Association between Caregiver-perceived Health Care Provider Cultural Sensitivity and Child Health Status in the National Survey of Children's Health: 2016-2020.

OBJECTIVES: To examine the association between caregiver-perceived cultural sensitivity of health care providers and child health status in the United States. METHODS: We analyzed National Survey of Children's Health data (n = 145,226) from 2016-2020. Using logistic regression, we determined odds of reporting a better health status by level of caregiver-perceived provider cultural sensitivity while controlling for potential confounders. RESULTS: Children with providers perceived as more culturally sensitive by their caregivers had 2.38 times the odds (95% confidence interval: 1.73, 3.28) of enjoying a better caregiver-assessed health status compared with children whose providers were perceived as less culturally sensitive. Caregivers of BIPOC children in our sample were 1.99 times more likely (95% CI: 1.89, 2.10) to report their provider as only sometimes or never culturally sensitive. CONCLUSIONS: Cultural sensitivity of health care providers, as perceived by caregivers, was associated with caregiver-assessed child health status in our study. This association remained significant when controlling for various sociodemographic variables. Our findings highlight the need for more research around the potential positive impact that improving provider cultural sensitivity could have on the health of children who are Black, Indigenous, or other People of Color (BIPOC).

An assessment of the mediating role of hypertension in the effect of long-term air pollution exposure on dementia.

Background: Growing evidence links air pollution exposure to the risk of dementia. We hypothesized that hypertension may partially mediate this effect. Methods: We previously documented an association between air pollution and dementia in the Ginkgo Evaluation of Memory Study, a randomized, placebo-controlled trial of 3069 adults ≥75 years across four US sites who were evaluated for dementia every 6 months from 2000-2008. We utilized a two-stage regression approach for causal mediation analysis to decompose the total effect of air pollution on dementia into its natural direct and indirect effect through prevalent hypertension. Exposure to air pollution in the 10 or 20 years before enrollment was assigned using estimates from fine-scale spatial-temporal models for PM2.5, PM10, and NO2. We used Poisson regression models for hypertension and Cox proportional hazard models for time-to-incident all-cause dementia, adjusting for a priori confounders. Results: Participants were free of mild cognitive impairment at baseline (n = 2564 included in analyses); 69% had prevalent hypertension at baseline. During follow-up, 12% developed all-cause dementia (Alzheimer's disease [AD] = 212; vascular dementia with or without AD [VaD/AD mixed] = 97). We did not find an adverse effect of any air pollutant on hypertension. Hypertension was associated with VaD/AD mixed (HR, 1.92 [95% CI = 1.14, 3.24]) but not AD. We did not observe mediation through hypertension for the effect of any pollutant on dementia outcomes. Conclusions: The lack of mediated effect may be due to other mechanistic pathways and the minimal effect of air pollution on hypertension in this cohort of older adults.

The impact of falls on activities of daily living in older adults: A retrospective cohort analysis.

BACKGROUND: Falls contribute to impairments in activities of daily living (ADLs), resulting in significant declines in the quality of life, safety, and functioning of older adults. Understanding the magnitude and duration of the effect of falls on ADLs, as well as identifying the characteristics of older adults more likely to have post-fall ADL impairment is critical to inform fall prevention and post-fall intervention. The purpose of this study is to 1) Quantify the association between falls and post-fall ADL impairment and 2) Model trajectories of ADL impairment pre- and post-fall to estimate the long-term impact of falls and identify characteristics of older adults most likely to have impairment. METHOD: Study participants were from the Ginkgo Evaluation of Memory Study, a randomized controlled trial in older adults (age 75+) in the United States. Self-reported incident falls and ADL scores were ascertained every 6 months over a 7-year study period. We used Cox proportional hazards analyses (n = 2091) to quantify the association between falls and ADL impairment and latent class trajectory modeling (n = 748) to visualize trajectories of ADL impairment pre-and post-fall. RESULTS: Falls reported in the previous 6 months were associated with impairment in ADLs (HR: 1.42; 95% CI 1.32, 1.52) in fully adjusted models. Based on trajectory modeling (n = 748), 19% (n = 139) of participants had increased, persistent ADL impairment after falling. Participants who were female, lived in a neighborhood with higher deprivation, or experienced polypharmacy were more likely to have ADL impairment post-fall. CONCLUSIONS: Falls are associated with increased ADL impairment, and this impairment can persist over time. It is crucial that all older adults, and particularly those at higher risk of post-fall ADL impairment have access to comprehensive fall risk assessment and evidence-based fall prevention interventions, to help mitigate the negative impacts on ADL function.

Change in gait speed and fall risk among community-dwelling older adults with and without mild cognitive impairment: a retrospective cohort analysis.

BACKGROUND: Although slow gait speed is an established risk factor for falls, few studies have evaluated change in gait speed as a predictor of falls or considered variability in effects by cognitive status. Change in gait speed may be a more useful metric because of its potential to identify decline in function. In addition, older adults with mild cognitive impairment are at an elevated risk of falls. The purpose of this research was to quantify the association between 12-month change in gait speed and falls in the subsequent 6 months among older adults with and without mild cognitive impairment. METHODS: Falls were self-reported every six months, and gait speed was ascertained annually among 2,776 participants in the Ginkgo Evaluation of Memory Study (2000-2008). Adjusted Cox proportional hazards models were used to estimate hazard ratios (HR) and 95% confidence intervals (CI) for fall risk relative to a 12-month change in gait speed. RESULTS: Slowing gait speed over 12 months was associated with increased risk of one or more falls (HR:1.13; 95% CI: 1.02 to 1.25) and multiple falls (HR:1.44; 95% CI: 1.18 to 1.75). Quickening gait speed was not associated with risk of one or more falls (HR 0.97; 95% CI: 0.87 to 1.08) or multiple falls (HR 1.04; 95% CI: 0.84 to 1.28), relative to those with a less than 0.10 m/s change in gait speed. Associations did not vary by cognitive status (pinteraction = 0.95 all falls, 0.25 multiple falls). CONCLUSIONS: Decline in gait speed over 12 months is associated with an increased likelihood of falls among community-dwelling older adults, regardless of cognitive status. Routine checks of gait speed at outpatient visits may be warranted as a means to focus fall risk reduction efforts.

Air pollution and plasma amyloid beta in a cohort of older adults: Evidence from the Ginkgo Evaluation of Memory study.

Air pollution has been linked to Alzheimer's disease and related dementias (ADRD), but the mechanisms connecting air pollution to ADRD have not been firmly established. Air pollution may cause oxidative stress and neuroinflammation and contribute to the deposition of amyloid beta (Aß) in the brain. We examined the association between fine particulate matter<2.5 µm in diameter (PM2.5), particulate matter<10 µm in diameter (PM10), nitrogen dioxide (NO2), and plasma based measures of Aß1-40, Aß1-42 and Aß1-42/Aß1-40 using data from 3044 dementia-free participants of the Ginkgo Evaluation of Memory Study (GEMS). Air pollution exposures were estimated at residential addresses that incorporated address histories dating back to 1980, resulting in one-, five-, 10- and 20- year exposure averages. Aß was measured at baseline (2000-2002) and then again at the end of the study (2007-2008) allowing for linear regression models to assess cross-sectional associations and linear random effects models to evaluate repeated measures. After adjustment for socio-demographic and behavioral covariates, we found small positive associations between each air pollutant and Aß1-40 but no association with Aß1-42 or the ratio measures in cross sectional analysis. In repeat measures analysis, we found larger positive associations between each air pollutant and all three outcomes. We observed a 4.43% (95% CI 3.26%, 5.60%) higher Aß1-40 level, 9.73% (6.20%, 13.38%) higher Aß1-42 and 1.57% (95% CI: 0.94%, 2.20%) higher Aß1-42/Aß1-40 ratio associated with a 2 µg/m3 higher 20-year average PM2.5. Associations with other air pollutants were similar. Our study contributes to the broader evidence base on air pollution and ADRD biomarkers by evaluating longer air pollution exposure averaging periods to better mimic disease progression and provides a modifiable target for ADRD prevention.

Air pollution and dementia in older adults in the Ginkgo Evaluation of Memory Study.

INTRODUCTION: Growing evidence implicates air pollution as a risk factor for dementia, but prior work is limited by challenges in diagnostic accuracy and assessing exposures in the decades prior to disease development. We evaluated the impact of long-term fine particulate matter (PM2.5 ) exposures on incident dementia (all-cause, Alzheimer's disease [AD], and vascular dementia [VaD]) in older adults. METHODS: A panel of neurologists adjudicated dementia cases based on extensive neuropsychological testing and magnetic resonance imaging. We applied validated fine-scale air pollutant models to reconstructed residential histories to assess exposures. RESULTS: An interquartile range increase in 20-year PM2.5 was associated with a 20% higher risk of dementia (95% confidence interval [CI]: 5%, 37%) and an increased risk of mixed VaD/AD but not AD alone. DISCUSSION: Our findings suggest that air pollutant exposures over decades contribute to dementia and that effects of current exposures may be experienced years into the future.

The Association between Gait Speed and Falls in Community Dwelling Older Adults with and without Mild Cognitive Impairment.

(1) Background: Falls are common in older adults and result in injuries, loss of independence, and death. Slow gait is associated with falls in older adults, but few studies have assessed the association between gait speed and falls among those with mild cognitive impairment (MCI). (2) Methods: The association between gait speed and falls was assessed in 2705 older adults with and without MCI participating in the Ginkgo Evaluation of Memory Study. Gait speed was measured via a 15-foot walk test and fall history through self-report. We used data collected at the 12-month (2001-2003) and 18-month visits (2002-2004). (3) Results: Participant average age was 78.5 years (sd = 3.2); 45% were female, and 14% had MCI at baseline. The average gait speed was 0.93 m/s (sd = 0.20). Sixteen percent (n = 433) and 18% (n = 498) reported at least one fall at the 12-month and 18-month visits, respectively. Faster gait speed was associated with decreased risk of falling (RR: 0.95, 95% CI: 0.91, 0.99) for every 10 cm/s increase in gait speed adjusted for age, gender, study arm, site, and MCI status. (4) Conclusions: The relationship between gait speed and risk of falling did not vary by MCI status (interaction p-value = 0.78).

hEIDI: An Intuitive Application Tool To Organize and Treat Large-Scale Proteomics Data.

Advances in high-throughput proteomics have led to a rapid increase in the number, size, and complexity of the associated data sets. Managing and extracting reliable information from such large series of data sets require the use of dedicated software organized in a consistent pipeline to reduce, validate, exploit, and ultimately export data. The compilation of multiple mass-spectrometry-based identification and quantification results obtained in the context of a large-scale project represents a real challenge for developers of bioinformatics solutions. In response to this challenge, we developed a dedicated software suite called hEIDI to manage and combine both identifications and semiquantitative data related to multiple LC-MS/MS analyses. This paper describes how, through a user-friendly interface, hEIDI can be used to compile analyses and retrieve lists of nonredundant protein groups. Moreover, hEIDI allows direct comparison of series of analyses, on the basis of protein groups, while ensuring consistent protein inference and also computing spectral counts. hEIDI ensures that validated results are compliant with MIAPE guidelines as all information related to samples and results is stored in appropriate databases. Thanks to the database structure, validated results generated within hEIDI can be easily exported in the PRIDE XML format for subsequent publication. hEIDI can be downloaded from http://biodev.extra.cea.fr/docs/heidi .