Physiographic predictors were latitude, elevation, distance from salt lakes, slope steepness, potential insolation, and topographic convergence.
Explanatory variables included in the model were latitude, normalised difference vegetation index, population density, longitude, rainfall, and temperature, which contributed 24, 22, 17, 15, 14, and 8% to the explanatory power of the model, respectively.
The predictor variable was zone, and covariates were latitude, longitude, and elevation.
The variables considered in the final analysis were latitude, longitude, distance to nearest coastline, annual maximum, mean and range for bottom spring temperature, annual mean, minimum and range for surface spring temperature, and annual mean bottom salinity.
With a prevalence rate of 77.8%, the positive predictive value (PPV) for mortality with a 25(OH D level less than 10 ng/dL was 83.64% and the negative predictive value (NPV) was 29.52%.. Factors that did not significantly differ between stratified groups were latitude, ventilator days and MICU length of stay.
The significance threshold for ranked Bayes factors was set to 2.0 and the environmental variables considered were latitude, longitude, and 19 climate variables current and past based on a model with an interglacial and two LGMs which were transformed to PC scores as described above.
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Elevation is more important in determining the thermal characteristics of the Mexican climate than is latitude.
