Populus Research Articles

Nationwide Cross-Sectional Analysis of Mortality Trends in Patients with Sarcoidosis and Non-Ischemic Cardiovascular Disease—The Impact of Gender, Ethnicity, Geographical Location, and COVID-19 Pandemic

Background and Objectives: The epidemiological data regarding mortality rates of adults with sarcoidosis and non-ischemic cardiovascular disease (CVD) are limited. A retrospective observational analysis was conducted to identify trends and disparities related to sarcoidosis and non-ischemic cardiovascular disease mortality among the adult US population from 1999 to 2022. Methods: We used the Centers for Disease Control and Prevention (CDC) WONDER database to extract death certificate data for the adult US population (≥25 years). The age-adjusted mortality rates (AAMRs) per 100,000 persons were calculated, and annual percent changes (APCs) were determined using Joinpoint. Results: Between 1999 and 2022, 23,642 deaths were identified related to non-ischemic CVD + sarcoidosis. The overall AAMR increased from 0.2 (95% CI, 0.2 to 0.3) in 1999 to 0.5 (95% CI, 0.5 to 0.6) in 2022. Females had a higher AAMR than males (0.6 vs. 0.5). Non-Hispanic (NH) blacks had the highest AAMR, followed by NH whites and Hispanic or Latinos. The southern region had the highest AAMR (0.7: 95% CI, 0.6–0.7), followed by the Midwest (0.6, 95% CI, 0.54–0.669), the Northeast (0.5, 95% CI, 0.5 to 0.6), and the West (0.4; 95% CI, 0.3–0.4). Urban and rural areas had comparable mortality rates (0.5 vs. 0.6). People aged 65+ had the highest AAMRs. Conclusions: The overall mortality rates for non-ischemic CVD and sarcoidosis have increased in the US from 1999 to 2022. Females and NH blacks had higher AAMRs, while a minimal variation was observed based on geographical regions. Early diagnosis and prompt management are the keys to reducing the mortality burden of non-ischemic CVD plus sarcoidosis.

Navigating Political Disagreement on Social Media: How Affective Responses and Belonging Influence Unfollowing and Unfriending

While recent research has demonstrated how exposure to cross-cutting political opinions intensifies politically motivated disconnectivity on social media, there has been a notable gap in examining the influence of emotions and psychological traits in this process. Guided by the theories of selective avoidance and affective intelligence, our study employed a survey through Qualtrics panel drawn from a population-matching sample (<em>N</em> = 498) of the US population to investigate how perceived political disagreement on social media affects decisions to unfollow and unfriend others through the induction of affective responses (e.g., anger, anxiety) and the role of psychological trait—need to belong. Controlling for demographics and political ideology, our mediation analysis revealed that perceived political disagreement was significantly related to anger, which was further positively associated with both unfollowing and unfriending on social media. Perceived political disagreement was also related to anxiety while anxiety was positively associated with individuals’ behaviors of unfollowing and unfriending. Furthermore, results showed that the need to belong played a significant role in moderating the relationship between perceived political disagreement and unfriending. When perceiving the same level of political disagreement, individuals with a higher need to belong were less likely to unfriend others on social media, compared to those with a lower need to belong. However, the need to belong did not exert a significant impact on how perceived political disagreement influenced unfollowing behavior. This study contributes to understanding the nuanced dynamics of disconnectivity on social media, particularly in navigating political disagreements.

Contribution of childhood lead exposure to psychopathology in the US population over the past 75 years.

More than half of the current US population was exposed to adverse lead levels in childhood as a result of lead's past use in gasoline. The total contribution of childhood lead exposures to US-population mental health and personality has yet to be evaluated. We combined serial, cross-sectional blood-lead level (BLL) data from National Health and Nutrition Examination Surveys (NHANES) with historic leaded-gasoline data to estimate US childhood BLLs from 1940 to 2015 and calculate population mental-health symptom elevations from known lead-psychopathology associations. We utilized five outcomes: (1) General Psychopathology "points",reflecting an individual's liability to overall mental disorder, scaled to match IQ scores (M = 100, SD = 15); (2) Symptoms of Internalizing disorders (anxiety and depression) and Attention-deficit/Hyperactivity Disorder (AD/HD), both z-scored (M = 0, SD = 1); and (3) Differences in the personality traits of Neuroticism and Conscientiousness (M = 0, SD = 1). Assuming that published lead-psychopathology associations are causal and not purely correlational: We estimate that by 2015, the US population had gained 602-million General Psychopathology factor points because of exposure arising from leaded gasoline, reflecting a 0.13-standard-deviation increase in overall liability to mental illness in the population and an estimated 151 million excess mental disorders attributable to lead exposure. Investigation of specific disorder-domain symptoms identified a 0.64-standard-deviation increase in population-level Internalizing symptoms and a 0.42-standard-deviation increase in AD/HD symptoms. Population-level Neuroticism increased by 0.14 standard deviations and Conscientiousness decreased by 0.20 standard deviations. Lead-associated mental health and personality differences were most pronounced for cohorts born from 1966 through 1986 (Generation X). A significant burden of mental illness symptomatology and disadvantageous personality differences can be attributed to US children's exposure to lead over the past 75 years. Lead's potential contribution to psychiatry, medicine, and children's health may be larger than previously assumed.

Association between non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio and sarcopenia based on NHANES

The ratio of non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol, or NHHR, has garnered increased attention because of its connection to metabolic diseases. It is yet unknown, nevertheless, how NHHR and sarcopenia relate to one another in the US population. Examining the relationship between NHHR and the prevalence of sarcopenia in the US population is the main goal of this study. Utilizing information gathered from the National Health and Nutrition Examination Survey (NHANES) from 2011 to 2018, a study was conducted to look at the connection between NHHR and sarcopenia in the US population. The individuals’ baseline features were categorized based on whether or not sarcopenia was present. We used subgroup analysis, restricted cubic spline (RCS), and weighted logistic regression to examine the connection between NHHR and sarcopenia prevalence. Sensitivity analysis was used to confirm that the study’s findings were reliable and consistent. R (version 4.2.3) was used for all analyses, and P < 0.05 was used to indicate statistical significance. There were 10,087 individuals in all, 9,187 of whom were not sarcopenic and 900 of whom were. Sarcopenic patients were generally older, predominantly of Mexican American descent, and had lower educational levels. These patients were generally less active and exhibited higher levels of total cholesterol and BMI, along with lower HDL levels. Following complete adjustment, the weighted logistic regression model indicated that a 7% increased risk of sarcopenia was linked to every unit rise in NHHR (OR = 1.07, 95% CI = 1.02–1.13). An inflection point was identified at 2.90 by RCS analysis, which revealed a nonlinear association between NHHR and the prevalence of sarcopenia. Subgroup analysis showed that, regardless of the demographic group, there was a continuous positive correlation between NHHR and the prevalence of sarcopenia. The results of the interaction test provided evidence in favor of NHHR functioning as a stand-alone risk factor for sarcopenia. Our research suggests that a higher prevalence of sarcopenia may be linked to an increase in NHHR. Consequently, NHHR may function as a separate risk factor for sarcopenia.

Differences in suicide acceptability by farming-related occupation, demographic, and religiosity factors, general social survey 2000–2022

Introduction Suicide acceptability beliefs must be considered when evaluating interventions to prevent suicide, as such beliefs can reveal cultural sanctions associated with suicide and suicidal behaviors and thoughts. Compared to the general US population, farmers/ranchers have an elevated suicide rate, requiring culturally competent interventions. This analysis investigated whether farmers and workers in agricultural-related industries differ from the general U.S. population in suicide acceptability levels. Methods Cross-sectional General Social Survey (GSS) data were combined from years 2000 to 2022. Four yes/no items assessing whether respondents thought an individual should be able to decide to end their life amid four negative life scenarios were used to define suicide acceptability or endorsement. U.S. Census Bureau industry and occupational codes were used to delineate occupations. Age, sex, race, ethnicity, educational level, survey administration year, and religiosity level were covariates for multiple logistic regression analyses. Among 18,191 respondents to the GSS, 167 people worked in farming/ranching roles, including 74 farmers/ranch operators and 93 farm/ranch workers. Results In unadjusted models, individuals in farm-related occupations had a lower prevalence than the general US adult population of sanctioning suicide if facing an incurable disease. Yet, suicide endorsement beliefs showed no statistically significant differences between farmers/ranchers and the general population after demographic factors were included in the model. Age, sex, race, ethnicity, and education were significant predictors of suicide acceptability, p &lt; 0.01. The prevalence of farmer/ranch operators identifying as very or moderately religious was significantly higher than that of farm/ranch workers and the general population, p &lt; 0.05. The sample identifying as non-religious had higher odds of sanctioning suicide when faced with an incurable disease (aOR 5.980, 95%CI 5.235–6.829), bankruptcy (aOR 3.281, 95%CI 2.791–3.857), having dishonored their family (aOR 3.215, 95%CI 2.732–3.784), or becoming tired of living (aOR 3.660, 95%CI 3.209–4.175). Conclusion The present results showed that farmers’/ranchers’ acceptability of suicide was not distinct from the general US population in multivariable models. However, given their disproportionately high suicide rate, they require customized outreach and interventions. Further research may elucidate how religiosity, demographic factors, and beliefs about suicide and religion impact interventions to prevent suicide for individuals working in farming/ranching.

Salicylic Aldehyde and Its Potential Use in Semiochemical-Based Pest Control Strategies Against Trypophloeus binodulus

The poplar bark beetle Trypophloeus binodulus (Coleoptera: Scolytidae) is a key pest of poplar trees (Malpighiales: Salicaceae, genus Populus) across northern Spain. However, among the more than 200 poplar clones available on the market, the clone USA 184-411 has the highest susceptibility to T. binodulus attacks. We tested the hypothesis that compounds released by the most susceptible poplar clone chemically mediate Trypophloeus binodulus behavior. The leaf and bark volatile chemical profile composition of host poplar Populus nigra L. (Salicaceae) clones were analyzed and tested on adult T. binodulus by electroantennography (EAG) and by monitoring their populations in baited traps in northern Spain. The collection of volatiles released by the leaves and bark of both clones by SPME revealed the emission of 53 components from different chemical classes. Salicylaldehyde dominated these collections of leaf volatiles and was more abundant in aerations of the more susceptible poplar clone (USA 184-411). The EAG response of adult beetles to salicylaldehyde was higher than that of any other plant odorants. In field trials, traps baited with salicylaldehyde + ethanol significantly captured more adults than all other treatments, irrespective of other lure components. The present study could aid in developing semiochemical-based management tactics against this important pest.

Clinical, Radiological and Pathological Features of a Large American Cohort of Spinocerebellar Ataxia (SCA27B).

Spinocerebellar ataxia 27B due to GAA repeat expansions in the fibroblast growth factor 14 (FGF14) gene has recently been recognized as a common cause of late-onset hereditary cerebellar ataxia. Here we present the first report of this disease in the US population, characterizing its clinical manifestations, disease progression, pathological abnormalities, and response to 4-aminopyridine in a cohort of 102 patients bearing GAA repeat expansions. We compiled a series of patients with SCA27B, recruited from 5 academic centers across the United States. Clinical manifestations and patient demographics were collected retrospectively from clinical records in an unblinded approach using a standardized form. Post-mortem analysis was done on 4 brains of patients with genetically confirmed SCA27B. In our cohort of 102 patients with SCA27B, we found that SCA27B was a late-onset (57 ± 12.5 years) slowly progressive ataxia with an episodic component in 51% of patients. Balance and gait impairment were almost always present at disease onset. The principal finding on post-mortem examination of 4 brain specimens was loss of Purkinje neurons that was most severe in the vermis most particularly in the anterior vermis. Similar to European populations, a high percent of patients 21/28 (75%) reported a positive treatment response with 4-aminopyridine. Our study further estimates prevalence and further expands the clinical, imaging and pathological features of SCA27B, while looking at treatment response, disease progression, and survival in patients with this disease. Testing for SCA27B should be considered in all undiagnosed ataxia patients, especially those with episodic onset. ANN NEUROL 2024;96:1092-1103.

Healthful plant-based diets are negatively associated with the rate of biological aging: A national study based on US adults

Plant-based diets are recognized for their health benefits. However, evidence on the association between plant-based diet quality and aging in the US population is limited. This study aimed to investigate the association between different plant-based diet indices, phenotypic age acceleration (PhenoAgeAccel), and biological age acceleration (BioAgeAccel). We hypothesized that healthful plant-based diets would negatively affect PhenoAgeAccel and BioAgeAccel in US adults. The cross-sectional analysis included 22,363 participants, and information was obtained from the National Health and Nutrition Examination Survey database. The quality of plant-based diet was assessed using three indices: overall plant-based diet index (PDI), healthful PDI (hPDI), and unhealthful PDI (uPDI). Phenotypic age (PA) and biological age (BA) was calculated based on a linear combination of chronological age and 12 multi-system clinical chemistry biomarkers in accordance with the previously established method. PhenoAgeAccel and BioAgeAccel are the residuals of the PA and BA. Weighted linear regression analyses were performed to evaluate the relationships between PDI, hPDI and uPDI, and PhenoAgeAccel and BioAgeAccel. After adjusting for all covariates, we observed that a 10-unit higher PDI score was associated with 0.80 years lower PhenoAgeAccel (β: −0.80, 95% confidence interval [CI]: -0.94,-0.67), and 1.91 years lower BioAgeAccel (β: −1.91, 95% CI: -2.42,-1.40). A 10-unit higher hPDI score was associated with 0.83 years lower PhenoAgeAccel (β: −0.83, 95% CI: -0.96,-0.70), and 1.76 years lower BioAgeAccel (β: −1.76, 95% CI: -2.18,-1.34). Conversely, a 10-unit higher uPDI score was associated with 0.77 years higher PhenoAgeAccel (β: 0.77, 95% CI: 0.66,0.89) and 1.21 years higher BioAgeAccel (β: 1.21, 95% CI: 0.80,1.62). These findings suggest that US adults may be able to slow the aging process by increasing adherence to a healthy plant-based diet.

Racial and Ethnical Disparities in Dietary Intakes Among Adults with Diagnosed Diabetes: National Health and Nutrition Examination Survey 2011-2020

Backgrounds: Diet holds crucial significance in the management and prevention of type 2 diabetes. This study aims to compare dietary intake of key macronutrients and micronutrients across different race/ethnicity among adults with diabetes.Method: A cross-sectional analysis was conducted in 3,120 adults with diagnosed diabetes using the NHANES data from 2010 to March 2020. Type 2 diabetes was defined based on self-reported diagnosis or the use of anti-diabetic medications. Participants diagnosed with diabetes at age < 25years were assumed to have type 1 diabetes and were excluded. Race/ethnicity were categorized into White, Black, Asian, Mexican and other Hispanic adults. We compared the energy-adjusted nutrient intakes by race/ethnicity group and adjusted for sex and age.Results: There were significant differences in various nutrient intakes across race/ethnicity in adults with diabetes . Compared to White adults, Black adults were less likely to consume saturated fatty acids, calcium, zinc, and potassium; Asian adults had higher carbohydrate, fiber, magnesium, and sodium intakes but lower sugar, fat, saturated fatty acids, cholesterol, and calcium consumptions; Mexican adults had higher fiber and magnesium intakes but a lower sugar intake; other Hispanic adults had lower intakes of total fat, saturated fatty acids and monounsaturated fatty acids.(all p<0.01.)Conclusion: There were significant racial/ethnical differences in dietary intake among various racial and ethnic groups in the US population. Tailored approaches through racial and ethnic considerations may

Development and Validation of an Index to Measure and Quantify Pet-Related Barriers to Healthcare Access and Utilization

ABSTRACT Issues such as inadequate transportation, language barriers, being uninsured, and living in geographic locations with poor service availability can prevent people from accessing necessary healthcare. In addition, approximately 60% of the US population has pets, which can also create barriers to healthcare that are related to pet caregiving responsibilities and concerns about pet welfare, particularly when they have inadequate social and economic resources. This study introduces a new index to measure pet-related barriers to healthcare: the Pet-Related Barriers to Healthcare Index (PRBH). We first describe the development of the index based on previous literature and expert consultation. Next, we evaluate the psychometric properties of the index in a sample of 219 pet-owning people with HIV in Florida. We use three validation approaches: (1) confirmatory factor analysis to test the hypothesized two-factor structure of the PRBH measure and to compare the fit of this model with alternative models, (2) assessment of construct validity for the PRBH factors with validated measures of commitment to pets, comfort derived from pets, and social support from people, and (3) latent class analysis to identify underlying patterns of endorsement of items. Additionally, we assessed differences in index scores by sociodemographic characteristics. Our results indicate that: (1) a modified 2-factor model that split items based on item phrasing fit the data best: one factor measured previously experienced barriers, while the other factor measured anticipated future barriers. This factor structure was further supported by the results of the latent class analysis. (2) Poorer social support from people was associated with higher endorsement of both factors. And (3) Twenty percent of the participants were characterized by high endorsement of the index items. The use of the PRBH in research and clinical settings is an important step in standardizing the quantification of this construct, identifying populations most at risk for pet-related barriers to their healthcare, and moving toward systematized support services for those groups and their animal companions.

Inverse association between serum klotho levels and C-reactive protein levels in the US population: a cross-sectional study

BackgroundThe inverse relationship between serum Klotho levels and systemic inflammation, particularly C-reactive protein (CRP), has been suggested in limited studies. However, the association within a large and diverse population remains underexplored.MethodsWe conducted a cross-sectional study using data from the National Health and Nutrition Examination Survey (NHANES) to investigate the association between serum Klotho levels and CRP among a nationally representative sample of the US population. Multiple linear regression analyses were performed to assess this relationship while adjusting for relevant covariates. Stratified analysis with interaction, restricted cubic splines (RCS) were employed to support the research objectives.ResultsA total of 5901 participants had a mean age of 57.9 ± 11.0 years, with 49.4% of them being male and 50.6% of them being female. A negative association between serum Klotho and CRP was revealed in the fully adjusted model (β -0.26; 95% CI -0.41∼-0.11). When serum Klotho was taken as quartiles with Q1 as reference, the adjusted β that were lowest in Q4 were − 0.1 (95% CI -0.16∼-0.04, p-value = 0.002) in model 4, respectively. These statistics were robust in stratified analyses.ConclusionWhile our study demonstrates an inverse association between serum Klotho levels and CRP, suggesting a potential cardioprotective role of Klotho, it is important to note that our cross-sectional design does not permit the establishment of causality. Therefore, we cannot definitively conclude that increasing Klotho levels will directly reduce cardiovascular risk. Our findings do, however, highlight the need for further research to explore the potential of Klotho as a therapeutic target for cardiovascular health.

Association between cardiometabolic index and biological aging in the US population: evidence from NHANES 2015–2020

Association between cardiometabolic index and biological aging in the US population: evidence from NHANES 2015–2020

Ensuring Appropriate Representation in Artificial Intelligence-Generated Medical Imagery: Protocol for a Methodological Approach to Address Skin Tone Bias.

In medical education, particularly in anatomy and dermatology, generative artificial intelligence (AI) can be used to create customized illustrations. However, the underrepresentation of darker skin tones in medical textbooks and elsewhere, which serve as training data for AI, poses a significant challenge in ensuring diverse and inclusive educational materials. This study aims to evaluate the extent of skin tone diversity in AI-generated medical images and to test whether the representation of skin tones can be improved by modifying AI prompts to better reflect the demographic makeup of the US population. In total, 2 standard AI models (Dall-E [OpenAI] and Midjourney [Midjourney Inc]) each generated 100 images of people with psoriasis. In addition, a custom model was developed that incorporated a prompt injection aimed at "forcing" the AI (Dall-E 3) to reflect the skin tone distribution of the US population according to the 2012 American National Election Survey. This custom model generated another set of 100 images. The skin tones in these images were assessed by 3 researchers using the New Immigrant Survey skin tone scale, with the median value representing each image. A chi-square goodness of fit analysis compared the skin tone distributions from each set of images to that of the US population. The standard AI models (Dalle-3 and Midjourney) demonstrated a significant difference between the expected skin tones of the US population and the observed tones in the generated images (P<.001). Both standard AI models overrepresented lighter skin. Conversely, the custom model with the modified prompt yielded a distribution of skin tones that closely matched the expected demographic representation, showing no significant difference (P=.04). This study reveals a notable bias in AI-generated medical images, predominantly underrepresenting darker skin tones. This bias can be effectively addressed by modifying AI prompts to incorporate real-life demographic distributions. The findings emphasize the need for conscious efforts in AI development to ensure diverse and representative outputs, particularly in educational and medical contexts. Users of generative AI tools should be aware that these biases exist, and that similar tendencies may also exist in other types of generative AI (eg, large language models) and in other characteristics (eg, sex, gender, culture, and ethnicity). Injecting demographic data into AI prompts may effectively counteract these biases, ensuring a more accurate representation of the general population.

Race and Ethnicity, Gender, and Promotion of Physicians in Academic Medicine

The ranks of academic physicians do not reflect the diversity of the US population. To create a diverse and effective medical workforce, it is important to know the extent to which gender, race and ethnicity, and the intersection of these factors are associated with career advancement. To assess whether race and ethnicity and gender are associated with appointment to or promotion within academic medicine. This cohort study used Association of American Medical Colleges data on graduates of all US MD-granting medical schools from 1979 to 2019 merged with faculty appointment data since 2000. Data for this study are based on a February 19, 2021, snapshot. The analysis was performed from March 8, 2021, to May 5, 2023. Gender and race and ethnicity among physician graduates. The main outcome was full-time faculty appointments and promotions to the ranks of instructor, assistant professor, associate professor, full professor, and department chair. Cox proportional hazards models were used to examine the differences in likelihood of appointment and promotion for racial and ethnic minority men and women compared with White men. The analytic sample included 673 573 graduates (mean [SD] age at graduation, 28.1 [3.2] years; 59.7% male; and 15.2% identifying as Asian, 6.1% as Black, and 69.6% as White). White men accounted for the largest subgroup of graduates (43.8%). Asian men, Asian women, Black women, and White women were more likely than White men to be appointed to entry-level positions. Among physicians graduating both before and after 2000, White men were more likely to be promoted to upper ranks compared with physicians of nearly every other combination of gender and race and ethnicity. Among physicians graduating prior to 2000, Black women were 55% less likely (HR, 0.45; 95% CI, 0.41-0.49) to be promoted to associate professor (n = 131 457) and 41% less likely (HR, 0.59; 95% CI, 0.51-0.69) to be promoted to full professor (n = 43 677) compared with White men. Conversely, Black men (HR, 1.29; 95% CI, 1.03-1.61) were more likely to be appointed as department chair (n = 140 052) than White men. These findings indicate that preferential promotion of White men within academic medicine continues to persist in the new millennium, with racially and ethnically diverse women experiencing greater underpromotion. To achieve a workforce that reflects the diversity of the US population, this study suggests that academic medicine needs to transform its culture and practices surrounding faculty appointments and promotions.

Merkel Cell Carcinoma and Immunosuppression, UV Radiation, and Merkel Cell Polyomavirus

Merkel cell carcinoma (MCC) is a rare but aggressive skin cancer. Quantifying the contribution of major potentially modifiable risk factors to the burden of MCC may inform prevention efforts. To estimate the population attributable fraction of MCC cases in the US that were attributable to major immunosuppressing conditions (eg, HIV, solid organ transplant, chronic lymphocytic leukemia [CLL]), ambient UV radiation [UVR] exposure, and Merkel cell polyomavirus [MCPyV]). This epidemiological assessment combined data from population-based registries and case series and included cases of MCC that were diagnosed from January 2001 to December 2019 diagnosed in people with HIV, solid organ transplant recipients, and patients with CLL who were identified through population-based cancer registries and linkages with HIV and transplant registries. UVR-based on cloud-adjusted daily ambient UVR irradiance was merged with cancer registry data on the county of residence at diagnosis. Studies reporting the prevalence of MCPyV in MCC specimens collected in the US were combined via a meta-analysis. HIV, solid organ transplant, CLL, UVR, and MCPyV. Population attributable fraction of MCC cases attributable to major risk factors. A total of 38 020 MCCs were diagnosed in the US among xx patients (14 325 [38%] female individuals; 1586 [4%] Hispanic, 561 [1%] non-Hispanic Black, and 35 171 [93%] non-Hispanic White individuals). Compared with the general US population, MCC incidence was elevated among people with HIV (standardized incidence ratio [SIR], 2.78), organ transplant recipients (SIR, 13.1), and patients with CLL (SIR, 5.75). Due to the rarity of these conditions, only 0.2% (95% CI, 0.1%-0.3%) of MCC cases were attributable to HIV, 1.5% (95% CI, 1.4%-1.7%) to solid organ transplant, and 0.8% (95% CI, 0.5%-1.3%) to CLL. Compared with individuals of racial and ethnic minority groups, MCC incidence was elevated among non-Hispanic White individuals at lower and higher ambient UVR exposure levels (incidence rate ratios: 4.05 and 4.91, respectively, for MCC on the head and neck). Overall, 65.1% (95% CI, 63.6%-66.7%) of MCCs were attributable to UVR. Based on a meta-analysis of 19 case series, 63.8% (95% CI, 54.5%-70.9%) of MCCs were attributable to MCPyV. Studies were identified from a MEDLINE search performed on October 12, 2023. The results of this study suggest that most MCC cases in the US were attributable to ambient UVR exposure or MCPyV, with a small fraction due to immunosuppressive conditions. Efforts to lower MCC incidence could focus on limiting UVR exposure.

Colorectal Cancer Incidence and Mortality After Negative Colonoscopy Screening Results

The current recommendation for a 10-year rescreening interval after a negative colonoscopy screening (NCS) result has been questioned, with some studies showing a persistently lower risk of colorectal cancer (CRC) after NCS results. To examine long-term CRC incidence and mortality after NCS results (ie, no presence of CRC or polyps) and according to a risk score based on major demographic and lifestyle risk factors. In this cohort study, 3 prospective US population-based cohorts from the Nurses' Health Study, Nurses' Health Study II, and Health Professionals Follow-up Study were followed up from 1988 and 1991 to 2020. Data from the National Health and Nutrition Examination Survey (NHANES) from the January 1, 2017, to December 31, 2018, cycle were used to compare the risk profile distribution with that of the general US population. Data analysis was performed from October 2023 to August 2024. Time-varying status of NCS results and risk score. Cox proportional hazards regression was used to calculate hazard ratios (HRs) and 95% CIs for incidence and mortality of CRC. A total of 195 453 participants (median [IQR] age, 44 [37-56] years at baseline; 81% female) were followed up for a median (IQR) of 12 (6-20) years. Among 81 151 individuals with NCS results and 114 302 without endoscopy, 394 and 2229 CRC cases and 167 and 637 CRC deaths, respectively, were documented. Negative colonoscopy screening results were consistently associated with lower CRC incidence (HR, 0.51; 95% CI, 0.44-0.58) and mortality (HR, 0.56; 95% CI, 0.46-0.70) for 20 years. Among individuals with NCS results, those with an intermediate risk (scores, 6-7) and low risk (scores, 0-5) did not reach the 10-year cumulative incidence of CRC (0.78%) of the high-risk individuals (scores, 8-12) until 16 and 25 years after initial screening, respectively. These findings provide evidence for shared decision-making between patients and physicians to consider extending the rescreening intervals after an NCS result beyond the currently recommended 10 years, particularly for individuals with a low-risk profile. These results showed, as a proof of concepts, the importance of considering known CRC risk factors when making decisions for colonoscopy rescreening.

Epidemiologic Study of Myasthenia Gravis in the Elderly US Population: A Longitudinal Analysis of the Medicare Claims Database, 2006-2019.

Epidemiologic studies suggest increasing incidence and prevalence of myasthenia gravis (MG) among the elderly population outside the United States. We aimed to provide an estimation of MG incidence and prevalence and their trend among the Medicare Fee-For-Service (FFS)-covered elderly US population. We performed a retrospective longitudinal study using Medicare claims data (2006-2019). Study-eligible beneficiaries were aged 65 years and older, had at least 1 month of FFS Part A/B coverage, and were without any health maintenance organization insurance coverage. Study-eligible beneficiaries were aggregated into 2-year periods from 2006-2007 through 2018-2019. MG cases were ascertained using a validated algorithm of 2 MG claims within each 2-year period, from 2 outpatient office visits or a combination of 1 inpatient admission and 1 outpatient office visit, separated by ≥ 28 days. Period prevalence was calculated from MG-ascertained cases divided by FFS Part A/B beneficiaries and reported as cases per 100,000 population. Incident cases were determined among MG prevalent cases if the initial MG claim occurred in that period after a full calendar year since coverage initiation. Incidence was calculated as case counts per 100,000 at-risk beneficiary person-years (PYs) in each period excluding 2006-2007. Trends of prevalence and incidence over time were examined with Poisson regression. All-cause mortality of each 2-year period was calculated. The period prevalence of MG increased from 81 to 119 per 100,000 FFS A/B population from 2006-2007 to 2018-2019 (p < 0.001). Increasing trends of prevalence were observed in all sex (male/female), age (65-69/70-74/75-79/80+), race/ethnic (African American/Asian/Hispanics of any race/non-Hispanic White/other), and census region (Northeast/Midwest/South/West) subgroups. MG incidence increased from 12.2 to 13.3 per 100,000 PYs from 2008-2009 to 2018-2019 (p < 0.05). Increasing incidence trends were significant in the following subgroups: men and women; all age groups except 75-79 years; White non-Hispanic race; Northeast, Midwest, and South census regions. All-cause mortality among MG beneficiaries was stable from 6.26 deaths per 100 PYs in 2006-2007 to 5.67 in 2018-2019 (p = 0.18). Increasing trends in MG prevalence and incidence in the elderly US population, with variation in rates of certain subgroups, are confirmed in this 14-year period.

Role of Cancer History in Cardiovascular Mortality among Different Age-group Patients with Differentiated Thyroid Cancer

Abstract Background Cardiovascular disease (CVD) is the leading cause of non-cancer related mortality among differentiated thyroid cancer (DTC) survivors, which account for a large portion of subsequent primary malignancies in childhood cancer survivors. This study aims to assess the risk of cardiovascular mortality among DTC as a second primary malignancy (DTC-2) patients compared with DTC as a first primary malignancy (DTC-1) and the general population. Methods Using the Surveillance, Epidemiology, and End Results database, we conducted a population-based cohort study including 159,395 DTC-1 and 20,010 DTC-2 patients diagnosed elder than 30 between 1975 and 2020, and the corresponding US population (71,214,642 person-years; 41,420,893 cardiovascular deaths). Compared with general population and DTC-1 patients, we calculated incidence rate ratios (IRRs) of cardiovascular deaths among DTC-2 patients using Poisson regression. To adjust for unmeasured confounders, we performed a nested, case-crossover analysis among DTC-2 patients who died from CVD. Results Although DTC-2 patients had a comparable risk compared with the population (IRR 1.01) and a mildly increased risk of cardiovascular mortality compared with DTC-1 patients (IRR 1.26), the association was pronounced among individuals aged 30–74 years, especially 30-44 years (DTC-2 vs. population: IRR 8.89; DTC-2 vs. DTC-1: IRR 3.00). The risk elevation was greatest within the first month after diagnosis, compared with population. The case-crossover analysis confirmed these results. Conclusion DTC-2 patients are at increased risk of cardiovascular mortality. Clinicians should carefully monitor CVD and manage other CVD-related factors, such as exogenous thyroxine and emotional distress, for DTC-2 patients, especially for those under 75 years.

Machine Learning a Probabilistic Structural Equation Model to Explain the Impact of Climate Risk Perceptions on Policy Support

While a flurry of studies and Integrated Assessment Models (IAMs) have independently investigated the impacts of switching mitigation policies in response to different climate scenarios, little is understood about the feedback effect of how human risk perceptions of climate change could contribute to switching climate mitigation policies. This study presents a novel machine learning approach, utilizing a probabilistic structural equation model (PSEM), for understanding complex interactions among climate risk perceptions, beliefs about climate science, political ideology, demographic factors, and their combined effects on support for mitigation policies. We use machine learning-based PSEM to identify the latent variables and quantify their complex interaction effects on support for climate policy. As opposed to a priori clustering of manifest variables into latent variables that is implemented in traditional SEMs, the novel PSEM presented in this study uses unsupervised algorithms to identify data-driven clustering of manifest variables into latent variables. Further, information theoretic metrics are used to estimate both the structural relationships among latent variables and the optimal number of classes within each latent variable. The PSEM yields an R2 of 92.2% derived from the “Climate Change in the American Mind” dataset (2008–2018 [N = 22,416]), which is a substantial improvement over a traditional regression analysis-based study applied to the CCAM dataset that identified five manifest variables to account for 51% of the variance in policy support. The PSEM uncovers a previously unidentified class of “lukewarm supporters” (~59% of the US population), different from strong supporters (27%) and opposers (13%). These lukewarm supporters represent a wide swath of the US population, but their support may be capricious and sensitive to the details of the policy and how it is implemented. Individual survey items clustered into latent variables reveal that the public does not respond to “climate risk perceptions” as a single construct in their minds. Instead, PSEM path analysis supports dual processing theory: analytical and affective (emotional) risk perceptions are identified as separate, unique factors, which, along with climate beliefs, political ideology, and race, explain much of the variability in the American public’s support for climate policy. The machine learning approach demonstrates that complex interaction effects of belief states combined with analytical and affective risk perceptions; as well as political ideology, party, and race, will need to be considered for informing the design of feedback loops in IAMs that endogenously feedback the impacts of global climate change on the evolution of climate mitigation policies.

Age at type 2 diabetes diagnosis and the risk of mortality among US population.

To examine the relationship between age at diagnosis of type 2 diabetes (T2DM) with cardiovascular and all-cause mortality in the U.S. population. Data was used from NHANES 1999 ~ 2018, which were screened to include a total of 8,654 participants with a diagnosis of diabetes for the study. We estimated the association between age at diagnosis and cardiovascular and all-cause mortality using weighted multivariate Cox regression analyses. Subgroup analyses and sensitivity analyses were performed to ensure the robustness of the data analysis. The number of participants diagnosed with diabetes at ages < 40, between 40 and 59, and > 60 are 1,492, 3,970, and 3,192, respectively, with median ages of 44.04, 57.59, and 72.24. Among patients diagnosed with T2DM, the relative risk of all-cause mortality increased with younger age at diagnosis: compared to patients with late-onset diabetes (age at type 2 diabetes diagnosis ≥ 60), the hazard ratio for all-cause mortality was 2.72 (95% CI 1.83-4.05) in those with early-onset diabetes (age at type 2 diabetes diagnosis < 40). Similarly, the risk of cardiovascular disease death was observed to be a higher relative risk with younger age at diagnosis. Exposure-effect analysis indicated that younger age at diagnosis is associated with higher risk of all-cause mortality. Subgroup analysis found that the association between age at diagnosis and cardiovascular and all-cause mortality was stronger in the current smokers and hypertensive population. The results of this study suggest that younger age at diagnosis of T2DM is associated with higher risk of death in patients. Younger patients diagnosed with T2DM had a higher risk of cardiovascular and all-cause mortality. These findings strengthen the understanding of the risk of death from T2DM and emphasize the importance of early prevention of diabetes.