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. 2024 Jan 25;165(7):1505–1512. doi: 10.1097/j.pain.0000000000003155

Table 2.

OLS and spatial regressions of model-based doctor-diagnosed arthritis.

OLS SAC
Coef. S.E. Coef. S.E.
Percent female 0.338*** 0.072 0.198*** 0.057
Percent non-Hispanic Black −0.829*** 0.084 −0.396*** 0.060
Percent non-Hispanic Asian −0.412*** 0.081 −0.175** 0.058
Percent Hispanic −1.578*** 0.088 −0.568*** 0.074
Percent separated or divorced 0.458*** 0.087 0.275*** 0.067
Percent less than high school 0.726*** 0.123 0.221* 0.091
Percent in manual labor occupations −0.132 0.089 −0.067 0.064
Percent in poverty 0.683*** 0.112 0.288** 0.088
Percent unemployed 0.437*** 0.087 0.217*** 0.062
Percent uninsured −0.341** 0.110 −0.188* 0.076
No. of primary care providers −0.050 0.086 −0.182** 0.069
No. of chiropractors −0.722*** 0.085 −0.310*** 0.066
No. of hospitals −0.257*** 0.077 −0.056 0.060
Opioid prescribing rate 0.291*** 0.079 0.125+ 0.064
(Intercept) 26.319*** 0.066 8.888*** 0.729
Rho 0.663***
Lambda§ −0.431***
AIC 11,333 10,929

Level of significance: +P < 0.1, *P < 0.05, **P < 0.01, ***P < 0.001.

The outcomes are model based and age adjusted. All covariates here are standardized.

Rho is the spatial lag parameter, indicating how the prevalence in a focal county is associated with the average prevalence in neighboring counties.

§

Lambda is the spatial error parameter, indicating how the residual/error of a focal county is associated with the average residuals/errors in neighboring counties.

AIC, Akaike information criterion; OLS, ordinary least squares; SAC, spatial autoregressive combined.