Disparities in Mortality by Sexual Orientation in a Large, Prospective Cohort of Female Nurses.

Importance: Extensive evidence documents health disparities for lesbian, gay, and bisexual (LGB) women, including worse physical, mental, and behavioral health than heterosexual women. These factors have been linked to premature mortality, yet few studies have investigated premature mortality disparities among LGB women and whether they differ by lesbian or bisexual identity. Objective: To examine differences in mortality by sexual orientation. Design, Setting, and Participants: This prospective cohort study examined differences in time to mortality across sexual orientation, adjusting for birth cohort. Participants were female nurses born between 1945 and 1964, initially recruited in the US in 1989 for the Nurses' Health Study II, and followed up through April 2022. Exposures: Sexual orientation (lesbian, bisexual, or heterosexual) assessed in 1995. Main Outcome and Measure: Time to all-cause mortality from assessment of exposure analyzed using accelerated failure time models. Results: Among 116 149 eligible participants, 90 833 (78%) had valid sexual orientation data. Of these 90 833 participants, 89 821 (98.9%) identified as heterosexual, 694 (0.8%) identified as lesbian, and 318 (0.4%) identified as bisexual. Of the 4227 deaths reported, the majority were among heterosexual participants (n = 4146; cumulative mortality of 4.6%), followed by lesbian participants (n = 49; cumulative mortality of 7.0%) and bisexual participants (n = 32; cumulative mortality of 10.1%). Compared with heterosexual participants, LGB participants had earlier mortality (adjusted acceleration factor, 0.74 [95% CI, 0.64-0.84]). These differences were greatest among bisexual participants (adjusted acceleration factor, 0.63 [95% CI, 0.51-0.78]) followed by lesbian participants (adjusted acceleration factor, 0.80 [95% CI, 0.68-0.95]). Conclusions and Relevance: In an otherwise largely homogeneous sample of female nurses, participants identifying as lesbian or bisexual had markedly earlier mortality during the study period compared with heterosexual women. These differences in mortality timing highlight the urgency of addressing modifiable risks and upstream social forces that propagate and perpetuate disparities.

Trend Toward Older Maternal Age Contributed To Growing Racial Inequity In Very-Low-Birthweight Infants In The US.

In 2016 the Centers for Disease Control and Prevention reported that for the first time, US women in their thirties were bearing more children than those in their twenties. Analyzing US vital statistics data from the period 1989-2019, we simulated the effect that the distributional shift to older maternal ages at first birth had on health inequity between Black and White infants. Net of maternal socioeconomic indicators, this shift increased the relative odds that White women gave birth to very-low-birthweight (VLBW) infants by 10 percent, versus 19 percent for Black women, largely accounting for the rise in VLBW and the increase in racial inequity seen in the years analyzed. Reductions in infant mortality over the period were dampened by the maternal age shift, especially among Black babies, exacerbating Black-White inequity. Policy implications for promoting reproductive justice include universal tertiary care access, increasing the supply and distribution of maternity care providers, addressing the holistic needs of mothers throughout pregnancy and postpartum, and expanding family support policies. Conceptually, we recommend centering the realities of pregnancy and parenting from the perspective of the populations at highest risk-centering on the margins-and taking into account their implications for maternal weathering (accelerated deterioration due to disparate impacts of structural racism).

Disparities in health condition diagnoses among aging transgender and cisgender medicare beneficiaries, 2008-2017.

Introduction: The objective of this research is to provide national estimates of the prevalence of health condition diagnoses among age-entitled transgender and cisgender Medicare beneficiaries. Quantification of the health burden across sex assigned at birth and gender can inform prevention, research, and allocation of funding for modifiable risk factors. Methods: Using 2009-2017 Medicare fee-for-service data, we implemented an algorithm that leverages diagnosis, procedure, and pharmacy claims to identify age-entitled transgender Medicare beneficiaries and stratify the sample by inferred gender: trans feminine and nonbinary (TFN), trans masculine and nonbinary (TMN), and unclassified. We selected a 5% random sample of cisgender individuals for comparison. We descriptively analyzed (means and frequencies) demographic characteristics (age, race/ethnicity, US census region, months of enrollment) and used chi-square and t-tests to determine between- (transgender vs. cisgender) and within-group gender differences (e.g., TMN, TFN, unclassified) difference in demographics (p<0.05). We then used logistic regression to estimate and examine within- and between-group gender differences in the predicted probability of 25 health conditions, controlling for age, race/ethnicity, enrollment length, and census region. Results: The analytic sample included 9,975 transgender (TFN n=4,198; TMN n=2,762; unclassified n=3,015) and 2,961,636 cisgender (male n=1,294,690, female n=1,666,946) beneficiaries. The majority of the transgender and cisgender samples were between the ages of 65 and 69 and White, non-Hispanic. The largest proportion of transgender and cisgender beneficiaries were from the South. On average, transgender individuals had more months of enrollment than cisgender individuals. In adjusted models, aging TFN or TMN Medicare beneficiaries had the highest probability of each of the 25 health diagnoses studied relative to cisgender males or females. TFN beneficiaries had the highest burden of health diagnoses relative to all other groups. Discussion: These findings document disparities in key health condition diagnoses among transgender Medicare beneficiaries relative to cisgender individuals. Future application of these methods will enable the study of rare and anatomy-specific conditions among hard-to-reach aging transgender populations and inform interventions and policies to address documented disparities.

US Black-White Differences in Mortality Risk Among Transgender and Cisgender People in Private Insurance, 2011-2019.

Objectives. To compare survival by gender and race among transgender and cisgender people enrolled in private insurance in the United States between 2011 and 2019. Methods. We examined Optum's Clinformatics Data Mart Database. We identified transgender enrollees using claims related to gender-affirming care. Our analytic sample included those we identified as transgender and a 10% random sample of cisgender enrollees. We limited our sample to those 18 years or older who were non-Hispanic Black or White. We identified 18 033 transgender and more than 4 million cisgender enrollees. We fit Kaplan-Meier survival curves and calculated standardized mortality ratios while adjusting for census region. Results. Black transfeminine and nonbinary people assigned male sex at birth were 2.73 times more likely to die than other Black transgender people and 2.38 and 3.34 times more likely than Black cisgender men and women, respectively; similar results were found when White transfeminine and nonbinary people assigned male sex at birth were compared with White cisgender cohorts. Conclusions. Our findings highlight glaring inequities in mortality risks among Black transfeminine and nonbinary people assigned male sex at birth and underscore the need to monitor mortality risks in transgender populations and address the social conditions that increase these risks. (Am J Public Health. 2022;112(10):1507-1514. https://doi.org/10.2105/AJPH.2022.306963).

Differences in All-Cause Mortality Among Transgender and Non-Transgender People Enrolled in Private Insurance.

Few studies have analyzed mortality rates among transgender (trans) populations in the United States and compared them to the rates of non-trans populations. Using private insurance data from 2011 to 2019, we estimated age-specific all-cause mortality rates among a subset of trans people enrolled in private insurance and compared them to a 10% randomly selected non-trans cohort. Overall, we found that trans people were nearly twice as likely to die over the period as their non-trans counterparts. When stratifying by gender, we found key disparities within trans populations, with people on the trans feminine to nonbinary spectrum being at the greatest risk of mortality compared to non-trans males and females. While we found that people on the trans masculine to nonbinary spectrum were at a similar risk of overall mortality compared to non-trans females, their overall mortality rate was statistically smaller than that of non-trans males. These findings provide evidence that some trans and non-trans populations experience substantially different mortality conditions across the life course and necessitate further study.

Improving Data-Driven Methods to Identify and Categorize Transgender Individuals by Gender in Insurance Claims Data.

Purpose: Prior algorithms enabled the identification and gender categorization of transgender people in insurance claims databases in which sex and gender are not simultaneously captured. However, these methods have been unable to categorize the gender of a large proportion of their samples. We improve upon these methods to identify the gender of a larger proportion of transgender people in insurance claims data. Methods: Using 2001-2019 Optum's Clinformatics® Data Mart insurance claims data, we adapted prior algorithms by combining diagnosis, procedure, and pharmacy claims to (1) identify a transgender sample; and (2) stratify the sample by gender category (trans feminine and nonbinary [TFN], trans masculine and nonbinary [TMN], unclassified). We used logistic regression to estimate the burden of 13 chronic health conditions, controlling for gender category, age, race/ethnicity, enrollment length, and census region. Results: We identified 38,598 unique transgender people, comprising 50% [n = 19,252] TMN, 26% (n = 10,040) TFN, and 24% (n = 9306) unclassified individuals. In adjusted models, relative to TMN people, TFN people had significantly higher odds of most chronic health conditions, including HIV, atherosclerotic cardiovascular disorder, myocardial infarction, alcohol use disorder, and drug use disorder. Notably, TMN individuals had significantly higher odds of post-traumatic stress disorder and depression than TFN individuals. Conclusion: By combining complex administrative claims-based algorithms, we identified the largest U.S.-based sample of transgender individuals and inferred the gender of >75% of the sample. Adjusted models extend prior research documenting key health disparities by gender category. These methods may enable researchers to explore rare and sex-specific conditions in hard-to-reach transgender populations.

State-Level Policy Stigma and Non-Prescribed Hormones Use among Trans Populations in the United States: A Mediational Analysis of Insurance and Anticipated Stigma.

BACKGROUND: Medical gender affirmation (i.e., hormone use) is one-way transgender (trans) people affirm their gender and has been associated with health benefits. However, trans people face stigmatization when accessing gender-affirming healthcare, which leads some to use non-prescribed hormones (NPHs) that increase their risk for poor health. PURPOSE: We examined whether healthcare policy stigma, as measured by state-level trans-specific policies, was associated with NPHs use and tested mediational paths that might explain these associations. Because stigmatizing healthcare policies prevent trans people from participation in healthcare systems and allow for discrimination by healthcare providers, we hypothesized that healthcare policy stigma would be associated with NPHs use by operating through three main pathways: skipping care due to anticipated stigma in healthcare settings, skipping care due to cost, and being uninsured. METHODS: We conducted analyses using data from the 2015 U.S. Transgender Survey. The analytic sample included trans adults using hormones (N = 11,994). We fit a multinomial structural equation model to examine associations. RESULTS: Among trans adults using hormones, we found that healthcare policy stigma was positively associated with NPHs use and operated through insurance coverage and anticipating stigma in healthcare settings. The effect sizes on key predictor variables varied significantly between those who use supplemental NPHs and those who only use NPHs suggesting the need to treat NPHs use as distinct from those who use supplemental NPHs. CONCLUSIONS: Our work highlights the importance of healthcare policy stigma in understanding health inequities among trans people in the USA, specifically NPHs use.

Privately Insured Transgender People Are At Elevated Risk For Chronic Conditions Compared With Cisgender Counterparts.

The burden of morbidity among privately insured transgender people is largely unknown. We identified transgender people enrolled in private insurance (using claims from 2001-19) and compared their rates of selected chronic conditions, using the Elixhauser Comorbidity Index, with claims for a matched cisgender cohort. We documented disparities between transgender and cisgender people across most conditions and found that transgender people were at elevated risk for nearly all chronic conditions compared with their cisgender counterparts. We also found that trans masculine and nonbinary people had the highest predicted average number of chronic conditions compared with all other gender groups. Our findings highlight key gender differences in morbidity between and within transgender and cisgender populations, and they underscore the importance of collecting gender identity information in national surveillance efforts to increase understanding of the health disparities among transgender and cisgender populations. In addition, these findings underscore the need for nondiscrimination protections for transgender people in the US.

Coming up short: Comparing venous blood, dried blood spots & saliva samples for measuring telomere length in health equity research.

BACKGROUND: Telomere length (TL) in peripheral blood mononuclear cells (PBMC) from fresh venous blood is increasingly used to estimate molecular impacts of accumulated social adversity on population health. Sometimes, TL extracted from saliva or dried blood spots (DBS) are substituted as less invasive and more scalable specimen collection methods; yet, are they interchangeable with fresh blood? Studies find TL is correlated across tissues, but have not addressed the critical question for social epidemiological applications: Do different specimen types show the same association between TL and social constructs? METHODS: We integrate expertise in social epidemiology, molecular biology, and the statistical impact of measurement error on parameter estimates. Recruiting a diverse sample of 132 Metro-Detroit women, we measure TL for each woman from fresh blood PBMC, DBS, and saliva. Using regression methods, we estimate associations between social characteristics and TL, comparing estimates across specimen types for each woman. RESULTS: Associations between TL and social characteristics vary by specimen type collected from the same woman, sometimes qualitatively altering estimates of the magnitude or direction of a theorized relationship. Being Black is associated with shorter TL in PBMC, but longer TL in saliva or DBS. Education is positively associated with TL in fresh blood, but negatively associated with TL using DBS. CONCLUSION: Findings raise concerns about the use of TL measures derived from different tissues in social epidemiological research. Investigators need to consider the possibility that associations between social variables and TL may be systematically related to specimen type, rather than be valid indicators of socially-patterned biopsychosocial processes.

Weathering in Detroit: Place, Race, Ethnicity, and Poverty as Conceptually Fluctuating Social Constructs Shaping Variation in Allostatic Load.

Policy Points Despite 30 years of attention to eliminating population health inequity, it remains entrenched, calling for new approaches. Targeted universalism, wellness-based local development, and Jedi Public Health approaches that are community informed, evidence based, and focused on improving everyday settings and diverse lived experiences are important policy directions. State and federal revenue transfers are necessary to mitigate the harms of austerity and assure greater equity in fiscal and population health in places like Detroit, Michigan. CONTEXT: US population health inequity remains entrenched, despite mandates to eliminate it. To promote a public health approach of consequence in this domain, stakeholders call for moving from risk-factor epidemiology toward consideration of dynamic local variations in the physiological impacts of structured lived experience. METHODS: Using a community-based, participatory research approach, we collected and analyzed a unique data set of 239 black, white, and Mexican adults from a stratified, multistage probability sample of three Detroit, Michigan, neighborhoods. We drew venous blood, collected saliva, took anthropometric measurements, and assayed specimens to measure allostatic load (AL), an indicator of stress-mediated biological dysregulation, linking participants' AL scores and survey responses. In a series of nested Poisson models, we regressed AL on socioeconomic, psychosocial, neighborhood, and behavioral stressors to test the hypothesis that race/ethnicity and poverty-to-income ratio (PIR) are conceptually fluctuating variables whose impacts on AL are sensitive to structured lived experience. FINDINGS: White and Mexican Detroit participants with PIR < 1 have higher AL than counterparts nationally; black participants in Detroit and nationwide had comparable AL. Within Detroit, disparities by PIR were higher in whites than blacks, with no significant difference by PIR in Mexicans. The size of estimated effects of having PIR < 1 for whites is 58 percentage points greater than that of Mexicans and twice that of blacks. CONCLUSIONS: Structurally rooted unobserved heterogeneity bias threatens the validity of independent main effects interpretations of associations between race/ethnicity, socioeconomic characteristics, or place and health. One-size-fits-all analytic or policy models developed from the perspective of the dominant social group insufficiently address the experiences of diverse populations in specific settings and historical moments; nor do they recognize culturally mediated protective resources residents may have developed against material and psychosocial hardship.

Adapting Healthcare Quality Measures to Transgender Individuals.

The healthcare system's rapid shift toward value-based payment poses unique quality measurement challenges and new foci for researchers and policy makers. Quality measures that use sex-specific criteria may inappropriately include or exclude transgender individuals. More large-scale studies must be conducted to incorporate transgender individuals into measures that use sex-specific criteria, and "measure stewards" should consider the existing clinical guidelines and recommendations regarding transgender individuals when developing measures. Systems designed only for cisgender individuals will exacerbate existing transgender healthcare disparities unless they are revamped and flexible to transgender individuals' needs.