F60).(ABSTRACT TRUNCATED AT 250 WORDS)