Nationally-representative Dataset Research Articles

Examining chronic kidney disease screening frequency among diabetics: a POMDP approach.

Forty percent of diabetics will develop chronic kidney disease (CKD) in their lifetimes. However, as many as 50% of these CKD cases may go undiagnosed. We developed screening recommendations stratified by age and previous test history for individuals with diagnosed diabetes and unknown proteinuria status by race and gender groups. To do this, we used a Partially Observed Markov Decision Process (POMDP) to identify whether a patient should be screened at every three-month interval from ages 30-85. Model inputs were drawn from nationally-representative datasets, the medical literature, and a microsimulation that integrates this information into group-specific disease progression rates. We implement the POMDP solution policy in the microsimulation to understand how this policy may impact health outcomes and generate an easily-implementable, non-belief-based approximate policy for easier clinical interpretability. We found that the status quo policy, which is to screen annually for all ages and races, is suboptimal for maximizing expected discounted future net monetary benefits (NMB). The POMDP policy suggests more frequent screening after age 40 in all race and gender groups, with screenings 2-4 times a year for ages 61-70. Black individuals are recommended for screening more frequently than their White counterparts. This policy would increase NMB from the status quo policy between $1,000to $8,000 per diabetic patient at a willingness-to-pay of $150,000 per quality-adjusted life year (QALY).

Determinants of organic soil fertilization methods use over time and in the face of climate vulnerability

Implementation of environment-friendly soil organic matter (SOM) enhancing technologies (SOMET) is crucial for addressing soil degradation. This study aims to examine the usage status of SOMET (i.e., organic fertilizer, manure, and compost) from the dimension of long-term non-usage, dis-usage, late-usage and long-term usage and identify the drivers of these four behaviors of usage. We utilized national representative datasets of 1659 Bangladeshi rice-farmers for the periods of 2013, 2016 and 2020 with climate hazards data. Households were categorized into long-term non-user (48%) who does not practice SOMET in any of three survey years, dis-user (29%) as the households who abandon SOMET after practicing a period of time, late-user (20%) for the households who apply SOMET a few years later than their peer, long-term user (3%) as the households who practice SOMET for three survey years. Ordered logit model was used to quantify drivers of likelihood of being the four above defined categories. SOMET use has been found to be highly constrained by climate hazards. Flood depth, salinity, heavy rainfall, storm and cyclone vulnerability decrease likelihood of long-term use and late-use while increase the probability of long-term non-use and dis-use (p≤0.01). Alternatively, the likelihood of long-term non-use and dis-use are 12% and 4% lower in drought-prone areas. Increasing drought experiences increase the probability of long-term use and late-use (p≤0.01). Higher SOM level decreases long-term non-use but induces dis-use. Other major drivers of SOMET long-term use are older household head, more educated women in households, larger farm-size, and higher livestock values. Considering these factors in developing and implementing policies could be instrumental in promoting SOMET application at farm-level. Long-term use is context-specific with various climate and socio-economic factors, thus, designing policies and strategies should emphasize contextual variations to promote usage continuities.

한국의 소비불평등 요인분해에 관한 연구

Purpose: This study examines the determinants of household consumption expenditure and quantifies their contribution to within group inequality by gender of household head in South Korea.
 Research design, data, and methodology: This study first decomposes total inequality into within and between inequality by gender of household head. It also examines the association between a vector of household demographic and socioeconomic characteristics and household consumption expenditure in an attempt to identify how much inequality can be attributed to each of explanatory factors. This study empirically draws upon the recent national representative dataset, Survey of Household Finance and Living Conditions (SFLC) 2 021 c ollected b y Korea Statistical Office.
 Results: According to the present study, inequality in 2021 in South Korea was found to be mainly dominated by inequality within population sub groups. Examining the determinants of household consumption inequality, it shows that factors and their conributions are different between male and female headed households. For instance, whilst the type of job occupation of a head appears to have a large impact on inequality within male headed households, it is found to have marginal contribution compared to within female headed households (25.2% vs. 7.4%). In case of household demography, it is observed as the second largest factor increasing within inequality among female headed households (31.2%) whereas its contribution to inequality within inequality among male group was relatively small (18.6%).
 Implications: Our study suggests that target specific investigation and deep structural understanding need to be made on the different characteristics of within inequality as reflected by the different role of factors and their contributions. Amongst, the different inequality impact of higher education might reflect that the expansion of higher education had a relatively lower impact on the living stand of female group than that of its counterpart, male group. Finally, the discriminatory barriers (e.g. job occupation) against female may reduce within inequality, it could widen total inequality, worsening distribution between male and female groups.

Protect the environment for impressing others? Understanding whether, why, and when relational mobility shapes individual pro-environmental behaviors

Despite a substantial body of literature on pro-environmental behaviors (PEBs), there has been an overlook of whether and how broader social contexts (relational mobility in particular) may shape PEBs. Integrating the perspective of the person-context interaction with impression management theory, our research aims to understand whether, why, and when relational mobility, an important societal factor, impacts individual self-reported PEBs. Study 1 utilized a national representative dataset and found that relational mobility was positively associated with PEBs. Study 2 replicated this result using a new sample, and further found that relational mobility increased PEBs via impression management motivation. Finally, Study 3 was conducted with an experimental design, revealing that environmental self-identity strengthened the mediating effect identified in Study 2. The findings highlight that PEBs can be shaped by broader environmental factors via impression management motivation, which provides practical implications for promoting environmental sustainability.

Variants of Gender Bias and Sexual-Orientation Discrimination in Career Development

Abstract We use a nationally-representative dataset that includes a large sample of sexual-orientation minorities to investigate gender bias and sexual-orientation discrimination in career progression. Our results are consistent with persistent gender bias findings and non-heterosexual identity-based employment discrimination. Our findings are consistent with previous work noting that protective legislation for gay and lesbian sexual identities have increased the cost of discrimination and contribute to the improved socioeconomic status of a substantial number of people in these minority groups. However, these gains have not been shared with other minority groups in the LGB+ community, which still have some of the lowest probabilities of holding managerial jobs, and higher probabilities of appearing in lower socioeconomic classes.

Nonmonotonic effects of subjective social class on pro-environmental engagement

Addressing environmental challenges necessitates collaborative efforts from individuals with diverse socioeconomic backgrounds. This article delves into the influence of social class on pro-environmental engagement, employing a comprehensive research approach involving five distinct studies. The investigations encompassed a national representative dataset (Study 1), an online survey (Study 2), and controlled experiments (Studies 3, 4a, & 4b). The consistent findings revealed an inverted-U class effect on pro-environmental engagement, indicating that individuals from the middle-class demonstrated a higher likelihood of engaging in pro-environmental behavior compared to both lower- and upper-class individuals. However, this effect only manifested in a particular form of pro-environmental engagement, namely easily observable good citizenship behavior. To elucidate the underlying mechanisms of this nonmonotonic relationship between social class and pro-environmental engagement, we turned to the middle-status anxiety hypothesis. As a result, moral identity symbolization emerged as a psychological foundation that could account for the observed effects. These novel findings contribute significantly to the existing research on environmental engagement and its connection to social class.

Examining the associations between testosterone and biomarkers as men age.

Testosterone concentrations in men decline with advancing age. However, the cause of the decline is yet to be fully elucidated. Therefore, the aims of this study were to examine the associations between chronic diseases such as obesity and type 2 diabetes mellitus (T2DM) with total testosterone (TT) and sex hormone-binding globulin (SHBG), using a large nationally-representative data set (National Health and Nutrition Examination Survey; NHANES). NHANES is a cross-sectional survey, physical examination, and laboratory evaluation of a nationally-representative sample of a non-institutionalized United States population. Male participants aged ≥18 years during the NHANES 2013-2014 and NHANES 2015-2016 survey periods were selected for this analysis. The analysis included the following data: body mass index (BMI), oral glucose tolerance test (OGTT), homeostatic model assessment of insulin resistance (HOMA-IR), insulin, glucose, and age. An overweight or obese condition was significantly inversely associated with TT and SHBG, even after adjusting for other variables. Several variables associated with T2DM (OGTT, HOMA-IR, insulin, and glucose) were also inversely associated with TT; however, only the associations between OGTT and insulin with TT remained significant after adjusting for the other variables. Insulin and HOMA-IR levels were significantly inversely associated with SHBG; however, only the association between SHBG and pre-diabetic HOMA-IR levels remained significant after adjusting for the other variables. OGTT became significantly associated with SHBG after adjusting for the other variables. Age was significantly inversely associated with TT, but positively associated with SHBG, even after adjusting for other variables. The results of the present study, which is the largest to date, indicate that a marker of obesity, BMI, and some markers of T2DM are both independently and significantly inversely associated with TT and SHBG.

Population-based validation of the melanoma institute australia (MIA) and the memorial sloan-kettering cancer center (MSKCC) predictive tool for sentinel node status in patients with melanoma.

9571 Background: Patients with primary cutaneous melanoma are selected for sentinel lymph node biopsy (SLNB) based upon their risk of a positive SLN being identified. To improve upon stage-based categorization, the Memorial Sloan Kettering Cancer Center (MSKCC) and Melanoma Institute Australia (MIA) developed predictive models. Which model is more clinically useful is currently unclear. Methods: Consecutive patients undergoing SLNB from 2007-2021 were identified from the Swedish Melanoma Registry (SweMR), which covers 99% of patients with invasive cutaneous melanoma in Sweden. The predicted probability of SLN positivity was calculated using the MSKCC and limited MIA models (using mitotic rate as absent/present instead of count and excluding the optional variable lymphovascular invasion) for each patient. The operating characteristics of the models were assessed and compared. The “clinical utility” of each model was assessed using decision curve analysis (DCA) and compared with a strategy of performing SLNB on all patients. Results: In total 10,089 patients were included; the median Breslow thickness was 1.8 mm, 33.7% were ulcerated, and 1,802 patients had a positive SLN (17.9%). Both the MSKCC and limited MIA models were well calibrated across the full range of predicted probabilities, and had similar external area under curve (AUC), MSKCC 70.8% (95% CI 69.5-72.1%) and MIA 70.3% (95% CI 68.9-71.7%). When new models were constructed to compare the incremental value of the additional parameters of either nomogram over Breslow thickness alone, the AUCs were 70.1%, 71.6% and 72.0% for Breslow alone, MIA parameters and MSKCC parameters, respectively. At a risk threshold of 5%, DCA indicated no added net benefit for either model compared to performing SLNB for all patients. At risk thresholds of 10% or higher, both models added net benefit compared to SLNB for all. The greatest benefit was observed from use of the models in patients with T2 melanomas when a threshold of 10% was used to select patients for SLNB. In that setting, use of the nomograms led to a net reduction in seven avoidable SLNBs per 100 patients for the limited MIA nomogram and eight for the MSKCC nomogram, when compared to a strategy of SLNB for all. Conclusions: This study confirms the statistical performance of both the MSKCC and limited MIA models in a large, nationally-representative dataset. However, clinical utility as assessed by DCA demonstrated that using the models only improved selection for SLNB when a risk threshold of at least 10% was employed, and then mainly for T2 melanomas. Either further development of the nomograms, or other strategies, are needed to improve selection at lower risk thresholds.

Brief Report: Longitudinal Trajectory of Working Memory in School-Aged Children on the Autism Spectrum: Period of High Plasticity and "Late Bloomers".

While working memory (WM) is a powerful predictor for children's school outcomes, autistic children are more likely to experience delays. This study compared autistic children and their neurotypical peers' WM development over their elementary school years, including relative growth and period of plasticity. Using a nationally-representative dataset, latent growth models were built to examine periods of high plasticity and the relationship between children's performance upon school entry and their relative growth. While both groups made steeper gains during the early school years, autistic children's period of highest plasticity was prolonged by 1year, which suggests a larger window for interventions. Further, autistic children who started kindergarten with poorer WM were more likely to make rapid growth during the last 3years of elementary school, which is when their neurotypical peers' development started to plateau. Findings should prompt various stakeholders to examine interventions and instructions to maximize autistic children's growth in WM. Further, the continued support and monitoring by educators throughout autistic children's late childhood can be particularly beneficial for the "late-bloomers."

MP19-16 LARGE STATE-LEVEL VARIATION IN INTRAVESICAL TREATMENT FOR NON-MUSCLE INVASIVE BLADDER CANCER DURING THE BCG DRUG SHORTAGE

You have accessJournal of UrologyCME1 Apr 2023MP19-16 LARGE STATE-LEVEL VARIATION IN INTRAVESICAL TREATMENT FOR NON-MUSCLE INVASIVE BLADDER CANCER DURING THE BCG DRUG SHORTAGE Brian Chun, Meiqi He, Cameron Jones, Robin Vasan, Bruce Jacobs, Inmaculada Hernandez, and Benjamin Davies Brian ChunBrian Chun More articles by this author , Meiqi HeMeiqi He More articles by this author , Cameron JonesCameron Jones More articles by this author , Robin VasanRobin Vasan More articles by this author , Bruce JacobsBruce Jacobs More articles by this author , Inmaculada HernandezInmaculada Hernandez More articles by this author , and Benjamin DaviesBenjamin Davies More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003244.16AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Bacillus Calmette-Guerin (BCG) is the gold standard for treatment of non-muscle invasive bladder cancer. In the last two decades, the two major manufacturers of BCG have suffered production failures or have left the market due to economic infeasibility. This has resulted in a worldwide shortage of this important biologic drug. We used a national representative dataset to describe the effect of this shortage on intravesical treatment patterns for non-muscle invasive bladder cancer. METHODS: Using claims data from a 5% random sample of Medicare beneficiaries, we identified patients ≥66 years of age who received intravesical therapy within 1 year of bladder cancer diagnosis from 2010-2017. The BCG shortage period was defined from July 2012, when the FDA ordered Sanofi to immediately cease drug production due to a facility contamination. We estimated changes in the proportion of patients treated with BCG, mitomycin C, gemcitabine, or other intravesical agents before and during the shortage. We evaluated state-level changes in BCG induction rates before and during the shortage period. RESULTS: 7971 patients were included in our study. The proportion of eligible patients receiving BCG induction therapy decreased 5.9%, from 38.9% (1030 of 2648 patients) in the pre-shortage period, to 33.0% (1756 of 5323 patients) in the shortage period (p<0.001). Mitomycin C use increased from 24.6% in 2010 to a peak in 30.9% in 2014 and 2015 (p=0.001). The use of gemcitabine remained stable (p=0.55). Among 19 states reporting data on ≥50 patients, 16 (84%) had a decrease in BCG initiation rate during the shortage period, ranging from 5.1% (New Jersey) to 35.5% (Washington). CONCLUSIONS: During the BCG drug shortage, BCG use for non-muscle invasive bladder cancer decreased with a compensatory rise in mitomycin C. A large variation in state-level BCG utilization may reflect differences in regional practice patterns or BCG availability. Source of Funding: None © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e271 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Brian Chun More articles by this author Meiqi He More articles by this author Cameron Jones More articles by this author Robin Vasan More articles by this author Bruce Jacobs More articles by this author Inmaculada Hernandez More articles by this author Benjamin Davies More articles by this author Expand All Advertisement PDF downloadLoading ...

SHORT- AND LONG-TERM OUTCOMES AFTER HIP SURGERY IN OLDER ADULTS WITH AND WITHOUT HEART FAILURE

Abstract Older adults with heart failure (HF) have a higher risk for adverse outcomes after hip fracture surgery than those without. Propensity score matching (PSM) reduces selection bias and makes a direct group comparison (older adults with and without HF) possible. Thus, this study aimed to assess the impact of HF on short-and long-term outcomes after hip fracture surgery in older adults living with and without HF. Electronic health records data of older adults (n = 1171) hospitalized for hip fracture surgery between October 2015 and December 2018 were extracted. Comparison groups (with and without HF) were identified using 1:1 ratio PSM to control for observed differences in baseline characteristics. Regression models were used to compare group differences in outcomes. Although in analyses without PSM, older adults with HF were more likely to have higher 90-day readmission, and 30-, 90-, and 365-day mortality, this association was not significant after controlling for selection bias. However, the associations between having HF with 30-day readmission and longer length of stay were significant before and after PSM. Additionally, if patients did not receive hip fracture surgery procedures within two days of admission, they had a 3.6-day longer inpatient stay (P-value &amp;lt; 0.0001) and were 47.8 times more likely to die during hospitalization (95%CI 4.9–482.0, P-value &amp;lt; 0.001). Being non-white was significantly associated with higher 90- and 365-day mortality. Future research should consider PSM approach on national representative datasets to rigorously evaluate the effects of HF on mortality and readmission following hip fracture surgery in older adults.

Maternal Centric Measurement and Data Gaps in Addressing Maternal Morbidities: A Scoping Review.

The objectives of this project were to (1) describe maternal-centric measures and survey data which are publicly available to evaluate the incidence, frequency, and distribution of maternal morbidity in the postpartum period, and (2) to identify postpartum care quality improvement targets and outline the types of measurement and data required to support them. We conducted a scoping review of two types of data sources: maternal health quality measures used by providers and payers and nationally-representative survey data sets administered by federal agencies. Each source was searched for keywords associated with pregnancy and the postpartum period. We included quality measures and survey questions that are maternal-centric and addressed the postpartum period. We excluded infant-centric measures and data. Quality measures were organized according to the Donabedian quality model. Our analysis demonstrates that existing maternal-centric quality measures and survey data offer limited insight into diagnosis and patient care delivery experiences associated with maternal morbidities during the postpartum period. There is inadequate maternal-centric data on the incidence, frequency, and distribution of postpartum maternal morbidities and associated care use. This gap reduces the ability of research to estimate the incidence of illness and injury among postpartum women and create targeted quality improvement efforts. Our findings highlight the need for quality measure stewards and data sponsors to enhance data collection and methods to become more inclusive of maternal-centric outcomes during the postpartum period.

Health gender gap in Uganda: do weather effects and water play a role?

BackgroundVulnerabilities of men and women to adverse health effects due to weather variability and climate change are not equal. Uganda was among the countries in the world most affected by extreme weather events during the last decade. However, there is still limited gendered empirical evidence on the links between weather variability and health and the possible pathways through which these health effects occur. Therefore, this study analyses the effect of weather variability on illness, and the extent to which water collection ‘time burden’ mediates the relationship between weather anomalies and illness among men and women of working age in Uganda. The study also quantifies the health inequalities to be eliminated if resources are equalized.MethodsSocioeconomic, health and time use data were obtained from the World Bank Living Standards Measurement Studies - Integrated Surveys on Agriculture (LSMS –ISA), combined with high resolution remotely-sensed weather data. Two-parts and non-linear decomposition regression analysis were used on the national representative pooled dataset from the four household survey waves collected between 2009 to 2014, comprising a total of 22,469 men and women aged between 15 and 64 years.ResultsEmpirical results show that low rainfall below the long-term mean increased the likelihood of illness by at least 8 and 6 percentage points for women and men, respectively. The indirect effect of low rainfall on illness through water access pathway was estimated at 0.16 percentage points in women. Decomposition results reveal that health inequalities among women and men would have been narrowed by 27–61%, if endowments were equalized.ConclusionsStrategies that promote women empowerment (such as education, labor force participation, access to financial services and clean water), health adaptation and time poverty reduction strategies (such as rain water harvesting and improved access to quality health care) would reduce gender-based health inequalities in Uganda despite changing climatic conditions.

Harnessing machine learning models for non-invasive pre-diabetes screening in children and adolescents

Background and objectivesPre-diabetes has been identified as an intermediate diagnosis and a sign of a relatively high chance of developing diabetes in the future. Diabetes has become one of the most frequent chronic disorders in children and adolescents around the world; therefore, predicting the onset of pre-diabetes allows a person at risk to make efforts to avoid or restrict disease progression. This research aims to create and implement a cross-validated machine learning model that can predict pre-diabetes using non-invasive methods. MethodsWe have analysed the national representative dataset of children and adolescents (5–19 years) to develop a machine learning model for non-invasive pre-diabetes screening. Based on HbA1c levels the data (n = 26,567) was segregated into normal (n = 23,777) and pre-diabetes (n = 2790). We have considered eight features, six hyper-tuned machine learning models and different metrics for model evaluation. The final model was selected based on the area under the receiver operator curve (AUC), Cohen's kappa and cross-validation score. The selected model was integrated into the screening tool for automated pre-diabetes prediction. ResultsThe XG boost classifier was the best model, including all eight features. The 10-fold cross-validation score was highest for the XG boost model (90.13%) and least for the support vector machine (61.17%). The AUC was highest for RF (0.970), followed by GB (0.968), XGB (0.959), ETC (0.918), DT (0.908), and SVM (0.574) models. The XGB model was used to develop the screening tool. ConclusionWe have developed and deployed a machine learning model for automated real-time pre-diabetes screening. The screening tool can be used over computers and can be transformed into software for easy usage. The detection of pre-diabetes in the pediatric age may help avoid its enhancement. Machine learning can also show great competence in determining important features in pre-diabetes.

NASA quesst mission—Site selection process for community testing

The National Aeronautics and Space Administration (NASA) has committed to deliver data to the International Civil Aviation Organization’s Committee on Aviation Environmental Protection (ICAO CAEP) defining community response to sounds from supersonic aircraft designed such that their sonic boom is replaced with a soft “thump” sound. NASA is developing the X-59, a unique research aircraft capable of quiet supersonic flight, and will use the aircraft in a series of four to six community overflight tests (2024–2026) to measure acoustic levels of its “sonic thump” and related public response in support of the agency’s commitment to ICAO. Unlike most NASA flight research, which is conducted primarily at the agency’s facilities, the community tests will occur at various locations across the contiguous United States and involve flight over the general population in order to obtain a nationally-representative dataset. The process for identifying both the airfields and community test locations involves multiple operational and technical considerations relative to both aircraft and data collection requirements, including flight operations, geographic, and climate diversity as well as population demographics. This presentation provides an overview of the ongoing selection process being applied to address those considerations while ultimately ensuring an representative community response dataset.

HPV vaccination in women living with HIV in the United States (133)

HPV vaccination in women living with HIV in the United States (133)

Association of time intervals in cancer screenings and older participants’ characteristics, in a U.S. nationally representative sample.

e24020 Background: Various guidelines regarding cancer screening intervals for older adults exist. They often differ based on age cut-offs. There is limited national data about factors impacting adherence to these guideline-based intervals. Using a national-representative dataset, self-reported screening rates between men and women for breast (Mammogram) or prostate (PSA) cancer were explored. The demographic and lifestyle characteristics associated with screening time intervals were also investigated. Methods: Data from the nationally representative National Social Life Health and Aging Project Wave 3 (NSHAP-W3, 2015) was used. Individuals with no history of cancer were asked: How long has it been since you last had a screening (Mammogram or PSA). Responses ranged from 1 = within the past year, 2 = between one and five years ago , 3 = more than five but less than ten years ago, 4 = ten or more years ago, 5 = never. Age groups consisted of 50-54, 55-59, 60-64, 65-69, 70-74, 75-79, ≥80. Ordinal Logistic regression was used to study the association between screening time intervals (Mammogram or PSA) and participants’ characteristics (demographic, emotional, self-reported physical health, and physical activity). Results: Community-dwelling older adults (n = 2,320) were included (52% women, 48% men, with mean age of 66.9 years). There was a curvilinear response by age. The middle-age groups (60 thru 79) were significantly more likely to report shorter screening intervals, compared to the youngest group (50-54) and oldest group (≥80): ORs ranging from 0.30 to 0.61. No significant differences were observed between the oldest and youngest groups. Higher household income was associated with shorter time intervals (Mammogram: OR = 0.77; PSA: OR = 0.78, p &lt; 0.001). African Americans were more likely to report shorter intervals between Mammograms (OR = 0.43, p &lt; 0.001), compared to white women. More physically active men were likely to report shorter intervals (OR = 0.92, p = 0.021). Conclusions: Participants who are in their 60s or 70s, are more likely to have shorter time intervals between cancer screenings. African American women, and men performing frequent exercise are also more likely to have shorter intervals. These results emphasize the importance of sociodemographic and lifestyle factors, when seeking to impact cancer screening timing.

Epidemic Rates of Child and Adolescent Mental Health Disorders Require an Urgent Response

A new Morbidity and Mortality Weekly Report (MMWR) from the Centers for Disease Control and Prevention (CDC) documents the high prevalence of mental health disorders among America's children even before the pandemic.1 Pandemic era reports recently led the American Academy of Pediatrics (AAP), the American Academy of Child and Adolescent Psychiatry (AACAP), and the Children's Hospital Association (CHA) to issue a joint declaration of a national emergency in child and adolescent mental health.2 This new MMWR represents remarkable work compiling diverse information from nine nationally-representative data sets. Findings indicate high rates of mental health disorders among US children and youth, including evidence that even very young children experience mental health conditions. Twenty percent of all children have an identified mental health condition annually while forty percent of all children will meet criteria by age 18. MMWR findings show that children living in poverty and minoritized children fare worse than their peers in access to care, identifiable risk factors, and prevalence of certain mental health conditions. Despite high rates of mental health conditions, the MMWR documents low rates of treatment (about 11.4% annually for White, 9.8% for Black, and 8.7% for LatinX children).

Financial Knowledge or Financial Situations? Toward Understanding Why Some College Students Use Credit Cards to Pay for College Tuition

While the majority of college students use credit cards for educational expenses like textbooks, recent data reports that college students also use credit cards to directly fund their schooling by charging for at least some part of their tuition (Sallie Mae, 2009). Because credit cards carry a higher interest rate than student loans, and because they do not have a period of deferred payment while a student is enrolled in school, credit cards are a particularly risky method of payment that students resort to in order to attend college. Why do college students participate in such risky spending behavior to fund their education? This paper uses data from a nationally-representative data set (Education Longitudinal Study) and from a recent national study on college student finances (Study on Collegiate Financial Wellness) to investigate whether financial knowledge or financial situations are better predictors of whether a student uses a credit card to pay for at least some of their college tuition. While most research on this topic has focused on social-psychological factors that influence college student credit card use, this study includes important financial resource and situation variables that shed light on the ways in which college students make financial decisions in a broader economic environment.

134Trends and projections of Treatment as Prevention strategy in Africa and progress towards UNAIDS targets

Abstract Background Africa is lagging behind in progress toward global HIV/AIDS elimination targets. We estimated trends in and projections of annual HIV testing and condom use at last higher-risk sex; and calculated the probability of reaching key UNAIDS’s target. Methods We included 114 nationally-representative datasets in 38 African countries from DHS and MICS with 1456224 sexually active adults age 15-49 from 2003 to 2018. We applied Bayesian mixed effect models to estimate the coverage of annual HIV testing and condom use at last higher-risk sex for every country and year to 2030; and the probability of reaching UNAIDS testing and condom use targets of 95% coverage by 2030. Results Seven countries saw downward trends in annual HIV testing and four saw decreases in condom use at higher-risk sex, while most countries have upward trends in both indicators. The highest coverages of testing in 2030 are predicted in Swaziland, Uganda and Lesotho. Meanwhile, Swaziland, Lesotho, and Namibia will have the highest proportion of condom use in 2030. The probabilities of reaching targets were very low for both HIV testing (0%-28.5%) and condom use (0%-12.1%). Conclusions We observed limited progress on annual HIV testing and condom use at last higher-risk sex in Africa, and little prospect of reaching global targets for HIV/AIDS elimination. Key messages Although some global sponsor agencies are considering withdrawal from supporting Africa, more considerable attention to funding and expanding testing and treatment are needed if HIV/AIDS elimination in Africa is to become more than a distant dream.