Dose-response analyses using restricted cubic spline functions in public health research.
Taking into account a continuous exposure in regression models by using categorization, when non-linear dose-response associations are expected, have been widely criticized. As one alternative, restricted cubic spline (RCS) functions are powerful tools (i) to characterize a dose-response association between a continuous exposure and an outcome, (ii) to visually and/or statistically check the assumption of linearity of the association, and (iii) to minimize residual confounding when adjusting for a continuous exposure. Because their implementation with SAS® software is limited, we developed and present here an SAS macro that (i) creates an RCS function of continuous exposures, (ii) displays graphs showing the dose-response association with 95 per cent confidence interval between one main continuous exposure and an outcome when performing linear, logistic, or Cox models, as well as linear and logistic-generalized estimating equations, and (iii) provides statistical tests for overall and non-linear associations. We illustrate the SAS macro using the third National Health and Nutrition Examination Survey data to investigate adjusted dose-response associations (with different models) between calcium intake and bone mineral density (linear regression), folate intake and hyperhomocysteinemia (logistic regression), and serum high-density lipoprotein cholesterol and cardiovascular mortality (Cox model).
Desquilbet
Loic
L
AgroParisTech, UMR 1290 BIOGER-CPP, F-75005 Paris, France. ldesquilbet@vet-alfort.fr
Mariotti
François
F
D015519:Bone Density / Q000187:drug effects; D002136:Calcium, Dietary / Q000008:administration & dosage; D002318:Cardiovascular Diseases / Q000097:blood / Q000401:mortality; D008076:Cholesterol, HDL / Q000097:blood; D003627:Data Interpretation, Statistical; D004305:Dose-Response Relationship, Drug; D005492:Folic Acid / Q000008:administration & dosage; D006801:Humans; D020138:Hyperhomocysteinemia / Q000209:etiology; D016014:Linear Models; D016015:Logistic Models; D009749:Nutrition Surveys / Q000706:statistics & numerical data; D016016:Proportional Hazards Models; D011634:Public Health; D012107:Research Design; D012984:Software
D002136:Calcium, Dietary; D008076:Cholesterol, HDL; D005492:Folic Acid