High Rates of Placental Inflammation Among Samples Collected by the MOMI Consortium.

BACKGROUND: The Multi-Omics for Mothers and Infants (MOMI) consortium aims to improve birth outcomes. Preterm birth is a major obstetric complication globally causing significant infant and childhood morbidity and mortality. OBJECTIVES: We analyzed placental samples (basal plate, placenta/chorionic villi and/or the chorionic plate) collected by the 5 MOMI sites: The Alliance for Maternal and Newborn Health Improvement (AMANHI) Bangladesh, AMANHI Pakistan, AMANHI Tanzania, The Global Alliance to Prevent Prematurity and Stillbirth (GAPPS) Bangladesh and GAPPS Zambia. The goal was to analyze the morphology and gene expression of samples collected from preterm and uncomplicated term births. STUDY DESIGN: The teams provided biopsies from 166 singleton preterm (<37 weeks) and 175 term (≥37 weeks) deliveries. They were formalin-fixed and paraffin embedded. Tissue sections from these samples were stained with hematoxylin and eosin and subjected to morphological analyses. Other placental biopsies (n = 35 preterm, 21 term) were flash frozen, which enabled RNA purification for bulk transcriptomics. RESULTS: The morphological analyses revealed a surprisingly high rate of inflammation involving the basal plate, placenta/chorionic villi and/or the chorionic plate. The rate in chorionic villus samples, likely attributable to chronic villitis, ranged from 25% (Pakistan site) to 60% (Zambia site) of cases. Leukocyte infiltration in this location vs. the basal plate or chorionic plate correlated with preterm birth. Our transcriptomic analyses identified 267 genes as differentially expressed (DE) between placentas from preterm vs. term births (123 upregulated, 144 downregulated). Mapping the DE genes onto single cell RNA-seq data from human placentas suggested that all the component cell types, either singly or in subsets, contributed to the observed dysregulation. Consistent with the histopathological findings, GO (Gene Ontology) analyses highlighted leukocyte infiltration/activation and inflammatory responses in both the fetal and maternal compartments. CONCLUSION: The relationship between placental inflammation and preterm birth is appreciated in developed countries. Here, we show that this link also exists in developing geographies. Also, among the participating sites, we found geographic- and/or population-based differences in placental inflammation and preterm birth, suggesting the importance of local factors.

Perinatal inflammation, fetal growth restriction, and long-term neurodevelopmental impairment in Bangladesh.

BACKGROUND: There are limited data on the impact of perinatal inflammation on child neurodevelopment in low-middle income countries and among growth-restricted infants. METHODS: Population-based, prospective birth cohort study of 288 infants from July 2016-March 2017 in Sylhet, Bangladesh. Umbilical cord blood was analyzed for interleukin(IL)-1α, IL-1ß, IL-6, IL-8, and C-reactive protein(CRP). Child neurodevelopment was assessed at 24 months with Bayley-III Scales of Infant Development. We determined associations between cord blood inflammation and neurodevelopmental outcomes, controlling for potential confounders. RESULTS: 248/288 (86%) live born infants were followed until 24 months, among whom 8.9% were preterm and 45.0% small-for-gestational-age(SGA) at birth. Among all infants, elevated concentrations (>75%) of CRP and IL-6 at birth were associated with increased odds of fine motor delay at 24 months; elevated CRP was also associated with lower receptive communication z-scores. Among SGA infants, elevated IL-1α was associated with cognitive delay, IL-8 with language delay, CRP with lower receptive communication z-scores, and IL-1ß with lower expressive communication and motor z-scores. CONCLUSIONS: In rural Bangladesh, perinatal inflammation was associated with impaired neurodevelopment at 24 months. The associations were strongest among SGA infants and noted across several biomarkers and domains, supporting the neurobiological role of inflammation in adverse fetal development, particularly in the setting of fetal growth restriction. IMPACT: Cord blood inflammation was associated with fine motor and language delays at 24 months of age in a community-based cohort in rural Bangladesh. 23.4 million infants are born small-for-gestational-age (SGA) globally each year. Among SGA infants, the associations between cord blood inflammation and adverse outcomes were strong and consistent across several biomarkers and neurodevelopmental domains (cognitive, motor, language), supporting the neurobiological impact of inflammation prominent in growth-restricted infants. Prenatal interventions to prevent intrauterine growth restriction are needed in low- and middle-income countries and may also result in long-term benefits on child development.

Young Infant Mortality Associated with Preterm and Small-for-Gestational-Age Births in Rural Bangladesh: A Prospective Cohort Study.

OBJECTIVE: To assess the relative risk of mortality in infants born preterm and small for gestational age (SGA) during the first and second months of life in rural Bangladesh. STUDY DESIGN: We analyzed data from a cohort of pregnant women and their babies in Sylhet, Bangladesh, assembled between 2011 and 2014. Community health workers visited enrolled babies up to 10 times from birth to age 59 days. Survival status was recorded at each visit. Gestational age was estimated from mother's reported last menstrual period. Birth weights were measured within 72 hours of delivery. SGA was defined using the INTERGROWTH-21st standard. We estimated unadjusted and adjusted hazard ratios (HRs) and corresponding 95% CIs for babies born preterm and SGA separately for the first and second month of life using bivariate and multivariable weighted Cox regression models. RESULTS: The analysis included 17 643 singleton live birth babies. Compared with infants born at term-appropriate for gestational age, in both unadjusted and adjusted analyses, infants born preterm-SGA had the greatest risk of death in the first (HR 13.25, 95% CI 8.65-20.31; adjusted HR 12.05, 95% CI 7.82-18.57) and second month of life (HR 4.65, 95% CI 1.93-11.23; adjusted HR 4.1, 95% CI 1.66-10.15), followed by infants born preterm-appropriate for gestational age and term-SGA. CONCLUSIONS: The risk of mortality in infants born preterm and/or SGA is increased and extends through the second month of life. Appropriate interventions to prevent and manage complications caused by prematurity and SGA could improve survival during and beyond the neonatal period.

The Hidden Toll of Psychological Distress in Australian Adults and Its Impact on Health-Related Quality of Life Measured as Health State Utilities.

BACKGROUND: Psychological distress (PD) is a major health problem that affects all aspects of health-related quality of life including physical, mental and social health, leading to a substantial human and economic burden. Studies have revealed a concerning rise in the prevalence of PD and various mental health conditions among Australians, particularly in female individuals. There is a scarcity of studies that estimate health state utilities (HSUs), which reflect the overall health-related quality of life in individuals with PD. No such studies have been conducted in Australia thus far. OBJECTIVE: We aimed to evaluate the age-specific, sex-specific and PD category-specific HSUs (disutilities) in Australian adults with PD to inform healthcare decision making in the management of PD. METHODS: Data on age, sex, SF-36/SF6D responses, Kessler psychological distress (K10) scale scores and other characteristics of N = 15,139 participants (n = 8149 female individuals) aged >15 years were derived from the latest wave (21) of the nationally representative Household, Income and Labor Dynamics in Australia survey. Participants were grouped into the severity categories of no (K10 score: 10-19), mild (K10: 20-24), moderate (K10: 25-29) and severe PD (K10: 30-50). Both crude and adjusted HSUs were calculated from participants' SF-36 profiles, considering potential confounders such as smoking, marital status, remoteness, education and income levels. The calculations were based on the SF-6D algorithm and aligned with Australian population norms. Additionally, the HSUs were stratified by age, sex and PD categories. Disutilities of PD, representing the mean difference between HSUs of people with PD and those without, were also calculated for each group. RESULTS: The average age of individuals was 46.130 years (46% male), and 31% experienced PD in the last 4 weeks. Overall, individuals with PD had significantly lower mean HSUs than those likely to be no PD, 0.637 (95% confidence interval [CI] 0.636, 0.640) vs 0.776 (95% CI 0.775, 0.777) i.e. disutility: -0.139 [95% CI -0.139, -0.138]). Mean disutilities of -0.108 (95% CI -0.110, -0.104), -0.140 (95% CI -0.142, -0.138), and -0.188 (95% CI -0.190, -0.187) were observed for mild PD, moderate PD and severe PD, respectively. Disutilities of PD also differed by age and sex groups. For instance, female individuals had up to 0.049 points lower mean HSUs than male individuals across the three classifications of PD. There was a clear decline in health-related quality of life with increasing age, demonstrated by lower mean HSUs in older population age groups, that ranged from 0.818 (95% CI 0.817, 0.818) for the 15-24 years age group with no PD to 0.496 (95% CI 0.491, 0.500) for the 65+ years age group with severe PD). Across all ages and genders, respondents were more likely to report issues in certain dimensions, notably vitality, and these responses did not uniformly align with ageing. CONCLUSIONS: The burden of PD in Australia is substantial, with a significant impact on female individuals and older individuals. Implementing age-specific and sex-specific healthcare interventions to address PD among Australian adults may greatly alleviate this burden. The PD state-specific HSUs calculated in our study can serve as valuable inputs for future health economic evaluations of PD in Australia and similar populations.

The validity of the environmental Kuznets curve in the presence of long-run civil wars: A case of Afghanistan.

The war in Afghanistan left significantly negative consequences in all spheres of its society, leading the country to the highest levels of poverty, hunger, and environmental damage. This study explores the long-run impact of civil wars on environmental degradation in Afghanistan using the conceptual framework of the Environmental Kuznets Curve and models augmented with pollutants, civil wars, comprehensive financial development index, and macroeconomic predictors on a set of data from the first quarter of 2002 to the first quarter of 2020. However, while the results confirm long-run relationships amid indicators by the autoregressive distributed lags bound test, the results of the vector error-correcting model to Granger causality reveal bidirectional causality links between CO2 emissions, per capita real GDP, civil wars, the financial development index, energy consumption, trade openness, and the inflation rate in the long-run, while the findings extend to confirm multidimensionality and interdependencies among predictors in the short-run. Moreover, the results indicate dual findings. First, it confirms that civil wars, the financial development index, per capita real gross domestic product, population growth, and the inflation rate significantly increase CO2 emissions, while the squared per capita real gross domestic product, energy consumption, and trade openness reduce CO2 emissions both in the short and long runs. Second, the results confirm an inverted U-shaped relationship, supporting the validity of the Environmental Kuznets Curve hypothesis in Afghanistan. Based on the findings, appropriate policy measures are recommended.

Socioeconomic inequalities in child and adolescent mental health in Australia: the role of parenting style and parents' relationships.

BACKGROUND: Socioeconomic inequalities in health and their determinants have been studied extensively over the past few decades. However, the role of parenting style and parents' couple relationships in explaining mental health inequalities is limited. Therefore, this study aims to investigate the distributional impact of parenting style (angry parenting, consistent parenting, and inductive parenting) and parents' couple relationships (e.g., argumentative, happy relationships) on socioeconomic inequalities and by extension on mental health status of Australian children and adolescents. METHODS: This study utilized data from the Longitudinal Study of Australian Children (Waves 1-7), specifically focusing on intact biological parent families, while excluding single-parent and blended-family households. We applied the decomposition index and the Blinder Oaxaca method to investigate the extent of the contribution and temporal impact of parenting style and parents' couple relationships on the mental health status of Australian children and adolescents. RESULTS: This study revealed that poor parenting style is the single most important factor that leads to developing mental health difficulties in children and adolescents, especially from low socioeconomic status, and it contributes almost 52% to socioeconomic inequalities in mental health status. Conversely, household income, maternal education, employment status, and parents' couple relationships contributed 28.04%, 10.67%, 9.28%, and 3.34%, respectively, to mental health inequalities in children and adolescents. CONCLUSION: Overall, this study underscores the importance of parenting style and parents' couple relationships as significant predictors of mental health outcomes in children and adolescents. These results highlight the need for targeted interventions to support families from low socioeconomic backgrounds to address the significant mental health inequalities observed in the study population.

Assessing the excess costs of the in-hospital adverse events covered by the AHRQ's Patient Safety Indicators in Switzerland.

There currently exists no comprehensive and up-to date overview on the financial impact of the different adverse events covered by the Patient Safety Indicators (PSIs) from the Agency for Healthcare Research and Quality. We conducted a retrospective case-control study using propensity score matching on a national administrative data set of 1 million inpatients in Switzerland to compare excess costs associated with 16 different adverse events both individually and on a nationally aggregated level. After matching 8,986 cases with adverse events across the investigated PSIs to 26,931 controls, we used regression analyses to determine the excess costs associated with the adverse events and to control for other cost-related influences. The average excess costs associated with the PSI-related adverse events ranged from CHF 1,211 (PSI 18, obstetric trauma with instrument) to CHF 137,967 (PSI 10, postoperative acute kidney injuries) with an average of CHF 27,409 across all PSIs. In addition, adverse events were associated with 7.8-day longer stays, 2.5 times more early readmissions (within 18 days), and 4.1 times higher mortality rates on average. At a national level, the PSIs were associated with CHF 347 million higher inpatient costs in 2019, which corresponds to about 2.2% of the annual inpatient costs in Switzerland. By comparing the excess costs of different PSIs on a nationally aggregated level, we offer a financial perspective on the implications of in-hospital adverse events and provide recommendations for policymakers regarding specific investments in patient safety to reduce costs and suffering.

Investigating school absenteeism and refusal among Australian children and adolescents using Apriori association rule mining.

Identifying and determining the multitude of reasons behind school absences of students is often challenging. This study aims to uncover the hidden reasons for school absence in children and adolescents. The analysis is conducted on a national survey that includes 2967 Australian children and adolescents aged 11-17. The Apriori association rule generator of machine learning techniques and binary logistic regression are used to identify the significant predictors of school absences. Out of 2484, 83.7% (n = 2079) aged (11-17) years children and adolescents have missed school for various reasons, 42.28% (n = 879) are (11-15) years old, 24.52% (n = 609) and 16.9% (n = 420) are 16- and 17-years old adolescents respectively. A considerable proportion of adolescents, specifically 16.4% (n = 407) and 23.4% (n = 486) of 16 and 17 years old, respectively, have selected 'refused to say' as their reason for not attending school. It also highlights the negative outcomes associated with undisclosed reasons for school absence, such as bullying, excessive internet/gaming, reduced family involvement, suicide attempts, and existential hopelessness. The findings of the national survey underscore the importance of addressing these undisclosed reasons for school absence to improve the overall well-being and educational outcomes of children and adolescents.

Early to mid-pregnancy HbA1c levels and its association with adverse pregnancy outcomes in three low middle-income countries in Asia and Sub-Saharan Africa.

BACKGROUND: Hyperglycemia during pregnancy leads to adverse maternal and fetal outcomes. Thus, strict monitoring of blood glucose levels is warranted. This study aims to determine the association of early to mid-pregnancy HbA1c levels with the development of pregnancy complications in women from three countries in South Asia and Sub-Saharan Africa. METHODS: We performed a secondary analysis of the AMANHI (Alliance for Maternal and Newborn Health Improvement) cohort, which enrolled 10,001 pregnant women between May 2014 and June 2018 across Sylhet-Bangladesh, Karachi-Pakistan, and Pemba Island-Tanzania. HbA1c assays were performed at enrollment (8 to < 20 gestational weeks), and epidemiological data were collected during 2-3 monthly household visits. The women were followed-up till the postpartum period to determine the pregnancy outcomes. Multivariable logistic regression models assessed the association between elevated HbA1c levels and adverse events while controlling for potential confounders. RESULTS: A total of 9,510 pregnant women were included in the analysis. The mean HbA1c level at enrollment was found to be the highest in Bangladesh (5.31 ± 0.37), followed by Tanzania (5.22 ± 0.49) and then Pakistan (5.07 ± 0.58). We report 339 stillbirths and 9,039 live births. Among the live births were 892 preterm births, 892 deliveries via cesarean section, and 532 LGA babies. In the multivariate pooled analysis, maternal HbA1c levels of ≥ 6.5 were associated with increased risks of stillbirths (aRR = 6.3, 95% CI = 3.4,11.6); preterm births (aRR = 3.5, 95% CI = 1.8-6.7); and Large for Gestational Age (aRR = 5.5, 95% CI = 2.9-10.6). CONCLUSION: Maternal HbA1c level is an independent risk factor for predicting adverse pregnancy outcomes such as stillbirth, preterm birth, and LGA among women in South Asia and Sub-Saharan Africa. These groups may benefit from early interventional strategies.

Patient-reported experience is associated with higher future revenue and lower costs of hospitals.

BACKGROUND: Despite the established positive association between patient experience and patient volume, the relationship between patient experience and the financial performance of hospitals has not been studied thoroughly. METHODS: To investigate this relationship, we used longitudinal data from 132 Swiss acute-care hospitals from 2016 to 2019 to examine the associations between patient experience and the proportion of elective patients, revenue, costs, and profits of hospitals. To account for a potential time lag effect, we utilized annual patient experience data and employed multilevel mixed-effects regression modeling to investigate its association with the aforementioned financial performance indicators for the following year. RESULTS: Data for private and public hospitals were analyzed both separately and in combination, to account for the different proportions of elective patients in these types of hospitals. The resulting mixed models, revealed that for each year studied, the previous year's patient experience was positively associated with the current year's proportion of elective patients (ß = 0.09, p = 0.004, all hospitals) and revenue (ß = 1789.83, p = 0.037, private hospitals only), and negatively associated with costs (ß = - 1191.13, p = 0.017, all hospitals); but not significantly associated with future profits (ß = 629.12, p = 0.240, all hospitals). CONCLUSIONS: This analysis showed that better patient experience is associated with a higher proportion of elective patients, greater revenue, and lower costs. Our findings may assist hospital managers and regulators in identifying strategies to increase revenue and reduce costs.

Socioeconomic status and health behavior in children and adolescents: a systematic literature review.

Socioeconomic status affects individuals' health behaviors and contributes to a complex relationship between health and development. Due to this complexity, the relationship between SES and health behaviors is not yet fully understood. This literature review, therefore, aims to assess the association between socioeconomic status and health behaviors in childhood and adolescence. Preferred Reporting for Systematic Review and Meta-Analysis protocol guidelines were used to conduct a systematic literature review. The electronic online databases EBSCO Host, PubMed, Web of Science, and Science Direct were utilized to systematically search published articles. The Joanna Briggs Institute's critical appeal tool was used to assess the quality of included studies. Eligibility criteria such as study context, study participants, study setting, outcome measures, and key findings were used to identify relevant literature that measured the association between socioeconomic status and health behaviors. Out of 2,391 studies, only 46 met the final eligibility criteria and were assessed in this study. Our review found that children and adolescents with low socioeconomic status face an elevated risk of unhealthy behaviors (e.g., early initiation of smoking, high-energy-dense food, low physical activity, and involvement in drug abuse), in contrast to their counterparts. Conversely, children and adolescents from higher socioeconomic backgrounds exhibit a higher prevalence of health-promoting behaviors, such as increased consumption of fruit and vegetables, dairy products, regular breakfast, adherence to a nutritious diet, and engagement in an active lifestyle. The findings of this study underscore the necessity of implementing specific intervention measures aimed at providing assistance to families from disadvantaged socioeconomic backgrounds to mitigate the substantial disparities in health behavior outcomes in children and adolescents.

Identifying Social Determinants and Measuring Socioeconomic Inequalities in the Use of Four Different Mental Health Services by Australian Adolescents Aged 13-17 Years: Results from a Nationwide Study.

AIM: In this study, we aimed to identify the determinants of four different forms of mental health service usage (general health services, school counselling, telephone, and online services), and the number of mental health services accessed (single and multiple) by Australian adolescents aged 13-17 years. We also measured socioeconomic inequality in mental health services' usage following the concentration index approach within the same sample. SUBJECT AND METHODS: The data came from the nationwide cross-sectional survey, Young Minds Matter (YMM): the second Australian Child and Adolescent Survey of Mental Health and Wellbeing. Random effect models were used to identify the factors associated with four different mental health services and the number of services accessed. Further, the Erreygers' corrected concentration indices for binary variables were used to quantify the socioeconomic inequality in each mental health service. The four services were the general health service (GP, specialist, psychiatrist, psychologist, hospital including emergency), school services, telephone counselling and online services. RESULTS: Overall, 31.9% of the total analytical sample (n = 2268) aged 13-17 years old visited at least one service, with 21.9% accessing a single service and 10% accessing multiple services. The highest percentage of adolescents used online services (20.1%), followed by general mental health services (18.3%), while school services (2.4%) were the least used service. Age, gender, family type and family cohesion statistically significantly increased the use of general health and multiple mental health service usage (p < 0.05). Area of residence was also found to be a significant factor for online service use. The concentration indices (CIs) were -0.073 (p < 0.001) and -0.032 (p < 0.001) for health and telephone services, respectively, which implies pro-rich socio-economic inequality. CONCLUSION: Adolescents from low-income families frequently used general mental health services and telephone services compared to those who belonged to high-income families. The study concluded that if we want to increase adolescents' usage of mental health services, we need to tailor our approaches to their socioeconomic backgrounds. In addition, from a policy standpoint, a multi-sectoral strategy is needed to address the factors related to mental health services to reduce inequity in service utilisation.

Comparative predictive power of serum vs plasma proteomic signatures in feto-maternal medicine.

BACKGROUND: Blood proteins are frequently measured in serum or plasma, because they provide a wealth of information. Differences in the ex vivo processing of serum and plasma raise concerns that proteomic health and disease signatures derived from serum or plasma differ in content and quality. However, little is known about their respective power to predict feto-maternal health outcomes. Predictive power is a sentinel characteristic to determine the clinical use of biosignatures. OBJECTIVE: This study aimed to compare the power of serum and plasma proteomic signatures to predict a physiological pregnancy outcome. STUDY DESIGN: Paired serum and plasma samples from 73 women were obtained from biorepositories of a multinational prospective cohort study on pregnancy outcomes. Gestational age at the time of sampling was the predicted outcome, because the proteomic signatures have been validated for such a prediction. Multivariate and cross-validated models were independently derived for serum and plasma proteins. RESULTS: A total of 1116 proteins were measured in 88 paired samples from 73 women with a highly multiplexed platform using proximity extension technology (Olink Proteomics Inc, Watertown, MA). The plasma proteomic signature showed a higher predictive power (R=0.64; confidence interval, 0.42-0.79; P=3.5×10-6) than the serum signature (R=0.45; confidence interval, 0.18-0.66; P=2.2×10-3). The serum signature was validated in plasma with a similar predictive power (R=0.58; confidence interval, 0.34-0.75; P=4.8×10-5), whereas the plasma signature was validated in serum with reduced predictive power (R=0.53; confidence interval, 0.27-0.72; P=2.6×10-4). Signature proteins largely overlapped in the serum and plasma, but the strength of association with gestational age was weaker for serum proteins. CONCLUSION: Findings suggest that serum proteomics are less informative than plasma proteomics. They are compatible with the view that the partial ex-vivo degradation and modification of serum proteins during sample processing are an underlying reason. The rationale for collecting and analyzing serum and plasma samples should be carefully considered when deriving proteomic biosignatures to ascertain that specimens of the highest scientific and clinical yield are processed. Findings suggest that plasma is the preferred matrix.

Early detection of paediatric and adolescent obsessive-compulsive, separation anxiety and attention deficit hyperactivity disorder using machine learning algorithms.

Purpose: Mental health issues of young minds are at the threshold of all development and possibilities. Obsessive-compulsive disorder (OCD), separation anxiety disorder (SAD), and attention deficit hyperactivity disorder (ADHD) are three of the most common mental illness affecting children and adolescents. Several studies have been conducted on approaches for recognising OCD, SAD and ADHD, but their accuracy is inadequate due to limited features and participants. Therefore, the purpose of this study is to investigate the approach using machine learning (ML) algorithms with 1474 features from Australia's nationally representative mental health survey of children and adolescents. Methods: Based on the internal cross-validation (CV) score of the Tree-based Pipeline Optimization Tool (TPOTClassifier), the dataset has been examined using three of the most optimal algorithms, including Random Forest (RF), Decision Tree (DT), and Gaussian Naïve Bayes (GaussianNB). Results: GaussianNB performs well in classifying OCD with 91% accuracy, 76% precision, and 96% specificity as well as in detecting SAD with 79% accuracy, 62% precision, 91% specificity. RF outperformed all other methods in identifying ADHD with 91% accuracy, 94% precision, and 99% specificity. Conclusion: Using Streamlit and Python a web application was developed based on the findings of the analysis. The application will assist parents/guardians and school officials in detecting mental illnesses early in their children and adolescents using signs and symptoms to start the treatment at the earliest convenience.

Individual preferences, government policy, and COVID-19: A game-theoretic epidemiological analysis.

Purpose: The ongoing COVID-19 pandemic imposes serious short-term and long-term health costs on populations. Restrictive government policy measures decrease the risks of infection, but produce similarly serious social, mental health, and economic problems. Citizens have varying preferences about the desirability of restrictive policies, and governments are thus forced to navigate this tension in making pandemic policy. This paper analyses the situation facing government using a game-theoretic epidemiological model. Methodology: We classify individuals into health-centered individuals and freedom-centered individuals to capture the heterogeneous preferences of citizens. We first use the extended Susceptible-Exposed-Asymptomatic-Infectious-Recovered (SEAIR) model (adding individual preferences) and the signaling game model (adding government) to analyze the strategic situation against the backdrop of a realistic model of COVID-19 infection. Findings: We find the following: 1. There exists two pooling equilibria. When health-centered and freedom-centered individuals send anti-epidemic signals, the government will adopt strict restrictive policies under budget surplus or balance. When health-centered and freedom-centered individuals send freedom signals, the government chooses not to implement restrictive policies. 2. When governments choose not to impose restrictions, the extinction of an epidemic depends on whether it has a high infection transmission rate; when the government chooses to implement non-pharmacological interventions (NPIs), whether an epidemic will disappear depends on how strict the government's restrictions are. Originality/value: Based on the existing literature, we add individual preferences and put the government into the game as a player. Our research extends the current form of combining epidemiology and game theory. By using both we get a more realistic understanding of the spread of the virus and combine that with a richer understanding of the strategic social dynamics enabled by game theoretic analysis. Our findings have important implications for public management and government decision-making in the context of COVID-19 and for potential future public health emergencies.

Vitamin D deficiency in pregnancy and the risk of preterm birth: a nested case-control study.

BACKGROUND: Each year, an estimated 15 million babies are born preterm. Micronutrient deficiencies, including vitamin D deficiency (VDD), are common in many low- and middle-income countries (LMICs), and these conditions are often associated with adverse pregnancy outcomes. Bangladesh experiences a high prevalence of VDD. The country also has a high preterm birth (PTB) rate. Using data from a population-based pregnancy cohort, we estimated the burden of VDD during pregnancy and its association with PTB. METHODS: Pregnant women (N = 3,000) were enrolled after ultrasound confirmation of gestational age at 8-19 weeks of gestation. Trained health workers prospectively collected phenotypic and epidemiological data at scheduled home visits. Trained phlebotomists collected maternal blood samples at enrollment and 24 -28 weeks of gestation. Aliquots of serum were stored at -800 C. We conducted a nested case-control study with all PTB (n = 262) and a random sample of term births (n = 668). The outcome, PTB, was defined as live births < 37 weeks of gestation, based on ultrasound. The main exposure was vitamin D concentrations of 24-28 weeks maternal blood samples. The analysis was adjusted for other PTB risk factors. Women were categorized as VDD (lowest quartile of 25(OH)D; < = 30.25 nmol/L) or not deficient (upper-three quartiles of 25(OH)D; > 30.25 nmol/L). We used logistic regression to determine the association of VDD with PTB, adjusting for potential confounders. RESULTS: The median and interquartile range of serum 25(OH)D was 38.0 nmol/L; 30.18 to 48.52 (nmol/L). After adjusting for co-variates, VDD was significantly associated with PTB [adjusted odds ratio (aOR) = 1.53, 95% confidence interval (CI) = 1.10 - 2.12]. The risk of PTB was also higher among women who were shorter (aOR = 1.81, 95% CI: 1.27-2.57), primiparous (aOR = 1.55, 95% CI = 1.12 - 2.12), passive smokers (aOR = 1.60, 95% CI = 1.09 - 2.34), and those who received iron supplementation during pregnancy (aOR = 1.66, 95% CI: 1.17, 2.37). CONCLUSION: VDD is common in Bangladeshi pregnant women and is associated with an increased risk of PTB.

Clustering of lifestyle and health behaviours in Australian adolescents and associations with obesity, self-rated health and quality of life.

OBJECTIVE: The primary aim of this study was to identify clusters of lifestyle and health behaviours and explore their associations with health outcomes in a nationally representative sample of Australian adolescents. METHODS: The study participants were 3127 adolescents aged 14-15 years who participated in the eighth wave of the birth cohort of the Longitudinal Study of Australian Children (LSAC). A latent class analysis (LCA) was performed to identify clusters based on the behaviours of physical activity, alcohol consumption, smoking, diet, eating disorders, sleep problems and weight consciousness. Multinomial logistic regression models were fitted to the following health outcome variables: obesity, self-rated general health and pediatric health-related quality of life, to investigate their associations with LCA clusters. RESULTS: Based on the prevalence of health behaviour related characteristics, LCA identified gender based distinct clusters of adolescents with certain outward characteristics. There were five clusters for male and four clusters for female participants which are named as: healthy lifestyle, temperate, mixed lifestyle, multiple risk factors, and physically inactive (male only). Adolescents in the healthy lifestyle and temperate clusters reported low and moderately active health risk behaviours, for example, low physical activity, inadequate sleep and so on, while these behaviours were prevailing higher among adolescents of other clusters. Compared to adolescents of healthy lifestyle clusters, male members of physically inactive (OR = 3.87, 95% CI: 1.12 - 13.33) or mixed lifestyle (OR = 5.57, 95% CI: 3.15 - 9.84) clusters were over three to five times more likely to have obesity; while for female adolescents, members of only multiple risk factors clusters (OR = 3.61, 95% CI: 2.00 - 6.51) were over three time more likely to have obesity compared to their counterpart of healthy lifestyle clusters. Adolescents of physically inactive (b = -9.00 for male only), mixed lifestyle (b = -2.77 for male; b = -6.72 for female) or multiple risk factors clusters (b = -6.49 for male; b = -6.59 for female) had a stronger negative association with health-related quality of life scores compared to adolescents of healthy lifestyle clusters. CONCLUSION: The study offers novel insights into latent class classification through the utilisation of different lifestyles and health-related behaviours of adolescents to identify characteristics of vulnerable groups concerning obesity, general health status and quality of life. This classification strategy may help health policy makers to target vulnerable groups and develop appropriate interventions.

Multiomic signals associated with maternal epidemiological factors contributing to preterm birth in low- and middle-income countries.

Preterm birth (PTB) is the leading cause of death in children under five, yet comprehensive studies are hindered by its multiple complex etiologies. Epidemiological associations between PTB and maternal characteristics have been previously described. This work used multiomic profiling and multivariate modeling to investigate the biological signatures of these characteristics. Maternal covariates were collected during pregnancy from 13,841 pregnant women across five sites. Plasma samples from 231 participants were analyzed to generate proteomic, metabolomic, and lipidomic datasets. Machine learning models showed robust performance for the prediction of PTB (AUROC = 0.70), time-to-delivery (r = 0.65), maternal age (r = 0.59), gravidity (r = 0.56), and BMI (r = 0.81). Time-to-delivery biological correlates included fetal-associated proteins (e.g., ALPP, AFP, and PGF) and immune proteins (e.g., PD-L1, CCL28, and LIFR). Maternal age negatively correlated with collagen COL9A1, gravidity with endothelial NOS and inflammatory chemokine CXCL13, and BMI with leptin and structural protein FABP4. These results provide an integrated view of epidemiological factors associated with PTB and identify biological signatures of clinical covariates affecting this disease.

Association of maternal physical and mental health characteristics with the hazard of having any medical condition or disability in Australian children: A 15-year birth cohort study.

Any long-term medical condition or disability among children is a significant health issue. This study measured the incidence rate of any medical condition or disability among children from a nationally representative birth cohort, then used the random effect parametric survival regression model to assess whether the hazard of any medical condition or disability in children is associated with maternal physical and mental health characteristics (obesity, general health status, having a medical condition, stressful life events or mental illness). The study followed up 5019 children from the Longitudinal Study of Australian Children, assessing their time-to-event data from birth (2004) to 14 or 15 years of age (2018). The hazard rate of any medical condition or disability was 26.11 per 1000 person-years for all the children and 29.29 for the males-a noticeable gender difference. It was the highest (hazard rate: 62.90) among the children when their mothers had a medical condition, while the hazard rate was 22.40 per 1000 person-years among the children whose mothers had no medical conditions. The parametric panel regression results also suggested that the children of mothers with a medical condition during the 15-year study period were more likely to have a medical condition or disability (hazard ratio [HR]: 2.61, 95% confidence interval [CI]: 2.24-3.02) compared to the children of mothers with none. Similar trends were observed among children of mothers who had fair or poor general health (HR: 1.48, 95% CI: 1.15-1.91), obesity (HR: 1.40, 95% CI: 1.18-1.66) or experienced stressful life events (HR: 1.23, 95% CI: 1.06-1.43) over time compared to those whose mothers did not. These findings suggest that additional healthcare interventions targeting mothers with medical conditions, obesity, poor general health, or mental illness would help minimise the risk of medical conditions and disabilities among children.

The Healthcare Cost Burden of Asthma in Children: A Longitudinal Population-Based Study.

OBJECTIVES: This study aimed to investigate the extent of healthcare cost increase at population level due to childhood asthma. We aimed to investigate the cross-sectional relationship between asthma and healthcare costs among children aged 2 to 18 years and, in longitudinal analyses, whether costs increase with an increase in the duration of asthma prevalence. METHODS: Study participants are 4175 and 4482 children of birth and kindergarten cohorts from the nationally representative Longitudinal Study of Australian Children for whom the linked Medicare cost data are available. The children were followed in all waves from the year 2004 to 2018. Generalized linear models were used to estimate the excess healthcare costs associated with asthma. The sum of Medicare Benefits Schedule and Pharmaceutical Benefits Scheme costs constitutes the total healthcare costs. RESULTS: Total excess healthcare costs associated with asthma among the 2- to 18-year-old children were A$4316 per child. At the population level, the estimated total excess Medicare costs associated with current asthma treatment among 2- to 18-year-old children were, on average, A$190.6 million per year (2018 population and price). Compared with the non-asthmatic children, peers with persistent asthma morbidity and treatment requirements had excess costs up to A$20 727 for the B cohort children until 14 years of age, whereas excess costs for the K cohort children were A$19 571 until 18 years of age. CONCLUSIONS: Asthma in children imposes a significant financial burden on the public health system. Higher excess healthcare costs of all asthmatic children than the costs of nonasthmatic children provide further economic justification for promoting preventive efforts at early ages.