Using nationally representative survey data for external adjustment of unmeasured confounders: An example using the NHANES data

Abstract

Purpose: To evaluate the use of data from population-based surveys such as the National Health and Nutrition Examination Survey (NHANES) for external adjustment for confounders imperfectly measured in health care databases in the United States.

Methods: Our example study used Medicaid Analytic eXtract (MAX) data to estimate the relative risk (RR) for prenatal serotonin-norepinephrine reuptake inhibitors (SNRIs) exposure and cardiac defects. Smoking and obesity are known confounders poorly captured in databases. NHANES collects information on lifestyle factors, depression, and prescription medications. External adjustment requires information on the prevalence of confounders and their association with SNRI use; which was obtained from the NHANES. It also requires estimates of their association with the outcome, which were based on the literature and allowed us to correct the RR using sensitivity analyses.

Results: In MAX, the RR for the association between prenatal SNRI exposure and cardiac defects was 1.51 unadjusted and 1.20 adjusted for measured confounders and restricted to women with depression. In NHANES, among women of childbearing age with depression, the prevalence of smoking was 60.2% (95% Confidence Interval 43.2, 74.3) for SNRI users and 44.1% (39.6, 48.8) for nonusers of antidepressants. The corresponding estimates for obesity were 59.2% (43.2, 74.3) and 40.5% (35.9, 45.0), respectively. If the associations between smoking and obesity with cardiac defects are independent from each other and from other measured confounders, additional adjustment for smoking and obesity would move the RR from 1.20 to around 1.10.

Conclusion: National surveys like NHANES are readily available sources of information on potential confounders and they can be used to assess and improve the validity of RR estimates from observational studies missing data on known risk factors.

Keywords: NHANES; bias; confounding; external adjustment; pharmacoepidemiology; sensitivity analyses.

Figure 1.

Deterministic sensitivity analysis for external adjustment of the observed crude relative risk (RR_ED) using NHANES data to estimate the prevalence of confounders in exposed and reference groups. Note: Graphs present the adjustment of the observed RR_ED of 1.51 between SNRIs and cardiac defects overall for smoking (left graph) and obesity (right graph) considering a range of associations between these confounders and the outcome (RR_CD) informed by the literature; using the estimated prevalence of smoking (30.6%) and obesity (36.3%) in the reference group of non-antidepressant users based on NHANES prevalence for women 12–55 on Medicaid; and a plausible range of smoking (50% to 85%) and obesity (40% to 75%) among the SNRIs exposed subjects based on the 95%CIs in table 2. The bolded line in the middle of the grid reflects the most likely prevalence of smoking (65%) and obesity (59%) among exposed based on estimates from NHANES; figure 2 focuses on these estimates.

Figure 2.

Deterministic Sensitivity Analysis for external adjustment of the observed crude (left panel) and adjusted (right panel) relative risk (RR_ED) using the NHANES data to estimate the prevalence of confounders in the exposed and reference groups. Note: The left graph presents the external adjustment of the observed crude RR_ED of 1.51 for obesity considering a range of associations between obesity and the outcome (RR_CD) from 1 to 1.4. It also presents the RR_ED adjusted for both obesity and smoking assuming independence and considering an association between smoking and cardiac defects overall of 1.2 (the upper bound of CI reported in published meta-analyses). For simplicity, only the range for obesity is presented since it is wider (1 to 1.4) than that for smoking (1 to 1.2) based on published meta-analyses. In NHANES, the estimated prevalence among women on Medicaid for smoking and obesity was 30.6% and 36.3% respectively for non-antidepressant users, and 65.0% and 58.7% respectively for SNRI exposed subjects. The right graph presents the corresponding results for the fully adjusted and depression-restricted RR_ED of 1.20 using information from the NHANES sample restricted to women with moderate to severe depression. The estimated prevalence among women with depression for smoking and obesity was 44.1% and 40.5% respectively for non-antidepressant users, and 60.2% and 59.2% respectively for SNRI exposed subjects.