TABLE 2.
Analysis strategies and details for methods available to estimate total usual intakes inclusive of nutrients from all sources1
| Group Mean Method | Combined method | Stratified method | Hybrid method | |
|---|---|---|---|---|
| Analysis strategy | Add average 24HR food source intake to average DS intake OR Add DS intake to each 24HR food source intake, then average | Adjust nutrient intake distribution from food source first and then add usual DS intake | Adjust nutrient intake distributions separately for DS users and nonusers | For DS users, jointly model food source intake and DS frequency from respective 24HRs, add modeled DS dose to adjusted food source intake; for DS nonusers, just adjust food source intake. |
| DS assessment2 | DS FBQ and/or DS amounts from 24HR | DS FBQ and/or DS amounts from 24HR | DS FBQ and/or DS amounts from 24HR | DS user/nonuser questionnaire, plus DS amounts from 24HR |
| Shrinkage procedure | N/A | Shrink then add OR Add then shrink3 | Shrink then add OR Add then shrink3,4 | Shrink then add |
| Strength | Simplistic | Covariates | Covariates | Covariates |
| Limitations | Cannot be used to assess the population distribution intakes (i.e., < EAR or > UL) | No publicly available implementation Frequency information may not be available to include as a covariate in some data sets | Small sample sizes for DS users or nonusers can lead to highly variable estimates Separate estimation for DS users more likely (but not guaranteed) to meet assumptions | As with stratified model, with added complexity and possible instability of joint modeling Rare to only have information on user compared with nonuser and 24HR Publicly available implementation only for the R software system5 |
124HR, 24 hour dietary recall; DS, dietary supplement; FBQ, frequency-based questionnaire that captures frequency and type of dietary supplements.
2The preferred assessment is always a frequency-based method.
3Depending on sample characteristics.
4Add then shrink should only be used if a covariate is sufficient to reduce the bimodal distribution.
5This method has not been used with the NHANES data.