In temperature and humidity layers there is also a column with macroclimate (outdoor) data; correlation of data in this column and those of the others is possible and plausible.
Within the indoor and outdoor school microenvironments, correlations among PM10, PM10 2.5, and PM2.5 at each school were strong [ r ≥ 0.80 for most relationships, except with PM10 2.5 in several cases; Supplemental Material, Table 1 (http://dx.doi.org/10.1289/ehp.1003169)].
Spearman correlations between outdoor and indoor Lnight with NO2 were 0.75 and 0.23, respectively.
Correlations among outdoor pollutant levels, as well as those between indoor and outdoor PM2.5 concentrations, were evaluated by non-parametric tests (Spearman correlation coefficient) applied to variables in the original scale.
We previously reported considerable longitudinal correlations between outdoor and personal PM2.5, absorbance (traffic), and S (long-range transport), but correlations were lower for Ca (soil), Cl (salt), and Cu (Janssen et al. 2005).
Correlations among outdoor school pollutant levels also varied, indicating spatiotemporal variability among the pollutants across the study sites [e.g., r = 0.36 0.93 for PM2.5; Supplemental Material, Table 1 (http://dx.doi.org/10.1289/ehp.1003169)].
The correlation between outdoor exposure and the personal exposure to ambient origin pollution is the most relevant correlation, but difficult to assess.
A first investigation on the correlation between outdoor thermal comfort indexes and subjective thermal perception have been conducted.
A 2013 UCLA study published in the BMC Public Health journal found a correlation between outdoor food advertisements and modest increased likelihood of obesity.
Likewise, there was a significant, positive correlation between outdoor hours and mean PAP (r = 0.42, p = 0.0008).
The results showed a statistically significant correlation between outdoor artificial light at night and breast cancer, even when controlling for population density, affluence, and air pollution.
