Results The 71 271 eligible women were aged between 57 and 85 years (mean 70 years) at the time of assessment of anxiety symptoms, with a prevalence of high anxiety symptoms of 15%. Exposure to particulate matter was characterized using estimated average exposure to particulate matter <2.5 μm in diameter (PM 2.5 ) and 2.5 to 10 μm in diameter (PM 2.5-10 ) in the one month, three months, six months, one year, and 15 years prior to assessment of anxiety symptoms, and residential distance to the nearest major road two years prior to assessment. Significantly increased odds of high anxiety symptoms were observed with higher exposure to PM 2.5 for multiple averaging periods (for example, odds ratio per 10 µg/m 3 increase in prior one month average PM 2.5 : 1.12, 95% confidence interval 1.06 to 1.19; in prior 12 month average PM 2.5 : 1.15, 1.06 to 1.26). Models including multiple exposure windows suggested short term averaging periods were more relevant than long term averaging periods. There was no association between anxiety and exposure to PM 2.5-10 . Residential proximity to major roads was not related to anxiety symptoms in a dose dependent manner.

The most biologically relevant period of exposure is currently unknown. If particulate matter induces anxiety through chronic oxidative stress, inflammation, or induction of chronic disease, long term cumulative exposure is most likely relevant. If particulate matter aggravates an existing propensity for anxiety symptoms, through either aggravation of chronic disease or transient changes in oxidative stress or inflammation, exposures closer to the time of symptom assessment may be relevant. Therefore, we considered the association between high anxiety symptoms and exposure to particulate matter averaged over five periods prior to the assessment of anxiety symptoms, specified a priori, ranging from a measure of long term, cumulative exposure (prior 15 years) to a measure of recent exposure (prior month).

Given the substantial personal and societal burden from anxiety and the problem of treatment resistance, it is imperative to identify modifiable risk factors for anxiety disorders and symptoms. One important environmental exposure that may be related to anxiety is air pollution. Specifically, exposure to particulate matter air pollution may induce or exacerbate anxiety through increased oxidative stress and systemic inflammation 9 10 11 12 13 14 15 16 17 or through promotion or aggravation of chronic disease. 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 Though there is a small set of studies considering the association between air pollution and mental health outcomes, 33 34 35 36 37 38 39 40 41 42 43 44 we are aware of only two small studies that considered anxiety, and neither looked at total particulate matter. The first (n=1002) reported that ozone levels in the prior week were associated with anxiety symptoms, 33 whereas the second (n=100) reported that cumulative exposure to airborne manganese was associated with anxiety symptoms. 44 Epidemiologic research on the relation between exposure to particulate matter and anxiety is clearly lacking; we evaluated this association in a large prospective cohort study. Specifically, we hypothesized that higher exposure to particulate matter would be associated with a greater risk of high symptoms of anxiety.

Anxiety disorders, characterized by disruptive fear, worry, and related behavioral disturbances such as avoidance or physical sensations of hyperarousal, 1 are the most common type of psychiatric disorder in the general population. 2 Globally, approximately 16% of people will have an anxiety disorder in their lifetime and 11% will have experienced an anxiety disorder in the past year. 2 Anxiety disorders are associated with reduced productivity and increased psychiatric and non-psychiatric medical care, absenteeism, and risk of suicide. 3 In 2010, anxiety disorders accounted for approximately 26.8 million disability adjusted life years worldwide. 4 The monetary cost of anxiety disorders is also substantial; in the United States, the annual direct cost of anxiety disorders in the 1990s has been estimated to be $42.3bn (£27.3bn; €37.3bn). 5 Women have a higher prevalence of anxiety disorders than men 6 and the onset for most anxiety disorders is commonly in adolescence or young adulthood. However, the incidence of anxiety disorders remains substantial in midlife, and new cases continue to arise into later life, especially in the case of generalized anxiety disorder. 7 Although numerous pharmacologic and non-pharmacologic therapies are available, remission is not always possible. Many people have persistent symptoms despite use of first line treatments. 8

Methods

Study population The Nurses’ Health Study is a prospective cohort study of women that began in 1976. A total of 121 701 married registered nurses, ages 30-55, residing in 11 states, were originally enrolled; at least 10 participants now reside in each of the 48 continental states. All participants are mailed follow-up questionnaires every two years, with a response rate of greater than 90% for each questionnaire.45 As such, we receive updated information on residential address biennially, and we have geocoded all home addresses 1986 to 2007 within the contiguous United States to obtain latitude and longitude, allowing estimation of exposure to particulate air pollution. The Crown-Crisp index phobic anxiety scale, one of six scales from the Crown-Crisp experiential index, is a measure of anxiety symptom levels and was included in the 1988 and 2004 questionnaires. As our exposure data were available from 1988 onward (inclusive), we used data from the 2004 Crown-Crisp index phobic anxiety scale as our outcome measure of anxiety. The nurses’ provided implied informed consent by completion and return of each questionnaire.

Residential proximity to roadways Using geographic information software (ArcGIS, Version 10.2; Esri, CA), we computed distance from the residential address of each participant in 2002, up to 500 m, with a street level geocoding match to the nearest US census feature class code A1 (limited access to primary roads with defined exits and divided directions of travel, that is, interstate highways), A2 (primary major, non-interstate highways and major roads without access restrictions), or A3 (smaller, secondary roads, typically with more than two lanes) road segment. Distance to a major road is a commonly used proxy for traffic related exposures, including traffic related air pollution (which typically contains a high proportion of ultrafine particles, those <0.1 μm in diameter).46 47 48 We classified distance to the nearest major road a priori as <50 m, 50 to <200 m, or ≥200 m, based on the observed pattern of particulate concentrations with increasing distance47 48 49 and the distribution of roadway proximity in our sample.

Particulate matter air pollution We used spatiotemporal prediction models yielding monthly estimates of exposure to particulate matter <10 μm (PM 10 ) and <2.5 μm (PM 2.5 or fine particulate matter) in aerodynamic diameter from January 1988 onward at the residential address with at least a zip code level geocoding match for each participant to derive multiple exposure metrics for each participant. These models cover the contiguous United States and are extensions of previously described models covering a more limited area.50 51 52 Data used in these models included nationwide monitor data, geographic data (for example, distance to major roadway, population density, elevation, proportion of urban land use, point or area source emissions), and meteorological data (for example, temperature, wind speed, precipitation, barometric pressure). As nationwide PM 2.5 monitor data were unavailable prior to 1999, our pre-1999 estimates of PM 2.5 exposure were derived from a model that estimates the predicted ratio of PM 2.5 to PM 10 between 1988 and 1999; to get PM 2.5 predictions we combined the results of this model with estimates from the PM 10 model. We derived estimates of exposure to coarse (PM 2.5-10 ) particulate matter by taking the difference between PM 10 and PM 2.5 estimates. For the current analyses we used these models to derive measures of average exposure to PM 2.5 and PM 2.5-10 , at the residential address of each participant for several exposure periods, including the average exposure between 1 January 1988 and 31 December 2003, and over the 1, 3, 6, and 12 calendar months prior to the participant’s 2004 questionnaire cycle return date (that is, for a questionnaire returned in July 2004, we use the average exposure in June 2004 for the one month averaging period).

Anxiety symptoms The Crown-Crisp index phobic anxiety scale consists of eight self rated questions about fearfulness and desire for avoidance of common situations or environments (that is, having “unreasonable fear of enclosed spaces”, being “scared of heights”, disliking “going out alone”, feeling “panicky in crowds”, feeling “more relaxed indoors”, feeling “uneasy traveling on buses or trains”) and tendency to worry (that is, “about getting some incurable illness”, worrying “unduly when relatives are late coming home”); total possible index scores range from 0-16 points, with higher scores indicating more anxiety.53 We required complete data on all eight items to compute a total score. The Crown-Crisp index phobic anxiety scale has been shown to differentiate between people with general anxiety or phobias from those with other psychiatric conditions and healthy comparison participants53 54 and has been used in population based research.55 56 57 58 59 60 61 For primary analyses, we dichotomized Crown-Crisp index phobic anxiety scale scores from 2004 and considered those with a score of 6 points or more to have high symptoms of anxiety, as prior work suggests that this cut-off represents a clinically important threshold.58 61

Covariates Covariates included in all models were selected a priori because they were thought to be potential confounders or proxies for potential confounders (for example, socioeconomic status) and include calendar month of questionnaire return (categorical month), educational attainment (RN, BA, MA, or PhD), husband’s educational attainment (≤12 years, 12-16 years, >16 years, not applicable, missing), age, age squared, married or has a partner (yes/no), employment status (yes/no), physical activity (<12, 12 to 30, >30 metabolic equivalent task hours per week), three residential census tract level characteristics (percent white race/ethnicity, percent of adults without a high school diploma, and median home value; in fourths), region of residence (north east, south, midwest, west), residence within a metropolitan statistical area (yes/no), and social support62 (low, low-medium, medium, high social networks). Many covariates were assessed at multiple cycles; we used the value at the 1988 or closest available questionnaire when considering the 1988-2003 averaging period and the 2002 or closest available questionnaire in models considering roadway proximity or particulate matter exposures within the year prior to the 2004 questionnaire return. With the exception of month of questionnaire return, we used missing indicators when covariate data were missing for more than 2% of our sample and replaced missing data with median or mode values when covariate data were missing in less than 2% of our sample.

Primary analysis For each model we restricted our analytical sample to people with 2004 Crown-Crisp index phobic anxiety scale scores and relevant exposure data. We used separate logistic regression models to estimate the association between each exposure and high anxiety symptoms (Crown-Crisp index phobic anxiety scale score ≥6). For models considering exposure to particulate matter, we evaluated the shape of the dose-response curve using penalized splines and report analyses using both fifths of exposure and linear terms. As exposures to particulate matter are correlated across averaging periods (see supplementary table e1), it is challenging to determine which exposure periods are most relevant when multiple periods appear associated with anxiety. Therefore, we also considered mutually adjusted models including either 1988-2003 and past one month or past 12 month and past one month exposures to particulate matter parameterized using penalized splines to tackle whether long term or short term exposures were more relevant when we observed an association between anxiety and multiple averaging periods. To avoid the potential for differences in the variability of metrics for exposure to particulate matter across the two averaging periods to influence the findings, we used z score transformations of each of the particulate matter exposures (that is, one month, 12 months, and 1988-2003) in the mutually adjusted models.

Sensitivity analyses We conducted several sensitivity analyses to examine the robustness of our primary findings, including use of alternate categorizations for roadway proximity (<50 m, 50-200 m, and >200 m from A1 or A2 roadways; <100 m, 100-300 m, and >300 m from either A1, A2, or A3 roadways or A1 or A2 only roadways; and as a continuous variable for distance from A1, A2, or A3 roadways using a linear or spline parameterization within the range of 0 to 500 m); additional adjustment for individual level covariates often correlated with anxiety symptoms but which were not expected to be confounders, including physical functioning63 (high, low), self rated health (excellent or very good, poor to average), number of major medical comorbidities (≥3, <3), alcohol consumption (non-drinker, <3, 3-6, >7 alcoholic drinks per week), body mass index (normal, overweight, obese), and smoking status (never, former, current); restriction to non-movers (to reduce misclassification of exposure measures given some participants changed addresses but exact move dates are unknown); restriction to those who returned the questionnaire within three months of the initial mailing (to reduce misclassification of short term exposure measures, which are based on the return date for the questionnaire); restriction to those living in a metropolitan area, defined using rural-urban commuting codes64 (to reduce potential confounding by urban versus rural environments); restriction to non-Hispanic white participants (96.7% of the sample, to allay concerns about confounding by race); use of negative binomial regression, which considers Crown-Crisp index phobic anxiety scale scores as count data and is similar to, but more appropriate and generally more conservative than Poisson regression when dealing with over-dispersed count data; and use of an alternate case definition with improved sensitivity but less specificity where we considered all people with a Crown-Crisp index phobic anxiety scale score of 6 or more and/or self report of use of anti-anxiety or antidepressant medications on the 2004 questionnaire to have high anxiety symptoms.