Use of and disparities in access to adaptive devices among U.S. adults with age-related eye diseases

This paper examines adaptive device use among two samples of U.S. adults aged 40 years and older with agerelated macular degeneration, diabetic retinopathy, glaucoma or cataracts from the 2008 and 2016 waves of the nationally-representative cross-sectional National Health Interview Survey (n=2875 and n=6233 respectively). Individuals who replied affirmatively to the question, “do you use any adaptive devices such as telescopic or other prescriptive lenses, magnifiers, large print or talking materials, CCTV, white cane or guide dogs?” were defined as adaptive device users. Descriptive statistics and logistic regression models of adaptive device use were estimated. The main regression models used 2008 data and included explanatory variables for vision-related limitations, other functional limitations, sociodemographic characteristics and the local availability of ophthalmologists and optometrists. 6.1% of the 2008 sample and 4.2% of the 2016 sample used adaptive devices, these percentages were significantly different. 31.4% of the 2008 sample and 24.0% of 2016 sample with multiple vision-related limitations used adaptive devices, these percentages were not significantly different. Based on previous research, adaptive device use among the subgroups with multiple vision-related limitations would be expected to improve functional ability. In the regression models, the likelihood of adaptive device use increased significantly with the number of vision-related limitations, family income and local ophthalmologist availability. The regression results provide evidence of socioeconomic and geographic disparities in adaptive device use in the U.S. Together the descriptive statistics and regression results suggest that public health strategies to increase access to adaptive devices are needed

State Actions and Shortages of Personal Protective Equipment and Staff in U.S. Nursing Homes

BACKGROUND: It is crucial that nursing homes have adequate personal protective equipment (PPE) and staff to protect residents and staff from COVID-19. Some states have taken actions to mitigate shortages of PPE and staffing in nursing homes, including creating dedicated long-term care (LTC) teams and supporting staffing capacity. OBJECTIVE: To examine whether state actions and nursing home characteristics are associated with shortages of PPE and staffing. DESIGN AND SETTING: Facility-level data, released July 31, 2020, from the Nursing Home COVID-19 Public File, were combined with data from other sources. Our sample was the 13,445 facilities with information about PPE and staffing shortages for each of the 5 weeks between the week ending June 21, 2020, and the week ending July 19, 2020. Associations between facility characteristics and shortages were examined using descriptive statistics and logistic regression models. MEASUREMENTS: Outcome variables were whether or not a facility lacked a 1-week supply of PPE (“PPE shortage”) and whether or not a facility had a staffing shortage during 1 or more weeks over the 5-week study period. RESULTS: Over the 5-week study period, 27.6% of facilities reported 1 or more weeks of PPE shortage, 30.2% of facilities reported at least 1 week of staffing shortage, and 46.5% of facilities lacked PPE and/or staff. Facilities located in states in the Northeast PPE Consortium or with LTC teams were modestly less likely to have had a PPE shortage, and facilities located in states that implemented processes to match job seekers with LTC facilities were marginally significantly less likely to have had a staffing shortage. CONCLUSION: Given that nearly half of U.S. nursing homes recently faced a shortage of PPE and/or staff, and that state budget deficits may limit further state actions, ongoing federal assistance with PPE and staffing of nursing homes is needed

Admissions of COVID-positive patients to US nursing homes with personal protective equipment or staffing shortages

Background: US nursing homes are required to follow Centers for Disease Control guidance for COVID-19 transmission-based precautions (TBP) when admitting COVID-positive patients. Objective: To assess how frequently nursing homes had shortages of personal protective equipment (PPE) or staffing in weeks when they admitted COVID-positive patients, which likely made it more difficult to follow TBP, and to compare facility characteristics by admissions practices. Design and Setting: Facility-level data from the Nursing Home COVID-19 Public File for the period between June 7, 2020 and March 7, 2021 was combined with additional data. The percentages of nursing homes that admitted COVID-positive patients and that had shortages when admitting were calculated for each week. Descriptive statistics and logistic regression models were used to examine the relationship between facility characteristics and the likelihood of admitting COVID-positive patients. Measurements: Facilities were categorized as having admitted COVID-positive patients in a week if one or more admissions requiring TBP were reported for that week. Facilities that reported having less than a 1-week supply of any type of PPE or being short any type of staff in a week were defined, respectively, as having a PPE shortage or staffing shortage in that week. Results: Over the 40-week study period, 39% of US nursing homes admitted COVID-positive patients in at least 1 week in which they were experiencing PPE or staffing shortages. Facilities that admitted COVID-positive patients with shortages generally had lower Centers for Medicare and Medicaid Services overall five-star ratings than other facilities. Only a small percentage of facilities that admitted COVID-positive patients while facing shortages were located in counties with severe shortages of PPE or staffing. In logistic regression models, shortages were not associated with COVID-positive admissions. Conclusion: The widespread practice of admitting COVID-positive patients while facing shortages may have put nursing home residents and staff at heightened risk of COVID-19 infection

A distributed geospatial approach to describe community characteristics for multisite studies

Understanding place-based contributors to health requires geographically and culturally diverse study populations, but sharing location data is a significant challenge to multisite studies. Here, we describe a standardized and reproducible method to perform geospatial analyses for multisite studies. Using census tract-level information, we created software for geocoding and geospatial data linkage that was distributed to a consortium of birth cohorts located throughout the USA. Individual sites performed geospatial linkages and returned tract-level information for 8810 children to a central site for analyses. Our generalizable approach demonstrates the feasibility of geospatial analyses across study sites to promote collaborative translational research

Prenatal Exposure to Traffic Pollution and Childhood Body Mass Index Trajectory

Background: Limited evidence suggests an association between prenatal exposure to traffic pollution and greater adiposity in childhood, but the time window during which growth may be most affected is not known.Methods: We studied 1,649 children in Project Viva, a Boston-area pre-birth cohort. We used spatiotemporal models to estimate prenatal residential air pollution exposures and geographic information systems to estimate neighborhood traffic density and roadway proximity. We used weight and stature measurements at clinical and research visits to estimate a BMI trajectory for each child with mixed-effects natural cubic spline models. In primary analyses, we examined associations of residential PM2.5 and black carbon (BC) exposures during the third trimester and neighborhood traffic density and home roadway proximity at birth address with (1) estimated BMI at 6 month intervals through 10 years of age, (2) magnitude and timing of BMI peak and rebound, and (3) overall BMI trajectory. In secondary analyses, we examined associations of residential PM2.5 and BC exposures during the first and second trimesters with BMI outcomes.Results: Median (interquartile range; IQR) concentration of residential air pollution during the third trimester was 11.4 (1.7) μg/m3 for PM2.5 and 0.7 (0.3) μg/m3 for BC. Participants had a median (IQR) of 13 (7) clinical or research BMI measures from 0 to 10 years of age. None of the traffic pollution exposures were significantly associated with any of the BMI outcomes in covariate-adjusted models, although effect estimates were in the hypothesized direction for neighborhood traffic density and home roadway proximity. For example, greater neighborhood traffic density [median (IQR) 857 (1,452) vehicles/day x km of road within 100 m of residential address at delivery] was associated with a higher BMI throughout childhood, with the strongest associations in early childhood [e.g., per IQR increment natural log-transformed neighborhood traffic density, BMI at 12 months of age was 0.05 (−0.03, 0.13) kg/m2 higher and infancy peak BMI was 0.05 (−0.03, 0.14) kg/m2 higher].Conclusions: We found no evidence for a persistent effect of prenatal exposure to traffic pollution on BMI trajectory from birth through mid-childhood in a population exposed to modest levels of air pollution

Residential PM2.5 exposure and the nasal methylome in children

Rationale: PM2.5-induced adverse effects on respiratory health may be driven by epigenetic modifications in airway cells. The potential impact of exposure duration on epigenetic alterations in the airways is not yet known. Objectives: We aimed to study associations of fine particulate matter PM2.5 exposure with DNA methylation in nasal cells. Methods: We conducted nasal epigenome-wide association analyses within 503 children from Project Viva (mean age 12.9 y), and examined various exposure durations (1-day, 1-week, 1-month, 3-months and 1-year) prior to nasal sampling. We used residential addresses to estimate average daily PM2.5 at 1 km resolution. We collected nasal swabs from the anterior nares and measured DNA methylation (DNAm) using the Illumina Methylation EPIC BeadChip. We tested 719,075 high quality autosomal CpGs using CpG-by-CpG and regional DNAm analyses controlling for multiple comparisons, and adjusted for maternal education, household smokers, child sex, race/ethnicity, BMI z-score, age, season at sample collection and cell-type heterogeneity. We further corrected for bias and genomic inflation. We tested for replication in a cohort from the Netherlands (PIAMA). Results: In adjusted analyses, we found 362 CpGs associated with 1-year PM2.5 (FDR < 0.05), 20 CpGs passing Bonferroni correction (P < 7.0 x 10(-8)) and 10 Differentially Methylated Regions (DMRs). In 445 PIAMA participants (mean age 16.3 years) 11 of 203 available CpGs replicated at P < 0.05. We observed differential DNAm at/ near genes implicated in cell cycle, immune and inflammatory responses. There were no CpGs or regions associated with PM2.5 levels at 1-day, 1-week, or 1-month prior to sample collection, although 2 CpGs were associated with past 3-month PM2.5. Conclusion: We observed wide-spread DNAm variability associated with average past year PM2.5 exposure but we did not detect associations with shorter-term exposure. Our results suggest that nasal DNAm marks reflect chronic air pollution exposure

Event-based record linkage in health and aged care services data: a methodological innovation

<p>Abstract</p> <p>Background</p> <p>The interface between acute hospital care and residential aged care has long been recognised as an important issue in aged care services research in Australia. However, existing national data provide very poor information on the movements of clients between the two sectors. Nevertheless, there are national data sets which separately contain data on individuals' hospital episodes and stays in residential aged care, so that linking the two data sets–if feasible–would provide a valuable resource for examining relationships between the two sectors. As neither name nor common person identifiers are available on the data sets, other information needs to be used to link events relating to inter-sector movement.</p> <p>Methods</p> <p>Event-based matching using limited demographic data in conjunction with event dates to match events in two data sets provides a possible method for linking related events. The authors develop a statistical model for examining the likely prevalence of false matches, and consequently the number of true matches, among achieved matches when using anonymous event-based record linkage to identify transition events.</p> <p>Results</p> <p>Theoretical analysis shows that for event-based matching the prevalence of false matches among achieved matches (a) declines as the events of interest become rarer, (b) declines as the number of matches increases, and (c) increases with the size of the population within which matching is taking place. The method also facilitates the examination of the trade-off between false matches and missed matches when relaxing or tightening linkage criteria.</p> <p>Conclusion</p> <p>Event-based record linkage is a method for linking related transition events using event dates and basic demographic variables (other than name or person identifier). The likely extent of false links among achieved links depends on the two event rates, the match rate and population size. Knowing these, it is possible to gauge whether, for a particular study, event-based linkage could provide a useful tool for examining movements. Analysis shows that there is a range of circumstances in which event-based record linkage could be applied to two event-level databases to generate a linked database useful for transition analysis.</p

Birth weight in a large series of triplets

Background: Triplets are often born premature and with a low birth weight. Because the incidence of triplet births is rare, there are relatively few studies describing triplet birth weight characteristics. Earlier studies are often characterized by small sample sizes and lack information on important background variables such as zygosity. The objective of this study is to examine factors associated with birth weight in a large, population-based sample of triplets registered with the Netherlands Twin Register (NTR).Methods: In a sample of 1230 triplets from 410 families, the effects of assisted reproductive techniques, zygosity, birth order, gestational age, sex, maternal smoking and alcohol consumption during pregnancy on birth weight were assessed. The resemblance among triplets for birth weight was estimated as a function of zygosity. Birth weight discordance within families was studied by the pair-wise difference between triplets, expressed as a percentage of the birth weight of the heaviest child. We compare data from triplets registered with the NTR with data from population records, which include live births, stillbirths and children that have deceased within days after birth.Results: There was no effect of assisted reproductive techniques on triplet birth weight. At gestational age 24 to 40 weeks triplets gained on average 130 grams per week; boys weighed 110 grams more than girls and triplets of smoking mothers weighted 104 grams less than children of non-smoking mothers. Monozygotic triplets had lower birth weights than di- and trizygotic triplets and birth weight discordance was smaller in monozygotic triplets than in di- and trizygotic triplets. The correlation in birth weight among monozygotic and dizygotic triplets was 0.42 and 0.32, respectively. In nearly two-thirds of the families, the heaviest and the lightest triplet had a birth weight discordance over 15%. The NTR sample is representative for the Dutch triplet population that is still alive 28 days after birth.Conclusion: Birth weight is an important determinant of childhood development. Triplet status, gestational age, sex, zygosity and maternal smoking affect birth weight. The combined effects amount to a difference of 364 grams between monozygotic girl triplets of smoking mothers compared to dizygotic boy triplets of non-smoking mothers of the same gestational age. Birth weight in triplets is also influenced by genetic factors, as indicated by a larger correlation in monozygotic than in di- and trizygotic triplets