Using unsupervised clustering approaches to identify common mental health profiles and associated mental health-care service-use patterns in Ontario, Canada.

Mental health is a complex, multidimensional concept that goes beyond clinical diagnoses, including psychological distress, life stress, and well-being. In this study, we aimed to use unsupervised clustering approaches to identify multidimensional mental health profiles that exist in the population, and their associated service-use patterns. The data source was the 2012 Canadian Community Health Survey-Mental Health, linked to administrative health-care data; all Ontario, Canada, adult respondents were included. We used a partitioning around medoids clustering algorithm with Gower's proximity to identify groups with distinct combinations of mental health indicators and described them according to their sociodemographic and service-use characteristics. We identified 4 groups with distinct mental health profiles, including 1 group that met the clinical threshold for a depressive diagnosis, with the remaining 3 groups expressing differences in positive mental health, life stress, and self-rated mental health. The 4 groups had different age, employment, and income profiles and exhibited differential access to mental health-care services. This study represents the first step in identifying complex profiles of mental health at the population level in Ontario. Further research is required to better understand the potential causes and consequences of belonging to each of the mental health profiles identified. This article is part of a Special Collection on Mental Health.

Application of multivariate binary logistic regression grouped outlier statistics and geospatial logistic model to identify villages having unusual health-seeking habits for childhood malaria in Malawi.

BACKGROUND: Early diagnosis and prompt treatment of malaria in young children are crucial for preventing the serious stages of the disease. If delayed treatment-seeking habits are observed in certain areas, targeted campaigns and interventions can be implemented to improve the situation. METHODS: This study applied multivariate binary logistic regression model diagnostics and geospatial logistic model to identify traditional authorities in Malawi where caregivers have unusual health-seeking behaviour for childhood malaria. The data from the 2021 Malawi Malaria Indicator Survey were analysed using R software version 4.3.0 for regressions and STATA version 17 for data cleaning. RESULTS: Both models showed significant variability in treatment-seeking habits of caregivers between villages. The mixed-effects logit model residual identified Vuso Jere, Kampingo Sibande, Ngabu, and Dzoole as outliers in the model. Despite characteristics that promote late reporting of malaria at clinics, most mothers in these traditional authorities sought treatment within twenty-four hours of the onset of malaria symptoms in their children. On the other hand, the geospatial logit model showed that late seeking of malaria treatment was prevalent in most areas of the country, except a few traditional authorities such as Mwakaboko, Mwenemisuku, Mwabulambya, Mmbelwa, Mwadzama, Zulu, Amidu, Kasisi, and Mabuka. CONCLUSIONS: These findings suggest that using a combination of multivariate regression model residuals and geospatial statistics can help in identifying communities with distinct treatment-seeking patterns for childhood malaria within a population. Health policymakers could benefit from consulting traditional authorities who demonstrated early reporting for care in this study. This could help in understanding the best practices followed by mothers in those areas which can be replicated in regions where seeking care is delayed.

Epidemiology of overweight in under-five children in India: insights from National Family Health Survey.

Childhood overweight is not only an immediate health concern due to its implications but also significantly increases the risk of persistent obesity and consequently CVD in the future, posing a serious threat to public health. The objective of this study was to examine the trends and associated factors of childhood overweight in India, using nationally representative data from three rounds of the National Family Health Survey (NFHS). For the primary analysis, we used data from 199 375 children aged 0-59 months from fifth round of the NFHS (NFHS-5). Overweight was defined as BMI-for-age Z (BMI Z) score > +2 sd above the WHO growth standards median. We compared the prevalence estimates of childhood overweight with third round of the third round of NFHS and fourth round of the NFHS. Potential risk factors were identified through multiple logistic regression analyses. The prevalence of overweight increased from 1·9 % in third round of NFHS to 4·0 % in NFHS-5, a trend seen across most states and union territories, with the Northeast region showing the highest prevalence. The BMI Z-score distributions from the latest two surveys indicated that the increase in overweight was substantially larger than the decrease in underweight. The consistent upward trend in the prevalence across different demographic groups raises important public health concerns. While undernutrition rates have remained relatively stable, there has been a noticeable rise in the incidence of overweight during the same time frame. The increasing trend of overweight among children in India calls for immediate action.

Physical comorbidity is associated with overnight hospitalization in U.S. adults with asthma: an assessment of the 2005-2018 National Health and Nutrition Examination Surveys.

OBJECTIVE: Identifying the effects of comorbidity on healthcare utilization is critical for understanding the benefits of improved comorbidity management. Asthma is a common respiratory condition, associated with gastrointestinal, metabolic, psychiatric, and other respiratory conditions. Adults with asthma represent a key population in understanding comorbidity and its consequences. The objective was to explore the relationship between comorbidity and overnight hospitalizations in U.S. adults with asthma. STUDY DESIGN AND METHODS: A cross-sectional sample of 3,887 subjects aged 20-79 was aggregated from seven cycles (2005-2018) of the National Health and Nutrition Examination Survey (NHANES). The survey design was created using the full seven cycles, then a subpopulation was used for the analysis. Design-based modified Poisson regression with robust standard errors compared the prevalence of overnight hospitalizations in subjects with and without comorbidities. Comorbidity was defined as the presence of one or more additional chronic conditions. RESULTS: Over half (61.6%) of patients with asthma reported having comorbidities. The overnight hospitalization prevalence was higher in those with comorbidities (21.6%) than those without (7.4%). The adjusted prevalence ratio of overnight hospitalizations in those with comorbidities vs. those without was 2.02 (95% CI: 1.54-2.66). Conclusions from sensitivity analyses remained the same. CONCLUSIONS: Comorbidity in U.S. adult asthma patients is associated with increased overnight hospitalizations. Study results concur with examinations of other healthcare utilization outcomes, revealing how comorbidity influences healthcare utilization patterns in patients with asthma. The reduction of overnight hospitalizations should be a targeted goal when developing and evaluating interventions to manage comorbidities in patients with asthma.

Defining and Identifying Only Children: A Research Note on the Concept and Measurement Illustrated With UK Survey Data.

Despite increasing interest in the circumstances and outcomes of only children in the demographic literature, the conceptualization of this group has received limited scholarly attention. This research note argues for greater engagement by demographers and social scientists in the conceptualization and identification of only children by addressing three aims. First, we outline potential definitions of only children, present a framework to guide researchers' decisions, and evaluate whether only children can be reliably identified using the British birth cohort studies. Second, we show that the prevalence estimates are contingent on the timing of measurement in childhood, indicating the need for caution when deriving only-child status from cross-sectional household grid data. Third, we demonstrate that both the size and the characteristics of the only-child group may differ across definitions, highlighting that the accurate operationalization of some definitions is particularly restricted by survey designs that prioritize mothers for data collection on children and families. We argue that researchers interested in sole children's outcomes must choose the most appropriate measure for a given research question and, given that many datasets limit how accurately any indicator of only children can capture the chosen definition, reflect on how the operationalization of their measure might affect the results.

A bivariate Poisson regression to analyse impact of outlier women on correlation between female schooling and fertility in Malawi.

BACKGROUND: Women's levels of education and fertility are commonly associated. In Sub-Saharan Africa, the pace of decreasing fertility rates varies greatly, and this is linked to women's levels of education. However, this association may be influenced by unusual females who have uncommon measurements on both variables. Despite this, most studies that researched this association have only analysed the data descriptively, without taking into account the effect of potential outliers. This study aimed to examine the presence and impact of outlier women on the relationship between female education and fertility in Malawi, using regression methods. METHODS: To analyse the correlation between women's schooling and fertility and evaluate the effect of outliers on this relationship, a bivariate Poisson model was applied to three recent demographic and health surveys in Malawi. The R software version 4.3.0 was used for model fitting, outlier computations, and correlation analysis. The STATA version 12.0 was used for data cleaning. RESULTS: The findings revealed a correlation of -0.68 to -0.61 between schooling and fertility over 15 years in Malawi. A few outlier women were identified, most of whom had either attended 0 or at least 9 years of schooling and had born either 0 or at least 5 children. The majority of the outliers were non-users of modern contraceptive methods and worked as domestic workers or were unemployed. Removing the outliers from the analysis led to marked changes in the fixed effects sizes and slight shifts in correlation, but not in the direction and significance of the estimates. The woman's marital status, occupation, household wealth, age at first sex, and usage of modern contraceptives exhibited significant effects on education and fertility outcomes. CONCLUSION: There is a high negative correlation between female schooling and fertility in Malawi. Some outlier women were identified, they had either attended zero or at least nine years of schooling and had either born zero or at least five children. Most of them were non-users of modern contraceptives and domestic workers. Their impact on regression estimates was substantial, but minimal on correlation. Their identification highlights the need for policymakers to reconsider implementation strategies for modern contraceptive methods to make them more effective.

Burden, trend and determinants of various forms of domestic violence among reproductive age-group women in India: findings from nationally representative surveys.

BACKGROUND: Violence, a notable human rights concern, has a public health impact across the globe. The study aimed to determine the prevalence and determinants of domestic violence among ever-married women aged 18-49 years in India. METHODS: Secondary data analysis with National Family Health Survey 5, 2019-21 data (NFHS-5) was conducted. The complex sampling design of the survey was accounted-for during analysis. The primary outcome was domestic violence. Prevalence was reported with 95% confidence interval (CI). Prevalence ratio was reported to provide the factors associated with domestic violence using Poisson regression. RESULTS: About 63 796 ever-married women aged 18-49 years covered under domestic violence module of NFHS-5 survey were included. Prevalence of domestic violence (12 months preceding the survey) was 31.9% (95% CI: 30.9-32.9%). Physical violence (28.3%) was the most common form followed by emotional (14.1%) and sexual violence (6.1%). Women with low education, being employed, husband being uneducated or with coercive behavior had significantly higher prevalence of domestic violence. CONCLUSIONS: One-third of the reproductive age-group women were facing some form of domestic violence. Target group interventions like violence awareness campaigns, women supportive services and stringent law enforcement should be implemented to eliminate domestic violence by year 2030.

Who continues to work after retirement age?

BACKGROUND: Demographic changes in all industrialized countries have led to a keen interest in extending working lives for older workers. To achieve this goal, it is essential to understand the patterns of retirement and specifically what characterizes individuals who continue to work beyond retirement age. Thus, the aim of this paper was to contribute to the international body of empirical knowledge about individuals who continue in the workforce after retirement age. We present evidence from Denmark and examine what characterizes individuals who continue in the workforce after retirement age and investigate the likelihood of continued work after retirement age while controlling for a set of socio-economic and lifestyle factors. METHODS: The study population consisted of 5,474 respondents to the Copenhagen Aging and Midlife Biobank (CAMB) 2021 survey, divided into two groups. The first group included subjects (n = 1,293) who stayed longer in the workforce even though they had the possibility to retire. The second group consisted of subjects who had retired full-time at the time of the survey (n = 4,181). Survey data was linked to register data to provide a broader dataset. In order to investigate the heterogeneity between the two groups in terms of important socio-economic, work-related and health-related variables, t-test, Mann-Whitney U (Wilcoxon Rank) test, and chi-square tests were employed. Further, to examine the probability of an individual working after retirement age a logit model with step-wise inclusion was utilized. RESULTS: Overall, individuals who continue to work even though they could retire tend to be wealthier, healthier, and males compared to individuals who are retired full-time. Further, there are more older workers who have partners and are co-habitants than retirees. The likelihood of continuing in the workforce past retirement age is affected by several work-related factors as well as life-style factors. The likelihood of working past retirement age decreases by years spent in the workforce (marginal effect of -0.003), if you have a partner (-0.080) and if your partner is outside of the workforce (marginal effect of -0.106). The likelihood increases by health (marginal effect of -0.044 of moving from excellent/very good health to good health or to fair/poor health, physical working capability (marginal effect of -0.083 of moving from no/some problems to severe problems or cannot work at all) and income (marginal effect of 0.083 from moving from the lowest income-quantile to higher quantiles). CONCLUSION: These results are in line with the previous literature and suggest the importance of designing retirement policies that tailor the transition toward retirement according to specific characteristics of both the individual and the segment of occupation.

High-risk pooling for mitigating risk selection incentives in health insurance markets with sophisticated risk equalization: an application based on health survey information.

BACKGROUND: Despite sophisticated risk equalization, insurers in regulated health insurance markets still face incentives to attract healthy people and avoid the chronically ill because of predictable differences in profitability between these groups. The traditional approach to mitigate such incentives for risk selection is to improve the risk-equalization model by adding or refining risk adjusters. However, not all potential risk adjusters are appropriate. One example are risk adjusters based on health survey information. Despite its predictiveness of future healthcare spending, such information is generally considered inappropriate for risk equalization, due to feasibility challenges and a potential lack of representativeness. METHODS: We study the effects of high-risk pooling (HRP) as a strategy for mitigating risk selection incentives in the presence of sophisticated- though imperfect- risk equalization. We simulate a HRP modality in which insurers can ex-ante assign predictably unprofitable individuals to a 'high risk pool' using information from a health survey. We evaluate the effect of five alternative pool sizes based on predicted residual spending post risk equalization on insurers' incentives for risk selection and cost control, and compare this to the situation without HRP. RESULTS: The results show that HRP based on health survey information can substantially reduce risk selection incentives. For example, eliminating the undercompensation for the top-1% with the highest predicted residual spending reduces selection incentives against the total group with a chronic disease (60% of the population) by approximately 25%. Overall, the selection incentives gradually decrease with a larger pool size. The largest marginal reduction is found moving from no high-risk pool to HRP for the top 1% individuals with the highest predicted residual spending. CONCLUSION: Our main conclusion is that HRP has the potential to considerably reduce remaining risk selection incentives at the expense of a relatively small reduction of incentives for cost control. The extent to which this can be achieved, however, depends on the design of the high-risk pool.

Linking Opinions Shared on Social Media About COVID-19 Public Health Measures to Adherence: Repeated Cross-Sectional Surveys of Twitter Use in Canada.

BACKGROUND: The effectiveness of public health measures (PHMs) depends on population adherence. Social media were suggested as a tool to assess adherence, but representativeness and accuracy issues have been raised. OBJECTIVE: The objectives of this repeated cross-sectional study were to compare self-reported PHM adherence and sociodemographic characteristics between people who used Twitter (subsequently rebranded X) and people who did not use Twitter. METHODS: Repeated Canada-wide web-based surveys were conducted every 14 days from September 2020 to March 2022. Weighted proportions were calculated for descriptive variables. Using Bayesian logistic regression models, we investigated associations between Twitter use, as well as opinions in tweets, and self-reported adherence with mask wearing and vaccination. RESULTS: Data from 40,230 respondents were analyzed. As self-reported, Twitter was used by 20.6% (95% CI 20.1%-21.2%) of Canadians, of whom 29.9% (95% CI 28.6%-31.3%) tweeted about COVID-19. The sociodemographic characteristics differed across categories of Twitter use and opinions. Overall, 11% (95% CI 10.6%-11.3%) of Canadians reported poor adherence to mask-wearing, and 10.8% (95% CI 10.4%-11.2%) to vaccination. Twitter users who tweeted about COVID-19 reported poorer adherence to mask wearing than nonusers, which was modified by the age of the respondents and their geographical region (odds ratio [OR] 0.79, 95% Bayesian credibility interval [BCI] 0.18-1.69 to OR 4.83, 95% BCI 3.13-6.86). The odds of poor adherence to vaccination of Twitter users who tweeted about COVID-19 were greater than those of nonusers (OR 1.76, 95% BCI 1.48-2.07). English- and French-speaking Twitter users who tweeted critically of PHMs were more likely (OR 4.07, 95% BCI 3.38-4.80 and OR 7.31, 95% BCI 4.26-11.03, respectively) to report poor adherence to mask wearing than non-Twitter users, and those who tweeted in support were less likely (OR 0.47, 95% BCI 0.31-0.64 and OR 0.96, 95% BCI 0.18-2.33, respectively) to report poor adherence to mask wearing than non-Twitter users. The OR of poor adherence to vaccination for those tweeting critically about PHMs and for those tweeting in support of PHMs were 4.10 (95% BCI 3.40-4.85) and 0.20 (95% BCI 0.10-0.32), respectively, compared to non-Twitter users. CONCLUSIONS: Opinions shared on Twitter can be useful to public health authorities, as they are associated with adherence to PHMs. However, the sociodemographics of social media users do not represent the general population, calling for caution when using tweets to assess general population-level behaviors.

Engaging adolescents in research: Home self-collection of biological samples and health questionnaires.

Adolescent health research with biomarker data collection is limited due to difficulties in recruiting and engaging this age group. Thus, successful recruitment, engagement, and retention of adolescents in translational research are necessary to elucidate factors influencing mental and physical health conditions, uncover novel biomarkers, and expand prevention and treatment options. This paper describes strategies for effective recruitment and retention of adolescents in a research study, using a project examining depressive symptoms and the microbiome to illustrate these approaches. This cross-sectional study collected electronic self-reported survey data and self-collected biospecimens (stool and salivary samples) from adolescents 13-19 years old. All but two participants completed the questionnaires, with few missing responses. 94% provided at least one salivary sample and 89% supplied a stool sample. Participants were able to adhere to the study instructions. Using a participant-centered approach, our study successfully recruited and engaged the targeted 90 participants in self-collection of electronic survey data and biospecimens. Successful strategies of recruitment and retention included: 1) on-site clinic recruitment by research team, 2) active involvement of parents as appropriate, 3) use of electronic surveys and self-collection of biospecimens to foster control and ease of participation while addressing privacy concerns, 4) noninvasive collection of data on biospecimen, 5) frequent texting to communicate with participants, 6) flexibility in the pickup and transferring of biospecimens to accommodate adolescent schedules, 7) developmentally appropriate research, 8) participant reimbursement, and 9) sensitivity toward discussing stool sample materials. As a result of these strategies, adolescent participation in the research proved feasible.

Dying at home: What is needed? Findings from a nationwide retrospective cross-sectional online survey of bereaved people in Germany.

OBJECTIVES: According to the "Last Year of Life in Cologne" study, 68% of patients with a serious and terminal illness wanted to die at home, but 42% died in hospital. Only 1 in 5 died at home. Most people want to spend their last days and hours at home, but the reality is that this is not always possible. Recommendations are needed on how best to support families to enable people to die at home - if this is their preferred place of death. Our aim was to identify the factors that make it possible for people to die at home and to analyze factors of dying at home. METHODS: Germany-wide quantitative cross-sectional online survey of bereaved adult relatives. RESULTS: The needs of 320 relatives of patients who wished to die at home were explored. Of these, 198 patients died at home and 122 did not. In the last 3 months of life, caregivers needed support in managing out-of-hours care (p < 0.001), financing (p = 0.012), preparing and organizing home care (both p < 0.001), communicating with the patient and medical staff (p = 0.012 and p = 0.009, respectively), and pain management (p < 0.001). Relatives whose next of kin did not die at home had higher needs, suggesting that these factors are key to home care of the dying. SIGNIFICANCE OF RESULTS: The process of dying at home begins long before the actual dying phase. To minimize caregiver burden and improve symptom management, advanced home care plans are needed, with ongoing reassessment of family preferences and abilities.

Conscientious use of patient-reported outcome measures in supportive care.

PURPOSE: Patient-reported outcome measures (PRO) are critical tools to developing an understanding of cancer patients' experience. This paper presents some of the lesser-understood implications of using patient-reported outcome measures in clinical research. METHODS: This study uses a combination of literature sources, real-world examples from supportive care studies, and statistical simulations to demonstrate the operating characteristics of patient-reported measures. RESULTS: It is demonstrated that care must be taken in the analysis of PROs as the assumptions of the most common mean-based approaches are often violated including linearity, normally distributed errors, interference with asymptotic convergence via boundary values, and more. Further, the implications of subjective discretization are shown to reduce the apparent statistical power of PRO-based studies. CONCLUSIONS: PRO-based studies must be designed conscientiously as each PRO item will demonstrate a varying degree of subjectivity in a given population. Sample sizes of randomized studies using PROs must be inflated to account for this. Analyses should consider using ordinal statistical models until such time as the assumptions of mean-based models can be verified.

Perspectives on the Doctor of Public Health (DrPH) education among students and alumni in the United States: a cross-sectional national online survey.

BACKGROUND: This study explored the current and desired identity of the DrPH degree, focusing on whether the competencies set by the Council on Education for Public Health (CEPH) adequately prepare DrPH graduates for effective public health practice. Additionally, the study investigated the necessity of standardization in DrPH training, referring to a consensus-driven approach that equips future public health practitioners with practical skillsets applicable in real-world scenarios. METHODS: A national cross-sectional online survey titled "National DrPH leaders & practitioners needs assessment" was conducted from November 2020 to February 2021. The survey was based on a self-report by DrPH students and DrPH professionals, consisting of the following two main components: (1) how their DrPH training aligns with CEPH competencies and (2) how they perceive the identity of the DrPH degree. Convenience sampling was used to collect the data, which may have limited representation for all DrPH institutions in the United States. RESULTS: A total of 222 participants (140 current DrPH students and 82 alumni) completed the survey. The mean of the 10-point Likert scale for the degree to which the DrPH training aligns with 26 CEPH competencies (1: not at all - 10: absolutely) ranged from 6.3 (SD: 2.78) to 7.96 (SD: 2.16). The majority of participants (191/222, 86.04%) were satisfied with the knowledge and skills reflected in their training based on the CEPH competencies. However, more than half of the participants (117/222, 52.70%) sought additional professional development/training outside their institutions. DrPH leaders and practitioners faced barriers where the value of their work might not be fully recognized and endorsed. Participants indicated that the DrPH education should be further distinguished from the PhD education. CONCLUSIONS: The DrPH degree holds significant value within the academic sphere of public health practice in the United States. However, its distinction from PhD programs poses a challenge for employers and organizations in the field, requiring attention from higher education programs. By solidifying the DrPH's identity, graduates can effectively address diverse public health issues and contribute to creating a safe and healthy environment, including addressing the challenges posed by the COVID-19 pandemic.

Identification of factors controlling heavy metals/metalloid distribution in agricultural soils using multi-source data.

Understanding the factors that controlling the agricultural soil heavy metals/metalloids distribution is vital for cropland soil remediation and management. For this objective, 227 agricultural soils were sampled in the Guanzhong Plain, China, to measure the concentration of five heavy metals (Pb, Cd, Ni, Zn, and Cu) and one metalloid (As) by X-ray fluorescence spectrometer, meanwhile, 24 possible influencing factors to agricultural soil heavy metals/metalloid distribution were collected and grouped into three categories. A sequential multivariate statistical analysis was carried out to provide insight into the controlling factors of soil heavy metals/metalloid distribution, then stepwise multiple linear regression (SMLR) and partial least squares regression (PLS) were used to predict heavy metals/metalloid concentrations in agricultural soil based on the result of soil heavy metals/metalloid controlling factors identification. The results demonstrated the types of soil and land use did not have a substantial effect on soil heavy metals/metalloid distribution, except Zn and Cu. The soil properties category played a major role in influencing the soil heavy metals/metalloid concentration. The concentrations of Mn and Fe, which are the main constitute elements of soil inorganic colloid, were the most significant factors, followed by the concentrations of P, K and Ca. Soil pH and soil organic matter (SOM) content, which are often considered as important factors for soil heavy metals/metalloid distribution, were not important in the present study. The SMLR was more effective than the PLS for predicting soil heavy metals/metalloid content. The results of this study enlighten that future soil heavy metals/metalloid contamination treatment in regions with high pH and low SOM content should concentrate on inorganic colloid particles, which have strong adsorption capacity for soil heavy metals/metalloid and are environmentally friendly. Moreover, the combination of successive multivariate statistical analysis and SMLR provide an effective tool to predict and monitor agricultural soil heavy metals/metalloid distribution, and facilitate the improvement of environmental and territorial management.

Attitude Towards Deposit Limits and Relationship with Their Account-Based Data Among a Sample of German Online Slots Players.

Social responsibility and duty of care have become major cornerstones for gambling operators. This has led to the introduction of many different responsible gambling tools such as limit-setting, mandatory play breaks, and personalized messaging. In the present study, the authors were given access to two secondary datasets provided by a German online slots game operator. The first dataset was from an online survey carried out by the gambling operator among 1000 of its players concerning their attitude towards deposit limits as well as self-reported problem gambling. In addition to the survey responses, the authors were given access to a second dataset of account-based data concerning each customer's wagers, wins, monetary deposits, and monetary withdrawals. These datasets were then combined. The majority of players had a positive attitude towards the maximum deposit monthly deposit limit which was introduced by the German State Treaty on Gambling in 2021. Players who disagreed with the maximum monthly deposit limit, deposited significantly more money in the 30 days prior to answering the survey questions compared to players who agreed with the monthly deposit limit. The tracking data found only 7.6% of players had deposited the maximum amount of money allowed in one month. However, 60.5% of players in the survey data said that they did so. Players who said that they continued to gamble after reaching the deposit limit wagered and deposited significantly more money in the 30 days prior to the survey compared to players who said they stopped gambling after reaching the deposit limit. Two-fifths of players said they continued to gamble after reaching the monthly deposit limit (42%). The majority of the players said they chose a personal deposit limit because it helped them to better control their gambling expenditure. A quarter of the players reported gambling problems using the Brief Biosocial Gambling Screen (27%). Self-reported problem gambling was not correlated with depositing, wagering or any other player tracking metric.

A spatial model to jointly analyze self-reported survey data of COVID-19 symptoms and official COVID-19 incidence data.

This work presents a joint spatial modeling framework to improve estimation of the spatial distribution of the latent COVID-19 incidence in Belgium, based on test-confirmed COVID-19 cases and crowd-sourced symptoms data as reported in a large-scale online survey. Correction is envisioned for stochastic dependence between the survey's response rate and spatial COVID-19 incidence, commonly known as preferential sampling, but not found significant. Results show that an online survey can provide valuable auxiliary data to optimize spatial COVID-19 incidence estimation based on confirmed cases in situations with limited testing capacity. Furthermore, it is shown that an online survey on COVID-19 symptoms with a sufficiently large sample size per spatial entity is capable of pinpointing the same locations that appear as test-confirmed clusters, approximately 1 week earlier. We conclude that a large-scale online study provides an inexpensive and flexible method to collect timely information of an epidemic during its early phase, which can be used by policy makers in an early phase of an epidemic and in conjunction with other monitoring systems.

Does socioeconomic status impact the relationship between school absence and outcomes?

Absence from school, especially frequent or prolonged absence, is acknowledged as a potential factor in school dropout and suboptimal academic achievement. The issue of absence from school took on added significance in 2020 with the onset of the COVID-19 crisis, which resulted in schooling interruptions in several jurisdictions. However, there is little agreement in the literature on the exact relationship between absence and school outcomes as a function of socioeconomic status (SES). Using nationally representative pre-COVID longitudinal data of young Australians aged 12-13 and 14-15, this paper examines the relationship between absence from school on the one hand and school belonging and academic achievement (numeracy and reading test scores) on the other. The paper also examines whether SES intersects this relationship. Controlling for gender, prior educational achievement, computer access, and time spent doing homework, the study finds that absence impacts belonging, but that SES does not significantly influence this relationship. The effect of absence on reading is not significant either. However, absence is associated with numeracy outcomes, with the strongest associations among low SES young people at age 14. Policy implications of these findings are discussed. Supplementary Information: The online version contains supplementary material available at 10.1007/s13384-022-00535-2.

Children with genetic conditions in the United States: Prevalence estimates from the 2016-2017 National Survey of Children's Health.

PURPOSE: Estimating the overall prevalence of genetic conditions among children in the United States and the burden of these conditions on children and their families has been challenging. The redesigned National Survey of Children's Health provides an opportunity to examine the prevalence and burden. METHODS: We used the combined 2016-2017 National Survey of Children's Health to estimate the prevalence of genetic conditions among children aged 0 to 17 years (N = 71,522). Bivariate analyses were used to assess differences in sociodemographic characteristics, health-related characteristics, and health care utilization between children with and without genetic conditions. RESULTS: In 2016-2017, the prevalence of children aged 0 to 17 years with a reported genetic condition was approximately 0.039, roughly equating to 2.8 million children. A greater percentage of children with genetic conditions had a physical (50.9% vs 24.8%), mental (27.9% vs 5.8%), or behavioral/developmental/intellectual condition (55.6% vs 14.4%) than children without a genetic condition. Furthermore, they used more care and had more unmet health needs (7.6% vs 2.9%). CONCLUSION: This study provides an estimate of the overall prevalence of children living with genetic conditions in the United States based on a nationally representative sample. It also highlights the physical, mental, and behavioral health needs among children with genetic conditions and their unmet health care needs.

The Association Between Adverse Childhood Experiences and Positive Dementia Screen in American Older Adults.

BACKGROUND: Adverse childhood experiences (ACEs) are linked to higher risk of common conditions driving mortality in adulthood, but little evidence exists on whether ACEs are associated with risk of dementia, a leading cause of death in the USA. OBJECTIVE: To estimate the relationship between US adults' reported ACE scores and a positive screen for dementia. DESIGN: Cross-sectional analysis of a longitudinal, national population-based survey of US older adults. PARTICIPANTS: Survey respondents aged ≥ 65 years with dementia screening data from the 2017 wave of the Panel Study of Income Dynamics (PSID) and ACE scores from the 2014 PSID Childhood Retrospective Circumstances Survey supplement (1,488 eligible participants unweighted). MAIN MEASURES: Dementia screening data was collected in the 2017 wave of the PSID using the 8-item informant interview to differentiate normal cognition and dementia (AD8). Mean change in AD8 score and probability of a positive dementia screen by ACE score were calculated using adjusted regression models with post-estimation. Analyses were stratified by age group. Measures were analyzed in 2020. RESULTS: Complete data were available for 1,223 (82%) participants, with a mean age of 73.4 years (SD 7.1, range 65 to 96 years). Adjusted estimated probability of a positive dementia screen increased with each additional adverse childhood experience reported. Older adults with ≥ 4 ACEs had higher rates of a positive dementia screen (AD8 score ≥ 2 points) compared to those with no ACEs (adjusted rate 26.6% versus 16.3%, p = 0.034). Compared to those with no ACE history, respondents with ≥ 4 ACEs had higher odds of a 1-point increase in AD8 score across all intervals of the AD8 scale (aOR 1.79, 95% CI 1.05-3.04). The ACE-positive dementia screen associations were strongest among those aged 65-75. CONCLUSIONS: Greater exposure to ACEs is independently associated with higher probability of a positive dementia screen in older adulthood.