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000299510 041__ $$aEnglish
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000299510 1001_ $$aWolf, Kathrin$$b0
000299510 245__ $$aEnvironmental exposure assessment in the German National Cohort (NAKO).
000299510 260__ $$aSan Diego, Calif.$$bElsevier$$c2025
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000299510 520__ $$aWe aimed to assess the exposure to multiple environmental indicators and compare the spatial variation across participants of the German National Cohort (NAKO) to lay the foundation for health analyses. We collected highly resolved German-wide data to capture the following environmental drivers: urbanisation by population density; outdoor air pollution by particulate matter (PM2.5), nitrogen dioxide (NO2), ozone; road traffic noise; meteorology by air temperature, relative humidity; and the built environment by greenspace and land cover. All assessed exposures were assigned to the NAKO participants based on their baseline residential addresses. The NAKO study regions ranged from highly urbanised areas (Berlin, Hamburg) to rural regions (Neubrandenburg). This large variation is reflected in the individual environmental exposures at the place of residence. In 2019, annual PM2.5 and NO2 levels ranged from 6.0-14.6 and 3.7-33.6 μg/m3, respectively. Annual mean air temperature ranged between 7.8-12.7 °C. Noise data was available for a subset of urban residents (22 %), of which 42 % fell into the lowest and 1.8 % into the highest category of Lden 55-59 and Lden >75 dB(A), respectively. Greenspace also showed considerable differences (Normalised Difference Vegetation Index between 0.08-0.84). Spearman correlation was moderate to high within the different exposure groups, but mostly low to moderate between the groups. For the first time, a comprehensive population-based dataset with high quality environmental indicators is available for the whole of Germany. Expanding the database by adding innovative indicators such as light pollution, walkability, biodiversity as well as contextual socioeconomic factors will further increase its usefulness for science and public health.
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000299510 650_7 $$2Other$$aEnvironmental epidemiology
000299510 650_7 $$2Other$$aair pollution
000299510 650_7 $$2Other$$agreenspace
000299510 650_7 $$2Other$$anoise
000299510 650_7 $$2Other$$apopulation-based cohort
000299510 650_7 $$2Other$$arisk factors
000299510 650_7 $$2Other$$atemperature
000299510 7001_ $$aDallavalle, Marco$$b1
000299510 7001_ $$aNiedermayer, Fiona$$b2
000299510 7001_ $$aBolte, Gabriele$$b3
000299510 7001_ $$aLakes, Tobia$$b4
000299510 7001_ $$aSchikowski, Tamara$$b5
000299510 7001_ $$0P:(DE-He78)e0ac0d57cdb66d87f2d95ae5f6178c1b$$aGreiser, Karin Halina$$b6$$udkfz
000299510 7001_ $$aSchwettmann, Lars$$b7
000299510 7001_ $$aWesterman, Ronny$$b8
000299510 7001_ $$aNikolaou, Nikolaos$$b9
000299510 7001_ $$aStaab, Jeroen$$b10
000299510 7001_ $$aWolff, Robert$$b11
000299510 7001_ $$aStübs, Gunthard$$b12
000299510 7001_ $$aRach, Stefan$$b13
000299510 7001_ $$aSchneider, Alexandra$$b14
000299510 7001_ $$aPeters, Annette$$b15
000299510 7001_ $$aHoffmann, Barbara$$b16
000299510 773__ $$0PERI:(DE-600)1467489-0$$a10.1016/j.envres.2025.121259$$gVol. 273, p. 121259 -$$p121259$$tEnvironmental research$$v273$$x0013-9351$$y2025
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