Experiences with and unmet needs for medication abortion support: A qualitative study with US abortion support providers.

INTRODUCTION: Quality abortion care must be person-centered. Although academic literature has focused on full-spectrum and abortion doulas supporting instrumentation abortion (also referred to as procedural abortion) clients, clients undergoing medication abortion remain understudied and may have unique needs. We aimed to understand United States (US) abortion support providers' perceptions of medication abortion clients' support needs by exploring which needs they address, which needs remain unmet, and how remote support provision might help address client needs. METHODOLOGY: Between April and October 2018, we conducted 60- to 90-min semi-structured, in-depth interviews by telephone with medication abortion support providers. The interviews focused on their experiences providing support to medication abortion clients in the US. We used a deductive thematic analysis approach. RESULTS: We interviewed 16 abortion support providers affiliated with nine US-based organizations. Six participants provided in-person support to medication abortion clients, five provided remote support, and five provided both remote and in-person support. Both in-person and remote providers described offering support that addressed clients' informational, emotional, physical, spiritual, and logistical needs. Through participant narratives, we identified interwoven benefits and challenges to remote support care provision. Participants highlighted that most medication abortion clients did not have a support provider. DISCUSSION: Participants revealed that abortion support providers, including remote support providers, can be a critical component of high-quality abortion care provision. More work is needed to ensure all abortion clients have access to support services as the abortion landscape in the US continues to evolve.

Will all youth answer sexual orientation and gender-related survey questions? An analysis of missingness in a large U.S. survey of adolescents and young adults.

Some researchers and clinicians may feel hesitant to assess sexual orientation and gender-related characteristics in youth surveys because they are unsure if youth will respond to these questions or are concerned the questions will cause discomfort or offense. This can result in missed opportunities to identify LGBTQ+ youth and address health inequities among this population. The aim of this study was to examine the prevalence and sociodemographic patterns of missingness among survey questions assessing current sexual orientation, gender identity and expression (SOGIE), and past change in sexual orientation (sexual fluidity) among a diverse sample of U.S. youth. Participants (N = 4,245, ages 14-25 years; 95% cisgender, 70% straight/heterosexual, 53% youth of color), recruited from an online survey panel, completed the Wave 1 survey of the longitudinal Sexual Orientation Fluidity in Youth (SO*FLY) Study in 2021. Current SOGIE, past sexual fluidity, and sociodemographic characteristics were assessed for missingness. Overall, 95.7% of participants had no missing questions, 3.8% were missing one question, and 0.5% were missing ≥ 2 questions. Past sexual fluidity and assigned sex were most commonly missing. Sociodemographic differences between participants who skipped the SOGIE questions and the rest of the sample were minimal. Missingness for the examined items was low and similar across sociodemographic characteristics, suggesting that almost all youth are willing to respond to survey questions about SOGIE. SOGIE and sexual fluidity items should be included in surveys and clinical assessments of youth to inform clinical care, policy-making, interventions, and resource development to improve the health of all youth. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Social media use, brand engagement, and tobacco product initiation among youth: Evidence from a prospective cohort study.

OBJECTIVE: To evaluate whether frequent social media use and liking/following tobacco brand accounts was associated with increased risk of tobacco and polytobacco initiation over approximately 1-year follow-up among youth with no prior tobacco use. METHODS: Associations between measures of social media engagement (daily social media use and liking/following tobacco brands) and tobacco initiation risk were examined using data from Waves 2 and 3 (2014-2015) of the US Population Assessment for Tobacco and Health study. Separate log-binomial models, accounting for missing data via multiple imputation and using propensity score adjustment to address confounding, estimated the adjusted relative risk (aRR) of any tobacco initiation and poly-use (2 + products) initiation at 1-year follow-up. RESULTS: Among the 8,672 youth with no prior tobacco use (49.3% female, mean [SD] age 14.1 [1.7]), 63.5% used social media at least daily, and 3.3% reported liking/following ≥ 1 tobacco brands on social media. Those reporting daily or more frequent social media use (compared to less) were at increased risk for tobacco (aRR 1.67; 95% CI 1.38-2.02) and polytobacco initiation (aRR 1.32; 95% CI 0.98-1.78). Although results were imprecise, liking/following ≥ 1 tobacco brands on social media (versus none) was associated with tobacco (aRR 1.34; 95% CI 0.95-1.89) or polytobacco initiation (aRR 1.60; 95% CI 0.99-2.60). In sensitivity analyses, liking/following cigarette or cigarillo brands was associated with polytobacco initiation. CONCLUSIONS: This study adds to a growing evidence-base describing the exposure of youth to tobacco-related social media content. Such content-often generated by tobacco companies-may contribute to youth tobacco initiation.

Fluidity in Gender Identity and Sexual Orientation Identity in Transgender and Nonbinary Youth.

Changes in sexual orientation identity (SOI) and gender identity (GI) have rarely been studied in transgender and/or nonbinary youth (TNBY), but documenting such changes is important for understanding identity development and gender transition and supporting the needs of TNBY. This study examined the frequency and patterning of changes in GI and SOI across 3 months (T1-T2) and 1.5 years (T1-T4) among 183 TNBY (baseline age 14-17 years; 83.6% White, 16.9% Hispanic/Latinx) who participated in a longitudinal US study. Participants completed online surveys including measures of GI and SOI. The most common gender identity selected at T1 (with or without another gender identity) was nonbinary (56.3%), and more than half (57.4%) of youth identified with a plurisexual identity (e.g., bisexual, pansexual). GI fluidity from T1-T2 was 13.2% and from T1-T4 was 28.9%. It was equally common to move toward a nonbinary gender identity as toward a binary gender identity. SOI fluidity was more common (30.6% from T1-T2; 55.8% from T1-T4) than GI fluidity. Shifts toward plurisexual identities were more common than shifts toward monosexual identities (e.g., straight, gay). Findings highlight the need to assess changes in GI and SOI in research and clinical practice to address the unique needs of TNBY accurately and effectively.

Identifying and describing trajectories of alcohol use frequency and binge drinking frequency among those aged 15-30 years in a national cohort of US adolescents: A group-based trajectory modeling approach.

BACKGROUND AND AIMS: Analyzing long-term trajectories of alcohol use has the potential to strengthen policy and intervention priorities and timing. We identified and described trajectories of alcohol use and binge drinking frequency from mid-adolescence to early adulthood and measured the association of the role of early drinking initiation with trajectory membership. DESIGN, SETTING, PARTICIPANTS: This was a longitudinal cohort study conducted in the United States. The National Longitudinal Survey of Youth 1997 is a nationally representative cohort of youth aged 12-16 years at baseline. The analytic sample included individuals who participated in two or more annual interviews between ages 15 and 30 years (n = 8809). MEASUREMENTS: Participants self-reported the number of days in the past 30 days they: (1) drank alcohol and (2) binge drank (five or more drinks on one occasion). We used group-based trajectory modeling to identify distinct trajectories from ages 15-30 years of past 30-day drinking and past 30-day binge drinking. Using multinomial logistic regression, we evaluated associations between early drinking initiation (≤ 14 years) and key demographics with trajectory membership. FINDINGS: We identified five past 30-day drinking groups: late-escalating (16.0%), moderate frequency (19.0%), high frequency (11.2%), low frequency (35.4%) and no/infrequent (18.4%). Early drinking initiation (versus later) was associated with higher odds of membership in the moderate [adjusted multinomial odds ratio (aMOR) = 4.88; 95% confidence interval (CI) = 4.00, 5.94] and high-frequency groups (aMOR = 4.68; 95% CI = 3.74, 5.86) than in the no/infrequent comparator trajectory. We identified five groups with distinct binge drinking frequency patterns: later escalating (9.9%), high frequency (3.9%), low frequency (28.7%), earlier onset (9.5%) and no/infrequent (48.0%). Early initiation was associated with increased odds of membership in earlier-onset and high-frequency groups compared with the no/infrequent group. For both outcomes, additional differences in probability of group membership were identified by gender, racial identity, parental factors (religiosity, high school completion) and household characteristics (household size, income, and region of residence). CONCLUSIONS: Youth in the United States appear to follow heterogeneous drinking and binge drinking trajectories from adolescence into adulthood. These may include higher-use trajectories as well as trajectories with different escalation timing (e.g. earlier versus later). Early initiation of drinking may increase risk of membership in higher- and earlier-use trajectory groups.

Compliance With the US Food and Drug Administration's Guidelines for Health Warning Labels and Engagement in Little Cigar and Cigarillo Content: Computer Vision Analysis of Instagram Posts.

Background: Health warnings in tobacco advertisements provide health information while also increasing the perceived risks of tobacco use. However, existing federal laws requiring warnings on advertisements for tobacco products do not specify whether the rules apply to social media promotions. Objective: This study aims to examine the current state of influencer promotions of little cigars and cigarillos (LCCs) on Instagram and the use of health warnings in influencer promotions. Methods: Instagram influencers were identified as those who were tagged by any of the 3 leading LCC brand Instagram pages between 2018 and 2021. Posts from identified influencers, which mentioned one of the three brands were considered LCC influencer promotions. A novel Warning Label Multi-Layer Image Identification computer vision algorithm was developed to measure the presence and properties of health warnings in a sample of 889 influencer posts. Negative binomial regressions were performed to examine the associations of health warning properties with post engagement (number of likes and comments). Results: The Warning Label Multi-Layer Image Identification algorithm was 99.3% accurate in detecting the presence of health warnings. Only 8.2% (n=73) of LCC influencer posts included a health warning. Influencer posts that contained health warnings received fewer likes (incidence rate ratio 0.59, P<.001, 95% CI 0.48-0.71) and fewer comments (incidence rate ratio 0.46, P<.001, 95% CI 0.31-0.67). Conclusions: Health warnings are rarely used by influencers tagged by LCC brands' Instagram accounts. Very few influencer posts met the US Food and Drug Administration's health warning requirement of size and placement for tobacco advertising. The presence of a health warning was associated with lower social media engagement. Our study provides support for the implementation of comparable health warning requirements to social media tobacco promotions. Using an innovative computer vision approach to detect health warning labels in influencer promotions on social media is a novel strategy for monitoring health warning compliance in social media tobacco promotions.

Sociodemographic Patterns in Retrospective Sexual Orientation Identity and Attraction Change in the Sexual Orientation Fluidity in Youth Study.

PURPOSE: This study examined sociodemographic patterns of retrospective fluidity in sexual orientation identity (i.e., any change from one identity to another) and attractions (i.e., any change in attractions to one or more gender(s)) in a large sample of US youth. METHODS: Participants were 4,087 youth (58% cisgender girls/women, 38% cisgender boys/men, 5% transgender or nonbinary individuals), ages 14-25 years, from across the United States, who were recruited from an online survey panel. Sexual and gender minorities and people of color were oversampled. Participants completed the Wave 1 survey of the longitudinal Sexual Orientation Fluidity in Youth study, which assessed sociodemographic characteristics and retrospective fluidity in sexual orientation identity and attractions. RESULTS: Across the sample, 17% reported a retrospective change in identity and 33% reported a change in attractions. Participants who were most likely to report identity change were in the younger age group (14-17 years), were transgender or nonbinary, had a plurisexual identity (pansexual, queer), and reported attractions to more than one gender. Participants who were most likely to report attraction change were nonbinary, had a plurisexual identity (pansexual, queer, bisexual), and reported attractions to more than one gender. DISCUSSION: This study found retrospective changes in sexual orientation identity and attractions were common in this sample of youth, with the prevalence of these changes differing by sociodemographic characteristics. Results from this study inform future research on adolescent health and have implications for supporting and caring for this age group, for whom sexual fluidity is common.

Assessment of Immigrants' Premium and Tax Payments for Health Care and the Costs of Their Care.

Importance: Some worry that immigrants burden the US economy and particularly the health care system. However, no analyses to date have assessed whether immigrants' payments for premiums and taxes that fund health care programs exceed third-party payers' expenditures on their behalf. Objective: To assess immigrants' net financial contributions to US health care programs. Design, Setting, and Participants: This cross-sectional analysis used 2017 data from the Medical Expenditure Panel Survey (MEPS) and the Current Population Survey (CPS) and 2014 to 2018 data from the American Community Survey. The main analyses used data from the calendar year 2017. Data from the calendar years 2012 to 2016 were also reported. Data were analyzed from June 15, 2020, to August 14, 2022. Participants comprised 210 669 community-dwelling respondents to the MEPS and CPS (main analysis) and nursing home residents who were included in the American Community Survey (additional analysis). Exposures: Citizenship and immigration status. Main Outcomes and Measures: Total and per capita payments for premiums and taxes that fund health care as well as third-party payers' expenditures for health care in 2018 US dollars. Results: Among 210 669 participants, 51.0% were female, 18.3% were Hispanic, 12.3% were non-Hispanic Black, 60.3% were non-Hispanic White, and 9.2% were of other races and/or ethnicities. A total of 180 084 participants were respondents to the 2018 CPS, and 30 585 were respondents to the 2017 MEPS. Among the 180 084 CPS respondents, immigrants accounted for 14.1% (weighted to be nationally representative), with the subgroup of citizen immigrants accounting for 6.8%, documented noncitizen immigrants accounting for 3.7%, and undocumented immigrants accounting for 3.6%; US-born citizens constituted 85.9% of the population. Relative to US-born citizens, immigrants were more often age 18 to 64 years (79.6% vs 58.3%), of Hispanic ethnicity (45.0% vs 14.0%), and uninsured (16.8% vs 7.4%); similar percentages (51.4% vs 50.9%) were female. US-born citizens vs immigrants paid similar amounts in premiums and taxes ($6269 per capita [95% CI, $6185-$6353 per capita] vs $6345 per capita [95% CI, $6220-$6470 per capita]). However, third-party expenditures for immigrants' health care ($5061 per capita; 95% CI, $4673-$5448 per capita) were lower than their expenditures for the care of US-born citizens ($6511 per capita; 95% CI, $6275-$6747 per capita). Immigrants, in general, paid significantly more per person (net contribution, $1284; 95% CI, $876-$1691) than was paid on their behalf. Most of this surplus was accounted for by undocumented immigrants, whose contributions exceeded their expenditures by $4418 per person (95% CI, $4047-$4789 per person). US-born citizens collectively paid $67.2 billion (95% CI, -$2.3 to $136.3 billion) less in premiums and taxes than third-party payers paid for their care. This deficit was mostly offset by the $58.3 billion (95% CI, $39.8-$76.8 billion) net surplus of payments from immigrants, 89% of which ($51.9 billion; 95% CI, $47.5-$56.3 billion) was attributable to undocumented immigrants. Conclusions and Relevance: In this study, immigrants appeared to subsidize the health care of other US residents, suggesting that concerns that immigrants deplete health care resources may be unfounded.

Prevalence of heavy episodic drinking and alcohol use disorder diagnosis among US college students: Results from the national Healthy Minds Study.

Alcohol use is a common, recognized problem on college campuses. This study examined alcohol use in a national sample of US college students across 78 campuses. Using four waves of data from the Healthy Minds Study (2015-2019), we explored variations by student demographics in prevalence of recent: alcohol consumption, heavy episodic drinking (HED, 4/5 + drinks in one sitting), frequent HED (3 + HED events), and lifetime alcohol use disorder (AUD) diagnosis. Stratified analyses and logistic regression with response propensity weights were used. Two-thirds of students consumed alcohol and roughly-one-third engaged in HED in the past 2 weeks. Alcohol use was more common among students who: identified as cis women/men, bisexual or gay/lesbian/queer, white non-Hispanic, lived in Greek housing or off-campus, were not first generation, or those not rating religion as important. Prevalence of HED among recent drinkers was high (56.7%) but varied by gender identity, race-ethnicity, living situation, and religiosity. In addition, higher HED prevalence was reported among: international, undergraduate, and underage (under 21) students. There was little variation in HED by sexual orientation identity or first generation status among recent drinkers. In a sub-sample of students engaging in frequent HED, AUD diagnosis was uncommon (1.4%) and less likely among students identifying as: cis women/men, heterosexual, racial-ethnic minorities (particularly Asian/Asian American or Pacific Islander), international, religious, or living in Greek housing. Alcohol use continues to be a part of college life, while screening and treatment remains rare. There are opportunities for improved programming and outreach acknowledging college student diversity.

Mobile health plus community health worker support for weight management among public housing residents (Path to Health): A randomized controlled trial protocol.

Interventions delivered by mobile devices (mHealth interventions) have the potential to increase access to weight management treatment in low-income populations. However, little prior research has examined effects of mHealth programming plus phone-based community health worker (CHW) support for weight management among public housing residents. For our intervention, we first interacted with a community advisory board to collect feedback on proposed intervention components. Transcripts from 5 advisory board meetings were coded and qualitative data was organized into themes. We used these data to inform our ongoing trial, in which public housing residents are randomized to one of three different groups: phone text messaging and digital self-weighing (mHealth only); mHealth intervention plus CHW behavioral phone counseling (mHealth+CHW); or assessment only to evaluate their differential effects on weight loss at 6- and 12-month follow-up. We will examine changes in diet and physical activity behaviors as well as potential mediating and moderating factors. Results of this trial could provide support for technology-based weight management interventions which may have greater potential for scalability and long-term dissemination than face-to-face programming. Clinical Trial Registration Number: NCT04852042.

Impact of United States 2017 Immigration Policy changes on missed appointments at two Massachusetts Safety-Net Hospitals.

INTRODUCTION: Studies have shown mixed findings regarding the impact of immigration policy changes on immigrants' utilization of primary care. METHODS: We used a difference-in-differences analysis to compare changes in missed primary care appointments over time across two groups: patients who received care in Spanish, Portuguese, or Haitian Creole, and non-Hispanic, white patients who received care in English. RESULTS: After adjustment for age, sex, race, insurance, hospital system, and presence of chronic conditions, immigration policy changes were associated with an absolute increase in the missed appointment prevalence of 0.74 percentage points (95% confidence interval: 0.34, 1.15) among Spanish, Portuguese and Haitian-Creole speakers. We estimated that missed appointments due to immigration policy changes resulted in lost revenue of over $185,000. CONCLUSIONS: We conclude that immigration policy changes were associated with a significant increase in missed appointments among patients who receive medical care in languages other than English.

Nodule net: A centralized prospective lung nodule tracking and safety-net program.

BACKGROUND: Inadequate follow-up of suspicious lung nodules can result in diagnostic delays and potential progression to advanced lung cancer. In 2015, a multidisciplinary lung nodule management program, Nodule Net, was implemented to increase the timely follow-up rate. In this study, we sought to evaluate the effectiveness of the program. METHODS: 2398 chest CT reports were reviewed for the presence of a lung nodule. Baseline demographics, nodule characteristics, and follow-up recommendations were collected. For reports that did not include structured recommendations, Fleischner Society guidelines were applied if appropriate. The rate of follow-up imaging was recorded and compared with historical rates. RESULTS: Lung nodules were reported on 1367 (57%) of scans. Of the 632 participants with recommendations for follow-up, the Nodule Net nurse navigator was notified on 523 (83%). Of these, 408 (78%) completed follow-up, compared to 57/109 (52%) in those who were not reported to Nodule Net tracking system (risk ratio: 1.49, 95% CI: 1.24-1.79, p-value < 0.05). Out of these 408, nodule net outreach was required to prompt the follow-up in 116 (28%). Of these, a lung malignancy was diagnosed in 4 (4%). CONCLUSIONS: Management of lung nodules is a complex process. Implementation of a lung nodule tracking program led to a significant increase in the completion of recommended follow-up imaging compared with usual care. Developing a comprehensive lung nodule program using an automated software system rather than manual processes to refer and track incidental findings may further reduce barriers to completion of follow-up.

Associations of spousal and non-spousal caregiving with six-year trajectories of depressive symptoms among older women in the Caregiver-Study of Osteoporotic Fractures study.

Objectives:Caregiving and becoming widowed are risk factors for depression in older adults, but few studies have examined their combined effect on depressive symptom trajectories. In a cohort of older women (mean age = 80.7 years) from the Caregiver-Study of Osteoporotic Fractures, we used latent class growth curve modeling to identify trajectories of depressive symptoms over approximately six years.Method:We used multinomial logistic regression to assess the relative odds of four depressive symptom trajectories (consistently low, consistently moderate, moderate/increasing, and consistently high), among three groups: spousal caregivers (n = 149), non-spousal caregivers (n = 157), and non-caregivers (n = 422). We also repeated this analysis with combined caregiving status and widowhood as the exposure.Results:Compared to non-caregivers, spousal caregivers had greater relative odds of consistently high versus consistently low depressive symptoms (adjusted odds ratio [aOR] = 3.6, 95% confidence interval [CI]: 1.9, 6.5). Non-spousal caregivers did not differ from non-caregivers in depressive trajectories. Compared to non-caregivers who did not become widowed, both widowed and non-widowed spousal caregivers had greater relative odds of consistently high versus consistently low depressive symptoms (aOR = 4.9, 95% CI: 1.9, 12.7 and aOR = 3.0, 95% CI: 1.5, 6.0, respectively). Non-widowed spousal caregivers, but not widowed spousal caregivers, had a non-statistically-significant trend toward increased relative odds of moderate/increasing depressive symptoms (aOR = 1.5, 95% CI: 0.7, 3.4).Conclusion:Spousal caregiving and widowhood, but not non-spousal caregiving, are associated with trajectories reflecting greater depressive symptoms over time. Informal caregiving is common among older women, and women caring for spouses should be monitored for depression, both during caregiving and after spousal loss.Supplemental data for this article can be accessed online at https://doi.org/10.1080/13607863.2021.1950611.

Exposure to Air Pollution in Relation to Risk of Dementia and Related Outcomes: An Updated Systematic Review of the Epidemiological Literature.

BACKGROUND: Dementia is a devastating neurologic condition that is common in older adults. We previously reviewed the epidemiological evidence examining the hypothesis that long-term exposure to air pollution affects dementia risk. Since then, the evidence base has expanded rapidly. OBJECTIVES: With this update, we collectively review new and previously identified epidemiological studies on air pollution and late-life cognitive health, highlighting new developments and critically discussing the merits of the evidence. METHODS: Using a registered protocol (PROSPERO 2020 CRD42020152943), we updated our literature review to capture studies published through 31 December 2020, extracted data, and conducted a bias assessment. RESULTS: We identified 66 papers (49 new) for inclusion in this review. Cognitive level remained the most commonly considered outcome, and particulate matter (PM) remained the most commonly considered air pollutant. Since our prior review, exposure estimation methods in this research have improved, and more papers have looked at cognitive change, neuroimaging, and incident cognitive impairment/dementia, though methodological concerns remain common. Many studies continue to rely on administrative records to ascertain dementia, have high potential for selection bias, and adjust for putative mediating factors in primary models. A subset of 35 studies met strict quality criteria. Although high-quality studies of fine particulate matter with aerodynamic diameter ≤2.5µm (PM2.5) and cognitive decline generally supported an adverse association, other findings related to PM2.5 and findings related to particulate matter with aerodynamic diameter ≤10µm (PM10, NO2, and NOx) were inconclusive, and too few papers reported findings with ozone to comment on the likely direction of association. Notably, only a few findings on dementia were included for consideration on the basis of quality criteria. DISCUSSION: Strong conclusions remain elusive, although the weight of the evidence suggests an adverse association between PM2.5 and cognitive decline. However, we note a continued need to confront methodological challenges in this line of research. https://doi.org/10.1289/EHP8716.

A systematic review of quantitative bias analysis applied to epidemiological research.

BACKGROUND: Quantitative bias analysis (QBA) measures study errors in terms of direction, magnitude and uncertainty. This systematic review aimed to describe how QBA has been applied in epidemiological research in 2006-19. METHODS: We searched PubMed for English peer-reviewed studies applying QBA to real-data applications. We also included studies citing selected sources or which were identified in a previous QBA review in pharmacoepidemiology. For each study, we extracted the rationale, methodology, bias-adjusted results and interpretation and assessed factors associated with reproducibility. RESULTS: Of the 238 studies, the majority were embedded within papers whose main inferences were drawn from conventional approaches as secondary (sensitivity) analyses to quantity-specific biases (52%) or to assess the extent of bias required to shift the point estimate to the null (25%); 10% were standalone papers. The most common approach was probabilistic (57%). Misclassification was modelled in 57%, uncontrolled confounder(s) in 40% and selection bias in 17%. Most did not consider multiple biases or correlations between errors. When specified, bias parameters came from the literature (48%) more often than internal validation studies (29%). The majority (60%) of analyses resulted in >10% change from the conventional point estimate; however, most investigators (63%) did not alter their original interpretation. Degree of reproducibility related to inclusion of code, formulas, sensitivity analyses and supplementary materials, as well as the QBA rationale. CONCLUSIONS: QBA applications were rare though increased over time. Future investigators should reference good practices and include details to promote transparency and to serve as a reference for other researchers.

Risk Factors for Hospitalization Among Patients with COVID-19 at a Community Ambulatory Clinic in Massachusetts During the Initial Pandemic Surge.

Among patients with COVID-19 evaluated in outpatient settings, factors associated with hospitalization remain poorly understood. Multivariable regressions were used to assess sociodemographic and clinical factors associated with increased odds of hospitalization among patients with confirmed COVID-19 between March 18, 2020 through April 25, 2020 at a community-based outpatient clinic in Massachusetts. Older age, BMI ≥ 25, self-reported dizziness/lightheadedness, temperature ≥ 99.5°F, tachycardia, and oxygen saturation < 95% were associated with increased odds of hospitalization after adjustment for age, sex, and BMI. There was also an association between speaking Spanish as primary language and increased odds of hospitalization (compared to English, adjusted OR = 2.99 [95% CI 1.39, 6.39]). Speaking Portuguese as primary language was not associated with increased odds of hospitalization (compared to English, adjusted OR = 1.83 [0.78, 4.28]). In addition to several clinical risk factors established among inpatients, our study found that primarily speaking Spanish, but not Portuguese, was a marker of hospitalization risk among a diverse outpatient cohort of patients with COVID-19.

Use of directed acyclic graphs (DAGs) to identify confounders in applied health research: review and recommendations.

BACKGROUND: Directed acyclic graphs (DAGs) are an increasingly popular approach for identifying confounding variables that require conditioning when estimating causal effects. This review examined the use of DAGs in applied health research to inform recommendations for improving their transparency and utility in future research. METHODS: Original health research articles published during 1999-2017 mentioning 'directed acyclic graphs' (or similar) or citing DAGitty were identified from Scopus, Web of Science, Medline and Embase. Data were extracted on the reporting of: estimands, DAGs and adjustment sets, alongside the characteristics of each article's largest DAG. RESULTS: A total of 234 articles were identified that reported using DAGs. A fifth (n = 48, 21%) reported their target estimand(s) and half (n = 115, 48%) reported the adjustment set(s) implied by their DAG(s). Two-thirds of the articles (n = 144, 62%) made at least one DAG available. DAGs varied in size but averaged 12 nodes [interquartile range (IQR): 9-16, range: 3-28] and 29 arcs (IQR: 19-42, range: 3-99). The median saturation (i.e. percentage of total possible arcs) was 46% (IQR: 31-67, range: 12-100). 37% (n = 53) of the DAGs included unobserved variables, 17% (n = 25) included 'super-nodes' (i.e. nodes containing more than one variable) and 34% (n = 49) were visually arranged so that the constituent arcs flowed in the same direction (e.g. top-to-bottom). CONCLUSION: There is substantial variation in the use and reporting of DAGs in applied health research. Although this partly reflects their flexibility, it also highlights some potential areas for improvement. This review hence offers several recommendations to improve the reporting and use of DAGs in future research.

Awareness of and potential for dependent error in the observational epidemiologic literature: A review.

PURPOSE: Measurement error discussions often assume classification errors of key variables are independent. Yet, small amounts of dependent error can create large biases in effect estimates. The purpose of this review was to evaluate frequency of measurement error discussions and potential for dependent error in the observational literature. METHODS: Two samples of articles analyzing exposure-outcome contrasts were collected: a random sample (n = 100) from high-impact epidemiology and medical journals (June 2015-July 2016), and a citation-based sample (n = 39) of studies citing one of two prominent dependent misclassification articles (through July 2016). We extracted study details, recorded measurement error mentions, and qualitatively assessed dependent error potential. RESULTS: Measurement error was often discussed. No random sample articles explicitly mentioned dependent error, compared with 59% of the citation-based sample. The random sample was found to be at low risk of exposure-outcome (15% plausible/probable) but increased risk for exposure-confounder (38% plausible/probable) dependency. The citation-based sample was at higher risk for dependent error (exposure-outcome: 46% plausible/probable; exposure-confounder: 61% plausible/probable). CONCLUSIONS: Although measurement error was frequently mentioned, potential impact on observed results was rarely discussed in-depth or quantified. Dependent error mentions were rare, even among studies deemed susceptible. Further education and steps to avoid dependent error are needed.

Assessing the Role of Selection Bias in the Protective Relationship Between Caregiving and Mortality.

Caregivers have lower mortality rates than noncaregivers in population-based studies, which contradicts the caregiver-stress model and raises speculation about selection bias influencing these findings. We examined possible selection bias due to 1) sampling decisions and 2) selective participation among women (baseline mean age = 79 years) in the Caregiver-Study of Osteoporotic Fractures (Caregiver-SOF) (1999-2009), an ancillary study to the Study of Osteoporotic Fractures (SOF). Caregiver-SOF includes 1,069 SOF participants (35% caregivers) from 4 US geographical areas (Baltimore, Maryland; Minneapolis, Minnesota; the Monongahela Valley, Pennsylvania; and Portland, Oregon). Participants were identified by screening all SOF participants for caregiver status (1997-1999; n = 4,036; 23% caregivers) and rescreening a subset of caregivers and noncaregivers matched on sociodemographic factors 1-2 years later. Adjusted hazard ratios related caregiving to 10-year mortality in all women initially screened, subsamples representing key points in constructing Caregiver-SOF, and Caregiver-SOF. Caregivers had better functioning than noncaregivers at each screening. The association between caregiving and mortality among women invited to participate in Caregiver-SOF (41% died; adjusted hazard ratio (aHR) = 0.73, 95% confidence interval (CI): 0.61, 0.88) was slightly more protective than that in all initially screened women (37% died; aHR = 0.83, 95% CI: 0.73, 0.95), indicating little evidence of selection bias due to sampling decisions, and was similar to that in Caregiver-SOF (39% died; aHR = 0.71, 95% CI: 0.57, 0.89), indicating no participation bias. These results add to a body of evidence that informal caregiving may impart health benefits.

Caregiving Intensity and Mortality in Older Women, Accounting for Time-Varying and Lagged Caregiver Status: The Caregiver-Study of Osteoporotic Fractures Study.

BACKGROUND AND OBJECTIVES: Caregiving is associated with reduced mortality in recent studies. Investigations of caregiving intensity may reveal an underlying mechanism. However, studies of caregiving intensity and mortality have mixed results, perhaps due to imprecise measurement of caregiving intensity, not accounting for healthier persons likely having greater caregiving involvement, or temporal changes in intensity. We examined the relationship between caregiving intensity (based on tasks performed) and mortality, treating intensity and health status as time-varying, and lagging exposure. RESEARCH DESIGN AND METHODS: Caregiving tasks among 1,069 women in the Caregiver-Study of Osteoporotic Fractures study (35% caregivers) were assessed at 5 interviews conducted between 1999 and 2009. Caregivers were categorized as high intensity if they assisted a person with dressing, transferring, bathing, or toileting; or as low intensity if they assisted with other instrumental or basic activities of daily living (I/ADLs). Alternatively, high intensity was defined as assisting with more than the median number of I/ADL tasks (median-based measure). Mortality was assessed through 2011. Cox proportional hazards models estimated adjusted hazard ratios (aHR) and 95% confidence intervals based on concurrent intensity, and lagging exposure 2 years. RESULTS: High-intensity caregivers had significantly lower mortality using the median-based measure after lagging exposure (aHR = 0.55, 0.34-0.89). Similar, but not statistically significant associations were observed in non-lagged analyses (aHR = 0.54, 0.29-1.04) and task-specific intensity (aHRs were 0.61 and 0.51). Low-intensity caregivers had similar mortality rates to noncaregivers in all analyses. DISCUSSION AND IMPLICATIONS: Among older women, high-intensity caregivers had lower mortality rates than noncaregivers. Whether this association extends to other populations merits investigation.