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Evaluation of Temporal Trends in Racial and Ethnic Disparities in Sleep Duration Among US Adults, 2004-2018

Caraballo, César; Mahajan, Shiwani; Valero-Elizondo, Javier; Massey, Daisy; Lu, Yuan; Roy, Brita; Riley, Carley; Annapureddy, Amarnath R; Murugiah, Karthik; Elumn, Johanna; Nasir, Khurram; Nunez-Smith, Marcella; Forman, Howard P; Jackson, Chandra L; Herrin, Jeph; Krumholz, Harlan M
Importance:Historically marginalized racial and ethnic groups are generally more likely to experience sleep deficiencies. It is unclear how these sleep duration disparities have changed during recent years. Objective:To evaluate 15-year trends in racial and ethnic differences in self-reported sleep duration among adults in the US. Design, Setting, and Participants:This serial cross-sectional study used US population-based National Health Interview Survey data collected from 2004 to 2018. A total of 429 195 noninstitutionalized adults were included in the analysis, which was performed from July 26, 2021, to February 10, 2022. Exposures:Self-reported race, ethnicity, household income, and sex. Main Outcomes and Measures:Temporal trends and racial and ethnic differences in short (<7 hours in 24 hours) and long (>9 hours in 24 hours) sleep duration and racial and ethnic differences in the association between sleep duration and age. Results:The study sample consisted of 429 195 individuals (median [IQR] age, 46 [31-60] years; 51.7% women), of whom 5.1% identified as Asian, 11.8% identified as Black, 14.7% identified as Hispanic or Latino, and 68.5% identified as White. In 2004, the adjusted estimated prevalence of short and long sleep duration were 31.4% and 2.5%, respectively, among Asian individuals; 35.3% and 6.4%, respectively, among Black individuals; 27.0% and 4.6%, respectively, among Hispanic or Latino individuals; and 27.8% and 3.5%, respectively, among White individuals. During the study period, there was a significant increase in short sleep prevalence among Black (6.39 [95% CI, 3.32-9.46] percentage points), Hispanic or Latino (6.61 [95% CI, 4.03-9.20] percentage points), and White (3.22 [95% CI, 2.06-4.38] percentage points) individuals (P < .001 for each), whereas prevalence of long sleep changed significantly only among Hispanic or Latino individuals (-1.42 [95% CI, -2.52 to -0.32] percentage points; P = .01). In 2018, compared with White individuals, short sleep prevalence among Black and Hispanic or Latino individuals was higher by 10.68 (95% CI, 8.12-13.24; P < .001) and 2.44 (95% CI, 0.23-4.65; P = .03) percentage points, respectively, and long sleep prevalence was higher only among Black individuals (1.44 [95% CI, 0.39-2.48] percentage points; P = .007). The short sleep disparities were greatest among women and among those with middle or high household income. In addition, across age groups, Black individuals had a higher short and long sleep duration prevalence compared with White individuals of the same age. Conclusions and Relevance:The findings of this cross-sectional study suggest that from 2004 to 2018, the prevalence of short and long sleep duration was persistently higher among Black individuals in the US. The disparities in short sleep duration appear to be highest among women, individuals who had middle or high income, and young or middle-aged adults, which may be associated with health disparities.
PMCID:8990329
PMID: 35389500
ISSN: 2574-3805
CID: 5324682

Scalable proximal methods for cause-specific hazard modeling with time-varying coefficients

Wu, Wenbo; Taylor, Jeremy M G; Brouwer, Andrew F; Luo, Lingfeng; Kang, Jian; Jiang, Hui; He, Kevin
Survival modeling with time-varying coefficients has proven useful in analyzing time-to-event data with one or more distinct failure types. When studying the cause-specific etiology of breast and prostate cancers using the large-scale data from the Surveillance, Epidemiology, and End Results (SEER) Program, we encountered two major challenges that existing methods for estimating time-varying coefficients cannot tackle. First, these methods, dependent on expanding the original data in a repeated measurement format, result in formidable time and memory consumption as the sample size escalates to over one million. In this case, even a well-configured workstation cannot accommodate their implementations. Second, when the large-scale data under analysis include binary predictors with near-zero variance (e.g., only 0.6% of patients in our SEER prostate cancer data had tumors regional to the lymph nodes), existing methods suffer from numerical instability due to ill-conditioned second-order information. The estimation accuracy deteriorates further with multiple competing risks. To address these issues, we propose a proximal Newton algorithm with a shared-memory parallelization scheme and tests of significance and nonproportionality for the time-varying effects. A simulation study shows that our scalable approach reduces the time and memory costs by orders of magnitude and enjoys improved estimation accuracy compared with alternative approaches. Applications to the SEER cancer data demonstrate the real-world performance of the proximal Newton algorithm.
PMID: 35092553
ISSN: 1572-9249
CID: 5228162

How health systems can adapt to a population ageing with HIV and comorbid disease

Kiplagat, Jepchirchir; Tran, Dan N; Barber, Tristan; Njuguna, Benson; Vedanthan, Rajesh; Triant, Virginia A; Pastakia, Sonak D
As people age with HIV, their needs increase beyond solely managing HIV care. Ageing people with HIV, defined as people with HIV who are 50 years or older, face increased risk of both age-regulated comorbidities and ageing-related issues. Globally, health-care systems have struggled to meet these changing needs of ageing people with HIV. We argue that health systems need to rethink care strategies to meet the growing needs of this population and propose models of care that meet these needs using the WHO health system building blocks. We focus on care provision for ageing people with HIV in the three different funding mechanisms: President's Emergency Plan for AIDS Relief and Global Fund funded nations, the USA, and single-payer government health-care systems. Although our categorisation is necessarily incomplete, our efforts provide a valuable contribution to the debate on health systems strengthening as the need for integrated, people-centred, health services increase.
PMID: 35218734
ISSN: 2352-3018
CID: 5175232

Development of a homelessness risk screening tool for emergency department patients

Doran, Kelly M; Johns, Eileen; Zuiderveen, Sara; Shinn, Marybeth; Dinan, Kinsey; Schretzman, Maryanne; Gelberg, Lillian; Culhane, Dennis; Shelley, Donna; Mijanovich, Tod
OBJECTIVE:To develop a screening tool to identify emergency department (ED) patients at risk of entering a homeless shelter, which could inform targeting of interventions to prevent future homelessness episodes. DATA SOURCES/METHODS:Linked data from (1) ED patient baseline questionnaires and (2) citywide administrative homeless shelter database. STUDY DESIGN/METHODS:Stakeholder-informed predictive modeling utilizing ED patient questionnaires linked with prospective shelter administrative data. The outcome was shelter entry documented in administrative data within 6 months following the baseline ED visit. Exposures were responses to questions on homelessness risk factors from baseline questionnaires. DATA COLLECTION/EXTRACTION METHODS/METHODS:Research assistants completed questionnaires with randomly sampled ED patients who were medically stable, not in police/prison custody, and spoke English or Spanish. Questionnaires were linked to administrative data using deterministic and probabilistic matching. PRINCIPAL FINDINGS/RESULTS:Of 1993 ED patients who were not homeless at baseline, 5.6% entered a shelter in the next 6 months. A screening tool consisting of two measures of past shelter use and one of past criminal justice involvement had 83.0% sensitivity and 20.4% positive predictive value for future shelter entry. CONCLUSIONS:Our study demonstrates the potential of using cross-sector data to improve hospital initiatives to address patients' social needs.
PMID: 34608999
ISSN: 1475-6773
CID: 5067672

Maternal Phthalate and Bisphenol Urine Concentrations during Pregnancy and Early Markers of Arterial Health in Children

Blaauwendraad, Sophia M; Gaillard, Romy; Santos, Susana; Sol, Chalana M; Kannan, Kurunthachalam; Trasande, Leonardo; Jaddoe, Vincent W V
BACKGROUND:Fetal exposure to endocrine-disrupting chemicals such as phthalates and bisphenols might lead to fetal cardiovascular developmental adaptations and predispose individuals to cardiovascular disease in later life. OBJECTIVES/OBJECTIVE:We examined the associations of maternal urinary bisphenol and phthalate concentrations in pregnancy with offspring carotid intima-media thickness and distensibility at the age of 10 y. METHODS:In a population-based, prospective cohort study of 935 mother-child pairs, we measured maternal urinary phthalate and bisphenol concentrations at each trimester. Later, we measured child carotid intima-media thickness and distensibility in the children at age 10 y using ultrasound. RESULTS: DISCUSSION/CONCLUSIONS:In this large prospective cohort, higher maternal urinary bisphenols concentrations were associated with smaller childhood carotid intima-media thickness. Further studies are needed to replicate this association and to identify potential underlying mechanisms. https://doi.org/10.1289/EHP10293.
PMCID:9041527
PMID: 35471947
ISSN: 1552-9924
CID: 5205582

Generalizability challenges of mortality risk prediction models: A retrospective analysis on a multi-center database

Singh, Harvineet; Mhasawade, Vishwali; Chunara, Rumi
Modern predictive models require large amounts of data for training and evaluation, absence of which may result in models that are specific to certain locations, populations in them and clinical practices. Yet, best practices for clinical risk prediction models have not yet considered such challenges to generalizability. Here we ask whether population- and group-level performance of mortality prediction models vary significantly when applied to hospitals or geographies different from the ones in which they are developed. Further, what characteristics of the datasets explain the performance variation? In this multi-center cross-sectional study, we analyzed electronic health records from 179 hospitals across the US with 70,126 hospitalizations from 2014 to 2015. Generalization gap, defined as difference between model performance metrics across hospitals, is computed for area under the receiver operating characteristic curve (AUC) and calibration slope. To assess model performance by the race variable, we report differences in false negative rates across groups. Data were also analyzed using a causal discovery algorithm "Fast Causal Inference" that infers paths of causal influence while identifying potential influences associated with unmeasured variables. When transferring models across hospitals, AUC at the test hospital ranged from 0.777 to 0.832 (1st-3rd quartile or IQR; median 0.801); calibration slope from 0.725 to 0.983 (IQR; median 0.853); and disparity in false negative rates from 0.046 to 0.168 (IQR; median 0.092). Distribution of all variable types (demography, vitals, and labs) differed significantly across hospitals and regions. The race variable also mediated differences in the relationship between clinical variables and mortality, by hospital/region. In conclusion, group-level performance should be assessed during generalizability checks to identify potential harms to the groups. Moreover, for developing methods to improve model performance in new environments, a better understanding and documentation of provenance of data and health processes are needed to identify and mitigate sources of variation.
PMCID:9931319
PMID: 36812510
ISSN: 2767-3170
CID: 5495362

Not a New Story: Place- and Race-Based Disparities in COVID-19 and Influenza Hospitalizations among Medicaid-Insured Adults in New York City

Howland, Renata E; Wang, Scarlett; Ellen, Ingrid Gould; Glied, Sherry
While SARS-CoV-2 is a novel virus, contagious respiratory illnesses are not a new problem. Limited research has examined the extent to which place- and race-based disparities in severe illness are similar across waves of the COVID-19 pandemic and historic influenza seasons. In this study, we focused on these disparities within a low-income population, those enrolled in Medicaid in New York City. We used 2015-2020 New York State Medicaid claims to compare the characteristics of patients hospitalized with COVID-19 during three separate waves of 2020 (first wave: January 1-April 30, 2020; second wave: May 1-August 31, 2020; third wave: September 1-December 31, 2020) and with influenza during the 2016 (July 1, 2016-June 30, 2017) and 2017 influenza seasons (July 1, 2017-June 30, 2018). We found that patterns of hospitalization by race/ethnicity and ZIP code across the two influenza seasons and the first wave of COVID-19 were similar (increased risk among non-Hispanic Black (aOR = 1.17, 95% CI: 1.10-1.25) compared with non-Hispanic white Medicaid recipients). Black/white disparities in hospitalization dissipated in the second COVID wave and reversed in the third wave. The commonality of disparities across influenza seasons and the first wave of COVID-19 suggests there are community factors that increase hospitalization risk across novel respiratory illness incidents that emerge in the period before aggressive public health intervention. By contrast, convergence in hospitalization patterns in later pandemic waves may reflect, in part, the distinctive public health response to COVID-19.
PMID: 35192184
ISSN: 1468-2869
CID: 5774382

Instagram and prostate cancer: using validated instruments to assess the quality of information on social media

Xu, Alex J; Myrie, Akya; Taylor, Jacob I; Matulewicz, Richard; Gao, Tian; Pérez-Rosas, Verónica; Mihalcea, Rada; Loeb, Stacy
BACKGROUND:The quality of prostate cancer (PCa) content on Instagram is unknown. METHODS:We examined 62 still-images and 64 video Instagram posts using #prostatecancer on 5/18/20. Results were assessed with validated tools. RESULTS:Most content focused on raising awareness or sharing patient stories (46%); only 9% was created by physicians. 90% of content was low-to-moderate quality and most was understandable, but actionability was 0%. Of the 30% of content including objective information, 40% contained significant misinformation. Most posts had comments offering social support. CONCLUSIONS:Instagram is a source of understandable PCa content and social support; however, information was poorly actionable and had some misinformation.
PMID: 34853412
ISSN: 1476-5608
CID: 5085402

Carcinogenic biomarkers of exposure in the urine of heated tobacco product users associated with bladder cancer: A systematic review

Svendsen, Christopher; James, Andrew; Matulewicz, Richard S; Moreton, Elizabeth; Sosnowski, Roman; Sherman, Scott; Jaspers, Ilona; Gordon, Terry; Bjurlin, Marc A
To identify biomarkers of exposure present in Heated Tobacco Products (HTPs) users' urine which are associated with bladder cancer and to compare quantitative biomarker levels to those seen in combustible cigarette users. A systematic literature review was conducted in December 2020 with no date limits. Relevant studies that reported quantitative urinary biomarker of exposure in HTP users were included. Biomarkers and their parent compounds were classified by carcinogenicity according to the International Agency for Research on Cancer Monographs and were cross-referenced with the Collaborative on Health and the Environment Toxicant and Disease Database to determine associations with bladder cancer. Our literature search identified 561 articles and 30 clinical trial reports. 11 studies met inclusion criteria. These studies identified 29 biomarkers of exposure present in HTP users' urine, which reflect exposure to 21 unique parent compounds. Of these parent compounds, 14 are carcinogens and 10 have a known link to bladder cancer. HTP users' biomarkers of exposure were present at lower levels than combustible cigarette users but higher than never-smokers. Biomarkers of exposure to bladder carcinogens are present in the urine of HTP users. While levels of these biomarkers appear to be lower than combustible cigarette users, chronic urothelial exposure to bladder carcinogens is concerning and degree of bladder cancer risk remains unknown. Further long-term study is needed to elucidate the bladder cancer risk of HTP use.
PMID: 34920944
ISSN: 1873-2496
CID: 5085412

Patterns of Medical Cannabis Use Among Older Adults from a Cannabis Dispensary in New York State

Kaufmann, Christopher N; Kim, Arum; Miyoshi, Mari; Han, Benjamin H
PMID: 33998868
ISSN: 2378-8763
CID: 5018282