Prediction of survival probabilities with Bayesian Decision Trees

Practitioners use Trauma and Injury Severity Score (TRISS) models for predicting the survival probability of an injured patient. The accuracy of TRISS predictions is acceptable for patients with up to three typical injuries, but unacceptable for patients with a larger number of injuries or with atypical injuries. Based on a regression model, the TRISS methodology does not provide the predictive density required for accurate assessment of risk. Moreover, the regression model is difficult to interpret. We therefore consider Bayesian inference for estimating the predictive distribution of survival. The inference is based on decision tree models which recursively split data along explanatory variables, and so practitioners can understand these models. We propose the Bayesian method for estimating the predictive density and show that it outperforms the TRISS method in terms of both goodness-of-fit and classification accuracy. The developed method has been made available for evaluation purposes as a stand-alone application

Gender inequality and sex differences in physical fighting, physical activity, and injury among adolescents across 36 countries

Purpose: Sex differences in adolescent health are widely documented, but social explanations for these sex differences are scarce. This study examines whether societal gender inequality (i.e., men’s and women’s unequal share in political participation, decision-making power, economic participation and command over resources) relates to sex differences in adolescent physical fighting, physical activity, and injuries. Methods: National-level data on gender inequality (i.e. the United Nations Development Program’s Gender Inequality Index) were linked to health data from 71,255 15-year olds from 36 countries in the 2009/10 Health Behavior in School-aged Children (HBSC) study. Using multilevel logistic regression analyses, we tested the association between gender inequality and sex differences in health while controlling for country wealth (GDP per capita). Results: In all countries, boys reported more physical fighting, physical activity, and injuries than girls, but the magnitude of these sex differences varied greatly between countries. Societal gender inequality positively related to sex differences in all three outcomes. In more gender unequal countries, boys reported higher levels of fighting and physical activity, compared to boys in more gender equal countries. In girls, scores were consistently low for these outcomes, however injury was more common in countries with less gender inequality. Conclusions: Societal gender inequality appears to relate to sex differences in some adolescent health behaviors and may contribute to the establishment of sex differences in morbidity and mortality. To reduce inequalities in the health of future generations, public health policy should target social and cultural factors that shape perceived gender norms in young people

Social disorganization and history of child sexual abuse against girls in sub-Saharan Africa : a multilevel analysis

Background: Child sexual abuse (CSA) is a considerable public health problem. Less focus has been paid to the role of community level factors associated with CSA. The aim of this study was to examine the association between neighbourhood-level measures of social disorganization and CSA. Methods: We applied multiple multilevel logistic regression analysis on Demographic and Health Survey data for 6,351 adolescents from six countries in sub-Saharan Africa between 2006 and 2008. Results: The percentage of adolescents that had experienced CSA ranged from 1.04% to 5.84%. There was a significant variation in the odds of reporting CSA across the communities, suggesting 18% of the variation in CSA could be attributed to community level factors. Respondents currently employed were more likely to have reported CSA than those who were unemployed (odds ratio [OR] = 2.05, 95% confidence interval [CI] 1.48 to 2.83). Respondents from communities with a high family disruption rate were 57% more likely to have reported CSA (OR=1.57, 95% CI 1.14 to 2.16). Conclusion: We found that exposure to CSA was associated with high community level of family disruption, thus suggesting that neighbourhoods may indeed have significant important effects on exposure to CSA. Further studies are needed to explore pathways that connect the individual and neighbourhood levels, that is, means through which deleterious neighbourhood effects are transmitted to individuals

Logistinen monitasomalli: rekisteritutkimus mielenterveyden häiriöistä, sosioekonomisesta asemasta ja alueellisista eroista lapsilla Suomen kunnissa

Mental disorders are common during childhood and they are associated with various negative consequences later in life, such as lower educational attainment and unemployment. In addition, the reduction of socioeconomic health disparities has attracted both political, research and media interest. While mental health inequalities have been found consistently in literature and regional disparities in health have been well documented in Finland altogether, the question of possible variation in mental disorder inequalities during childhood among Finnish regions is not fully examined. This master’s thesis contributes to this gap in the research with a statistical perspective and use of a multilevel logistic model, which allows random variation between levels. Using register-based data, I ask whether the association between socioeconomic status and mental disorder in childhood varies between the child’s municipality of residence, and which regional factors possibly explain the differences. The second objective of this thesis is to find out whether the use of a multilevel logistic model provides additional value to this context. The method used in the thesis is a multilevel logistic model, which can also be called a generalized linear mixed-effects model. In multilevel models, the observations are nested within hierarchical levels, which all have corresponding variables. Both intercept and slopes of independent variables can be allowed to vary between the Level 2 units. Intraclass correlation coefficient and median odds ratio (MOR) are used to measure group level variation. In addition, centering of variables and choosing a suitable analysis strategy are central steps in model application. High-quality Finnish register data from Statistics Finland and the Finnish Institute of Health and Welfare is utilised. The study sample consists of 815 616 individuals aged 4–17 living in Finland in the year 2018. The individuals who are used as Level 1 units are nested within 306 Level 2 units based on their municipality of residence. The dependent variable is a dichotomous variable indicating a mental disorder and it is based on visits and psychiatric diagnoses given in specialised healthcare during 2018. Independent variables in Level 1 are maternal education level and household income quintile, and models are controlled for age group, gender, family structure and parental mental disorders. In Level 2, the independent variables are urbanisation, major region, share of higher-educated population and share of at-risk-of-poverty children. In the final model, children with the lowest maternal education level are more likely (OR=1.37, SE=0.0026) to have mental disorders than children with the highest maternal education level. Odds ratios for the household income quintile mostly decline close to one when control variables are included. Interestingly, children from the poorest quintile have slightly lower odds for mental disorder (OR=0.84, SE=0.017) compared with children from the richest quintile. Urbanisation, share of higher-educated population and share of at-risk-of-poverty children are statistically insignificant variables. Differences are found between major regions; children from Åland are more likely (OR=1.5, SE=0.209) to have a mental disorder compared with Helsinki-Uusimaa residents, whereas children from Western Finland (OR=0.71, SE 0.053) have lower odds compared to the same reference. Random slopes for maternal education are not significant, and the model fit does not improve. However, there is some variation among municipalities (MOR=1.34), and this finding defends the usefulness of the multilevel model in the context of mental disorders in childhood. The results show that mental disorder inequalities persist in childhood, but there is complexity. Although no variation in socioeconomic inequalities among municipalities is found, there are still contextual effects between municipalities. Health policies should focus on reducing overall mental health inequalities in the young population, but it is an encouraging finding that disparities in childhood mental disorders are not shown to be stronger in some municipalities than others. Multilevel models can contribute to the methodology of future mental disorder research, if societal context is assumed to affect the outcomes of individuals

Predictors of multiple sexual partners among men in Ethiopia: A multilevel analysis

BACKGROUND:Multiple sexual partnerships were one of the public health issues in the spread of high rates of sexually transmitted infections in sub-Saharan regions. An increase in the number of non-marital sexual partners can lead to a loss of satisfaction as well as other mental health repercussions such as greater rates of anxiety, depression, etc. This study examined the predictors of multiple sexual partners among men in Ethiopia.METHODS: This study used 2016 nationally representative data which was conducted using a multistage stratified cluster sampling method. Multilevel binary logistic regression models were employed to estimate the predictors of multiple sexual partners among men in Ethiopia with the assistance of the STATA software.RESULTS: In this study 6778 participants were considered with an overall prevalence rate of multiple sexual partners of 6.5% during the 12 months preceding the survey. The findings showed that older-age, urban-resident, inconsistent use of a condom, exposure to any media, abuse of alcohol, early-time first-sex, and religion were predictors of multiple sexual partners among men in Ethiopia.CONCLUSIONS: The findings revealed that the prevalence rate of men's multiple sexual partners in Ethiopia was very high. Therefore, the country needs to re-examine the behavioral change strategies periodically to adapt to the contextual realities and engage relevant stakeholders. Specifically, health sectors and religious organizations should develop strategies to create awareness in society on the risk of having multiple sexual partnerships. In addition, we highly recommend stakeholders prepare risk reduction interventions that take the significant predictors of multiple sexual partners