Using National Health and Nutrition Examination Survey (NHANES) Dietary Supplement Data Centers for Disease Control and Prevention National Center for Health Statistics Jaime Wilger

Sponsor Office of Dietary Supplements National Institutes of Health Bethesda, Maryland US

The collection of data on dietary supplement use is financially supported by the NIH's Office of Dietary Supplements. This includes supporting the huge amount of labor necessary to get all the label information from manufacturers of the dietary supplements reported in NHANES and converting that information into public use files that can be used to analyze dietary supplement use in the United States. Additionally, the Office of Dietary Supplements supports the collection and analysis of numerous nutritional biochemistries in the Laboratory component of NHANES. Office of Dietary Supplements

NHANES Civilian, non-institutionalized household population Residents of the 50 States and District of Columbia All ages A nationally representative sample of about 5,000 individuals each year

NHANES Oversamples( ): African Americans Mexican Americans Adolescents aged Older persons aged 60+ Pregnant women

What Dietary Supplements are Americans Taking? NHANES is working on answering this question by: –Collecting dietary supplements data from participants –Compiling a Dietary Supplement LABEL database

Dietary Supplements Flowchart h i Household interviews Field Office/WESTAT NCHS Reported supplement labels are found in our internal database, requested from manufacturers/distributors, or found on internet. Dietary Supplement data released to public NHANES website

Supplement Use SurveyTotal MenWomen NHANES I ‘71-73 (no ref time)33%28%38% NHANES II ‘76-80 (no ref time)35%32%43% NHANES III ‘88-94 (30 days)36%48% NHIS 1986 (2 weeks)36% NHIS 1987 (past year)51% NHIS 1992 (past year)46% CSFII ’94-96 (no ref time)42%56% NHANES ’99-00 (30 days)52%47%57% NHANES ’99-02 combined (30 days) adults %45%57% 51%

Household Interview Interviewers ask participants about their use of dietary supplements and also about their use of antacids. “Have you used or taken any vitamins, minerals, herbals or other dietary supplements in the past 30 days? Include prescription and non-prescription supplements.”

Supplement Containers If participant says that they have taken a dietary supplement then interviewer asks to see all supplement containers. –Containers are seen 88% of the time –It is very important that containers are seen so that supplement names can be recorded accurately and completely.

TRIAL SIZE PLUS IRON Complete WITH ESSENTIAL MINERALS Complete

Product Usage Questions For how long have you been taking the product or a similar type of product? In the past 30 days, how many days did you take the product? On the days that you took the product, how much did you usually take on a single day?

How do we find the actual supplement label that was reported by participants? NCHS nutritionists review supplement names recorded by interviewers Match reported supplement with supplement in our dietary supplement database. If supplement is not in our database we obtain the product label. Matches are made with varying degrees of precision.

Obtaining Supplement Label Data If we do not have the supplement label already in our database, or the label information is outdated we obtain the label by: –Contacting manufacturers and distributors –Company websites –Other internet sources –Physicians Desk Reference

Matching Supplements 1.Exact or near exact match of name; 2.Close match; name not identical to one in database, but no other reasonable option exists. 3.Generic match; supplement has known strength for all ingredients, either as part of name (e.g. vitamin C 500mg) or because the manufacturer is known and we have an identical supplement made by this manufacturer for a different distributor or retailer.

Matching Supplements, cont. 4.Entered name could identify two or more supplements; the supplement name may be incomplete or could be complete but other supplements of this brand also start with these same words. 5.Default match; exact supplement could not be obtained because the name was imprecise or the exact brand supplement could not be located. 6.No match; no supplement could be found and not enough detail existed for a generic or default match to be made.

Create Generic Products Generic supplements: all supplement ingredients and amounts known. Example: –Single or dual ingredient calcium 600mg; calcium vitamin D 200 IU

Create default products When or if an exact supplement could not be obtained because the name was imprecise or the exact brand supplement could not be located. Based upon: –the most commonly reported strengths for single ingredients and most commonly reported brands for major multiple ingredient supplements such as multivitamins and multivitamins/minerals; Example: –Multivitamin/Multimineral >> Centrum Advance Formula High Potency Multivitamin Multimineral with Lycopene

What Information do we enter into our Dietary Supplement Database? –Supplement name –Source of information (manufacturer, distributor, and other references such as the Internet and PDR. –Product type (infant/pediatric, prenatal, geriatric, standard) –Ingredient and dosage information –Manufacturer and Distributor information –Contact information

What is entered from the label?

Update Supplement Information We periodically obtain new labels for products and compare it to the label in our internal dietary supplement database to look for any changes in: –Ingredients; –ingredient amounts; –Name of supplement. If a product has changed, the date it was changed is requested from the manufacturer.

Data Release We release supplement information from our dietary supplement database as well as participant information collected during the interview. Data is released in 2 year cycles.

Uses for Dietary Supplement Data 1.How to determine the prevalence of dietary supplement user. 2. How to estimate total calcium intake from both the dietary supplements and Dietary Interview (total Nutrient Intake) data.

EXAMPLE 1 1.Determine prevalence of dietary supplement use. A.Navigating the website B.Download data C.Merge files D.Append different cycle years ( AND DATA) E.Merge demographic data – which also includes weight variables, design variables F.Use SAS callable SUDAAN to analyze data

A. Navigating the Website

NHANES Data Files Questionnaire files: data collected through household interview and mobile examination center (MEC) interview Examination files: information collected through physical exams, dental exams, and dietary interview components (Note: not every survey participant agreed to a physical examination) Laboratory files: results from analyses of blood, urine, hair, air, tuberculosis skin test, and household dust and water specimens Demographics files: survey design (e.g. weights, design strata) and demographic variables

A. Navigating the Website

B. Downloading Data

LIBNAME DSQ_BXP XPORT "C:\NHANES\DSQ_B.XPT"; LIBNAME DSQ_B "C:\NHANES\DSQ_B"; PROC COPY IN= DSQ_BXP OUT= DSQ_B ; RUN; Extract Data and Save as SAS Dataset The second line of the program assigns a library name (DSQ_B) to the permanent data file. proc copy : to copy your data from the transport file to the permanent data file. The in statement refers to the directory containing the SAS transport file to be copied. The out statement refers to the SAS library (directory) into which the permanent SAS file will be stored. The first line of the program assigns a library name (DSQ_BXP) to the SAS transport file you downloaded

File 1: Supplement Counts Variable NameLabel SEQNRespondent sequence number? DSD010Any dietary supplements taken? DSDCOUNTTotal # of dietary supplements taken Named DSQ1_B in the Data and DSQfile1 in the data

Flie 2: Supplement Records Variable NameLabel SEQNRespondent sequence number DSDSUPIDSupplement ID number DSDSUPPSupplement name DSD070Was container seen? DSDMTCHMatching code DSD090How long supplement taken (day)? DSD103Days supplement taken, past 30 days DSD122QQuantity of supplement taken per day DSD122UDosage form DSDANTAAntacid reported as a dietary supplement Named DSQ2_B in the data and DSQfile2 in the data

File 3: Supplement Information Variable NameLabel DSDSUPIDSupplement ID number DSDSUPPSupplement name DSDSRCESupplement information source DSDTYPEFormulation type DSDSERVQServing size quantity DSDSERVUServing size unit DSDSERVAAlternative serving size DSDCNTVCount of vitamins in the supplement DSDCNTMCount of minerals in the supplement DSDCNTACount of amino acids in the supplement DSDCNTBCount of botanicals in the supplement DSDCNTOCount of other ingredients in the supplement Named DSQ3_B in the data and DSQfile3 in the data

File 4: Ingredient Information Variable NameLabel DSDSUPIDSupplement ID number DSDSUPPSupplement name DSDINGIDIngredient ID DSDINGRIngredient name DSDOPERIngredient operator(,=) DSDQTYIngredient quantity DSDUNITIngredient unit DSDCATIngredient category DSDBLFLGBlend flag Named DSQ4_B in the data and DSQfile4 in the data

File 5: Supplement Blend Variable NameLabel DSDINGIDIngredient ID number DSDINGRIngredient name DSDBCIDBlend component ID DSDBCNAMBlend component name DSDBCCATBlend component category Named DSQ5_B in the data and DSQfile5 in the data

File 1: Supplement Counts Respondent sequence number (SEQN) Any dietary supplements taken? (DSD010) Total # of dietary supplements taken? (DSDCOUNT) File 2: Supplement Records SEQN Supplement ID (DSDSUPID) Supplement name (DSDSUPP) Was Container Seen? (DSD070) Matching code (DSDMTCH) How long supplement taken (days)? (DSD090) Day supplement taken, past 30 days (DSD103) Quantity of supplement taken per day (DSD122Q) Dosage form (DSD122U) Antacid reported as dietary supplement (DSDANTA) File 3: Supplement information DSDSUPID DSDSUPP Supplement information source (DSDSRCE) Formulation type (DSDTYPE) Serving size quantity (DSDSERVQ) Serving size unit (DSDSERVU) Alternative serving size (DSDSERVA) Count of vitamins in the supplement (DSDCNTV) Count of minerals in the supplement (DSDCNTM) Count of amino acids in the supplement (DSDCNTA) Count of botanicals in the supplement (DSDCNTB) Count of other ingredients in the supplement (DSDCNTO) File 4: Ingredient information DSDSUPID DSDSUPP Ingredient ID (DSDINGID) Ingredient Name (DSDINGR) Ingredient operator (DSDOPER) Ingredient Quantity (DSDQTY) Ingredient Unit (DSDUNIT) Ingredient category (DSDCAT) Blend Flag (DSDBLFLG) File 5: Supplement blend DSDINGID DSDINGR Blend component ID (DSDBCID) Blend component name (DSDBCNAM) Blend component category (DSDBCCAT) File 4: Ingredient information DSDSUPID DSDSUPP Ingredient ID (DSDINGID) Ingredient Name (DSDINGR) Ingredient operator (DSDOPER) Ingredient Quantity (DSDQTY) Ingredient Unit (DSDUNIT) Ingredient category (DSDCAT) Blend Flag (DSDBLFLG) DSDSUPID SEQN DSDINGID DSDSUPID Data File Structure and Relationships

SEQNDSD010DSDCOUNT 101 (Steve)1 (Yes)2 102 (Mary)2 (No)0 File 1 SEQNDSDSUPIDDSDSUPPDSD (Steve) Calcium 600 mg + Vitamin D 200 IU 1 (Yes) 101 (Steve) Brand X Fat Reducer 1 (Yes) DSDSUPIDDSDSUPPDSDCNTVDSDCNTMDSDCNTBDSDCNTADSDCNTO Calcium 600 mg + Vitamin D 200 IU Brand X Fat Reducer File 2 File 3 Indicates if any dietary supplements were taken Indicates the number of dietary supplements taken Supplement ID Supplement Name Indicates whether or not container was seen The counts of vitamins, minerals, botanicals, amino acids, and other ingredients in each supplement

DSDSUPIDDSDSUPPDSDINGIDDSDINGRDSDQTYDSDUNITDSDCATDSDBLFLG Calcium 600 mg + Vitamin D 200 IU Calcium (MG)Mineral2 (Not a Blend) Calcium 600 mg + Vitamin D 200 IU Vitamin D (IU)Vitamin2 (Not a Blend) Brand X Fat Reducer Chitozyme (MG)Other1 (BLEND) DSDINGIDDSDINGRDSDBCIDDSDBCNAMDSDSBCCAT Chitozyme Psyllium Seed Husks Botanical Chitozyme ChitosanOther File 4 File 5 Ingredient ID Ingredient Name Ingredient Quantity and Unit Indicates if there is a blend in the supplement Ingredient Category Blend ingredient ID, name, category

C. Program – Merging files */Sorting File 1 and File 2 in the data by the respondent number*/ PROC SORT DATA = DSQ_B.DSQ1_b; BY SEQN; RUN; PROC SORT DATA = DSQ_B.DSQ2_B; BY SEQN; RUN; */Merging File 1 and File 2 in the data by the respondent number*/ DATA F1_2; MERGE DSQ_B.DSQ1_b DSQ_B.DSQ2_B; BY SEQN; RUN; SORT File 1 and File 2 by SEQN MERGE File 1 and File 2 by SEQN

C. Program – Merging files */Sorting F1_2 and File 3 in the data by the Supplement ID number*/ PROC SORT DATA = F1_2; BY DSDSUPID; RUN; PROC SORT DATA = DSQ_B.DSQ3_B; (File 3 in the data) BY DSDSUPID; RUN; */Merging F1_2 and File 3 in the data by the Supplement ID number */ DATA F1_3; MERGE F1_2 DSQ_B.DSQ3_B; BY DSDSUPID; RUN; */Sorting F1_3 and File 4 in the data by the Supplement ID number*/ PROC SORT DATA = DSQ_B.DSQ4_B; (File 4 in the data) BY DSDSUPID; RUN; */Merging F1_3 and File 4 in the data by the Supplement ID number */ proc sql; create table file1_4 as select * from dsq_b.dsq4_b as h, F1_3 as m where h.dsdsupid=m.dsdsupid; SORT that last file in which FILE 1 and FILE 2 were merged, by DSDSUPID as well as File 3 MERGE FILE1 and 2 with FILE 3 by DSDSUPID SORT FILE 4 by DSDSUPID MERGE FILE 1,2, 3 with FILE 4 by DSDSUPID

C. Program – Merging files */Sorting F1_4 and File 5 in the data by the Ingredient ID number*/ PROC SORT DATA = F1_4; BY DSDINGID; RUN; PROC SORT DATA = DSQ_B.DSQ5_B; BY DSDINGID; RUN; */Merging F1_4 and File 5 in the data by the Ingredient ID number */ proc sql; create table DS01_02 as select * from dsq_b.dsq5_b as h, F1_4 as m where h.dsdsupid=m.dsdsupid; MERGE FILE 1,2, 3, 4 with FILE 5 by DSDINGID SORT FILE 1,2,3,4 by DSDSUPID SORT FILE 5 by DSDSUPID

D. Appending and Data DATA ALLDATA; SET DS01_02 DS99_00; RUN; APPEND AND DATA

Variables in Demographic File VariableLabel RIAGENDRGender RIDAGEYRAge in years RIDRETH1Race/ethnicity SDMVPSUMasked Variance Pseudo- PSU SDMVSTRAMasked Variance Pseudo- Stratum WTINT4YR4 year Interview Weight WTINT2YR2 year Interview Weight

E. Adding Demographic Data DATA DEMO; SET DSQ.DEMO ( Demographic data) DSQ_B.DEMO_B( Demographic data); RUN; PROC SORT DATA=DEMO; BY SEQN; RUN; PROC SORT DATA=ALLDATA; BY SEQN; RUN; DATA DEMO_DS; MERGE DEMO ALLDATA; BY SEQN; RUN; APPEND demographic data from and SORT demographic data file and the Dietary Supplements Data from and MERGE demographic data file and the Dietary Supplements Data from and , by SEQN

F. SAS callable SUDAAN PROC CROSSTAB DATA=“DEMO_DS" FILETYPE=SAS DESIGN=WR; NEST SDMVSTRA SDMVPSU; WEIGHT WTINT4YR; SUBPOPN RIDAGEYR (age) >=18/ NAME="ADULTS"; SUBGROUP RIAGENDR (gender) DSD010(yes or no to taking dietary supplement); LEVELS 2 4; TABLES DSD010*RIAGENDR; RUN; Use the nest statement with strata and PSU to account for the design effect. Use the weight statement to account for the survey design, oversampling, non-response and post stratification.

Example 2 2.Estimate daily intake of Calcium to the diet. Combining dietary supplements to total nutrient intake from foods. A.Calculate total calcium intake from supplements for each participant. B.Merge Food Data files with Dietary Supplement Data file C.limitations and issues

A. Calculating total Calcium per participant DATA CALCIUM; SET DS01_02; IF DSD010=1 (took a supplement) AND DSDINGID= (the Ingredient ID for Calcium) THEN OUTPUT; RUN; First we are out all supplement users in which calcium is an ingredient in the supplement (s) used.

DATA CALCIUM1; SET CALCIUM; SSCALCIUM = DSD122Q / DSDSERVQ; if DSDINGID= then totalcal = SSCALCIUM*dsdqty; if (dsdunit=5)then total = totalcal * 1000; else if (DSDunit = 1) then total = totalcal; RUN; Calculate the amount that was actually taken by the participant. Multiply the amount of the serving size taken by the amount of calcium in the supplement

A. Calculating total Calcium per participant DATA FinalCa; SET Calcium1; BY SEQN; IF FIRST.SEQN THEN TOTCAL=0; TOTCAL+TOTAL; IF LAST.SEQN; RUN; This code adds up the calcium intake for each participant

DATA DS_Calcium; MERGE FINALCA (KEEP=SEQN TOTCAL) DSQ_B.DSQ1_B DSQ_B.DSQ2_B DEMO; BY SEQN; RUN; Merge file with total calcium for each participant with File 1 and File 2 by respondents number.

B. Merge Food Data files with Dietary Supplement Data file DATA COMBINE; MERGE DS_CALCIUM RECALL.DRXTOT_B; BY SEQN; TOTALCALCIUM = DRXTCALC + TOTCAL RUN; Dietary Interview Total Nutrient Intakes File Dietary supplement total calcium file Dietary supplement total calcium variable Dietary Interview total calcium variable New Total Calcium Variable

C. Limitations and Issues Different reference periods for the Dietary Supplement Data collection (past 30 days) and the Dietary Interview (past 24-hours) Assume Dietary Supplements were taken daily Analysts must be aware of differences in and dietary supplements data

Strengths of Data Nationally representative sample In-person interview Transcription of supplement name and manufacturer information from supplement container (88% of the time)

Limitations of Data Short reference time frame of the past month/ 30 days Recording supplement names from labels is still subject to error. Analytic verification of supplements actual ingredient content would be required to accurately depict nutrient content.

Acknowledgements Office of Dietary Supplements National Institutes of Health Bethesda, Maryland US NCHS, Kathy Radimer

Stage 4 SPs Stage 1 Counties Stage 2 Segments Stage 3 Households OP96017

Formatting Variables data PROC FORMAT CNTLIN=DSQ_B.DSQFMT_B ; PROC DATASETS LIB=DSQ_B; MODIFY DSQ1_B; FORMAT DSD010 DSD010F. ; FORMAT DSDCOUNT DSDCNTF. ; MODIFY DSQ2_B; FORMAT DSDSUPP $DSDSUPF. ; FORMAT DSD070 DSD070F. ; FORMAT DSDMTCH DSDMTCHF. ; FORMAT DSD122U DSD122UF. ; FORMAT DSDANTA DSDANTAF. ; MODIFY DSQ3_B; FORMAT DSDSUPP $DSDSUPF. ; FORMAT DSDSRCE DSDSRCEF. ; FORMAT DSDTYPE DSDTYPEF. ; FORMAT DSDSERVU DSDSRVF. ; MODIFY DSQ4_B; FORMAT DSDSUPP $DSDSUPF. ; FORMAT DSDINGR $DSDINGF. ; FORMAT DSDUNIT DSDUNTF. ; FORMAT DSDCAT DSDCATF. ; FORMAT DSDBLFLG DSDBLF. ; MODIFY DSQ5_B; FORMAT DSDINGR $DSDINGF. ; FORMAT DSDBCCAT DSDCATF. ; FORMAT DSDBCNAM $BCNAMF. ; QUIT; OPTIONS LS=240;

Merging formats for and Data Data dsqfmt_combined; set dsq_b.dsqfmt_b dsq.dsqfmt; run; proc sort data=dsqfmt_combined nodupkey; by fmtname start; proc format cntlin=dsqfmt_combined; run;