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In the US, dementia risk is higher in non-Hispanic Black individuals than in non-Hispanic White individuals. To evaluate progress toward reducing such disparities, tracking secular trends in racial disparities in dementia prevalence is essential. OBJECTIVE To examine whether relative racial disparities in dementia prevalence or incidence have changed in the US from 2000 to 2016. DESIGN, SETTINGS, AND PARTICIPANTSThe Health and Retirement Study (HRS) is a nationally representative study of adults 50 years or older. New participants are recruited every 6 years, and study visits occur biennially. Approximately 17 000 to 22 000 respondents have been surveyed at each wave since 2000, achieving response rates of 81% to 89%. Data for this cohort study were obtained from non-Hispanic White and non-Hispanic Black participants aged 70 years and older from the 2000 to 2016 waves. For analyses of secular trends in racial disparities in dementia prevalence, each HRS wave was considered separately (range of participants meeting eligibility criteria in each wave, 6322-7579). For analyses of secular trends in racial disparities in dementia incidence, 7 subcohorts were created (range of participants meeting eligibility criteria in each subcohort, 5322-5961) following up people without dementia for 4 years from subcohort baseline visits

Introduction Systematic disparities in misdiagnosis of dementia across racial/ethnic groups have implications for health disparities. We compared the risk of dementia under‐ and overdiagnosis in clinical settings across racial/ethnic groups from 2000 to 2010. Methods We linked fee‐for‐service Medicare claims to participants aged ≥70 from the nationally representative Health and Retirement Study. We classified dementia status using an algorithm with similar sensitivity and specificity across racial/ethnic groups and assigned clinical dementia diagnosis status using ICD‐9‐CM codes from Medicare claims. Multinomial logit models were used to estimate relative risks of clinical under‐ and overdiagnosis between groups and over time. Results Non‐Hispanic blacks had roughly double the risk of underdiagnosis as non‐Hispanic whites. While primary analyses suggested a shrinking disparity over time, this was not robust to sensitivity analyses or adjustment for covariates. Risk of overdiagnosis increased over time in both groups. Discussion Our results suggest that efforts to reduce racial disparities in underdiagnosis are warranted.

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 ( ) and cognitive decline generally supported an adverse association, other findings related to and findings related to particulate matter with aerodynamic diameter ( , , and ) 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 and cognitive decline. However, we note a continued need to confront methodological challenges in this line of research. https://doi.org/10.1289/EHP8716

Background: Disparities research in dementia is limited by lack of large, diverse, and representative samples with systematic dementia ascertainment. Algorithmic diagnosis of dementia offers a cost-effective alternate approach. Prior work in the nationally-representative Health and Retirement Study (HRS) has demonstrated that existing algorithms are ill-suited for racial/ethnic disparities work given differences in sensitivity and specificity by race/ethnicity. Methods:We implemented traditional and machine learning methods to identify an improved algorithm that (a) had ≤5 percentage point difference in sensitivity and specificity across racial/ ethnic groups, (b) achieved ≥80% overall accuracy across racial/ethnic groups, and (c) achieved ≥75% sensitivity and ≥90% specificity overall. Final recommendations were based on robustness, accuracy of estimated race/ethnicity-specific prevalence and prevalence ratios compared to those using in-person diagnoses, and ease of use. Results:We identified six algorithms that met our pre-specified criteria. Our three recommended algorithms achieved ≤3 percentage point difference in sensitivity and ≤5 percentage point difference in specificity across racial/ethnic groups, as well as 77%−83% sensitivity, 92-94% specificity, and 90-92% accuracy overall in analyses designed to emulate out-of-sample performance. Pairwise prevalence ratios between non-Hispanic whites, non-Hispanic blacks, and Hispanics estimated by application of these algorithms are within 1% to 10% of prevalence ratios estimated based on in-person diagnoses.

Introduction Clinic‐based study samples, including the Alzheimer's Disease Neuroimaging Initiative (ADNI), offer rich data, but findings may not generalize to community‐based settings. We compared associations in ADNI to those in the Atherosclerosis Risk in Communities (ARIC) study to assess generalizability across the two settings. Methods We estimated cohort‐specific associations among risk factors, cognitive test scores, and neuroimaging outcomes to identify and quantify the extent of significant and substantively meaningful differences in associations between cohorts. We explored whether using more homogenous samples improved comparability in effect estimates. Results The proportion of associations that differed significantly between cohorts ranged from 27% to 34% across sample subsets. Many differences were substantively meaningful (e.g., odds ratios [OR] for apolipoprotein E ε4 on amyloid positivity in ARIC: OR = 2.8, in ADNI: OR = 8.6). Discussion A higher proportion of associations differed significantly and substantively than would be expected by chance. Findings in clinical samples should be confirmed in more representative samples.

Urea cycle disorders (UCD) are rare inherited metabolic disorders caused by deficiencies of enzymes and transporters required to convert neurotoxic ammonia into urea. These deficiencies cause elevated blood ammonia, which if untreated may result in death, but even with optimal medical management, often results in recurrent brain damage. There are two major treatments for UCD: medical management or liver transplantation. Both are associated with mortality and morbidity but the evidence comparing outcomes is sparse. Thus, families face a dilemma: should their child be managed medically, or should they undergo a liver transplant? To (a) describe the factors that contribute to treatment choice among parents of children diagnosed with UCD and to (b) organise these factors into a conceptual framework that reflects how these issues interrelate to shape the decision-making experience of this population. Utilising grounded theory, qualitative data were collected through semistructured interviews with parents (N = 35) and providers (N = 26) of children diagnosed with UCD and parent focus groups (N = 19). Thematic content analysis and selective and axial coding were applied. The framework highlights the life-cycle catalysts that frame families' personal perceptions of risks and benefits and describes the clinical, personal, social, and system factors that drive treatment choice including disease severity, stability, and burden, independence, peer experiences, and cost, coverage and access to quality care.Findings equip providers with evidence upon which to prepare for productive patient interactions about treatment options. They also provide a foundation for the development of patient-centred outcome measures to better evaluate effectiveness of treatments in this population. K E Y W O R D S decision-making, liver transplant, qualitative research, treatment choice, urea cycle disorders

BACKGROUND/OBJECTIVE To evaluate the relationship between self‐reported hearing loss and nonfatal fall‐related injury in a nationally representative sample of community‐dwelling adults living in the United States. DESIGN Cross‐sectional analysis of national survey data. SETTING National Health Interview Survey (2016). PARTICIPANTS A total of 30 994 community‐dwelling adults in the United States, aged 18 years and older. MEASUREMENTS We evaluated the association between self‐reported hearing loss and nonfatal injury resulting from a fall in the previous 3 months. We used multivariate logistic regression to calculate adjusted odds ratios (ORs) and evaluated effect measure modification by age. RESULTS The odds of nonfatal fall‐related injury were 1.60 times higher among respondents with hearing loss compared to respondents without hearing loss (95% confidence interval [CI] = 1.20‐2.12; P = .0012). Results were unchanged when adjusting for demographics (OR = 1.59; 95% CI = 1.18‐2.15; P = .002). After adjustment for cardiovascular risk factors, cardiovascular disease, visual impairment, and limitation caused by nervous system/sensory organ conditions and depression, anxiety, or another emotional problem, the OR fell to 1.27 (95% CI = 0.92‐1.74; P = .14). In the fully adjusted model, including adjustment for vestibular vertigo, there was little support to link hearing loss and fall‐related injury (OR = 1.16; 95% CI = 0.84‐1.60; P = .36). Effect modification by age was not observed. CONCLUSIONS Self‐reported hearing loss may be a clinically useful indicator of increased fall risk, but treatment for hearing loss is unlikely to mitigate this risk, given that there is no independent association between self‐reported hearing loss and nonfatal falls after accounting for vestibular function and other potential confounders.