trends in prescription drug use among adults in the united states

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Trends in Prescription Drug Use Among Adultsin the United States From 1999-2012Elizabeth D. Kantor, PhD, MPH; Colin D. Rehm, PhD, MPH; Jennifer S. Haas, MD, MSc;Andrew T. Chan, MD, MPH; Edward L. Giovannucci, MD, ScD

IMPORTANCE It is important to document patterns of prescription drug use to inform bothclinical practice and research.

OBJECTIVE To evaluate trends in prescription drug use among adults livingin the United States.

DESIGN, SETTING, AND PARTICIPANTS Temporal trends in prescription drug use wereevaluated using nationally representative data from the National Health and NutritionExamination Survey (NHANES). Participants included 37 959 noninstitutionalized US adults,aged 20 years and older. Seven NHANES cycles were included (1999-2000 to 2011-2012),and the sample size per cycle ranged from 4861 to 6212.

EXPOSURES Calendar year, as represented by continuous NHANES cycle.

MAIN OUTCOMES AND MEASURES Within each NHANES cycle, use of prescription drugs in theprior 30 days was assessed overall and by drug class. Temporal trends across cycles wereevaluated. Analyses were weighted to represent the US adult population.

RESULTS Results indicate an increase in overall use of prescription drugs among US adultsbetween 1999-2000 and 2011-2012 with an estimated 51% of US adults reporting use of anyprescription drugs in 1999-2000 and an estimated 59% reporting use of any prescriptiondrugs in 2011-2012 (difference, 8% [95% CI, 3.8%-12%]; P for trend <.001). The prevalence ofpolypharmacy (use of �5 prescription drugs) increased from an estimated 8.2% in1999-2000 to 15% in 2011-2012 (difference, 6.6% [95% CI, 4.4%-8.2%]; P for trend <.001).These trends remained statistically significant with age adjustment. Among the 18 drugclasses used by more than 2.5% of the population at any point over the study period, theprevalence of use increased in 11 drug classes including antihyperlipidemic agents,antidepressants, prescription proton-pump inhibitors, and muscle relaxants.

CONCLUSIONS AND RELEVANCE In this nationally representative survey, significant increasesin overall prescription drug use and polypharmacy were observed. These increases persistedafter accounting for changes in the age distribution of the population. The prevalence ofprescription drug use increased in the majority of, but not all, drug classes.

JAMA. 2015;314(17):1818-1831. doi:10.1001/jama.2015.13766

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Author Affiliations: Authoraffiliations are listed at the end of thisarticle.

Corresponding Author: Elizabeth D.Kantor, PhD, MPH, Department ofEpidemiology and Biostatistics,Memorial Sloan Kettering CancerCenter, 485 Lexington Ave,Second Floor, New York, NY 10017([email protected]).

Research

Original Investigation

1818 (Reprinted) jama.com


U se of prescription drugs represents a major expendi-ture in the United States,1 and research suggests thatuse of prescription drugs is increasing.2 Yet much of

the information about prescription use is derived from phar-macy databases or expenditure data,1,3,4 neither of which di-rectly captures use at the population level. Although severalstudies have sought to assess prescription drug use on thepopulation level,5-15 these studies are either outdated, nar-row in scope, or limited to certain populations such as olderindividuals or those with a given clinical indication.

An updated comprehensive assessment of prescriptiondrug use is important given that practice patterns are continu-ally evolving to reflect the changing health needs of the popu-lation, advances in treatment, new clinical guidelines, the en-trance or exit of drugs from the market, and shifts in policiesregarding drug marketing and promotion. Because of this dy-namic climate, it is important to document patterns of pre-scription drug use to inform both clinical practice and re-search, while also identifying population subgroups with thepotential for underuse, misuse, and polypharmacy.

Nationally representative data from the National Healthand Nutrition Examination Survey (NHANES) were used to es-timate the prevalence of prescription drug use from 1999-2000 to 2011-2012.

MethodsData Source and Study PopulationNHANES is a nationally representative cross-sectional surveyof civilian noninstitutionalized persons living in the UnitedStates.16 Analyses for our study are based on data collected frompersons aged 20 years and older during the 7 most recent cycles.The selection of cycles was determined by data availability:1999-2000 represents the first year of continuous NHANES,and 2011-2012 is the most recent cycle for which data are avail-able. As a stratified, complex, multistage, probability-based sur-vey, NHANES oversamples older adults, low-income individu-als, and certain racial/ethnic groups; participants were assignedweights to account for their unequal sampling probability andnonresponse.

All participants provided written informed consent, anddata are publicly available.17 This study was deemed exemptfrom human subjects approval by the Harvard T. H. ChanSchool of Public Health institutional review board.

Assessment of Prescription Drug UseInformation about prescription drug use was collected duringa household interview. Participants were asked if they hadtaken prescription drugs over the prior 30 days. Those whoresponded “yes” were asked to show the containers of allproducts; when unavailable, participants were asked toreport the medication name. For each drug reported, theinterviewer entered the information into a laptop computer,and the drug was linked to a prescription drug database(Lexicon Plus) that includes all prescription drugs available.This database was updated at the beginning of each surveyyear to include new products.

Most drug categories are classified as defined by theNational Center for Health Statistics (NCHS). Some additionaldefinitions were generated, including antihypertensives,noncontraceptive hormones, antibiotics (including oralantibiotic-containing medications and antibiotic-containingdermatologic, ophthalmic, and respiratory medications), andoral antibiotics. Subclasses of drugs within a given drug classare not presented if used by too few individuals to providereliable estimates on the prevalence of use. Medicationsdefined as combination drugs are included within both com-binations as well as their component drug categories to allowfor tracking of both combination drugs and specific drugclasses. For example, combination drugs containing adrener-gic bronchodilators are classified as adrenergic bronchodila-tors and also as bronchodilator combinations to allow forsimple quantification of trends in the use of medications con-taining adrenergic bronchodilators and also of combinationtherapies.

Statistical AnalysisThe prevalence of use within each 2-year NHANES cycle wasestimated for any prescription drug use and use by drug class.Polypharmacy was defined as use of at least 5 drugs, which in-dicates a threshold commonly used in the literature.18 Addi-tional results are presented for the most commonly used in-dividual drugs in 2011-2012. Survey-weighted logisticregression was used to calculate a P value for trend across sur-vey cycles. Statistical significance of trends was assessed at the2-sided α=.05 level. In the results presentation, data reportedas an increase refers to a P value for trend of less than .05 anda ratio greater than 1, a decrease refers to a P value for trend ofless than .05 and ratio of less than 1, and stable refers to aP value for trend of .05 or greater. We have also presented thedifference in prevalence in 2011-2012 vs 1999-2000, al-though these data, in some cases, may not represent the mostextreme difference in use across years

Because changes in the age distribution of the populationmay account for observed trends in prescription drug use,secondary age-adjusted analyses were conducted using stan-dardization based on the US 2000 Standard Population(eTable 1 in the Supplement).

Given potential for heterogeneity by population sub-groups, results were stratified by age (20-39 years, 40-64years, and ≥65 years), sex, and race/ethnicity (non-Hispanicwhite, non-Hispanic black, and Mexican American). Data forother race/ethnicity groups were not included in the strati-fied analyses due to insufficient sample sizes to reliably esti-mate the prevalence of use. Results are presented forMexican Americans rather than overall Hispanics because oftemporal changes in data collection among Hispanics.19 Addi-tional analyses evaluated race/ethnicity–stratified estimateswith adjustment for age (previously described) and with fur-ther adjustment for insurance coverage. In analyses adjustedfor both age and insurance, standardization was imple-mented using the age and insurance distribution of the 1999-2000 NHANES cycle. Given the large number of drug classesanalyzed, results for a given overarching drug class are dis-cussed if they meet any of the following criteria: (1) a greater

Prescription Drug Use in US Adults 1999-2012 Original Investigation Research

jama.com (Reprinted) JAMA November 3, 2015 Volume 314, Number 17 1819


than 10% prevalence of use in any cycle; (2) prevalence of usegreater than 5% with at least a 1.5-fold change; or (3) preva-lence of use greater than 2.5% with at least a 2-fold change inuse. This approach was selected to focus on commonly useddrugs and on modestly used drugs with notable trends.

For drugs meeting the previously described criteria, wehave calculated an average annual percentage change usingJoinpoint Statistical Software (version 4.2.0.2), which uses apermutation test to identify points of inflection (providing anannual percentage change (APC) before and after the point ofinflection [eTable 2 in the Supplement]).20,21

All analyses account for complex survey design and post-stratification weighting using Stata version 13.1.

Results

In these NHANES cycles, the response rate for adults aged 20years and older was 73.6%,22 and 84% of medication contain-ers were seen by interviewers. After excluding 65 individualswho did not have data on prescription drug use, the finalsample size was 37 959; the sample size for individual NHANEScycles ranged from 4861 to 6212.

Table 1 shows the estimated percentage of US adults re-porting use of any prescription medication in 2011-2012 andalso of those reporting use of 5 or more prescription medica-tions both overall and by population characteristics. Fifty-

Table 1. Prevalence of Prescription Drug Use in Prior 30 Days Among US Adults—2011-2012a

No. of Participants

No. (%) [95% CI]b

Any PrescriptionsPolypharmacy(≥5 Prescriptions)

Overall 5558 3144 (59) [55-62] 917 (15) [13-17]

Age group, y

20-39 1957 596 (35) [32-39] 47 (3.1) [2.1-4.6]

40-64 2352 1428 (65) [62-67] 372 (15) [13-17]

≥65 1249 1120 (90) [87-93] 498 (39) [35-44]

Sex

Men 2739 1398 (52) [48-57] 418 (13) [10-16]

Women 2819 1746 (65) [62-67] 499 (16) [14-19]

Race/ethnicity

White non-Hispanic 2040 1377 (66) [63-69] 440 (17) [15-20]

Black non-Hispanic 1455 835 (52) [49-55] 266 (14) [12-17]

Asian non-Hispanic 794 335 (41) [36-45] 54 (6) [4.0-8.7]

Mexican American 539 214 (33) [28-38] 56 (6.8) [4.2-10]

Other Hispanic 578 305 (41) [36-45] 77 (8.5) [6.0-12]

Other 152 78 (51) [38-63] 24 (17) [8.6-32]

Education

<High school 1331 806 (57) [50-64] 296 (19) [16-23]

High school 1169 658 (58) [53-64] 196 (15) [12-19]

Some college 1657 901 (57) [52-62] 264 (15) [13-19]

College 1396 776 (61) [57-65] 160 (12) [9.2-14]

Family income-to-poverty ratioc

<1 (Lowest income) 1303 677 (49) [43-54] 241 (16) [11-21]

1-<2 1326 755 (59) [52-65] 258 (18) [15-21]

2-<4 1167 662 (58) [51-64] 173 (15) [11-19]

≥4 (Highest income) 1267 760 (65) [60-69] 148 (12) [10-14]

Insurance status (age <65 y)d

No insurance 1259 369 (31) [25-38] 47 (3.6) [2.1-6.0]

Government only 872 544 (64) [59-70] 201 (21) [17-25]

Any private insurance 2175 1110 (57) [54-60] 171 (9.1) [7.5-11]

Body mass indexe

<18.5 103 50 (59) [50-68] 12 (18) [9.8-32]

18-<25 1577 768 (52) [48-57] 148 (8.4) [5.5-13]

25-<30 1684 939 (57) [52-62] 245 (12) [10-15]

30-<35 1066 1066 (62) [58-66] 212 (17) [15-19]

35-<40 451 284 (68) [60-75] 109 (24) [18-30]

≥40 354 250 (73) [66-78] 117 (29) [24-35]

a All paticipants were aged 20 yearsor older.

b The values for % (95% CI) areweighted to be nationallyrepresentative.

c Data were based on the federalpoverty level. In 2012, the federalpoverty level for a family of 4 was$22 050. A family of 4 with anincome of $40 000 would have afamily income-to-poverty ratio of1.81, indicating that their income is181% greater than the federalpoverty level.

d Information on insurance status wasobtained from the health insurancequestionnaire, assessing whetherthe individual was covered byhealth insurance at the time of thesurvey. Limited to adults who wereyounger than aged 65 since 98.9%of adults aged 65 years and olderreported having some form ofhealth insurance.

e Body mass index was calculated asweight in kilograms divided byheight in meters squared. Data wereavailable for 94.2% of respondents.Mobile Exam Center weights wereused for analyses of body massindex (interview analytic weightswere used in all other cases).

Research Original Investigation Prescription Drug Use in US Adults 1999-2012

1820 JAMA November 3, 2015 Volume 314, Number 17 (Reprinted) jama.com


nine percent of adults used any prescription in the prior 30days, while 39% of adults aged 65 years and older reportedpolypharmacy. A significant increase in polypharmacy was ob-served in all 3 adult age groups: among those aged 20 to 39years, from 0.7% to 3.1%; among 40- to 64-year-olds, from 10%to 15%; and among those aged 65 years and older, from 24%to 39% (Figure 1).

From 1999-2000 to 2011-2012, the percentage of adults re-porting use of any prescription in the previous 30 days in-creased from an estimated 51% to 59% (difference, 8% [95%CI, 3.8%-12%]). Polypharmacy increased from an estimated8.2% to 15% (difference, 6.6% [95% CI, 4.4%-8.2%]; Figure 1

and Table 1). The increase in any prescription drug use and poly-pharmacy remained statistically significant in age-adjustedmodels (eTable 1 in the Supplement). Among the 18 drug classesused by more than 2.5% of the population, the prevalence ofuse increased in 11 drug classes (Table 2). All subsequent rangespresent prevalence of use in 1999-2000 vs 2011-2012 unlessspecified as otherwise.

Use of antihypertensives increased (20%-27%), with in-creases observed in most drug classes (Table 2). Antihyperlip-idemics use increased, a trend largely driven by statins (6.9%-17%). Use of statins increased markedly prior to 2005-2006(APC = 12%, after which the APC was 4.0%; eTable 2 in the

Figure 1. Trends in Any Prescription Drug Use and Use of 5 or More Prescription Drugs (Polypharmacy), Overall, and by Age Group, Sex,and Race/Ethnicity—1999-2012

80

60

40

20

100

80

60

40

20

100

60

40

20

80

100

0

Repo

rted

Use

in P

rior 3

0 Da

ys, %

YearNo. of participants20-39 y40-64 y≥65 y

1999-2000

169217871382

2001-2002

192520221452

2003-2004

173717991493

2005-2006

192318641183

2007-2008

191024691551

2009-2010

208126111520

2011-2012

195723521249

Reported by ageBAge 20-39 y

Any usePolypharmacy

Age 40-64 yAny usePolypharmacy

Age ≥65 yAny usePolypharmacy

Non-Hispanic whiteAny usePolypharmacy

Non-Hispanic blackAny usePolypharmacy

Mexican AmericanAny usePolypharmacy

80

60

40

20

100

0

Repo

rted

Use

in P

rior 3

0 Da

ys, %

YearNo. of participants

1999-2000

4861

2001-2002

5399

2003-2004

5029

2005-2006

4970

2007-2008

5930

2009-2010

6212

2011-2012

5558

All participantsA

0

Repo

rted

Use

in P

rior 3

0 Da

ys, %

YearNo. of participantsNon-Hispanic

WhiteBlack

MexicanAmerican

1999-2000

2210904

1280

2001-2002

285410101112

2003-2004

2686987985

2005-2006

249111201003

2007-2008

275812271032

2009-2010

297511211138

2011-2012

20401455

539

Reported by race/ethnicityD

0

Repo

rted

Use

in P

rior 3

0 Da

ys, %

YearNo. of participantsWomenMen

1999-2000

26002261

2001-2002

28672532

2003-2004

26172412

2005-2006

25872383

2007-2008

30212909

2009-2010

32103002

2011-2012

28192739

Reported by sexC

Any use

Polypharmacy

WomenAny usePolypharmacy

MenAny usePolypharmacy

All trends statistically significant except for any prescription drug use amongpersons aged 20 to39 years (P for trend = .22) and for any prescription drug use

among Mexican Americans (P for trend = .17). All data are weighted to benationally representative. Error bars indicate 95% CIs.



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1-14

)11

(9.4

-12)

13(1

1-15

)<.

001

6.0

(3.5

to8.

6)1.

9(1

.5to

2.4)

Phen

ylpi

pera

zine

1.0

(0.8

-1.2

)1.

4(1

.0-1

.9)

1.0

(0.7

-1.4

)1.

0(0

.8-1

.4)

1.0

(0.8

-1.3

)0.

9(0

.7-1

.2)

1.3

(0.9

-1.7

).9

20.

3(−

0.1

to0.

7)1.

3(0

.92

to1.

9)

SSN

RIs

0.4

(0.3

-0.7

)0.

7(0

.4-1

.0)

1.1

(0.7

-1.7

)1.

9(1

.5-2

.5)

2.3

(1.8

-2.8

)1.

9(1

.5-2

.4)

2.0

(1.5

-2.6

)<.

001

1.6

(1.0

to2.

2)4.

7(2

.6to

8.5)

SSRI

s4.

3(3

.6-5

.2)

5.8

(5.1

-6.7

)7.

4(6

.5-8

.5)

7.0

(6.2

-7.9

)7.

3(6

.3-8

.4)

6.9

(5.6

-8.5

)8.

5(6

.9-1

0.4)

<.00

14.

2(2

.3to

6.1)

2.0

(1.5

to2.

6)

(con

tinue

d)




Tabl

e2.

Tren

dsin

Pres

crip

tion

Dru

gU

sein

the

Prio

r30

Day

sAm

ong

US

Adul

tsby

Top

18–U

sed

Dru

gCl

asse

s—19

99-2

012

a(c

ontin

ued)

Prev

alen

ceof

Use,

%b

(95%

CI)

Pfo

rTr

end

2011

-201

2vs

1999

-200

0

1999

-200

0(n

=48

61)

2001

-200

2(n

=53

99)

2003

-200

4(n

=50

29)

2005

-200

6(n

=49

70)

2007

-200

8(n

=59

30)

2009

-201

0(n

=62

12)

2011

-201

2(n

=55

58)

Diff

eren

cein

Prev

alen

ce,

%(9

5%CI

)c

Ratio

ofPr

eval

ence

,Ra

tio(9

5%CI

)d

Tric

yclic

s1.

2(0

.9-1

.7)

1.5

(0.9

-2.3

)1.

5(1

.2-1

.9)

1.1

(0.9

-1.4

)1.

4(1

.2-1

.6)

1.0

(0.8

-1.5

)1.

3(1

.0-1

.8)

.59

0.1

(−0.

4to

0.7)

1.1

(0.7

2to

1.8)

Pres

crip

tion

anal

gesi

cs11

(10-

12)

13(1

2-14

)17

(15-

19)

12(1

0-13

)12

(10-

14)

12(1

0-13

)11

(9.2

-14)

.13

−0.1

(−2.

6to

2.5)

0.99

(0.7

9to

1.2)

COX-

2in

hibi

tors

1.9

(1.3

-2.7

)4.

3(3

.6-5

.0)

4.5

(3.8

-5.2

)1.

3(0

.8-2

.0)

1.0

(0.7

-1.6

)0.

5(0

.3-0

.7)

0.6

(0.4

-1.0

)<.

001

−1.3

(−2.

0to

−0.6

)0.

32(0

.17

to0.

59)

Nar

cotic

anal

gesi

cs3.

8(3

.1-4

.8)

4.5

(3.6

-5.6

)5.

8(4

.7-7

.2)

5.9

(4.9

-7.0

)5.

8(4

.5-7

.4)

5.1

(4.2

-7.6

)5.

7(4

.2-7

.6)

.05

1.8

(0.0

to3.

7)1.

5(1

.0to

2.1)

Pres

crip

tion

NSA

IDsf

5.6

(4.7

-6.6

)3.

7(3

.1-4

.4)

6.6

(5.6

-7.8

)4.

6(4

.0-5

.2)

4.2

(3.4

-5.1

)4.

5(3

.8-5

.2)

4.2

(3.4

-5.2

).0

3−1

.4(−

2.7

to−0

.1)

0.75

(0.5

7to

0.98

)

Salic

ylat

es0.

6(0

.4-0

.9)

0.7

(0.5

-0.9

)0.

5(0

.3-0

.8)

0.6

(0.5

-0.8

)1.

0(0

.7-1

.4)

1.5

(1.2

-2.0

)0.

6(0

.4-0

.9)

.002

0.0

(−0.

3to

0.3)

1.0

(0.5

8to

1.8)

Mis

cella

neou

san

alge

sics

0.4

(0.2

-0.7

)0.

4(0

.2-0

.6)

1.0

(0.7

-1.7

)0.

8(0

.5-1

.2)

1.1

(0.7

-1.6

)1.

3(1

.0-1

.7)

1.3

(1.0

-1.8

)<.

001

0.9

(0.4

to1.

4)3.

3(1

.8to

5.9)

Hor

mon

esg

Sex

19(1

6-21

)21

(18-

24)

14(1

3-16

)12

(11-

14)

12(1

0-14

)10

(8.6

-12)

11(8

.7-1

3)<.

001

−7.9

(−11

to−4

.6)

0.57

(0.4

5to

0.73

)

Cont

race

ptiv

e8.

1(6

.6-9

.8)

8.5

(6.7

-11)

7.0

(6.0

-8.3

)6.

9(5

.7-8

.3)

7.6

(5.8

-9.9

)7.

1(5

.9-8

.5)

7.1

(5.1

-9.9

).3

5−0

.9(−

3.8

to1.

9)0.

88(0

.60

to1.

3)

Non

cont

race

ptiv

e12

(10-

15)

14(1

2-16

)7.

2(6

.0-8

.7)

5.6

(4.8

-6.5

)4.

3(3

.2-5

.6)

3.1

(2.6

-3.8

)4.

0(3

.2-5

.1)

<.00

1−8

.5(−

11to

−5.6

)0.

32(0

.23

to0.

45)

Antid

iabe

ticag

ents

4.6

(3.8

-5.5

)5.

3(4

.5-6

.1)

6.4

(5.5

-7.5

)6.

4(5

.6-7

.3)

7.7

(6.5

-9.1

)7.

7(6

.8-8

.6)

8.2

(7.2

-9.3

)<.

001

3.6

(2.3

to5.

0)1.

8(1

.4to

2.2)

Bigu

anid

es2.

0(1

.5-2

.6)

2.5

(2.0

-3.1

)3.

6(3

.0-4

.3)

3.6

(2.9

-4.5

)4.

7(3

.9-5

.7)

4.9

(4.3

-5.7

)5.

5(4

.7-6

.4)

<.00

13.

5(2

.5to

4.5)

2.7

(2.0

to3.

7)

Insu

lin1.

1(0

.8-1

.6)

1.3

(0.9

-1.8

)1.

5(1

.2-1

.9)

1.6

(1.4

-1.9

)2.

1(1

.6-2

.8)

2.1

(1.6

-2.7

)2.

6(2

.2-3

.1)

<.00

11.

5(0

.9to

2.1)

2.3

(1.6

to3.

3)

Sulfo

nylu

reas

2.6

(2.2

-3.2

)2.

7(2

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3.3

(2.6

-4.1

)2.

9(2

.3-3

.6)

3.3

(2.8

-3.8

)3.

0(2

.6-3

.5)

3.2

(2.5

-4.2

)<.

001

0.6

(−0.

4to

1.5)

1.2

(0.8

8to

1.7)

Thia

zolid

ined

ione

s0.

5(0

.3-0

.8)

0.9

(0.7

-1.2

)2.

0(1

.7-2

.4)

2.0

(1.5

-2.6

)1.

9(1

.4-2

.4)

1.2

(1.0

-1.6

)0.

8(0

.6-1

.1)

.17

0.3

(−0.

1to

0.7)

1.6

(0.8

6to

2.9)

Pres

crip

tion

prot

on-p

ump

inhi

bito

rs3.

9(3

.0-5

.0)

6.2

(5.5

-7.1

)7.

5(6

.4-8

.7)

8.0

(6.7

-9.5

)9.

0(7

.4-1

1)9.

3(8

.0-1

1)7.

8(6

.2-9

.6)

<.00

13.

9(1

.9to

5.9)

2.0

(1.4

to2.

8)

Thyr

oid

horm

ones

5.1

(4.4

-5.9

)5.

2(4

.5-6

.0)

7.0

(6.1

-8.0

)7.

1(6

.0-8

.3)

6.7

(5.9

-7.6

)7.

1(6

.2-8

.3)

6.4

(5.3

-7.7

).0

071.

3(−

0.2

to2.

7)1.

2(0

.98

to1.

6)

Anxi

olyt

ics,

seda

tives

,hy

pnot

ics

4.2

(3.4

-5.1

)4.

4(3

.7-5

.2)

6.1

(4.6

-7.9

)5.

5(4

.8-6

.4)

6.5

(5.5

-7.7

)6.

1(5

.4-6

.8)

6.1

(5.0

-7.3

)<.

001

1.9

(0.5

to3.

3)1.

5(1

.1to

1.9)

Benz

odia

zepi

nes

2.8

(2.2

-3.5

)3.

2(2

.6-3

.8)

4.2

(3.1

-5.6

)3.

4(2

.9-4

.0)

3.8

(3.1

-4.6

)3.

8(3

.1-4

.6)

3.9

(3.3

-4.8

).0

41.

1(0

.2to

2.1)

1.4

(1.0

to1.

9)

Antic

onvu

lsan

ts2.

3(1

.9-2

.9)

3.5

(2.8

-4.3

)4.

5(3

.7-5

.5)

4.3

(3.7

-5.0

)5.

3(4

.5-6

.3)

5.3

(4.8

-5.8

)5.

5(4

.6-6

.6)

<.00

13.

2(2

.0to

4.3)

2.3

(1.8

to3.

1)

Benz

odia

zepi

nes

1.2

(0.9

-1.7

)1.

6(1

.1-2

.1)

2.1

(1.5

-2.9

)1.

8(1

.5-2

.2)

1.9

(1.6

-2.3

)2.

1(1

.7-2

.7)

2.3

(1.8

-2.9

).0

021.

1(0

.4to

1.7)

1.8

(1.3

to2.

7)

γ-Am

inob

utyr

icac

idan

alog

se

0.9

(0.7

-1.2

)1.

2(0

.8-1

.8)

1.2

(0.8

-1.7

)1.

9(1

.4-2

.5)

1.9

(1.6

-2.3

)2.

1(1

.6-2

.7)

<.00

11.

8(1

.2to

2.4)

7.4

(2.8

to19

)

Bron

chod

ilato

rs3.

2(2

.6-4

.0)

3.3

(2.6

-4.2

)3.

9(3

.1-4

.8)

4.4

(3.7

-5.2

)5.

1(4

.3-5

.9)

4.7

(3.8

-5.7

)5.

2(4

.0-6

.6)

<.00

11.

9(0

.5to

3.4)

1.6

(1.1

to2.

2)

Adre

nerg

icbr

onch

odila

tors

2.9

(2.3

-3.6

)3.

2(2

.5-4

.1)

3.7

(3.0

-4.5

)4.

2(3

.6-5

.0)

4.9

(4.1

-5.7

)4.

4(3

.6-5

.3)

4.9

(3.7

-6.3

)<.

001

2.0

(0.5

to3.

4)1.

7(1

.2to

2.4)

Antic

holin

ergi

cbr

onch

odila

tors

0.6

(0.5

-0.7

)0.

5(0

.4-0

.7)

1.1

(0.8

-1.6

)0.

9(0

.7-1

.2)

1.3

(1.0

-1.8

)1.

0(0

.7-1

.5)

1.1

(0.8

-1.6

)<.

001

0.5

(0.1

to1.

0)1.

9(1

.2to

3.0)

(con

tinue

d)




ble

2.Tr

ends

inPr

escr

iptio

nD

rug

Use

inth

ePr

ior3

0D

aysA

mon

gU

SAd

ults

byTo

p18

–Use

dD

rug

Clas

ses—

1999

-20

12a

(con

tinue

d)

Prev

alen

ceof

Use,

%b

(95%

CI)

Pfo

rTr

end

2011

-201

2vs

1999

-200

0

1999

-200

0(n

=48

61)

2001

-200

2(n

=53

99)

2003

-200

4(n

=50

29)

2005

-200

6(n

=49

70)

2007

-200

8(n

=59

30)

2009

-201

0(n

=62

12)

2011

-201

2(n

=55

58)

Diff

eren

cein

Prev

alen

ce,

%(9

5%CI

)c

Ratio

ofPr

eval

ence

,Ra

tio(9

5%CI

)d

Bron

chod

ilato

rco

mbi

natio

ns0.

3(0

.2-0

.4)

0.6

(0.4

-0.8

)1.

9(1

.4-2

.5)

1.9

(1.4

-2.4

)2.

2(1

.7-2

.7)

2.1

(1.5

-2.9

)2.

1(1

.4-3

.0)

<.00

11.

8(1

.0to

2.6)

7.9

(4.6

to14

)

Antib

iotic

s5.

7(5

.1-6

.3)

5.6

(4.5

-6.9

)5.

5(4

.8-6

.3)

5.4

(4.5

-6.4

)4.

3(3

.8-4

.8)

4.0

(3.4

-4.7

)4.

2(3

.7-4

.9)

<.00

1−1

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2.3

to−0

.6)

0.75

(0.6

3to

0.90

)

Ora

lant

ibio

tics

3.8

(3.2

-4.4

)3.

6(2

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3.7

(3.1

-4.4

)3.

4(2

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.4)

2.8

(2.3

-3.3

)2.

7(2

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2.9

(2.5

-3.3

)<.

001

−0.9

(−1.

6to

−0.1

)0.

77(0

.63

to0.

96)

Antia

rrhy

thm

icag

ents

4.9

(4.5

-5.4

)4.

5(3

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.3)

4.3

(3.7

-5.0

)4.

5(3

.8-5

.3)

3.4

(2.8

-4.1

)3.

0(2

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2.7

(2.1

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)<.

001

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(−3.

0to

−1.4

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55(0

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to0.

73)

Clas

sIV

2.7

(2.4

-2.9

)2.

4(1

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2.1

(1.7

-2.6

)2.

2(1

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1.3

(1.0

-1.6

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4(1

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1.0

(0.6

-1.5

)<.

001

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(−2.

2to

−1.2

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52(0

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to0.

89)

Clas

sV1.

4(1

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1.0

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-1.3

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1(0

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0.9

(0.6

-1.3

)0.

7(0

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0.5

(0.3

-1.0

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7(0

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to−0

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0.83

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2to

1.6)

Coag

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mod

ifier

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3(1

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2.6

(2.1

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)3.

3(2

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3.8

(3.1

-4.8

)4.

8(4

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4.8

(3.9

-5.8

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2.6)

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(1.4

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3)

Antic

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lant

s1.

3(0

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1.5

(1.2

-1.9

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4(1

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1.7

(1.5

-2.0

)1.

9(1

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1.8

(1.4

-2.4

)1.

7(1

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0.4

(−0.

2to

1.0)

1.3

(0.8

7to

2.0)

War

farin

1.3

(0.9

-1.8

)1.

4(1

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1.4

(1.1

-1.9

)1.

7(1

.5-2

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1.9

(1.4

-2.6

)1.

8(1

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1.5

(1.1

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3(−

0.3

to0.

9)1.

2(0

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to1.

9)

Antip

late

let

agen

ts0.

9(0

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1.1

(0.8

-1.4

)1.

8(1

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2.2

(1.6

-3.0

)2.

9(2

.3-3

.5)

3.1

(2.4

-4.0

)2.

4(1

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<.00

11.

5(0

.9to

2.1)

2.7

(1.9

to3.

9)

Clop

idog

rel

0.3

(0.2

-0.4

)0.

5(0

.4-0

.8)

1.3

(0.9

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Confidential. Do not distribute. Pre-embargo material.Supplement). Use of antidepressants increased (6.8%-13%),reflected by an increase in use of selective serotonin-norepinephrine reuptake inhibitors (SSNRIs) (0.4%-2.0%) andalso in selective serotonin reuptake inhibitors (SSRIs) (4.3%-8.5%). Use of antidepressants increased most in the early years,driven by a sharp increase in SSNRIs before 2005-2006(APC = 32%), after which time, the trend leveled off (APC,−0.2%).

Prescription analgesic use remained stable (11%), al-though trends differed by type. Use of cyclooxygenase-2(COX-2) inhibitors decreased from 1.9% to 0.6%, while theprevalence of narcotic analgesic use increased from 3.8% to5.7%. Notably, narcotic analgesics increased before 2003-2004 (APC=12%), after which time, the use stabilized (APC,−1.2%).

Use of sex hormones among women decreased from 19%to 11%, which was a change primarily driven by a decline in useof noncontraceptive hormones (12.0%-4.0%, a drug class com-posed largely of menopausal hormone therapy). Use ofantidiabetic agents increased from 4.6% to 8.2%, specifi-cally, increases were observed for biguanides, insulin, and sul-fonylureas. Although use of thiazolidinediones remained un-changed overall, a significant inflection point was observed in2003-2004 (before which, use increased [APC = 48%], and af-ter which, use decreased [APC, −8.8%]).

An increase was reported in the use of prescription proton-pump inhibitors (PPIs) (3.9%-7.8%) and also the use of anti-convulsants (2.3%-5.5%). Notably, the use of anticonvulsantsincreased most in the early years with an APC of 16% ob-served before 2003-2004, and an APC of 3.0% was observedthereafter. Use of bronchodilators increased (3.2%-5.2%) over-all, with use of adrenergic bronchodilators increasing most be-fore 2007-2008 (APC = 6.6%) and stabilizing afterwards (APC,−1.2%). Use of bronchodilator combinations increased sharplybefore 2003-2004 (APC = 66%), and were reported with an APC2.2% afterwards. Further, use of muscle relaxants increased(1.2%-2.5%), with the increase sharpest in the periods be-tween 1999-2000 and 2003-2004 (APC prior to 2003-2003,19%; thereafter, −1.7%). Use of antibiotics decreased from 5.7%to 4.2% over the study period. Trends of use for prescriptiondrug classifications with a prevalence of use less than 2.5% arereported in Table 3.

Prescription drug use increased significantly among per-sons aged 40 to 64 years (57%-65%) and also among those aged65 years and older (84%-90%) (Table 4), but not among adultsaged 20 to 39 years (32%-35%) (Figure 1, panel B). For specificdrug classes, trends were generally similar by age and sex withsome exceptions (eg, use of prescription analgesics did notchange among adults aged 40-64 years [13%-14%], but use sig-nificantly decreased among adults aged ≥65 years [18%-14%]; use of muscle relaxants increased significantly amongwomen [1.2%-3.3%], but did not increase significantly amongmen [1.3%-1.7%]) (Table 4 and Table 5; eTables 3 and 4 in theSupplement).

Although significant increases in the percentage of per-sons using 5 or more prescriptions were observed in all racial/ethnic groups (eTable 5 in the Supplement), an overall in-crease in prescription drug use was evident among individuals

who were non-Hispanic white (55%-66%) and non-Hispanicblack (43%-52%), but not Mexican American (30%-33%). Thispattern remained unchanged with age adjustment, and theprevalence of use among individuals who were Mexican Ameri-can remained markedly lower than among that of those whowere non-Hispanic white (although the difference was attenu-ated somewhat; eTable 6 in the Supplement). Further sensi-tivity analyses revealed that this difference in any prescrip-tion use was not entirely attributable to adjustment forinsurance status, although race/ethnicity–specific differ-ences in polypharmacy were attenuated (eTable 6 and eTable7 in the Supplement).

The most commonly used individual drug in 2011-2012 wassimvastatin (7.9%), increasing from 2.0% in 1999-2000 (eTable8 in the Supplement and Figure 2). The remaining top 10 drugsincluded lisinopril, levothyroxine, metoprolol, metformin, hy-drochlorothiazide, omeprazole, amlodipine, atorvastatin, andalbuterol; all of the top 10 most commonly used drugs in-creased over the study period except atorvastatin.

DiscussionOverall, prescription drug use increased among US adults be-tween 1999-2000 and 2011-2012, as reflected by an increasein any prescription drug use and a marked increase in poly-pharmacy. Specifically, the prevalence of prescription drug useincreased from 51% in 1999-2000 to 59% in 2011-2012, whilethe prevalence of polypharmacy increased from 8.2% to 15%.The increase in prescription drug use was observed for the ma-jority of but not all drug classes.

Use of antihypertensive drugs increased over the study pe-riod, with a marked increase observed for several antihyper-tensives, including thiazide diuretics. The increase in use ofthiazide diuretics is notable, given the recommendations fortheir use as first-line agents by the 2003 JNC 7 (Seventh Re-port of the Joint National Committee on Prevention, Detec-tion, Evaluation, and Treatment of High Blood Pressure).24

However, in trend analyses accounting for potential inflec-tion points the APC was highest before 2003-2004, suggest-ing that the increase in thiazide diuretics use preceded ratherthan resulted from the 2003 recommendations. In 2014, theJNC 8 guidelines relaxed recommendations for drug initia-tion and expanded the options for first-line drug therapy, whichmay further influence the landscape of antihypertensive use.25

Use of antihyperlipidemics increased markedly, drivenprimarily by an increase in use of statins, for which the great-est increase was observed prior to 2005-2006. Although useof both simvastatin and atrovastatin increased early in thestudy period, use of atorvastatin started to decline after2005-2006. This pattern likely reflects the fact that simvasta-tin came off patent in 2006 while atorvastatin remained pat-ent protected, and therefore more costly, until 2011. Notably,this study preceded the release of the 2013 American Collegeof Cardiology/American Heart Association recommendations,which expanded guidelines for statin use.26

The increase in use of antidepressant drugs may, in part,reflect shifting attitudes regarding depression.27 Use of SSRIs




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lute

incr

ease

orde

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sein

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ceof

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een

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00

and

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here

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crea

seor

decr

ease

inpr

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ence

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lect

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rugs

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eval

ence

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CI)

Pfo

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end

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eval

ence

ofUs

e,%

(95%

CI)

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rTr

end

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cate

sthe

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lute

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sein

prev

alen

ceof

use

betw

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1999

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00

and

2011

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dica

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2011

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CI)

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1999

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0

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Confidential. Do not distribute. Pre-embargo material.and SSNRIs markedly increased; notably, use of SSNRIs in-creased between 1999-2000 and 2005-2006, remaining stablethereafter. Even so, SSRIs remain much more commonly usedthan the other antidepressant drugs, and the continued popu-larity of the SSRIs may reflect the availability of several ge-neric options with a wide range of indications and a favorableprofile regarding adverse effects.28

Overall, trends in analgesic use were stable; however, therewas marked heterogeneity by class. Use of COX-2 inhibitors de-creased, likely a result of rofecoxib being taken off the marketin 2004.29 Conversely, use of narcotic analgesic drugs in-creased from 1999-2000 to 2011-2012. Although increased useof narcotic analgesics may raise concern about their potentialmisuse or abuse, it should be noted that use stabilized after2003-2004. This flattening trend may reflect increased aware-ness of prescription opioid drug misuse or abuse,30 althoughunderreporting of these drugs may have increased with aware-ness regarding their potential for abuse.

Use of sex hormones decreased substantially amongwomen, resulting from the decrease in noncontraceptive hor-mone use (following the release of results from the Women’sHealth Initiative Hormone Therapy Trial).10,31 This decrease isnotable because conjugated estrogens once represented themost commonly used prescription drug.11

As the prevalence of diabetes increased,32 use of antidia-betic drugs also increased, driven by a sharp rise in use of in-sulin and biguanides. Accordingly, metformin, considered afirst-line agent in the treatment of diabetes,33 is now the fifthmost commonly used drug. Use of thiazolidinediones de-creased in recent years, likely owing to concern regarding thelink between rosiglitazone and risk of cardiovascular events.34

Despite certain proton-pump inhibitors becoming avail-able over the counter (OTC), use of prescription proton-pump inhibitors increased, a trend which would be likely evenmore marked if we were able to account for OTC use. The in-crease in prescription proton-pump inhibitors may, in part, re-flect the availability of more affordable varied options for pro-ton-pump inhibitors following the loss of patent protection foromeprazole in 2001 and subsequent market entry of esome-prazole. It remains unclear how use of prescription proton-pump inhibitors will be affected long term by increasing avail-ability of OTC proton-pump inhibitors.

Use of anticonvulsant drugs increased over the studyperiod. Several anticonvulsants are cross-classified in otherdrug classes (eg, benzodiazepines), and it is likely that thesealternative indications are in part driving the observedincrease in use.

A significant inflection point was observed for use of ad-renergic bronchodilators in 2007-2008, after which time usestabilized. It is possible that this pattern may in part reflect the2005 US Food and Drug Administration’s Public Health Advi-sory regarding use of long-acting β2-adrenergic agonists. Thesharp early increase in use of bronchodilator combinations mayreflect other market forces, including direct-to-consumer ad-vertising (DCTA), which peaked in the mid-2000s.35,36 DCTAis particularly relevant to bronchodilator combinations suchas the popular combination drug Advair, which was ranked asone of the top drugs in terms of DCTA in 2010.36 Even so, a re-

cent study found little evidence of association between DCTAand Advair prescriptions, and it therefore seems unlikely thatDCTA alone is responsible.37

Use of muscle relaxants increased over the study period.Although the reasons underlying this increase are unclear, therehas been discussion about the potential for misuse or abuseof carisoprodol, one of the more commonly used muscle re-laxants. In 2011, the Drug Abuse Warning Network released areport showing an increase in emergency department visits as-sociated with carisoprodol between 2004 and 2009,38 and in2012, the Drug Enforcement Administration classified this drugas a controlled substance. Notably, however, in our data, thesharpest increase in prevalence of use of muscle relaxants wasobserved before 2003-2004, with no significant change ob-served thereafter.

The increases in any prescription drug use and polyphar-macy are not explained by changes in the age distribution ofthe population. An alternative explanation for the observed in-crease in prescription drug use might be large-scale policychanges, including the implementation of Medicare Part D.However, the increase in prescription drug use was not ob-served only among adults aged 65 years and older but alsoamong adults aged 40 to 64 years. Furthermore, MedicarePart D went into effect in 2006, and for many of the drug classesdiscussed, the sharpest increase occurred before 2006.

It is unclear if this pattern, with the sharpest increases ob-served early in the study period, reflects a saturation of the mar-ket, the peak of DCTA in the mid-2000s,36 or lagged effects re-sulting from the increase in obesity in the population. Eightof the 10 most commonly used drugs in 2011-2012 are used totreat components of the cardiometabolic syndrome, includ-ing hypertension, diabetes, and dyslipidemia. Another is a pro-ton-pump inhibitor used for gastroesophageal reflux, a con-dition more prevalent among individuals who are overweight

Figure 2. Trends in Individual Prescription Medications UsedBy More Than 4% of US Adults—2011-2012

8

6

4

2

10

0

Repo

rted

Use

in P

rior 3

0 Da

ys, %

Year

No. ofparticipants

1999-2000

4861

2001-2002

5399

2003-2004

5029

2005-2006

4970

2007-2008

5930

2009-2010

6212

2011-2012

5558

SimvastatinLisinoprilLevothyroxineMetoprololMetforminHydrochlorothiazideOmeprazole

All trends were statistically significant (P for trend for each drug < .001). All dataare weighted to be nationally representative. Error bars indicate 95% CIs.



Confidential. Do not distribute. Pre-embargo material.or obese.39 Thus, the increase in use of some agents may re-flect the growing need for treatment of complications associ-ated with the increase in overweight and obesity.

For most drugs and drug classes, trends were generallycomparable across age, sex, and race/ethnicity. One majordifference was that any prescription drug use was substan-tially lower for Mexican American than for non-Hispanicwhite individuals. Because the Mexican American popula-tion is younger than the non-Hispanic white population,40

we conducted age-adjusted analyses and found that amarked difference between groups persisted, although thedifference attenuated somewhat. Further adjustment forinsurance status did not entirely account for the difference inany prescription use, although it is possible that prescriptiondrug coverage may better account for the observed pattern.An alternative explanation may be the Hispanic paradox,which is that despite lower socioeconomic status, individualsof Hispanic descent have better-than-expected health status,which would likely result in less use of prescriptionmedications.41 The reasons underlying these differences arelikely multifactorial, meriting further investigation.

We have provided a comprehensive picture of prescrip-tion drug use in the US adult population using nationally rep-resentative data. Prescription drug use was assessed viain-home interviews in which containers were seen for 84% of

drugs, giving confidence to participants’ self-reported use.Further, NHANES has a high response rate, reducing concernabout bias. Even so, this study has several limitations. First,recall of intermittently used drugs may be more prone tomeasurement error than drugs used daily. Second, we areunable to capture OTC drug use, and some trends, such asthe decrease in antihistamines use, reflect the availability ofcertain drugs becoming available OTC. Third, this survey wasconducted among noninstitutionalized adults; thus, resultsdo not capture use among adults living in nursing homes andshould only be generalized to the community-dwelling USadult population. Additionally, certain drugs may be in morethan one class and some drugs may be taken for off-label use,and therefore, the classifications of drugs do not perfectlyalign with reasons for use.

ConclusionsIn this nationally representative survey, significant increasesin overall prescription drug use and polypharmacy were ob-served. These increases persisted even after accounting forchanges in the age distribution of the population. The preva-lence of prescription drug use increased in the majority of butnot all drug classes.

ARTICLE INFORMATION

Author Affiliations: Department of Epidemiology,Harvard T. H. Chan School of Public Health, Boston,Massachusetts (Kantor, Giovannucci); Departmentof Epidemiology and Biostatistics, Memorial SloanKettering Cancer Center, New York, New York(Kantor); Friedman School of Nutrition Science andPolicy, Tufts University, Boston, Massachusetts(Rehm); Office of Community & Population Health,Montefiore Medical Center, Bronx, New York(Rehm); Division of General Internal Medicine andPrimary Care, Brigham and Women’s Hospital,Boston, Massachusetts (Haas); Department ofSocial and Behavioral Sciences, Harvard T. H. ChanSchool of Public Health, Boston, Massachusetts(Haas); Channing Division of Network Medicine,Brigham and Women's Hospital, Boston,Massachusetts (Chan, Giovannucci); Division ofGastroenterology, Massachusetts General Hospital,Boston (Chan); Clinical and TranslationalEpidemiology Unit, Massachusetts GeneralHospital, Boston (Chan); Department of Nutrition,Harvard T. H. Chan School of Public Health, Boston,Massachusetts (Giovannucci).

Author Contributions: Drs Kantor and Rehm hadfull access to all of the data in the study and takeresponsibility for the integrity of the data and theaccuracy of the data analysis. Both authorscontributed equally to this article.Study concept and design: Kantor, Rehm, Chan.Acquisition, analysis, or interpretation of data:Kantor, Rehm, Haas, Chan, Giovannucci.Drafting of the manuscript: Kantor, Rehm, Chan.Critical revision of the manuscript for importantintellectual content: Rehm, Haas, Chan,Giovannucci.Statistical analysis: Kantor, Rehm, Giovannucci.Study supervision: Haas, Chan, Giovannucci.

Conflict of Interest Disclosures: All authors havecompleted and submitted the ICMJE Form forDisclosure of Potential Conflicts of Interest. Dr Chanreports having consulted for Pfizer Inc, BayerHealthcare, and Pozen Inc.

Funding/Support: This work was conducted withsupport from the National Cancer Institute (supportfor Kantor, T32 CA 009001) and the NationalInstitute of Diabetes and Digestive and KidneyDiseases (support for Chan, K24 DK098311).Support for Haas: Harvard Catalyst—The HarvardClinical and Translational Science Center (NationalCenter for Research Resources and the NationalCenter for Advancing Translational Sciences,National Institutes of Health Award UL1 TR001102)and financial contributions from Harvard Universityand its affiliated academic health care centers.

Role of the Funder/Sponsor: The funder had norole in the design and conduct of the study;collection, management, analysis, andinterpretation of the data; and preparation, review,or approval of the manuscript; or the decision tosubmit the manuscript for publication.

Disclaimer: The content is solely the responsibilityof the authors and does not necessarily representthe official views of Harvard Catalyst, HarvardUniversity and its affiliated academic health carecenters, or the National Institutes of Health.

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