A Bayesian Bernoulli-Exponential joint model for binary longitudinal outcomes and informative time with applications to bladder cancer recurrence data.

BACKGROUND: A variety of methods exist for the analysis of longitudinal data, many of which are characterized with the assumption of fixed visit time points for study individuals. This, however is not always a tenable assumption. Phenomenon that alter subject visit patterns such as adverse events due to investigative treatment administered, travel or any other emergencies may result in unbalanced data and varying individual visit time points. Visit times can be considered informative, because subsequent or current subject outcomes can change or be adapted due to previous subject outcomes. METHODS: In this paper, a Bayesian Bernoulli-Exponential model for analyzing joint binary outcomes and exponentially distributed informative visit times is developed. Via statistical simulations, the influence of controlled variations in visit patterns, prior and sample size schemes on model performance is assessed. As an application example, the proposed model is applied to a Bladder Cancer Recurrence data. RESULTS AND CONCLUSIONS: Results from the simulation analysis indicated that the Bayesian Bernoulli-Exponential joint model converged in stationarity, and performed relatively better for small to medium sample size scenarios with less varying time sequences regardless of the choice of prior. In larger samples, the model performed better for less varying time sequences. This model's application to the bladder cancer data showed a statistically significant effect of prior tumor recurrence on the probability of subsequent recurrences.

SARS-CoV-2 incidence monitoring and statistical estimation of the basic and time-varying reproduction number at the early onset of the pandemic in 45 sub-Saharan African countries.

The world battled to defeat a novel coronavirus 2019 (SARS-CoV-2 or COVID-19), a respiratory illness that is transmitted from person to person through contacts with droplets from infected persons. Despite efforts to disseminate preventable messages and adoption of mitigation strategies by governments and the World Health Organization (WHO), transmission spread globally. An accurate assessment of the transmissibility of the coronavirus remained a public health priority for many countries across the world to fight this pandemic, especially at the early onset. In this paper, we estimated the transmission potential of COVID-19 across 45 countries in sub-Saharan Africa using three approaches, namely, [Formula: see text] based on (i) an exponential growth model (ii) maximum likelihood (ML) estimation and (iii) a time-varying basic reproduction number at the early onset of the pandemic. Using data from March 14, 2020, to May 10, 2020, sub-Saharan African countries were still grappling with COVID-19 at that point in the pandemic. The region's basic reproduction number ([Formula: see text]) was 1.89 (95% CI: 1.767 to 2.026) using the growth model and 1.513 (95% CI: 1.491 to 1.535) with the maximum likelihood method, indicating that, on average, infected individuals transmitted the virus to less than two secondary persons. Several countries, including Sudan ([Formula: see text]: 2.03), Ghana ([Formula: see text]: 1.87), and Somalia ([Formula: see text]: 1.85), exhibited high transmission rates. These findings highlighted the need for continued vigilance and the implementation of effective control measures to combat the pandemic in the region. It is anticipated that the findings in this study would not only function as a historical record of reproduction numbers during the COVID-19 pandemic in African countries, but can serve as a blueprint for addressing future pandemics of a similar nature.

Association between breakfast skipping and psychosomatic symptoms among Canadian adolescents.

This cross-sectional study aimed to examine the mediating roles of gender and substance use in the influence of breakfast skipping on psychosomatic symptoms. The study used data among a nationally-representative sample of 2855 Canadian adolescents who participated in the 2018 Health Behavior in School-aged Children (HBSC) survey. Sequential logistic regressions were used to estimate the associations between breakfast skipping and psychosomatic symptoms. Path analysis using a non-parametric bootstrapping technique tested the hypothesized mediating roles. Results showed that adolescents who skipped breakfast were 2.55 times more likely to report higher psychosomatic symptoms compared to non-breakfast skippers (AOR = 2.55; 95% CI = 1.75-3.82). The bootstrapping mediation models showed that breakfast skipping indirectly influenced psychosomatic symptoms through substance use and gender, accounting for 18.47% ( ß = 0.0052, Boots 95% CI = 0.0025, 0.00730) and 10.70% ( ß = 0.0091, Boots 95% CI = 0.0052, 0.0125), respectively, of the total effect. Our findings have important implications for targeted public and mental health interventions to address both breakfast skipping and psychosomatic symptoms among adolescents.  Conclusion: The study compellingly underscores the significance of incorporating gender-specific factors and substance use in understanding the correlation between breakfast skipping and psychosomatic symptoms. These insights hold importance for tailoring public health interventions to alleviate the prevalence of psychosomatic symptoms among adolescents by actively addressing breakfast skipping. What is Known: • Breakfast is considered the most important meal of the day due to its role in providing the brain with the energy necessary to enhance cognitive functions. • Adolescents commonly exhibit a prevalent lifestyle behaviour of skipping breakfast. What is New: • This study provides robust evidence supporting the association between breakfast skipping and elevated psychosomatic symptoms in adolescents. • Gender and substance use mediate this association, offering novel insights into the complex interplay that contributes to psychosomatic symptoms among this demographic group. • Longitudinal research is needed to unravel causal relationships and illuminate the underlying mechanisms of this intricate connection.

Cyberbullying victimization and suicidal ideation among in-school adolescents in three countries: implications for prevention and intervention.

BACKGROUND: Countries in South and Central America and the Caribbean are among the countries with the highest adolescent cyberbullying crimes. However, empirical evidence about the effect of cyberbullying victimization on suicidal ideation among in-school adolescents in these countries remains limited. The present study examined the association between cyberbullying victimization and suicidal ideation among in-school adolescents in Argentina, Panama, St Vincent, and the Grenadines. METHODS: A representative cross-sectional data from 51,405 in-school adolescents was used. Hierarchical logistic regression analysis was used to estimate the association between cyberbulling victimization and suicidal ideation. RESULTS: Overall, 20% and 21.1% of the adolescents reported cyberbullying victimization and suicidal ideation, respectively in the past year before the survey. Suicidal ideation was higher among adolescents who experienced cyberbullying victimization (38.4%) than those who did not experience cyberbullying victimization (16.6%). Significantly higher odds of suicidal ideation were found among adolescents who had experienced cyberbullying victimization than those who had not experienced cyberbullying victimization [aOR = 1.88, 95% CI: 1.77-1.98]. CONCLUSION: This finding calls for developing and implementing evidence-based programs and practices by school authorities and other relevant stakeholders to reduce cyberbullying victimization among adolescents in this digital age. Protective factors such as parental support and peer support should be encouraged.

Problematic social media use and overweight/obesity: explanatory pathway analysis of 124 667 in-school adolescents in 39 high-income countries.

BACKGROUND: The relationship between adolescent problematic social media use (PSMU) and overweight/obesity and the potential explanatory pathways for this association are unclear. This study (1) examined the relationship between PSMU and overweight/obesity and (2) evaluated potential explanatory pathways for this association. METHODS: The data used in this study came from the 2018 Health Behaviour in School-aged Children (HBSC) survey. A sample of 124 667 in-school adolescents from 39 high-income countries was analysed. Sequential logistic regressions were used to estimate the association between PSMU and overweight/obesity. Pathway analysis using a non-parametric bootstrapping technique tested the hypothesized mediating roles. RESULTS: The multivariable logistic regressions indicated that higher problematic social media users were 1.11 times more likely to be overweight/obese compared with those who reported low PSMU (AOR = 1.11; 95% CI = 1.05-1.18). Our bootstrapping mediation analyses showed that PSMU indirectly influenced overweight/obesity through breakfast skipping, life satisfaction, family communication, self-rated health, and physical activity, accounting for 19.8% (ß = 0.0068, Boots 95% CI = 0.0056-0.0074), 15.1% (ß = 0.0050, Boots 95% CI = 0.0046-0.0056), 9.2% (ß = 0.0031, Boots 95% CI = 0.0024-0.0038), 7.8% (ß = 0.0024, Boots 95% CI = 0.001-0.004), and 5.2% (ß = 0.0017, Boots 95% CI = 0.0014-0.0023), respectively, of the total effect. CONCLUSION: To the best of our knowledge, this is the first study that used nationally representative data from multiple countries in high-income countries to examine the association between PSMU and overweight/obesity and potential explanatory pathways among school-going adolescents. This finding has important implications for public health interventions to reduce overweight/obesity rates among young people.

Staying in or out? COVID-19-induced healthcare utilization avoidance and associated socio-demographic factors in rural India.

BACKGROUND: Although evidence on healthcare utilization avoidance during COVID-19 pandemic is emerging, such knowledge is limited in rural settings. An effective policy to the COVID-19 shocks and stresses in rural settings require empirical evidence to inform the design of health policies and programmes. To help overcome this evidence gap and also contribute to policy decisions, this study aimed at examining COVID-19-induced healthcare utilization avoidance and associated factors in rural India. METHODS: This study used the third-round data from the COVID-19-Related Shocks in Rural India survey conducted between 20-24 September, 2020 across six states. The outcome variable considered in this study was COVID-19-induced healthcare utilization avoidance. Multivariable Binary Logistic Regression Model via Multiple Imputation was used to assess the factors influencing COVID-19-induced healthcare utilization avoidance. RESULTS: Data on 4,682 respondents were used in the study. Of this, the prevalence of COVID-19-induced healthcare utilization avoidance was 15.5% in rural India across the six states. After adjusting for relevant covariates, participants from the Bihar State have significantly higher likelihood of COVID-19-induced healthcare utilization avoidance compared to those from the Andhra Pradesh. Also, participants whose educational level exceeds high school, those who use government hospital/clinic, engage in daily wage labour in agriculture have significantly higher odds of COVID-19-induced healthcare utilization avoidance compared to their counterparts. CONCLUSION: Our study revealed that state of residence, type of health facility used, primary work activity and educational level were associated with COVID-19-induced healthcare utilization avoidance in rural India. The findings suggest that policy makers and public health authorities need to formulate policies and design interventions that acknowledge socioeconomic and demographic factors that influence healthcare use avoidance.