Characterizing temporal trends in populations exposed to aircraft noise around U.S. airports: 1995-2015.

BACKGROUND: Aircraft noise is a key concern for communities surrounding airports, with increasing evidence for health effects and inequitable distributions of exposure. However, there have been limited national-scale assessments of aircraft noise exposure over time and across noise metrics, limiting evaluation of population exposure patterns. OBJECTIVE: We evaluated national-scale temporal trends in aviation noise exposure by airport characteristics and across racial/ethnic populations in the U.S. METHODS: Noise contours were modeled for 90 U.S. airports in 5-year intervals between 1995 and 2015 using the Federal Aviation Administration's Aviation Environmental Design Tool. We utilized linear fixed effects models to estimate changes in noise exposure areas for day-night average sound levels (DNL) of 45, 65, and a nighttime equivalent sound level (Lnight) of 45 A-weighted decibels (dB[A]). We used group-based trajectory modeling to identify distinct groups of airports sharing underlying characteristics. We overlaid noise contours and Census tract data from the U.S. Census Bureau and American Community Surveys for 2000 to 2015 to estimate exposure changes overall and by race/ethnicity. RESULTS: National-scale analyses showed non-monotonic trends in mean exposed areas that peaked in 2000, followed by a 37% decrease from 2005 to 2010 and a subsequent increase in 2015. We identified four distinct trajectory groups of airports sharing latent characteristics related to size and activity patterns. Those populations identifying as minority (e.g., Hispanic/Latino, Black/African American, Asian) experienced higher proportions of exposure relative to their subgroup populations compared to non-Hispanic or White populations across all years, indicating ethnic and racial disparities in airport noise exposure that persist over time. SIGNIFICANCE: Overall, these data identified differential exposure trends across airports and subpopulations, helping to identify vulnerable communities for aviation noise in the U.S. IMPACT STATEMENT: We conducted a descriptive analysis of temporal trends in aviation noise exposure in the U.S. at a national level. Using data from 90 U.S. airports over a span of two decades, we characterized the noise exposure trends overall and by airport characteristics, while estimating the numbers of exposed by population demographics to help identify the impact on vulnerable communities who may bear the burden of aircraft noise exposure.

Self-rated health and its association with perceived environmental hazards, the social environment, and cultural stressors in an environmental justice population.

BACKGROUND: Communities with large minority populations often are located near sources of pollution and have higher crime rates, which may work in combination with other factors to influence health. Poor self-rated health is related to chronic health conditions and premature mortality, with minority populations most likely to report poor health. To address how both resident perception of neighborhood environments and chronic health conditions individually and collectively influence health, we examined self-rated health and its association with multiple types of perceived environmental hazards in a majority-Hispanic urban population. METHODS: We conducted interviews with 354 residents of Chelsea, Massachusetts, US and asked about self-rated health, perceptions of their neighborhood, including participant-reported environmental hazards (e.g., air quality, odors and noise), aspects of the social environment (e.g., feeling safe, neighborhood crime, social cohesion), and culture-related stressors (e.g., immigration status, language stress, ethnic identity). Log-linear models examined the independent and multivariable associations between these factors and fair/poor self-rated health, controlling for socio-demographic characteristics and preexisting health conditions. RESULTS: Forty-one percent of participants reported fair/poor self-rated health. Participants frequently perceived environmental hazards such as problems with pests and regular noise disturbance as well as feeling unsafe. In a multivariable model, a greater number of reported noise disturbances (≥ 2 noise sources = 1.53 [1.04-2.26]) and reported insecurity with immigration status (1.66 [1.01-2.73]) were positively associated with fair/poor self-rated health. High social cohesion was inversely associated (0.74 [0.48-1.14]) with fair/poor self-rated health in the multivariable model. CONCLUSIONS: Negative perceptions of environmental hazards and reported cultural stressors were significantly associated with fair/poor self-rated health among residents in a low-income majority-minority community, with social cohesion having a beneficial association with self-rated health. Efforts to improve health should recognize the importance of public perceptions of social and environmental hazards found in neighborhood environments, and benefits of strengthening community connections.

Community-wide health risk assessment using geographically resolved demographic data: a synthetic population approach.

BACKGROUND: Evaluating environmental health risks in communities requires models characterizing geographic and demographic patterns of exposure to multiple stressors. These exposure models can be constructed from multivariable regression analyses using individual-level predictors (microdata), but these microdata are not typically available with sufficient geographic resolution for community risk analyses given privacy concerns. METHODS: We developed synthetic geographically-resolved microdata for a low-income community (New Bedford, Massachusetts) facing multiple environmental stressors. We first applied probabilistic reweighting using simulated annealing to data from the 2006-2010 American Community Survey, combining 9,135 microdata samples from the New Bedford area with census tract-level constraints for individual and household characteristics. We then evaluated the synthetic microdata using goodness-of-fit tests and by examining spatial patterns of microdata fields not used as constraints. As a demonstration, we developed a multivariable regression model predicting smoking behavior as a function of individual-level microdata fields using New Bedford-specific data from the 2006-2010 Behavioral Risk Factor Surveillance System, linking this model with the synthetic microdata to predict demographic and geographic smoking patterns in New Bedford. RESULTS: Our simulation produced microdata representing all 94,944 individuals living in New Bedford in 2006-2010. Variables in the synthetic population matched the constraints well at the census tract level (e.g., ancestry, gender, age, education, household income) and reproduced the census-derived spatial patterns of non-constraint microdata. Smoking in New Bedford was significantly associated with numerous demographic variables found in the microdata, with estimated tract-level smoking rates varying from 20% (95% CI: 17%, 22%) to 37% (95% CI: 30%, 45%). CONCLUSIONS: We used simulation methods to create geographically-resolved individual-level microdata that can be used in community-wide exposure and risk assessment studies. This approach provides insights regarding community-scale exposure and vulnerability patterns, valuable in settings where policy can be informed by characterization of multi-stressor exposures and health risks at high resolution.

Childhood and adult socioeconomic position, cumulative lead levels, and pessimism in later life: the VA Normative Aging Study.

Pessimism, a general tendency toward negative expectancies, is a risk factor for depression and also heart disease, stroke, and reduced cancer survival. There is evidence that individuals with higher lead exposure have poorer health. However, low socioeconomic status (SES) is linked with higher lead levels and greater pessimism, and it is unclear whether lead influences psychological functioning independently of other social factors. The authors considered interrelations among childhood and adult SES, lead levels, and psychological functioning in data collected on 412 Boston area men between 1991 and 2002 in a subgroup of the VA Normative Aging Study. Pessimism was measured by using the Life Orientation Test. Cumulative (tibia) lead was measured by x-ray fluorescence. Structural equation modeling was used to quantify the relations as mediated by childhood and adult SES, controlling for age, health behaviors, and health status. An interquartile range increase in lead quartile was associated with a 0.37 increase in pessimism score (P < 0.05). Low childhood and adult SES were related to higher tibia lead levels, and both were also independently associated with higher pessimism. Lead maintained an independent association with pessimism even after childhood and adult SES were considered. Results demonstrate an interrelated role of lead burden and SES over the life course in relation to psychological functioning in older age.

A community-based participatory research study of multifaceted in-home environmental interventions for pediatric asthmatics in public housing.

Pest infestation is a major problem in urban, low-income housing and may contribute to elevated asthma prevalence and exacerbation rates in such communities. However, there is poor understanding of the effectiveness of integrated pest management (IPM) efforts in controlling pediatric asthma, or of the interactions among various interventions and risk factors in these settings. As part of the Boston-based Healthy Public Housing Initiative, we conducted a longitudinal, single-cohort community-based participatory research intervention study. Fifty asthmatic children aged 4-17 from three public housing developments in Boston, Massachusetts, USA successfully completed interventions and detailed environmental, medical, social, and health outcome data collection. Interventions primarily consisted of IPM and related cleaning and educational efforts, but also included limited case management and support from trained community health advocates. In pre-post analyses, we found significant reductions in a 2-week recall respiratory symptom score (from 2.6 to 1.5 on an 8-point scale, p = 0.0002) and in the frequency of wheeze/cough, slowing down or stopping play, and waking at night. Longitudinal analyses of asthma-related quality of life similarly document significant improvements, with a suggestion of some improvements prior to environmental interventions with an increased rate of improvement subsequent to pest management activities. Analyses of potential explanatory factors demonstrated significant between-development differences in symptom improvements and suggested some potential contributions of allergen reductions, increased peak flow meter usage, and improved social support, but not medication changes. In spite of limitations with pre-post comparisons, our results are consistent with aggressive pest management and other allergen reduction efforts having a positive impact on clinical health outcomes associated with asthma. Our findings reinforce the multifactorial nature of urban asthma and suggest a need for further study of the relative contributions of and possible synergies between environmental and social factors in asthma intervention programs.