Background:Traffic noise affects a large number of people, particularly in urbanized areas. Noise causes stress and annoyance, but less is known about the relationship between noise and depression.Objective:We investigated the association of residential road traffic noise with depressive symptoms using 5-year follow-up data from a German population-based study.Methods:We analyzed data from 3,300 participants in the Heinz Nixdorf Recall study who were between 45 and 75 years old and were without depressive symptoms at baseline (2000–2003). Depressive symptoms were defined based on the Center for Epidemiologic Studies Depression scale (CES-D) 15-item questionnaire (total score ≥ 17) and antidepressant medication intake. Road traffic noise was modeled according to European Parliament/Council Directive 2002/49/EC. High noise exposure was defined as annual mean 24-hr noise levels > 55 A-weighted decibels [dB(A)]. Poisson regression with robust variance was used to estimate relative risks (RRs) a) adjusting for the potential confounders age, sex, socioeconomic status (SES), neighborhood-level SES, and traffic proximity; b) additionally adjusting for body mass index and smoking; and c) additionally adjusting for the potential confounders/intermediates comorbidities and insomnia.Results:Overall, 35.7% of the participants were exposed to high residential road traffic noise levels. At follow-up (mean = 5.1 years after baseline), 302 participants were classified as having high depressive symptoms, corresponding to an adjusted RR of 1.29 (95% CI: 1.03, 1.62; Model 1) for exposure to > 55 versus ≤ 55 dB(A). Adjustment for potential confounders/intermediates did not substantially alter the results. Associations were stronger among those who reported insomnia at baseline (RR = 1.62; 95% CI: 1.10, 2.59 vs. RR = 1.21; 95% CI: 0.94, 1.57) and appeared to be limited to those with ≤ 13 years of education (RR = 1.43; 95% CI: 1.10, 1.85 vs. 0.92; 95% CI: 0.56, 1.53 for > 13 years).Conclusion:Our results suggest that exposure to residential road traffic noise increases the risk of depressive symptoms.Citation:Orban E, McDonald K, Sutcliffe R, Hoffmann B, Fuks KB, Dragano N, Viehmann A, Erbel R, Jöckel KH, Pundt N, Moebus S. 2016. Residential road traffic noise and high depressive symptoms after five years of follow-up: results from the Heinz Nixdorf Recall Study. Environ Health Perspect 124:578–585; http://dx.doi.org/10.1289/ehp.1409400

This study used latent class analysis to classify adolescent home neighborhoods (n=344) according to built environment characteristics, and tested how adolescent physical activity, sedentary behavior, and screen time differ by neighborhood type/class. Four distinct neighborhood classes emerged: 1) low-density retail/transit, low walkability index (WI), further from recreation; 2) high-density retail/transit, high WI, closer to recreation; 3) moderate-high-density retail/transit, moderate WI, further from recreation; and 4) moderate-low-density retail/transit, low WI, closer to recreation. We found no difference in adolescent activity by neighborhood class. These results highlight the difficulty of disentangling the potential effects of the built environment on adolescent physical activity.

Context.-Pituitary adenoma classification is complex, and diagnostic strategies vary greatly from laboratory to laboratory. No optimal diagnostic algorithm has been defined.Objective.-To develop a panel of immunohistochemical (IHC) stains that provides the optimal combination of cost, accuracy, and ease of use.Design.-We examined 136 pituitary adenomas with stains of steroidogenic factor 1 (SF-1), Pit-1, anterior pituitary hormones, cytokeratin CAM5.2, and a subunit of human chorionic gonadotropin. Immunohistochemical staining was scored using the Allred system. Adenomas were assigned to a gold standard class based on IHC results and available clinical and serologic information. Correlation and cluster analyses were used to develop an algorithm for parsimoniously classifying adenomas.Results.-The algorithm entailed a 1-or 2-step process: (1) a screening step consisting of IHC stains for SF-1, Pit-1, and adrenocorticotropic hormone; and (2) when screening IHC pattern and clinical history were not clearly gonadotrophic (SF-1 positive only), corticotrophic (adrenocorticotropic hormone positive only), or IHC null cell (negative-screening IHC), we subsequently used IHC for prolactin, growth hormone, thyroid-stimulating hormone, and cytokeratin CAM5.2.Conclusions.-Comparison between diagnoses generated by our algorithm and the gold standard diagnoses showed excellent agreement. When compared with a commonly used panel using 6 IHC for anterior pituitary hormones plus IHC for a low-molecular-weight cytokeratin in certain tumors, our algorithm uses approximately onethird fewer IHC stains and detects gonadotroph adenomas with greater sensitivity.

There is no evidence of an effect of population density by block size on BMI.

Background: Children living near greenhouse agriculture may have an increased risk of pesticide exposure due to drift or direct contact with pesticide-treated areas. However, little is known about whether this increased potential for chronic exposure may impair their neurodevelopment. Methods:We examined 307 children aged 4-9 years, living in agricultural communities in Ecuador (ESPINA study). The two exposures calculated were residential distance from the nearest flower plantation perimeter and flower plantation surface area within 100m of homes. Five neurobehavioral domains were assessed: Attention/Inhibitory Control, Memory/Learning, Visuospatial processing and Sensorimotor (higher values reflect better performance). Low scores were defined according to the test's cut-offs. Models were adjusted for demographic, socioeconomic and growth variables.

Context.— We previously examined pituitary adenomas with immunohistochemical (IHC) stains for steroidogenic factor 1, Pit-1, anterior pituitary hormones, cytokeratin CAM 5.2, and the α-subunit of human chorionic gonadotropin and found that a screening panel comprising stains for steroidogenic factor 1, Pit-1, and adrenocorticotropic hormone successfully classified most cases and reduced the overall number of stains required. Objectives.— To examine the potential role of IHC stain for T-box transcription factor (Tpit) in the classification of our series of pituitary adenomas and to update our screening panel as necessary. Design.— We collected 157 pituitary adenomas from 2 institutions and included these in tissue microarrays. Immunostains for Tpit were scored in a blinded fashion using the Allred system. Adenomas were assigned to a gold standard class based on IHC pattern followed by application of available clinical and serologic information. Test characteristics were calculated. Correlation analyses, cluster analyses, and classification tree analyses were used to see whether IHC staining patterns reliably reflected adenoma class. Results.— Of the cases collected, 147 (93.6%) had sufficient material for Tpit analysis. IHC stain for Tpit identified 8 null cell adenomas (all nonfunctioning clinically) as silent corticotrophs; Tpit stains showed better sensitivity, specificity, positive predictive value, and negative predictive value than IHC for adrenocorticotropic hormone and cytokeratin CAM 5.2. Correlation analyses continued to show the expected relationships among IHC stains. Cluster analyses showed grouping of adenomas into clinically consistent groups. Classification tree analysis underscored the central role of transcription factor IHC stains, including Tpit, in adenoma classification. Conclusions.— Substitution of Tpit stain for the adrenocorticotropic hormone stain improves our prior algorithm by reducing the number of false-negatives and false-positives. As a result, fewer adenomas are classified as null cell adenoma, and more adenomas are classified as silent corticotroph adenoma.

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Proximity of homes to flower plantations and greater plantation areas within 150 m from homes were associated with higher systolic BP, independent of cholinesterase activity. This suggests that non-cholinesterase inhibitor pesticide drift from agricultural plantations may be sufficient to induce physiologic changes on children living nearby.