Our novel combination of temporal and spatial scales was the best overall model fit for most variables, including SRP where this model explained 54% of the variation.
Results indicated the effects of seasons and turf grass types and their interaction had significant effects on most variables including quality, season color, leaf texture, density, quality after clipping (p < 0.01).
When subjected to the more rigorous multivariate analysis, most variables – including age – fell out of statistical significance (Table 2), a phenomenon seen in many other geriatric studies.
In many administrative data-based studies, most variables, including primary outcomes, are based on the International Classification of Diseases (ICD), clinical modification codes (ICD-9 or ICD-10).
Finally, although most variables, including those for abortion legislation, showed significant correlations with maternal mortality outcomes in Mexico, this study emphasises the importance of multivariate analyses correcting for multicollinearity between covariates and the presence of outliers on mortality outcomes.
After we dichotomized cardiometabolic risk factors (see Table 1 for thresholds), we found that the proportions of children and youth with cardiometabolic risk factors were higher in the SO group compared to the OW/OB group for most variables, including WC, TG, HDL-C, ALT, HOMA-IR, SBP and DBP (see Figure 1).
