The link Between traumatic experiences and health in late life: challenges and opportunities for US-based longitudinal aging cohorts.

Trauma, defined as exposure to actual or threatened death, serious injury or sexual violence, is a pervasive, major public health challenge that disproportionately burdens socially disadvantaged groups and has known consequences for health outcomes in early and midlife. Despite plausible mechanisms by which trauma may also be a critically important risk factor for health outcomes in late life, there is presently a lack of literature evaluating the consequences of trauma on aging related health outcomes and inequities, such as dementia. In this commentary, we (a) discuss drivers of the paucity of epidemiological evidence on trauma and health outcomes in late life, namely a lack of available data, supported by detailed review of trauma measures, including interpersonal violence-a particularly common form of trauma-in seven established longitudinal aging cohort studies in the United States (US); (b) address four common concerns about the inclusion of trauma measures in cohort studies; and (c) suggest ways forward, including specific assessment tools to measure interpersonal violence after a structured review of the PhenX Toolkit, to facilitate critical research to understand the impact of trauma on outcomes in late life.

Considerations for Use of Blood-Based Biomarkers in Epidemiologic Dementia Research.

Dementia represents a growing public health burden with large social, racial, and ethnic disparities. The etiology of dementia is poorly understood, and the lack of robust biomarkers in diverse, population-representative samples is a barrier to moving dementia research forward. Existing biomarkers and other measures of pathology-derived from neuropathology, neuroimaging, and cerebrospinal fluid samples-are commonly collected from predominantly White and highly educated samples drawn from academic medical centers in urban settings. Blood-based biomarkers are noninvasive and less expensive, offering promise to expand our understanding of the pathophysiology of dementia, including in participants from historically excluded groups. Although largely not yet approved by the Food and Drug Administration or used in clinical settings, blood-based biomarkers are increasingly included in epidemiologic studies on dementia. Blood-based biomarkers in epidemiologic research may allow the field to more accurately understand the multifactorial etiology and sequence of events that characterize dementia-related pathophysiological changes. As blood-based dementia biomarkers continue to be developed and incorporated into research and practice, we outline considerations for using them in dementia epidemiology, and illustrate key concepts with Alzheimer's Disease Neuroimaging Initiative (2003-present) data. We focus on measurement, including both validity and reliability, and on the use of dementia blood-based biomarkers to promote equity in dementia research and cognitive aging. This article is part of a Special Collection on Mental Health.

Heterogeneity in the effect of type 2 diabetes on dementia incidence in a diverse cohort of Asian American and non-Latino White older adults.

Dementia incidence is lower among Asian Americans than among Whites, despite higher prevalence of type 2 diabetes, a well-known dementia risk factor. Determinants of dementia, including type 2 diabetes, have rarely been studied in Asian Americans. We followed 4846 Chinese, 4129 Filipino, 2784 Japanese, 820 South Asian, and 123 360 non-Latino White members of a California-based integrated health-care delivery system from 2002 to 2020. We estimated dementia incidence rates by race/ethnicity and type 2 diabetes status, and we fitted Cox proportional hazards and Aalen additive hazards models for the effect of type 2 diabetes (assessed 5 years before baseline) on age of dementia diagnosis, controlling for sex/gender, educational attainment, nativity, height, race/ethnicity, and a race/ethnicity × diabetes interaction. Type 2 diabetes was associated with higher dementia incidence in Whites (hazard ratio [HR] = 1.46; 95% CI, 1.40-1.52). Compared with Whites, the estimated effect of diabetes was larger in South Asians (HR = 2.26; 95% CI, 1.48-3.44), slightly smaller in Chinese (HR = 1.32; 95% CI, 1.08-1.62) and Filipino (HR = 1.31; 95% CI, 1.08-1.60) individuals, and similar in Japanese individuals (HR = 1.44; 95% CI, 1.15-1.81). Heterogeneity in this association across Asian subgroups may be related to type 2 diabetes severity. Understanding this heterogeneity may inform prevention strategies to prevent dementia for all racial and ethnic groups.

School racial/ethnic composition, effect modification by caring teacher/staff presence, and mid-/late-life depressive symptoms: findings from the Study of Healthy Aging in African Americans.

For Black students in the United States, attending schools with a higher proportion of White students is associated with worse mental and physical health outcomes in adolescence/early adulthood. To our knowledge, no prior studies have evaluated the association between school racial/ethnic composition from kindergarten through grade 12 and later-life mental health. In a cohort of Black adults aged ≥50 years in Northern California who retrospectively reported (2017-2020) school racial/ethnic composition for grades 1, 6, 9, and 12, we assessed the association between attending a school with mostly Black students versus not and mid-/late-life depressive symptoms (8-item Patient-Reported Outcomes Measurement Information System (PROMIS) depression score, standardized to the 2000 US adult population) using age-, sex/gender-, southern US birth-, and parental education-adjusted generalized estimating equations, and assessed effect modification by the presence of a caring teacher/staff member. Levels of later-life depressive symptoms were lower among those who attended schools with mostly Black students in grades 1 and 6 (ß = -0.12 [95% CI, -0.23 to 0.00] and ß = -0.11 [95% CI, -0.22 to 0.00], respectively). In grade 6, this difference was larger for students without an adult at school who cared about them (ß = -0.29 [95% CI, -0.51 to -0.07] vs ß = -0.04 [95% CI, -0.17 to 0.09]). Among Black Americans, experiencing early schooling with mostly Black students may have later-life mental health benefits; this protective association appears more important for students without the presence of caring teachers/staff. This article is part of a Special Collection on Mental Health.

Estimating dementia incidence in insured older Asian Americans and Pacific Islanders in California: an application of inverse odds of selection weights.

Literature shows heterogeneous age-standardized dementia incidence rates across US Asian American, Native Hawaiian, and Pacific Islanders (AANHPI), but no estimates of population-representative dementia incidence exist due to lack of AANHPI longitudinal probability samples. We compared harmonized characteristics between AANHPI Kaiser Permanente Northern California members (KPNC cohort) and the target population of AANHPI 60+ with private or Medicare insurance using the California Health Interview Survey. We used stabilized inverse odds of selection weights (sIOSW) to estimate ethnicity-specific crude and age-standardized dementia incidence rates and cumulative risk by age 90 in the target population. Differences between the KPNC cohort and target population varied by ethnicity. sIOSW eliminated most differences in larger ethnic groups; some differences remained in smaller groups. Estimated crude dementia incidence rates using sIOSW (versus unweighted) were similar in Chinese, Filipinos, Pacific Islanders and Vietnamese, and higher in Japanese, Koreans, and South Asians. Unweighted and weighted age-standardized incidence rates differed for South Asians. Unweighted and weighted cumulative risk were similar for all groups. We estimated the first population-representative dementia incidence rates and cumulative risk in AANHPI ethnic groups. We encountered some estimation problems and weighted estimates were imprecise, highlighting challenges using weighting to extend inferences to target populations.

Methods for extending inferences from observational studies: considering causal structures, identification assumptions, and estimators.

Most prior work in quantitative approaches to generalizability and transportability emphasizes extending causal effect estimates from randomized trials to target populations. Extending findings from observational studies is also of scientific interest, and identifiability assumptions and estimation methods differ from randomized settings when there is selection on both the exposure and exposure-outcome mediators in combination with exposure-outcome confounders (and both confounders and mediators can modify exposure-outcome effects). We argue that this causal structure is common in observational studies, particularly in the field of lifecourse epidemiology, e.g., when extending estimates of the effect of an early-life exposure on a later-life outcome from a cohort enrolled in mid- to late-life. We describe identifiability assumptions and identification using observed data in such settings, highlighting differences from work extending findings from randomized trials. We describe statistical methods, including weighting, outcome modeling, and doubly robust approaches to estimate potential outcome means and verage treatment effects in the target population and illustrate performance of the methods in a simulation study. We show that in the presence of selection into the study sample on both exposure and confounders, estimators must be able to address confounding in the target population. When there is also selection on mediators of the exposure-outcome relationship, estimators need to be able to use different sets of variables to account for selection (including the mediator), and confounding. We discuss conceptual implications of our results, as well as highlight unresolved practical questions for applied work to extend findings from observational studies to target populations.

Association of cancer history with structural brain aging markers of Alzheimer's disease and related dementias risk.

INTRODUCTION: Cancer survivors are less likely than comparably aged individuals without a cancer history to develop Alzheimer's disease and related dementias (ADRD). METHODS: In the UK Biobank, we investigated associations between cancer history and five structural magnetic resonance imaging (MRI) markers for ADRD risk, using linear mixed-effects models to assess differences in mean values and quantile regression to examine whether associations varied across the distribution of MRI markers. RESULTS: Cancer history was associated with smaller mean hippocampal volume (b = -19 mm3 , 95% CI = -36, -1) and lower mean cortical thickness in the Alzheimer's disease signature region (b = -0.004 mm, 95% CI = -0.007, -0.000). Quantile regressions indicated individuals most vulnerable to ADRD were more affected by cancer history. DISCUSSION: Some brain MRI markers associated with ADRD risk were elevated in adults with a history of cancer. The magnitude of the adverse associations varied across quantiles of neuroimaging markers, and the pattern suggests possible harmful associations for individuals already at high ADRD risk. HIGHLIGHTS: We found no evidence of an inverse association between cancer history and ADRD-related neurodegeneration. Cancer history was associated with smaller mean hippocampal volume and lower mean cortical thickness in the Alzheimer's disease signature region. Quantile regressions indicated individuals most vulnerable to ADRD were more affected by cancer history.

Racial and ethnic differences in the association between depressive symptoms and cognitive outcomes in older adults: Findings from KHANDLE and STAR.

INTRODUCTION: Depressive symptoms are associated with higher risk of dementia, but how they impact cognition in diverse populations is unclear. METHODS: Asian, Black, Latino, or White participants (n = 2227) in the Kaiser Healthy Aging and Diverse Life Experiences (age 65+) and the Study of Healthy Aging in African Americans (age 50+) underwent up to three waves of cognitive assessments over 4 years. Multilevel models stratified by race/ethnicity were used to examine whether depressive symptoms were associated with cognition or cognitive decline and whether associations differed by race/ethnicity. RESULTS: Higher depressive symptoms were associated with lower baseline verbal episodic memory scores (-0.06, 95% CI: -0.12, -0.01; -0.15, 95% CI: -0.25, -0.04), and faster decline annually in semantic memory (-0.04, 95% CI: -0.07, -0.01; -0.10, 95% CI: -0.15, -0.05) for Black and Latino participants. Depressive symptoms were associated with lower baseline but not decline in executive function. DISCUSSION: Depressive symptoms were associated with worse cognitive outcomes, with some evidence of heterogeneity across racial/ethnic groups. HIGHLIGHTS: We examined whether baseline depressive symptoms were differentially associated with domain-specific cognition or cognitive decline by race/ethnicity. Depressive symptoms were associated with worse cognitive scores for all racial/ethnic groups across different domains examined. Higher depressive symptoms were associated with faster cognitive decline for semantic memory for Black and Latino participants. The results suggest a particularly harmful association between depressive symptoms and cognition in certain racial/ethnic groups.

Comparison of Imputation Strategies for Incomplete Longitudinal Data in Life-Course Epidemiology.

Incomplete longitudinal data are common in life-course epidemiology and may induce bias leading to incorrect inference. Multiple imputation (MI) is increasingly preferred for handling missing data, but few studies explore MI-method performance and feasibility in real-data settings. We compared 3 MI methods using real data under 9 missing-data scenarios, representing combinations of 10%, 20%, and 30% missingness and missing completely at random, at random, and not at random. Using data from Health and Retirement Study (HRS) participants, we introduced record-level missingness to a sample of participants with complete data on depressive symptoms (1998-2008), mortality (2008-2018), and relevant covariates. We then imputed missing data using 3 MI methods (normal linear regression, predictive mean matching, variable-tailored specification), and fitted Cox proportional hazards models to estimate effects of 4 operationalizations of longitudinal depressive symptoms on mortality. We compared bias in hazard ratios, root mean square error, and computation time for each method. Bias was similar across MI methods, and results were consistent across operationalizations of the longitudinal exposure variable. However, our results suggest that predictive mean matching may be an appealing strategy for imputing life-course exposure data, given consistently low root mean square error, competitive computation times, and few implementation challenges.

Association between cancer and dementia risk in the UK Biobank: evidence of diagnostic bias.

Epidemiological studies have identified an inverse association between cancer and dementia. Underlying methodological biases have been postulated, yet no studies have systematically investigated the potential for each source of bias within a single dataset. We used the UK Biobank to compare estimates for the cancer-dementia association using different analytical specifications designed to sequentially address multiple sources of bias, including competing risk of death, selective survival, confounding bias, and diagnostic bias. We included 140,959 UK Biobank participants aged ≥ 55 without dementia before enrollment and with linked primary care data. We used cancer registry data to identify cancer cases prevalent before UK Biobank enrollment and incident cancer diagnosed after enrollment. We used Cox models to evaluate associations of prevalent and incident cancer with all-cause dementia, Alzheimer's disease (AD), and vascular dementia. We used time-varying models to evaluate diagnostic bias. Over a median follow-up of 12.3 years, 3,310 dementia cases were diagnosed. All-site incident cancer was positively associated with all-cause dementia incidence (hazard ratio [HR] = 1.14, 95% CI: 1.02-1.29), but prevalent cancer was not (HR = 1.04, 95% CI: 0.92-1.17). Results were similar for vascular dementia. AD was not associated with prevalent or incident cancer. Dementia diagnosis was substantially elevated in the first year after cancer diagnosis (HR = 1.83, 95% CI: 1.42-2.36), after which the association attenuated to null, suggesting diagnostic bias. Following a cancer diagnosis, health care utilization or cognitive consequences of diagnosis or treatment may increase chance of receiving a dementia diagnosis, creating potential diagnostic bias in electronic health records-based studies.

Neighborhood disadvantage and dementia incidence in a cohort of Asian American and non-Latino White older adults in Northern California.

INTRODUCTION: Some evidence suggests that neighborhood socioeconomic disadvantage is associated with dementia-related outcomes. However, prior research is predominantly among non-Latino Whites. METHODS: We evaluated the association between neighborhood disadvantage (Area Deprivation Index [ADI]) and dementia incidence in Asian American (n = 18,103) and non-Latino White (n = 149,385) members of a Northern California integrated health care delivery system aged 60 to 89 at baseline. Race/ethnicity-specific Cox proportional hazards models adjusted for individual-level age, sex, socioeconomic measures, and block group population density estimated hazard ratios (HRs) for dementia. RESULTS: Among non-Latino Whites, ADI was associated with dementia incidence (most vs. least disadvantaged ADI quintile HR = 1.09, 95% confidence interval [CI] = 1.02-1.15). Among Asian Americans, associations were close to null (e.g., most vs. least disadvantaged ADI quintile HR = 1.01, 95% CI = 0.85-1.21). DISCUSSION: ADI was associated with dementia incidence among non-Latino Whites but not Asian Americans. Understanding the potentially different mechanisms driving dementia incidence in these groups could inform dementia prevention efforts.

Pragmatic approaches to handling practice effects in longitudinal cognitive aging research.

INTRODUCTION: The challenge of accounting for practice effects (PEs) when modeling cognitive change was amplified by the COVID-19 pandemic, which introduced period and mode effects that may bias the estimation of cognitive trajectory. METHODS: In three Kaiser Permanente Northern California prospective cohorts, we compared predicted cognitive trajectories and the association of grip strength with cognitive decline using three approaches: (1) no acknowledgment of PE, (2) inclusion of a wave indicator, and (3) constraining PE based on a preliminary model (APM) fit using a subset of the data. RESULTS: APM-based correction for PEs based on balanced, pre-pandemic data, and with current age as the timescale produced the smallest discrepancy between within-person and between-person estimated age effects. Estimated associations between grip strength and cognitive decline were not sensitive to the approach used. DISCUSSION: Constraining PEs based on a preliminary model is a flexible, pragmatic approach allowing for meaningful interpretation of cognitive change. HIGHLIGHTS: The magnitude of practice effects (PEs) varied widely by study. When PEs were present, the three PE approaches resulted in divergent estimated age-related cognitive trajectories. Estimated age-related cognitive trajectories were sometimes implausible in models that did not account for PEs. The associations between grip strength and cognitive decline did not differ by the PE approach used. Constraining PEs based on estimates from a preliminary model allows for a meaningful interpretation of cognitive change.

Monte Carlo Simulation Approaches for Quantitative Bias Analysis: A Tutorial.

Quantitative bias analysis can be used to empirically assess how far study estimates are from the truth (i.e., an estimate that is free of bias). These methods can be used to explore the potential impact of confounding bias, selection bias (collider stratification bias), and information bias. Quantitative bias analysis includes methods that can be used to check the robustness of study findings to multiple types of bias and methods that use simulation studies to generate data and understand the hypothetical impact of specific types of bias in a simulated data set. In this article, we review 2 strategies for quantitative bias analysis: 1) traditional probabilistic quantitative bias analysis and 2) quantitative bias analysis with generated data. An important difference between the 2 strategies relates to the type of data (real vs. generated data) used in the analysis. Monte Carlo simulations are used in both approaches, but the simulation process is used for different purposes in each. For both approaches, we outline and describe the steps required to carry out the quantitative bias analysis and also present a bias-analysis tutorial demonstrating how both approaches can be applied in the context of an analysis for selection bias. Our goal is to highlight the utility of quantitative bias analysis for practicing epidemiologists and increase the use of these methods in the epidemiologic literature.

Association of Social Integration with Cognitive Status in a Multi-Ethnic Cohort: Results From the Kaiser Healthy Aging and Diverse Life Experiences Study.

We evaluated overall and race-specific relationships between social integration and cognition in older adults. Kaiser Healthy Aging and Diverse Life Experiences (KHANDLE) cohort participants included 1343 Asian, Black, Latino, or non-Latino White Kaiser Permanente Northern California members. We estimated the effect of social integration on verbal episodic memory, semantic memory, and executive function derived from the Spanish and English Neuropsychological Assessment (SENAS) Scales. Social integration scores included marital status; volunteer activity; and contact with children, relatives, friends, and confidants. We estimated covariate-adjusted linear mixed-effects models for baseline and 17-month follow-up cognition. Social integration was associated with higher baseline cognitive scores (average  ß = 0.066 (95% confidence interval: 0.040, 0.092)) overall and in each racial/ethnic group. The association did not vary by race/ethnicity. Social integration was not associated with the estimated rate of cognitive change. In this cohort, more social integration was similarly associated with better late-life cognition across racial/ethnic groups.

The role of nativity in heterogeneous dementia incidence in a large cohort of three Asian American groups and white older adults in California.

INTRODUCTION: Literature shows lower dementia incidence in Asian American groups versus whites, varying by Asian ethnicity. One hypothesized driver is nativity differences (eg, healthy immigrant effect). METHODS: We followed a cohort of 6243 Chinese, 4879 Filipino, 3256 Japanese, and 141,158 white Kaiser Permanente Northern California members for incident dementia (2002 to 2020), estimating age-adjusted dementia incidence rates by ethnicity and nativity, and hazard ratios (HR) for nativity on dementia incidence using ethnicity-stratified age- and sex-adjusted Cox proportional hazards models. RESULTS: Dementia incidence appeared higher in foreign- versus US-born Filipinos (HR, 95% confidence interval: 1.39, 1.02 to 1.89); differences were small in Japanese (1.07, 0.88 to 1.30) and Chinese (1.07, 0.92 to 1.24). No nativity differences were observed among whites (1.00, 0.95 to 1.04). DISCUSSION: Nativity does not explain lower dementia incidence in Asian Americans versus whites, but may contribute to heterogeneity across Asian ethnicities. Future research should explore differential impacts of social and cardiometabolic factors.

Accounting for lack of representation in dementia research: Generalizing KHANDLE study findings on the prevalence of cognitive impairment to the California older population.

INTRODUCTION: Most dementia studies are not population-representative; statistical tools can be applied to samples to obtain critically-needed population-representative estimates, but are not yet widely used. METHODS: We pooled data from the Kaiser Healthy Aging and Diverse Life Experiences (KHANDLE) study and the California Behavioral Risk Factor Surveillance System (CA-BRFSS), a population-representative study. Using weights accounting for sociodemographic/health differences between KHANDLE and CA-BRFSS, we estimated cognitive impairment prevalence and age- and sex-adjusted racial/ethnic inequalities in California adults 65+ without prior dementia diagnosis. RESULTS: After weighting KHANDLE, the estimated cognitive impairment prevalence in California was 20.3% (95% confidence interval 17.8-23.0); unweighted prevalence was 24.8% (23.1%-26.6%). Inequalities (larger prevalences) were observed among Black and Asian groups versus whites. DISCUSSION: We used a novel statistical approach to estimate population-representative cognitive impairment prevalence and inequalities. Such statistical tools can help obtain population-representative estimates from existing studies and inform efforts to reduce racial/ethnic disparities.

Association Between Cognitive Test Performance and Subjective Cognitive Decline in a Diverse Cohort of Older Adults: Findings From the KHANDLE Study.

BACKGROUND: Subjective cognitive decline (SCD) may represent a low-burden indicator of dementia risk. The value of SCD as a proxy marker, however, depends on the consistency of associations between subjective and objective cognitive measures across sociodemographic and psychological factors. METHODS: We evaluated baseline data from the Kaiser Healthy Aging and Diverse Life Experiences (KHANDLE) study (n=1615). SCD was measured using the 12-item Everyday Cognition (ECog) scale. Using linear regression models with interaction terms, we evaluated 6 potential modifiers (age, sex, race/ethnicity, educational attainment, family history of dementia, and depressive symptoms) of the association between cognitive performance (episodic memory, executive function) and SCD. RESULTS: Lower episodic memory and executive function scores were associated with higher log(ECog scores) (more SCD). Older age and elevated depressive symptoms were associated with higher log(ECog scores). Age (interaction P=0.002) and education (interaction P=0.01) modified the association between executive function and log(ECog scores). Specifically, associations between executive function and log(ECog scores) were stronger among participants with more education and less pronounced among older participants. CONCLUSIONS: The association between cognitive performance and log(ECog scores) differed little across sociodemographic and psychological factors. SCD as measured by the ECog may be a valuable proxy for cognitive performance in diverse older adults.

The competing risk of death and selective survival cannot fully explain the inverse cancer-dementia association.

INTRODUCTION: We evaluated whether competing risk of death or selective survival could explain the reported inverse association between cancer history and dementia incidence (incidence rate ratio [IRR] ≈ 0.62-0.85). METHODS: A multistate simulation model of a cancer- and dementia-free cohort of 65-year-olds was parameterized with real-world data (cancer and dementia incidence, mortality), assuming no effect of cancer on dementia (true IRR = 1.00). To introduce competing risk of death, cancer history increased mortality. To introduce selective survival, we included a factor (prevalence ranging from 10% to 50%) that reduced cancer mortality and dementia incidence (IRRs ranged from 0.30 to 0.90). We calculated IRRs for cancer history on dementia incidence in the simulated cohorts. RESULTS: Competing risk of death yielded unbiased cancer-dementia IRRs. With selective survival, bias was small (IRRs = 0.89 to 0.99), even under extreme scenarios. DISCUSSION: The bias induced by selective survival in simulations was too small to explain the observed inverse cancer-dementia link, suggesting other mechanisms drive this association.

Limited awareness of pre-exposure prophylaxis among black men who have sex with men and transgender women in New York city.

Awareness of Pre-exposure prophylaxis (PrEP) was assessed among a cohort of substance-using black men who have sex with men and transgender women (MSM/TGW) participating in the STAR Study, which recruited black MSM/TGW in New York City for HIV testing and linked HIV-infected individuals into care from July 2012 to April 2015. Sociodemographic, psychosocial, known HIV risk factors, and PrEP awareness were assessed among participants. Multivariable logistic regression was conducted to assess factors associated with PrEP awareness. Of 1673 participants, median age was 43 years and 25% were under age 30. Most participants (85.8%) reported having insufficient income for basic necessities at least occasionally, 54.8% were homeless, and 71.3% were unemployed. Awareness of PrEP was reported among 18.2% of participants. PrEP awareness was associated with younger age (adjusted odds ratio [aOR] 0.87, per 5 years), gay identity (aOR 2.46), higher education (aOR 1.70), more frequent past HIV testing (aOR 3.18), less HIV stigma (aOR 0.61), less hazardous/harmful alcohol use (aOR 0.61), and more sexual partners (aOR 1.04, per additional partner in past 30 days). In this substance-using black MSM/TGW cohort with high rates of poverty and homelessness, PrEP awareness was low. This study demonstrates the need for targeted dissemination of PrEP information to key populations to increase awareness and ultimately improve uptake and utilization of PrEP.

Prevalence, patterns, and correlates of HIV disclosure among TB-HIV patients initiating antiretroviral therapy in Lesotho.

Disclosure of HIV-positive status has important implications for patient outcomes and preventing HIV transmission, but has been understudied in TB-HIV patients. We assessed disclosure patterns and correlates of non-disclosure among adult TB-HIV patients initiating ART enrolled in the START Study, a mixed-methods cluster-randomized trial conducted in Lesotho, which evaluated a combination intervention package (CIP) versus standard of care. Interviewer-administered questionnaire data were analyzed to describe patterns of disclosure. Patient-related factors were assessed for association with non-disclosure to anyone other than a health-care provider and primary partners using generalized linear mixed models. Among 371 participants, 95% had disclosed their HIV diagnosis to someone other than a health-care provider, most commonly a spouse/primary partner (76%). Age, TB knowledge, not planning to disclose TB status, greater perceived TB stigma, and CIP were associated with non-disclosure in unadjusted models (p < .1). In adjusted models, all point estimates were similar and greater TB knowledge (adjusted odds ratio [aOR] 0.59, 95% confidence interval [CI] 0.39-0.90) and CIP (aOR 0.20, 95% CI 0.05-0.79) remained statistically significant. Among 220 participants with a primary partner, 76% had disclosed to that partner. Significant correlates of partner non-disclosure (p < .1) in unadjusted analyses included being female, married/cohabitating, electricity at home, not knowing if partner was HIV-positive, and TB knowledge. Adjusted point estimates were largely similar, and being married/cohabitating (aOR 0.03, 95% CI 0.01-0.12), having electricity at home (aOR 0.38, 95% CI 0.17-0.85) and greater TB knowledge (aOR 0.76, 95% CI 0.59-0.98) remained significant. In conclusion, although nearly all participants reported disclosing their HIV status to someone other than a health-care provider at ART initiation, nearly a quarter of participants with a primary partner had not disclosed to their partner. Additional efforts to support HIV disclosure (e.g., counseling) may be needed for TB-HIV patients, particularly for women and those unaware of their partners' status.