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    <title>Exposome | Ian Buller, PhD, MA</title>
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    <description>Exposome</description>
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      <title>Exposome</title>
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      <title>New Publication in Environmental Research</title>
      <link>https://idblr.rbind.io/post/environres-2026/</link>
      <pubDate>Sat, 30 May 2026 00:00:00 +0000</pubDate>
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      <description>&lt;p&gt;I co-authored an article in 
&lt;a href=&#34;https://www.sciencedirect.com/journal/environmental-research&#34; target=&#34;_blank&#34; rel=&#34;noopener&#34;&gt;&lt;em&gt;Environmental Research&lt;/em&gt;&lt;/a&gt; entitled 
&lt;a href=&#34;https://doi.org/10.1016/j.envres.2026.124912&#34; target=&#34;_blank&#34; rel=&#34;noopener&#34;&gt;&amp;ldquo;Revisiting the modifiable areal unit problem in the era of exposome-wide association studies: Assessing the performance of the CDC/ATSDR Social Vulnerability Index at privacy-protecting spatial scales&amp;rdquo;&lt;/a&gt; led by 
&lt;a href=&#34;https://orcid.org/0009-0008-0025-7435&#34; target=&#34;_blank&#34; rel=&#34;noopener&#34;&gt;Jonathan Lewis&lt;/a&gt;.&lt;/p&gt;
&lt;p&gt;We assessed the impact of the 
&lt;a href=&#34;https://doi.org/10.1016/B978-0-08-102295-5.10406-8&#34; target=&#34;_blank&#34; rel=&#34;noopener&#34;&gt;modifiable areal unit problem&lt;/a&gt; in the context of exposome-wide association study (ExWAS) designs with a simulation and case study using the 
&lt;a href=&#34;https://www.atsdr.cdc.gov/place-health/php/svi/index.html&#34; target=&#34;_blank&#34; rel=&#34;noopener&#34;&gt;Social Vulnerability Index&lt;/a&gt; from the 
&lt;a href=&#34;https://www.cdc.gov&#34; target=&#34;_blank&#34; rel=&#34;noopener&#34;&gt;U.S. Centers for Disease Control and Prevention&lt;/a&gt; (CDC) and the 
&lt;a href=&#34;https://www.niehs.nih.gov/research/atniehs/labs/crb/studies/pegs&#34; target=&#34;_blank&#34; rel=&#34;noopener&#34;&gt;Personalized Environment and Genes Study&lt;/a&gt; (PEGS).&lt;/p&gt;
&lt;p&gt;With coarser spatial aggregation (e.g., 
&lt;a href=&#34;https://www.census.gov&#34; target=&#34;_blank&#34; rel=&#34;noopener&#34;&gt;U.S. Census Bureau&lt;/a&gt; census tracts vs. counties), models lost precision, empirical coverage decreased, model estimates were more biased, and statistical power was reduced. Investigators must weigh the trade-offs between epidemiologic efficacy and protect privacy when choosing the geospatial resolution of the analysis.&lt;/p&gt;</description>
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