Abstract
Importance
It is important to document patterns of prescription drug use to inform both clinical practice and research.
Objective
To evaluate trends in prescription drug use among adults living in the United States.
Design, Setting, and Participants
Temporal trends in prescription drug use were evaluated using nationally representative data from the National Health and Nutrition Examination Survey (NHANES). Participants include 37,959 non-institutionalized 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 4,861 to 6,212.
Exposures
Calendar year, as represented by continuous NHANES cycle.
Main Outcome(s) and Measure(s)
Within each NHANES cycle, use of prescription drugs in the prior 30 days was assessed overall and by drug class. Temporal trends across cycles were evaluated. Analyses were weighted to represent the US adult population.
Results
Results indicate an increase in overall use of prescription drugs among US adults between 1999–2000 and 2011–2012 with an estimated 51% of US adults reporting use of any prescription drugs in 1999–2000 and an estimated 59% reporting use in 2011–2012 (Difference: 8%; 95% CI: 3.8%–12%; p-trend<0.001). The prevalence of polypharmacy (use of ≥5 prescription drugs) increased from an estimated 8.2% in 1999–2000 to 15% in 2011–2012 (Difference: 6.6%; 95% CI: 4.4%–8.2%; p-trend<0.001). These trends remained statistically significant with age adjustment. Among the 18 drug classes used by more than 2.5% of the population at any point over the study period, the prevalence 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 increases in overall prescription drug use and polypharmacy were observed. These increases persisted after accounting for changes in the age distribution of the population. The prevalence of prescription drug use increased in the majority of, but not all, drug classes.
Keywords: Adults, CDC, Centers for Disease Control and Prevention, National Health and Nutrition Examination Survey, NHANES, Prescription Drugs, Trends
INTRODUCTION
Use of prescription drugs represents a major expenditure in the United States (US),1 and research suggests that use of prescription drugs is increasing.2 Yet, much of the information on prescription use is derived from pharmacy databases, or expenditure data,1,3,4 neither of which directly captures use at the population-level. While several studies have sought to capture prescription drug use on the population-level,5–15 these studies are either outdated, narrower in scope, or are limited to certain populations, such as the elderly or those with a given clinical indication.
An updated, comprehensive assessment of prescription drug use is important, given that practice patterns are continually evolving to reflect the changing health needs of the population, advances in treatment, new clinical guidelines, the entrance or exit of drugs from the market, and shifts in policies regarding drug marketing and promotion. Given this dynamic climate, it is important to document patterns of prescription drugs to inform both clinical practice and research, while also identifying population subgroups with the potential for underuse, misuse, and polypharmacy.
Nationally-representative data from the National Health and Nutrition Examination Survey (NHANES) were used to estimate the prevalence of prescription drug use from 1999–2000 to 2011–2012.
METHODS
Data Source/Study Population
NHANES is a nationally-representative cross-sectional survey of civilian, non-institutionalized persons living in the US.16 Analyses are based on data collected from persons ages ≥20y 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 available. As a stratified, complex, multistage probability-based survey, NHANES oversamples older adults, low-income individuals, and certain racial/ethnic groups; participants were assigned weights to account for their unequal sampling probability and non-response.
All participants provided written informed consent, and data are publicly available. This study was deemed exempt from human subjects approval by the Harvard T.H. Chan School of Public Health Institutional Review Board.
Assessment of Prescription Drug Use
Information on prescription drug use was collected during a household interview. Participants were asked if they had taken prescription drugs over the prior 30 days. Those responding “yes” were asked to show the containers of all products; when unavailable, the participant was asked to report the medication name. For each drug reported, the interviewer entered the information into the computer, and the drug was linked to a prescription drug database (Lexicon Plus), which includes all prescription drugs available. This database was updated at the beginning of each survey year to include new products.
Most drug categories are presented as defined by the National Center for Health Statistics (NCHS). Some additional definitions were generated, including: anti-hypertensives, non-contraceptive hormones, antibiotics (including oral antibiotic-containing medications and antibiotic-containing dermatologic, ophthalmic, and respiratory medications), and oral antibiotics. Sub-classes of drugs within a given drug class are not presented if used by too few individuals to provide reliable estimates on the prevalence of use. Medications defined as ‘combination drugs’ are included within both ‘combinations’ as well as their component drug categories, to allow for tracking of both combination drugs and specific drug classes. For example, statin-containing combination drugs are classified as both ‘statins’ and ‘combination anti-hyperlipidemics’ to allow for simple quantification of trends in both statin-containing medications and the use of combination therapies.
Statistical Analysis
The prevalence of use within each 2-year NHANES cycle was estimated for any prescription drug use and use by drug class. Polypharmacy was defined as use of ≥5 drugs, a threshold commonly used in the literature.17 Additional results are presented for the most commonly used individual drugs in 2011–2012. Survey-weighted logistic regression was used to calculate a p-trend across survey cycles. Statistical significance of trends was assessed at the two-sided α=0.05 level. In the results presentation, an ‘increase’ refers to a p-trend<0.05 and ratio>1, a ‘decrease’ refers to a p-trend<0.05 and ratio <1, and ‘stable’ refers to a p-trend≥0.05. We have also presented the difference in prevalence in 2011–2012 vs. 1999–2000, although this in some cases may not represent the most extreme difference in use across years.
As changes in the age-distribution of the population may account for observed trends in prescription drug use, secondary age-adjusted analyses were conducted using standardization based on the US 2000 Standard Population (detailed in eTable 1 footnote).
Given potential for heterogeneity by population sub-groups, results were stratified by age (20–39y, 40–64y and ≥65y), sex, and race/ethnicity (non-Hispanic white, non-Hispanic black, and Mexican American). Data for other race/ethnicity groups were not included in the stratified analyses due to insufficient sample sizes to reliably estimate the prevalence of use. Results are presented for ‘Mexican Americans’ rather than overall ‘Hispanics,’ given temporal changes in data collection among Hispanics.18 Additional analyses evaluated race/ethnicity-stratified estimates with adjustment for age (as described above), and with further adjustment for insurance coverage. In analyses adjusted for both age and insurance, standardization was implemented using the age and insurance distribution of the 1999–2000 NHANES cycle. Given the large number of drug classes analyzed, results for a given overarching drug class are discussed if they meet any of the following criteria: i) prevalence of use >10% in any cycle; ii) prevalence >5%, with ≥1.50-fold change in use; or iii) prevalence >2.5%, with a ≥ 2.00-fold change in use. This approach was selected to focus on commonly used drugs, and on modestly used drugs with notable trends.
For drugs meeting the above-listed criteria, we have calculated an average annual percentage change (AAPC) and have conducted Joinpoint analyses, which use a permutation test to identify points of inflection, providing an annual percentage change (APC) before and after the point of inflection (more detail provided in eTable 2 footnote).19,20
All analyses account for complex survey design and post-stratification weighting using Stata 13.1 (College Station, TX).
RESULTS
In these NHANES cycles, the response rate for adults ≥20y was 73.6%,21 and 84% of medication containers were seen by interviewers. After excluding 65 individuals missing data on prescription drug use, the final sample size was 37,959; the sample size for individual NHANES cycles ranged from 4,861 to 6,212.
Table 1 shows the estimated percentage of US adults reporting any prescription medication in 2011–2012, as well as ≥5 prescription medications, overall and by population characteristics. Fifty-nine percent of adults used any prescription in the prior 30 days, while 39% of persons ≥65y reported polypharmacy. A significant increase in polypharmacy was observed in all age groups: specifically, among adults ages 20–39y, polypharmacy increased from 0.7% to 3.1%, while polypharmacy increased from 10% to 15% among adults ages 40–64y and from 24% to 39% among adults 65+y (Figure 1).
Table 1.
Overall | Any prescriptions | Polypharmacy (≥5 prescriptions) | |||||
---|---|---|---|---|---|---|---|
n | n | %b | 95% CI | n | %b | 95% CI | |
Overall | 5,558 | 3,144 | 59 | 55, 62 | 917 | 15 | 13,17 |
Age Group (years) | |||||||
20–39 | 1,957 | 596 | 35 | 32, 39 | 47 | 3.1 | 2.1, 4.6 |
40–64 | 2,352 | 1,428 | 65 | 62, 67 | 372 | 15 | 13, 17 |
≥65 | 1,249 | 1,120 | 90 | 87, 93 | 498 | 39 | 35, 44 |
Sex | |||||||
Male | 2,739 | 1,398 | 52 | 48, 57 | 418 | 13 | 10, 16 |
Female | 2,819 | 1,746 | 65 | 62, 67 | 499 | 16 | 14, 19 |
Race/ethnicity | |||||||
Non-Hispanic white | 2,040 | 1,377 | 66 | 63, 69 | 440 | 17 | 15, 20 |
Non-Hispanic black | 1,455 | 835 | 52 | 49, 55 | 266 | 14 | 12, 17 |
Non-Hispanic Asian | 794 | 335 | 41 | 36, 45 | 54 | 6.0 | 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 | 1,331 | 806 | 57 | 50, 64 | 296 | 19 | 16, 23 |
High school | 1,169 | 658 | 58 | 53, 64 | 196 | 15 | 12, 19 |
Some college | 1,657 | 901 | 57 | 52, 62 | 264 | 15 | 13, 19 |
≥ College | 1,396 | 776 | 61 | 57, 65 | 160 | 12 | 9.2, 14 |
Family income-to-poverty ratioc | |||||||
<1 (lowest income) | 1,303 | 677 | 49 | 43, 54 | 241 | 16 | 11, 21 |
1– <2 | 1,326 | 755 | 59 | 52, 65 | 258 | 18 | 15, 21 |
2– <4 | 1,167 | 662 | 58 | 51, 64 | 173 | 15 | 11, 19 |
≥4 (highest income) | 1,267 | 760 | 65 | 60, 69 | 148 | 12 | 10, 14 |
Insurance status (age<65yd) | |||||||
No insurance | 1,259 | 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 | 2,175 | 1,110 | 57 | 54, 60 | 171 | 9.1 | 7.5, 11 |
Body Mass Indexe(kg/m2) | |||||||
<18.5 | 103 | 50 | 59 | 50, 68 | 12 | 18 | 9.8, 32 |
18– <25 | 1,577 | 768 | 52 | 48, 57 | 148 | 8.4 | 5.5, 13 |
25– <30 | 1,684 | 939 | 57 | 52, 62 | 245 | 12 | 10, 15 |
30– <35 | 1,066 | 1,066 | 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 |
Table 1 presents the percent of the population using any prescriptions and the percent using ≥ 5 prescriptions within given socio-demographic groups. For example, 19% of adults with less than a high school education reported taking 5 or more prescription drugs.
All data are weighted to be nationally representative.
Ratio of family income to federal poverty level. In 2012, the federal poverty level for a family of 4 was $22,050. A family of 4 with an income of $40,000 would have a family income-to-poverty ratio of 1.81, indicating that their income is 181% greater than the federal poverty level.
Information on insurance status was obtained from the health insurance questionnaire, assessing whether the individual was covered by health insurance at the time of the survey. Limited to adults age<65y since 98.9% of adults age ≥ 65y reported having some form of health insurance.
Body mass index was calculated based on measured heights and weights. As measured heights and weights were available for 94.2% of respondents Mobile Exam Center weights were used for analyses of body mass index (interview weights were used in all other cases).
From 1999–2000 to 2011–2012, the percentage of adults reporting use of any prescription increased from an estimated 51% to 59% (Difference: 8%; 95% CI: 3.8%–12%). Polypharmacy increased from an estimated 8.2% to 15% (Difference: 6.6%; 95% CI: 4.4%–8.2%; Figure 1). The increase in any prescription drug use and polypharmacy remained statistically significant in age-adjusted models (detailed in eTable 1). All subsequent ranges presented correspond to the prevalence of use in 1999–2000 and 2011–2012.
Use of anti-hypertensives increased (20%–27%), with increases observed in most classes (Table 2). Anti-hyperlipidemics 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=4.0%; eTable 2). Use of anti-depressants increased (6.8%–13%), reflected by an increase in selective serotonin-norepinephrine reuptake inhibitors (SSNRIs) (0.4%–2.0%) and selective serotonin reuptake inhibitors (SSRIs) (4.3%–8.5%). Use of anti-depressants increased most in the early years, driven by a sharp increase in SSNRIs before 2005–2006 (APC=32%), after which the trend leveled off (APC=−0.2%).
Table 2.
1999–2000 (n=4,861) |
2001–2002 (n=5,399) |
2003–2004 (n=5,029) |
2005–2006 (n=4,970) |
2007–2008 (n=5,930) |
2009–2010 (n=6,212) |
2011–2012 (n=5,558) |
P-trend |
Difference in
Prevalence: 2011–2012 vs
1999–2000c % (95% CI) |
Ratio of Prevalence:
2011–2012
vs 1999–2000d Ratio (95% CI) |
|
---|---|---|---|---|---|---|---|---|---|---|
%a | % | % | % | % | % | % (95% CI) | ||||
Any prescription |
51 (48, 53) |
54 (50, 58) |
57 (55, 59) |
55 (53, 58) |
58 (55, 60) |
57 (54, 61) |
59 (55, 62) |
<.001 |
8.0 (3.8, 12) |
1.2 (1.1, 1.3) |
≥5 prescriptions |
8.2 (7.4, 9.2) |
11 (9.4, 12) |
14 (12, 16) |
14 (12, 15) |
15 (13, 17) |
14 (13, 15) |
15 (13, 17) |
<.001 |
6.6 (4.4, 8.2) |
1.8 (1.5, 2.1) |
Anti-hypertensive Agents |
20 (18, 22) |
20 (18, 23) |
24 (22, 27) |
25 (23, 27) |
26 (25, 28) |
27 (24, 30) |
27 (25, 30) |
<.001 |
8.2 (4.6, 12) |
1.4 (1.2, 1.6) |
ACE Inhibitors | 6.3 (5.3, 7.5) |
7.6 (7.0, 8.2) |
9.7 (8.5, 11) |
9.7 (8.5, 11) |
10 (9.0, 11) |
11 (10, 12) |
12 (10, 13) |
<.001 | 5.3 (3.4, 7.1) |
1.8 (1.5, 2.3) |
Angiotensin II Inhibitors | 2.1 (1.6, 2.8) |
3.0 (2.5, 3.7) |
4.7 (3.8, 5.7) |
4.5 (3.6, 5.6) |
6.5 (5.7, 7.4) |
6.5 (5.3, 8.0) |
5.8 (4.9, 6.9) |
<.001 | 3.6 (2.5, 4.8) |
2.7 (1.9, 3.7) |
Beta-blockers | 6.0 (5.2, 7.0) |
6.8 (5.6, 8.1) |
9.4 (8.5, 10) |
11 (9.2, 12) |
10 (9.2, 11) |
11 (9.8, 13) |
11 (8.7, 13) |
<.001 | 4.5 (2.4, 6.7) |
1.8 (1.4, 2.2) |
Cardioselective | 4.7 (3.9, 5.6) |
5.7 (4.7, 7.0) |
7.7 (6.9, 8.6) |
8.9 (7.4, 11) |
8.4 (7.5, 9.3) |
8.9 (7.7, 10) |
8.2 (6.5, 10) |
<.001 | 3.5 (1.5, 5.5) |
1.7 (1.3, 2.3) |
Non-cardioselective | 1.5 (1.3, 1.8) |
1.4 (1.1, 1.8) |
2.8 (2.3, 3.4) |
3.0 (2.5, 3.6) |
3.0 (2.4, 3.7) |
3.7 (3.0, 4.5) |
3.2 (2.8, 3.7) |
<.001 | 1.7 (1.2, 2.2) |
2.1 (1.7, 2.7) |
Calcium-channel Blockers | 6.3 (5.8, 6.9) |
5.3 (4.3, 6.6) |
6.7 (5.8, 7.8) |
7.1 (6.1, 8.3) |
6.2 (5.5, 7.1) |
6.7 (6.0, 7.5) |
6.5 (5.4, 7.8) |
.28 | 0.2 (−1.1, 1.5) |
1.0 (0.84, 1.3) |
Any Diuretic | 8.6 (7.3, 10) |
9.3 (7.6, 11) |
11 (9.9, 13) |
11 (9.8, 13) |
12 (10, 14) |
12 (11, 13) |
12 (11, 14) |
<.001 | 3.7 (1.6, 5.8) |
1.4 (1.2, 1.8) |
Loop | 2.5 (2.0, 3.0) |
2.6 (2.1, 3.3) |
3.1 (2.6, 3.8) |
2.7 (2.2, 3.4) |
2.9 (2.4, 3.7) |
2.9 (2.4, 3.5) |
2.7 (2.2, 3.4) |
.49 | 0.3 (−0.6, 1.1) |
1.1 (0.81, 1.5) |
Potassium-sparing | 2.3 (2.0, 2.8) |
2.0 (1.5, 2.7) |
2.6 (1.9, 3.4) |
2.1 (1.8, 2.4) |
2.4 (2.0, 2.9) |
2.0 (1.6, 2.5) |
1.6 (1.4, 1.9) |
.04 | −0.7 (−1.2, −0.2) |
0.70 (0.54, 0.90) |
Thiazide | 5.6 (4.4, 7.0) |
6.3 (5.0, 7.9) |
7.9 (6.8, 9.3) |
8.4 (7.1, 9.9) |
8.8 (7.7, 10) |
8.8 (7.5, 10) |
9.4 (8.2, 11) |
<.001 | 3.8 (2.0, 5.7) |
1.7 (1.3, 2.2) |
Anti-hypertensive Combinations | 3.6 (2.9, 4.5) |
4.1 (3.1, 5.3) |
5.6 (4.7, 6.7) |
5.0 (4.2, 6.1) |
6.1 (5.3, 7.1) |
6.3 (5.3, 7.5) |
5.4 (4.4, 6.6) |
<.001 | 1.8 (0.4, 3.2) |
1.5 (1.1, 2.0) |
Anti-hyperlipidemic Agents |
7.6 (6.9, 8.3) |
9.5 (8.0, 11) |
12 (11, 14) |
14 (13, 16) |
17 (16, 18) |
18 (16, 19) |
18 (16, 21) |
<.001 |
11 (8.5, 13) |
2.4 (2.1, 2.8) |
Fibric Acid Derivatives | 0.7 (0.4, 1.3) |
1.0 (0.7, 1.5) |
1.1 (0.8, 1.6) |
1.0 (0.7, 1.5) |
1.6 (1.2, 2.0) |
1.5 (1.1, 2.2) |
1.7 (1.2, 2.5) |
.002 | 1.0 (0.2, 1.8) |
2.3 (1.2, 4.7) |
Statins | 6.9 (6.4, 7.5) |
8.5 (7.1, 10) |
11 (9.6, 12) |
13 (12, 15) |
15 (14, 16) |
16 (15, 18) |
17 (15, 19) |
<.001 | 10.2 (8.1, 12.2) |
2.5 (2.1, 2.8) |
Anti-hyperlipidemic Combinations | – | – | ¶ | 1.0 (0.7-1.5) |
1.9 (1.5, 2.4) |
0.9 (0.7, 1.2) |
¶ | .07 | – | – |
Anti-depressants |
6.8 (5.8, 7.9) |
9.1 (8.0, 10) |
11 (9.9, 12) |
11 (10, 12) |
12 (11, 14) |
11 (9.4, 12) |
13 (11, 15) |
<.001 |
6.0 (3.5, 8.6) |
1.9 (1.5, 2.4) |
Phenylpiperazine | 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) |
.92 | 0.3 (−0.1, 0.7) |
1.3 (0.92, 1.9) |
SSNRIs | 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, 2.2) |
4.7 (2.6, 8.5) |
SSRIs | 4.3 (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, 10) |
<.001 | 4.2 (2.3, 6.1) |
2.0 (1.5, 2.6) |
Tricyclics | 1.2 (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 (−0.4, 0.7) |
1.1 (0.72, 1.8) |
Prescription Analgesics |
11 (10, 12) |
13 (12, 14) |
17 (15, 19) |
12 (10, 13) |
12 (10, 14) |
12 (10, 13) |
11 (9.2, 14) |
.13 | −0.1 (−2.6, 2.5) |
0.99 (0.79, 1.2) |
COX-2 Inhibitors | 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 (−2.0, −0.6) |
0.32 (0.17, 0.59) |
Narcotic Analgesics | 3.8 (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, 3.7) |
1.5 (1.0, 2.1) |
Prescription NSAIDse | 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) |
.03 | −1.4 (−2.7, −0.1) |
0.75 (0.57, 0.98) |
Salicylates | 0.6 (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 (−0.3, 0.3) |
1.0 (0.58, 1.8) |
Miscellaneous Analgesics | 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, 1.4) |
3.3 (1.8, 5.9) |
Sex Hormonesf |
19 (16, 21) |
21 (18, 24) |
14 (13, 16) |
12 (11, 14) |
12 (10, 14) |
10 (8.6, 12) |
11 (8.7, 13) |
<.001 | −7.9 (−11, −4.6) |
0.57 (0.45, 0.73) |
Contraceptive Hormonesf | 8.1 (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) |
.35 | −0.9 (−3.8, 1.9) |
0.88 (0.60, 1.3) |
Non-contraceptive Hormonesf | 12 (10, 15) |
14 (12, 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) |
<.001 | −8.5 (−11, −5.6) |
0.32 (0.23, 0.45) |
Anti-diabetic Agents |
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, 5.0) |
1.8 (1.4, 2.2) |
Biguanides | 2.0 (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) |
<.001 | 3.5 (2.5, 4.5) |
2.7 (2.0, 3.7) |
Insulin | 1.1 (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) |
<.001 | 1.5 (0.9, 2.1) |
2.3 (1.6, 3.3) |
Sulfonylureas | 2.6 (2.2, 3.2) |
2.7 (2.3, 3.1) |
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 (−0.4, 1.5) |
1.2 (0.88, 1.7) |
Thiazolidinediones | 0.5 (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 (−0.1, 0.7) |
1.6 (0.86, 2.9) |
Prescription Proton-pump Inhibitors |
3.9 (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, 11) |
9.3 (8.0, 11) |
7.8 (6.2, 9.6) |
<.001 |
3.9 (1.9, 5.9) |
2.0 (1.4, 2.8) |
Thyroid Hormones |
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) |
.007 |
1.3 (−0.2, 2.7) |
1.2 (0.98, 1.6) |
Anxiolytics, Sedatives, Hypnotics |
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, 3.3) |
1.5 (1.1, 1.9) |
Benzodiazapines | 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) |
.04 | 1.1 (0.2, 2.1) |
1.4 (1.0, 1.9) |
Anti-convulsants |
2.3 (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) |
<.001 |
3.2 (2.0, 4.3) |
2.3 (1.8, 3.1) |
Benzodiazapines | 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) |
.002 | 1.1 (0.4, 1.7) |
1.8 (1.3, 2.7) |
Gamma-aminobutyric acid analogs | ¶ | 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) |
<.001 | 1.8 (1.2, 2.4) |
7.4 (2.8, 19) |
Bronchodilators |
3.2 (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) |
<.001 |
1.9 (0.5, 3.4) |
1.6 (1.1, 2.2) |
Adrenergic Bronchodilators | 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, 3.4) |
1.7 (1.2, 2.4) |
Anti-cholinergic Bronchodilators | 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, 1.0) |
1.9 (1.2, 3.0) |
Bronchodilator Combinations | 0.3 (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) |
<.001 | 1.8 (1.0, 2.6) |
7.9 (4.6, 14) |
Antibiotics |
5.7 (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) |
<.001 | −1.4 (−2.3, −0.6) |
0.75 (0.63, 0.90) |
Oral antibiotics | 3.8 (3.2, 4.4) |
3.6 (2.9, 4.5) |
3.7 (3.1, 4.4) |
3.4 (2.6, 4.4) |
2.8 (2.3, 3.3) |
2.7 (2.3, 3.2) |
2.9 (2.5, 3.3) |
<.001 | −0.9 (−1.6, −0.1) |
0.77 (0.63, 0.96) |
Anti-arrhythmic Agents |
4.9 (4.5, 5.4) |
4.5 (3.8, 5.3) |
4.3 (3.7, 5.0) |
4.5 (3.8, 5.3) |
3.4 (2.8, 4.1) |
3.0 (2.5, 3.7) |
2.7 (2.1, 3.5) |
<.001 | −2.2 (−3.0, −1.4) |
0.55 (0.42, 0.73) |
Class IV | 2.7 (2.4, 2.9) |
2.4 (1.9, 2.9) |
2.1 (1.7, 2.6) |
2.2 (1.8, 2.8) |
1.3 (1.0, 1.6) |
1.4 (1.1, 1.8) |
1.0 (0.6, 1.5) |
<.001 | −1.7 (−2.2, −1.2) |
0.52 (0.30, 0.89) |
Class V | 1.4 (1.1, 1.8) |
1.0 (0.8, 1.3) |
1.1 (0.8, 1.5) |
0.9 (0.6, 1.3) |
0.7 (0.5, 0.9) |
0.5 (0.3, 1.0) |
0.7 (0.4, 1.0) |
<.001 | −0.8 (−1.2, −0.3) |
0.83 (0.42, 1.6) |
Coagulation Modifiers |
2.3 (1.9, 2.8) |
2.6 (2.1, 3.1) |
3.3 (2.6, 4.2) |
3.8 (3.1, 4.8) |
4.8 (4.1, 5.6) |
4.8 (3.9, 5.8) |
4.0 (3.4, 4.8) |
<.001 |
1.8 (0.9, 2.6) |
1.8 (1.4, 2.3) |
Anti-coagulants | 1.3 (0.9, 1.8) |
1.5 (1.2, 1.9) |
1.4 (1.1, 1.9) |
1.7 (1.5, 2.0) |
1.9 (1.4, 2.6) |
1.8 (1.4, 2.4) |
1.7 (1.3, 2.1) |
.04 | 0.4 (−0.2, 1.0) |
1.3 (0.87, 2.0) |
Warfarin | 1.3 (0.9, 1.8) |
1.4 (1.1, 1.8) |
1.4 (1.1, 1.9) |
1.7 (1.5, 2.0) |
1.9 (1.4, 2.6) |
1.8 (1.4, 2.3) |
1.5 (1.1, 2.1) |
.10 | 0.3 (−0.3, 0.9) |
1.2 (0.79, 1.9) |
Anti-platelet Agents | 0.9 (0.7, 1.2) |
1.1 (0.8, 1.4) |
1.8 (1.4, 2.4) |
2.2 (1.6, 3.0) |
2.9 (2.3, 3.5) |
3.1 (2.4, 4.0) |
2.4 (1.9, 3.0) |
<.001 | 1.5 (0.9, 2.1) |
2.7 (1.9, 3.9) |
Clopidogrel | 0.3 (0.2, 0.4) |
0.5 (0.4, 0.8) |
1.3 (0.9, 1.8) |
1.6 (1.1, 2.4) |
1.9 (1.5, 2.4) |
1.3 (0.9, 2.0) |
1.6 (1.2, 2.0) |
<.001 | 1.3 (0.9, 1.7) |
6.1 (3.6, 10) |
Muscle Relaxants |
1.2 (0.9, 1.7) |
1.6 (1.2, 2.2) |
2.6 (2.2, 3.0) |
2.2 (1.8, 2.7) |
2.2 (1.8, 2.8) |
2.0 (1.6, 2.6) |
2.5 (1.8, 3.5) |
.008 |
1.3 (0.4, 2.2) |
2.0 (1.3, 3.2) |
Nasal Preparations |
1.9 (1.5, 2.3) |
2.0 (1.5, 2.6) |
2.6 (2.0, 3.2) |
3.4 (2.8, 4.1) |
2.3 (1.8, 2.9) |
2.2 (1.7, 3.0) |
2.5 (1.9, 3.3) |
.16 |
0.7 (−0.1, 1.5) |
1.4 (0.96, 1.9) |
Nasal Steroids | 1.7 (1.4, 2.2) |
1.9 (1.5, 2.6) |
2.4 (1.9, 3.1) |
3.2 (2.7, 3.9) |
2.1 (1.6, 2.8) |
2.1 (1.5, 2.7) |
2.2 (1.8, 2.8) |
.39 | 0.5 (−0.2, 1.2) |
1.3 (0.91, 1.8) |
H2 Antagonists |
2.1 (1.6, 2.9) |
1.8 (1.4, 2.4) |
2.4 (1.9, 3.1) |
1.7 (1.3, 2.2) |
2.2 (1.7, 2.8) |
3.0 (2.3, 3.8) |
2.4 (1.9, 3.1) |
.08 |
0.3 (−0.6, 1.2) |
1.1 (0.76, 1.7) |
Prescription Anti-histamines |
3.9 (3.3, 4.5) |
5.0 (4.1, 6.1) |
4.2 (3.5, 4.9) |
4.4 (3.8, 5.1) |
4.0 (3.4, 4.7) |
2.8 (2.2, 3.7) |
2.1 (1.6, 2.7) |
<.001 | −1.8 (−2.6, −1.0) |
0.54 (0.40, 0.72) |
Peripherally-acting Anti-adrenergic Agents |
1.6 (1.3, 2.0) |
1.4 (1.1, 1.9) |
1.7 (1.4, 2.1) |
1.7 (1.3, 2.1) |
2.0 (1.6, 2.6) |
1.9 (1.6, 2.2) |
2.1 (1.6, 2.8) |
.01 |
0.5 (−0.1, 1.2) |
1.3 (0.95, 1.9) |
5-alpha Reductase Inhibitorsg | ¶ | ¶ |
0.7 (0.5, 1.1) |
1.0 (0.6, 1.5) |
1.5 (1.1, 2.0) |
1.4 (0.8, 2.2) |
2.0 (1.5, 2.7) |
<.001 |
1.6 (0.9, 2.3) |
5.4 (2.1, 14) |
Anti-emetic/Anti-vertigo Agents |
1.8 (1.3, 2.5) |
2.1 (1.6, 2.7) |
2.0 (1.4, 2.7) |
2.0 (1.5, 2.5) |
2.4 (2.0, 2.8) |
1.8 (1.4, 2.5) |
2.0 (1.5, 2.7) |
.72 |
0.2 (−0.6, 1.0) |
1.1 (0.73, 1.7) |
CNS Stimulants | ¶ |
0.6 (0.4, 1.1) |
¶ |
0.9 (0.7, 1.2) |
1.1 (0.8, 1.6) |
0.8 (0.6, 1.1) |
1.8 (1.1, 2.8) |
<.001 |
1.3 (0.5, 2.2) |
4.1 (1.7, 9.7) |
Anti-psychotics |
1.2 (0.7, 2.0) |
1.2 (0.8, 1.7) |
1.2 (0.7, 1.9) |
1.4 (1.0, 1.8) |
1.4 (1.0, 2.0) |
1.3 (1.0, 1.8) |
1.7 (1.3, 2.1) |
.15 |
0.4 (−0.3, 1.2) |
1.4 (0.77, 2.4) |
Atypical Anti-psychotics | ¶ | 0.8 (0.5, 1.3) |
0.8 (0.5, 1.3) |
1.1 (0.8, 1.5) |
1.2 (0.9, 1.7) |
1.0 (0.7, 1.3) |
1.3 (1.0, 1.7) |
.006 | 0.7 (0.2, 1.2) |
2.2 (1.1, 4.4) |
Glucocorticoids |
2.2 (1.8, 2.8) |
1.8 (1.4, 2.4) |
1.5 (1.2, 1.9) |
1.6 (1.2, 2.2) |
1.2 (1.0, 1.6) |
1.2 (0.9, 1.6) |
1.5 (1.2, 2.0) |
.004 | −0.7 (−1.3, −0.1) |
0.69 (0.48, 0.97) |
Prescription Ophthalmic Preparations |
1.0 (0.8, 1.4) |
1.1 (0.9, 1.5) |
1.5 (1.1, 2.0) |
1.4 (1.0, 1.8) |
1.5 (1.3, 1.7) |
1.6 (1.3, 1.9) |
1.5 (1.1, 2.0) |
.03 |
0.4 (−0.1, 1.0) |
1.4 (0.94, 2.2) |
Ophthalmic Glaucoma Agents | 0.8 (0.6, 1.1) |
0.9 (0.6, 1.3) |
1.2 (0.8, 1.7) |
1.0 (0.8, 1.4) |
0.9 (0.8, 1.1) |
1.1 (0.9, 1.3) |
1.0 (0.7, 1.3) |
.44 | 0.2 (−0.2, 0.5) |
1.2 (0.78, 1.9) |
Anti-viral Agents |
0.5 (0.3, 1.0) |
0.5 (0.3, 0.9) |
0.3 (0.2, 0.6) |
0.7 (0.4, 1.1) |
0.7 (0.5, 1.0) |
0.7 (0.5, 1.1) |
1.4 (1.0, 1.9) |
<.001 |
0.9 (0.3, 1.4) |
2.7 (1.3, 5.6) |
Anti-Parkinson Agents |
0.7 (0.5, 1.0) |
0.6 (0.4, 1.0) |
0.5 (0.3, 0.8) |
0.8 (0.6, 1.1) |
0.9 (0.7, 1.2) |
0.9 (0.6, 1.2) |
1.3 (0.9, 1.9) |
.002 |
0.6 (0.1, 1.2) |
1.9 (1.2, 3.2) |
Prescription Dermatologic Agents |
1.0 (0.7, 1.3) |
1.4 (0.9, 2.1) |
1.8 (1.3, 2.4) |
1.2 (0.8, 1.6) |
0.9 (0.6, 1.3) |
1.3 (1.0, 1.7) |
1.2 (0.8, 1.9) |
.76 |
0.3 (−0.3, 0.9) |
1.3 (0.75, 2.2) |
Anti-gout Agents |
0.7 (0.5, 1.0) |
1.1 (0.8, 1.6) |
0.7 (0.5, 0.9) |
1.2 (0.9, 1.6) |
1.3 (0.9, 1.8) |
1.4 (1.0, 1.9) |
1.1 (0.7, 1.6) |
.02 |
0.4 (−0.1, 0.9) |
1.6 (0.94, 2.6) |
Leukotriene Modifiers |
0.4 (0.3, 0.6) |
0.8 (0.5, 1.2) |
1.1 (0.8, 1.5) |
1.3 (0.9, 1.9) |
1.1 (0.9, 1.5) |
1.2 (0.9, 1.7) |
1.1 (0.7, 1.7) |
.003 |
0.7 (0.2, 1.2) |
2.6 (1.5, 4.5) |
Urinary Anti-spasmodics |
0.8 (0.5, 1.3) |
0.6 (0.5, 0.8) |
0.8 (0.5, 1.2) |
1.0 (0.8, 1.3) |
1.1 (0.8, 1.4) |
1.1 (0.7, 1.6) |
0.9 (0.6, 1.4) |
.14 |
0.1 (−0.5, 0.7) |
1.1 (0.58, 2.2) |
Anti-anginal Agents |
1.5 (1.2, 2.0) |
1.3 (1.0, 1.5) |
1.1 (0.8, 1.6) |
1.1 (0.8, 1.6) |
0.8 (0.6, 1.2) |
0.7 (0.5, 0.9) |
0.8 (0.6, 1.0) |
<.001 | −0.8 (−1.2, −0.3) |
0.50 (0.33, 0.75) |
Bone-resorption Inhibitors |
0.6 (0.4, 0.8) |
1.3 (1.1, 1.6) |
2.2 (1.8, 2.7) |
2.0 (1.5, 2.7) |
2.2 (1.8, 2.8) |
1.7 (1.5, 2.0) |
0.8 (0.5, 1.2) |
.12 |
0.3 (−0.1, 0.6) |
1.5 (0.82, 2.6) |
Anti-neoplastic Hormones |
2.0 (1.6, 2.6) |
1.9 (1.6, 2.4) |
1.3 (1.0, 1.8) |
1.1 (0.9, 1.5) |
1.1 (0.9, 1.4) |
1.1 (0.7, 1.6) |
0.7 (0.5, 1.2) |
<.001 | −1.3 (−1.9, −0.7) |
0.37 (0.22, 0.61) |
Inotropic Agents (Digoxin) |
1.4 (1.1,1.8) |
1.0 (0.8,1.3) |
1.1 (0.8,1.5) |
0.9 (0.6,1.3) |
0.7 (0.5, 0.9) |
0.5 (0.3,1.0) |
0.7 (0.4,1.0) |
<.001 |
−0.8 (−1.2, −0.3) |
0.47 (0.28, 0.77) |
Respiratory-inhalant Products |
0.9 (0.7,1.3) |
1.2 (0.9,1.7) |
0.8 (0.5,1.1) |
0.8 (0.5,1.3) |
0.9 (0.7,1.3) |
0.7 (0.5,1.1) |
0.6 (0.4,1.0) |
.046 |
−0.3 (−0.7,0.1) |
0.69 (0.40,1.2) |
Inhaled Corticosteroids | 0.9 (0.7, 1.1) |
1.0 (0.7, 1.5) |
0.7 (0.5, 1.1) |
0.7 (0.4, 1.3) |
0.9 (0.6, 1.2) |
0.6 (0.4, 0.9) |
0.6 (0.4, 1.0) |
.06 | −0.3 (−0.6, 0.1) |
0.70 (0.40, 1.2) |
Selective Estrogen Receptor Modulators6 |
1.1 (0.8,1.6) |
1.6 (1.2,2.1) |
1.4 (1.0,2.1) |
1.4 (0.9, 2.0) |
1.4 (1.0,1.8) |
1.0 (0.7,1.5) |
¶ | .01 |
−0.3 (−0.6, 0.0) |
0.54 (0.26,1.1) |
ABBREVIATION: ACE (Angiotensin Converting Enzyme); COX-2 (Cyclooxygenase-2); NSAID (Non-Steroidal Anti-Inflammatory Drug); SSNRI (Selective Serotonin–Norepinephrine Reuptake Inhibitor); SSRI (Selective Serotonin Reuptake Inhibitor)
All data are weighted to be nationally representative.
Overarching drug classes are presented in order of descending prevalence in 2011–2012.
Difference in prevalence represents the absolute increase or decrease in prevalence of use between 1999–2000 and 2011–2012.
Ratio of prevalence represents the relative increase or decrease in prevalence of use between 1999–2000 and 2011–2012.
Excludes COX-2 inhibitors
Analyses limited to women
Analyses limited to men
– No use
Data withheld due to relative standard error >30%; results for a given survey cycle are not presented if the relative standard error (RSE=[SE of prevalence/prevalence]*100) exceeds 30%, as denoted by ‘¶’, consistent with NHANES analytic guidelines.40
Prescription analgesic use remained stable (11%), although trends differed by type. Use of cyclooxygenase-2 (COX-2) inhibitors decreased from 1.9% to 0.6%, while the prevalence of narcotic analgesic use rose from 3.8% to 5.7%. Notably, narcotic analgesics increased before 2003–2004 (APC=12%), after which use leveled off (APC=−1.2%).
Use of sex hormones among women decreased from 19% to 11%, which was a change primarily driven by a decline in use of non-contraceptive hormones (12% to 4.0%, a drug class composed largely of menopausal hormone therapy). Anti-diabetic agents increased from 4.6% to 8.2%, with increases observed for biguanides, insulin, and sulfonylureas. Although use of thiazolidinediones remained unchanged overall, a significant joinpoint was observed in 2003–2004, before which use increased (APC=48%) and after which use decreased (APC=−8.8%).
Use of prescription PPIs increased (3.9%–7.8%), as did use of anti-convulsants (2.3%–5.5%). Notably, use of anti-convulsants increased most in the early years, with an APC of 16% observed before 2003–2004, and an APC of 3.0% observed thereafter. Use of bronchodilators increased (3.2%–5.2%) overall, with use of adrenergic bronchodilators increasing most before 2007–2008 (APC=6.6%), after which use leveled off (APC=−1.2%). Use of bronchodilator combinations increased sharply before 2003–2004 (APC= 66%), after which the APC=2.2%. Further, use of muscle relaxants increased (1.2%–2.5%), with the increase sharpest in the period between 1999–2000 and 2003–2004 (APC prior to 2003–2003 =19%, −1.7% thereafter). Lastly, use of antibiotics decreased from 5.7% to 4.2% over the study period.
Prescription drug use increased significantly among persons 40–64y (57%–65%) and ≥65y (from 84%–90%), but not among adults 20–39y (32–35%) (Figure 1, panel B). For specific drug classes, trends were generally similar by age and sex, with some exceptions (Table 3; eTables 3 and 4). For example, use of prescription analgesics did not change among adults aged 40–64y (13%–14%), but significantly decreased among adults aged 65+y (18%–14%). Use of muscle relaxants increased significantly among women (1.2%–3.3%) but not among men (1.3%–1.7%).
Table 3.
Age 40–64 | Age ≥65 | |||||||||
---|---|---|---|---|---|---|---|---|---|---|
1999–2000 (n=1,787) % |
2011–2012 (n=2,352) % (95% CI) |
P-trend |
Difference
in Prevalenced % (95% CI) |
Ratio
of Prevalencee Ratio (95% CI) |
1999–2000 (n=1,382) % |
2011–2012 (n=1,249) % (95% CI) |
P-trend |
Difference
in Prevalenced % (95% CI) |
Ratio
of Prevalencee Ratio (95% CI) |
|
Any prescription | 57 (52, 63) | 65 (62, 67) | 0.01 | 7.4 (1.7, 13) | 1.1 (1.0, 1.2) | 84 (81, 86) | 90 (87, 93) | <.001 | 6.5 (2.8, 10) | 1.1 (1.0, 1.1) |
≥5 prescriptions | 10 (8.8, 12) | 15 (13, 17) | 0.002 | 4.4 (1.8, 6.9) | 1.4 (1.2, 1.7) | 24 (21, 26) | 39 (35, 44) | <.001 | 16 (10, 21) | 1.7 (1.4, 1.9) |
Anti-hypertensive Agents | 24 (21, 28) | 31 (28, 33) | <.001 | 6.4 (2.0, 11) | 1.3 (1.1, 1.5) | 55 (50, 59) | 66 (62, 69) | <.001 | 11 (5.9, 17) | 1.2 (1.1, 1.3) |
Anti-hyperlipidemic Agents | 11 (8.9, 13) | 21 (18, 24) | <.001 | 10 (6.5, 14) | 2.0 (1.6, 2.4) | 21 (17, 25) | 47 (44, 51) | <.001 | 27 (22, 32) | 2.3 (1.9, 2.7) |
Anti-depressants | 8.4 (7.0, 10) | 15 (13, 18) | <.001 | 6.9 (3.9, 9.8) | 1.8 (1.4, 2.3) | 8.4 (6.8, 10) | 17 (13, 22) | <.001 | 8.8 (4.3, 13) | 2.0 (1.5, 2.8) |
Prescription Analgesics | 13 (12, 15) | 14 (11, 18) | .27 | 0.4 (−3.3, 4.2) | 1.0 (0.79, 1.3) | 18 (16, 21) | 14 (11, 18) | .01 | −3.9 (−8.4, 0.7) | 0.79 (0.59, 1.1) |
Sex Hormonesf | 24 (19, 29) | 9.7 (7.5, 12) | <.001 | −14 (−20, −8.8) | 0.41 (0.28, 0.53) | 16 (12, 22) | 3.9 (2.0, 7.5) | <.001 | −13 (−18, −7.3) | 0.24 (0.08, 0.40) |
Anti-diabetic Agents | 5.5 (4.2, 7.3) | 9.4 (7.9, 11) | <.001 | 3.9 (1.7, 6.1) | 1.7 (1.3, 2.3) | 13 (11, 15) | 19 (17, 22) | <.001 | 6.5 (3.4, 9.7) | 1.5 (1.3, 1.8) |
Prescription Protonpump Inhibitors | 4.9 (3.4, 7.1) | 8.3 (5.8, 12) | .006 | 3.4 (0.0, 6.7) | 1.7 (1.0, 2.7) | 8.2 (6.4, 10) | 18 (14, 22) | <.001 | 9.6 (5.4, 14) | 2.2 (1.6, 2.9) |
Thyroid Hormones | 5.9 (4.6, 7.4) | 6.9 (5.1, 9.2) | .13 | 1.0 (−1.4, 3.4) | 1.2 (0.82, 1.7) | 13 (11, 17) | 15 (12, 18) | .25 | 1.6 (−2.7, 5.8) | 1.1 (0.84, 1.5) |
Anxiolytics, Sedatives, Hypnotics | 5.5 (4.1, 7.3) | 6.7 (5.1, 8.7) | .17 | 1.2 (−1.2, 3.6) | 1.2 (0.83, 1.8) | 8.6 (6.8, 11) | 9.3 (7.7, 11) | .52 | 0.7 (−1.9, 3.4) | 1.1 (0.81, 1.4) |
Anti-convulsants | 3.1 (2.1, 4.8) | 5.8 (4.3, 7.8) | .002 | 2.7 (0.5, 4.8) | 1.8 (1.1, 3.0) | 4.5 (3.5, 5.8) | 9 (6.5, 12) | <.001 | 4.5 (1.5, 7.4) | 2.0 (1.4, 2.9) |
Bronchodilators | 3.4 (2.5, 4.5) | 6.0 (4.0, 8.7) | .002 | 2.6 (0.1, 5.1) | 1.8 (1.1, 2.8) | 6.3 (4.2, 9.2) | 7.3 (5.8, 9.2) | .14 | 1.1 (−1.8, 3.9) | 1.2 (0.77, 1.8) |
Antibiotics | 5.9 (4.5, 7.6) | 3.7 (2.5, 5.6) | .009 | −2.1 (−4.2, −0.1) | 0.64 (0.40, 1.0) | 4.4 (3.2, 6.0) | 3.5 (2.2, 5.4) | .014 | −0.9 (−2.9, 1.1) | 0.80 (0.47, 1.3) |
Anti-arrhythmic Agents | 5.4 (4.7, 6.2) | 2.1 (1.6, 2.7) | <.001 | −3.3 (−4.3, −2.4) | 0.38 (0.28, 0.51) | 17 (14, 19) | 9.0 (6.9, 12) | <.001 | −7.5 (−11, −4.0) | 0.54 (0.40, 0.74) |
Coagulation Modifiers | 2.7 (1.9, 3.8) | 2.8 (1.9, 3.9) | .02 | 0.0 (−1.3, 1.3) | 1.0 (0.64, 1.6) | 7.0 (5.6, 8.9) | 15 (13, 18) | <.001 | 7.9 (5.0, 11) | 2.1 (1.6, 2.8) |
Muscle Relaxants | 1.8 (1.1, 2.9) | 3.4 (2.4, 4.7) | .04 | 1.6 (0.2, 3.0) | 1.9 (1.1, 3.3) | 1.1 (0.6, 1.9) | 2.6 (0.9, 7) | .19 | 1.5 (−1.2, 4.2) | 2.4 (0.79, 7.2) |
H2 Antagonists | 1.9 (1.2, 2.9) | 2.2 (1.2, 4) | .34 | 0.3 (−1.2, 1.8) | 1.2 (0.58, 2.4) | 5.8 (3.7, 9.1) | 4.9 (3.3, 7.1) | .45 | −0.9 (−4.0, 2.2) | 0.84 (0.48, 1.5) |
Prescription Anti-histamines | 4.6 (3.3, 6.3) | 2.0 (1.3, 2.9) | <.001 | −2.6 (−4.2, −1.0) | 0.43 (0.27, 0.69) | 3.9 (2.7, 5.4) | 3.3 (1.9, 5.6) | .09 | −0.6 (−2.7, 1.6) | 0.85 (0.46, 1.6) |
Anti-emetic/Anti-vertigo Agents | 2.6 (1.7, 3.8) | 2.1 (1.3, 3.3) | .54 | −0.5 (−1.8, .9) | 0.81 (0.46, 1.4) | 3.8 (2.1, 6.6) | 3.6 (2.4, 5.6) | .38 | −0.1 (−2.7, 2.4) | 0.97 (0.49, 1.9) |
Glucocorticoids | 2.7 (2.1, 3.5) | 1.8 (1.2, 2.8) | .01 | −0.9 (−1.9, 0.1) | 0.66 (0.41, 1.1) | 3.8 (2.7, 5.2) | 2.4 (1.7, 3.4) | .02 | −1.4 (−2.8, 0.1) | 0.64 (0.41, 1.0) |
Male | Female | |||||||||
1999–2000 (n=2,261) % |
2011–2012 (n=2,352) % (95% CI) |
P-trend |
Difference
in Prevalenced % (95% CI) |
Ratio
of Prevalencee Ratio (95% CI) |
1999–2000 (n=1,382) % |
2011–2012 (n=1,249) % (95% CI) |
P-trend |
Difference
in Prevalenced % (95% CI) |
Ratio
of Prevalencee Ratio (95% CI) |
|
Any prescription | 42 (39, 45) | 52 (48, 57) | <.001 | 11 (5.4, 16) | 1.3 (1.1, 1.4) | 59 (55, 63) | 65 (62, 67) | .03 | 5.7 (0.7, 11) | 1.1 (1.0, 1.2) |
≥5 prescriptions | 5.8 (5.2, 6.6) | 13 (10, 16) | <.001 | 7.2 (4.3, 10) | 2.2 (1.8, 2.8) | 10 (9.0, 12) | 16 (15, 19) | <.001 | 6.0 (3.5, 8.6) | 1.6 (1.3, 1.9) |
Anti-hypertensive Agents | 18 (16, 21) | 26 (23, 30) | <.001 | 8.0 (3.6, 12) | 1.4 (1.2, 1.7) | 21 (18, 24) | 29 (26, 32) | <.001 | 7.7 (3.9, 12) | 1.4 (1.2, 1.6) |
Anti-hyperlipidemic Agents | 8.6 (7.4, 10) | 19 (16, 22) | <.001 | 10 (7.3, 14) | 2.2 (1.8, 2.7) | 6.7 (5.8, 7.7) | 18 (15, 20) | <.001 | 11 (8.5, 14) | 2.7 (2.2, 3.2) |
Anti-depressants | 4.1 (3.1, 5.4) | 8.8 (7.2, 11) | <.001 | 4.8 (2.6, 6.9) | 2.2 (1.6, 3.0) | 9.3 (7.7, 11) | 17 (14, 20) | <.001 | 7.2 (3.6, 11) | 1.8 (1.4, 2.3) |
Prescription Analgesics | 9.4 (8.0, 11) | 9.7 (7.6, 12) | .73 | 0.2 (−2.5, 3.0) | 1.0 (0.78, 1.4) | 13 (11, 15) | 13 (10, 16) | .04 | −0.4 (−3.5, 2.8) | 0.97 (0.76, 1.2) |
Anti-diabetic Agents | 4.6 (3.5, 6.0) | 9.1 (7.7, 11) | <.001 | 4.5 (2.6, 6.4) | 2.0 (1.5, 2.7) | 4.6 (3.7, 5.8) | 7.4 (6.2, 8.8) | <.001 | 2.8 (1.2, 4.4) | 1.6 (1.2, 2.0) |
Prescription Protonpump Inhibitors | 3.4 (2.3, 4.9) | 7.0 (5.1, 9.4) | <.001 | 3.6 (1.1, 6.0) | 2.1 (1.3, 3.3) | 4.3 (3.3, 5.7) | 8.5 (6.6, 11) | <.001 | 4.2 (1.8, 6.6) | 2.0 (1.4, 2.8) |
Thyroid Hormones | 2.0 (1.3, 3.0) | 3.2 (2.3, 4.6) | .04 | 1.2 (−0.2, 2.7) | 1.6 (0.96, 2.8) | 8.0 (6.7, 9.4) | 9.3 (7.8, 11) | .02 | 1.3 (−0.7, 3.3) | 1.2 (0.93, 1.5) |
Anxiolytics, Sedatives, Hypnotics | 3.0 (2.2, 4.3) | 5.3 (4.0, 7.0) | .002 | 2.3 (0.5, 4.1) | 1.8 (1.2, 2.7) | 5.2 (4.1, 6.6) | 6.8 (5.4, 8.5) | .01 | 1.5 (−0.4, 3.5) | 1.3 (0.94, 1.8) |
Anti-convulsants | 1.8 (1.3, 2.4) | 4.9 (3.9, 6.2) | <.001 | 3.1 (1.9, 4.4) | 2.8 (1.9, 3.9) | 2.8 (2.0, 3.9) | 6.0 (4.8, 7.6) | <.001 | 3.2 (1.5, 4.8) | 2.1 (1.5, 3.1) |
Bronchodilators | 2.3 (1.6, 3.2) | 5.0 (3.6, 6.9) | .001 | 2.7 (0.9, 4.5) | 2.2 (1.4, 3.4) | 4.1 (3.0, 5.5) | 5.3 (4, 6.9) | .006 | 1.2 (−0.6, 3.1) | 1.3 (0.88, 1.9) |
Antibiotics | 4.6 (3.8, 5.6) | 3.7 (2.7, 5.0) | .047 | −0.9 (−2.3, 0.5) | 0.79 (0.56, 1.1) | 6.6 (5.4, 8.0) | 4.8 (3.7, 6.2) | .001 | −1.7 (−3.4, 0.1) | 0.72 (0.53, 0.99) |
Anti-arrhythmic Agents | 4.6 (3.6, 5.8) | 2.7 (1.8, 4) | .001 | −1.9 (−3.4, −0.4) | 0.58 (0.37, 0.92) | 5.3 (4.4, 6.2) | 2.8 (2.2, 3.5) | <.001 | −2.5 (−3.5, −1.4) | 0.53 (0.40, 0.70) |
Coagulation Modifiers | 2.3 (1.7, 3.3) | 4.1 (3.0, 5.7) | <.001 | 1.8 (0.2, 3.3) | 1.8 (1.1, 2.7) | 2.2 (1.5, 3.3) | 3.9 (3.3, 4.7) | <.001 | 1.7 (0.6, 2.9) | 1.8 (1.2, 2.7) |
Muscle Relaxants | 1.3 (0.7, 2.2) | 1.7 (1.1, 2.8) | .27 | 0.5 (−0.6, 1.5) | 1.4 (0.68, 2.8) | 1.2 (0.8, 1.9) | 3.3 (2.4, 4.4) | .001 | 2.0 (0.9, 3.2) | 2.7 (1.6, 4.3) |
H2 Antagonists | 1.7 (1.3, 2.3) | 2.1 (1.6, 2.8) | .04 | 0.4 (−0.4, 1.1) | 1.2 (0.82, 1.8) | 2.4 (1.5, 3.9) | 2.7 (1.9, 3.9) | .30 | 0.3 (−1.2, 1.7) | 1.1 (0.63, 1.9) |
Prescription Anti-histamines | 2.8 (2.0, 3.8) | 1.4 (0.8, 2.2) | <.001 | −1.4 (−2.5, −0.3) | 0.49 (0.28, 0.87) | 4.9 (3.8, 6.3) | 2.7 (2.1, 3.6) | <.001 | −2.1 (−3.5, −0.7) | 0.56 (0.39, 0.80) |
Anti-emetic/Anti-vertigo Agents | 1.2 (0.9, 1.7) | 1.4 (0.9, 2.1) | .62 | 0.2 (−0.5, 0.9) | 1.2 (0.69, 2.0) | 2.4 (1.5, 3.7) | 2.6 (1.8, 3.7) | .85 | 0.2 (−1.1, 1.6) | 1.1 (0.64, 1.9) |
Glucocorticoids | 2.0 (1.5, 2.7) | 1.5 (1.0, 2.4) | .04 | −0.5 (−1.4, 0.4) | 0.76 (0.45, 1.3) | 2.5 (1.8, 3.3) | 1.5 (1.1, 2.1) | .02 | −0.9 (−1.8, 0.0) | 0.63 (0.41, 0.96) |
Results for adults ages 20–39 not presented due to small numbers; however, these results are presented in eTable 4.
Overarching drug classes are presented in order of descending prevalence in 2011–2012.
All data are weighted to be nationally representative.
Difference in prevalence represents the absolute increase or decrease in prevalence of use between 1999–2000 and 2011–2012.
Ratio of prevalence represents the relative increase or decrease in prevalence of use between 1999–2000 and 2011–2012.
Analyses limited to women
Data withheld due to relative standard error >30%; Results for a given survey cycle are not presented if the relative standard error (RSE=[SE of prevalence/prevalence]*100) exceeds 30%, as denoted by ‘¶’, consistent with NHANES analytic guidelines.40
Although significant increases in the percentage of persons using ≥5 prescriptions were observed in all racial/ethnic groups (eTable 5), an overall increase in prescription drug use was evident among non-Hispanic whites (55%–66%) and non-Hispanic blacks (43%–52%), but not Mexican Americans (30%–33%). This pattern remained unchanged with age-adjustment and the prevalence of use among Mexican Americans remained markedly lower than non-Hispanic whites, although the difference was attenuated somewhat (eTable 6). Further sensitivity analyses revealed that this difference in any prescription use was not entirely accounted for by adjustment for insurance status, either, although race/ethnicity-specific differences in polypharmacy were attenuated (eTable 6 and eTable 7).
The most commonly used individual drug in 2011–2012 was simvastatin (7.9%), increasing from 2.0% in 1999–2000 (eTable 8 and Figure 2). The remaining top-10 drugs included: lisinopril, levothyroxine, metoprolol, metformin, hydrochlorothiazide, omeprazole, amlodipine, atorvastatin, and albuterol; all increased except atorvastatin.
COMMENT
Overall, prescription drug use increased among US adults between 1999–2000 and 2011–2012, as reflected by an increase in any prescription drug use, and a marked increase in polypharmacy. Specifically, the prevalence of prescription drug use increased from 51% in 1999–2000 to 59% in 2011–2012, while the prevalence of polypharmacy increased from 8.2% to 15%. The increase in prescription drug use was observed for most, but not all, drug classes.
Use of anti-hypertensives increased over the study period, with a marked increase observed for several anti-hypertensives, including thiazide diuretics. The increase in use of thiazide diuretics is notable, given the recommendations for their use as first-line agents by the 2003 JNC 7 (Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure).22 However, Joinpoint analyses reveal that APC was highest before 2003–2004, suggesting that the increase in thiazide diuretics preceded, rather than resulted from, the 2003 recommendations. In 2014, the JNC 8 guidelines relaxed recommendations for drug initiation and expanded the options for first-line drug therapy, which may further influence the landscape of anti-hypertensive use.23
Use of anti-hyperlipidemics increased markedly, driven primarily by an increase in use of statins, for which the greatest increase was observed prior to 2005–2006. While both simvastatin and atrovastatin increased early in the study period, use of atorvastatin started to decline after 2005–2006. This pattern likely reflects the fact that simvastatin came off patent in 2006 while atorvastatin remained patent-protected, and therefore more costly, until 2011. Notably, this study preceded the release of the 2013 American College of Cardiology/American Heart Association recommendations, which expanded guidelines for statin use.24
The increase in use of anti-depressants may, in part, reflect shifting attitudes regarding depression.25 Both SSRIs and SSNRIs markedly increased; notably, use of SSNRIs increased between 1999–2000 and 2005–2006, remaining stable thereafter. Even so, SSRIs remain much more commonly used than the other anti-depressants, and the continued popularity of the SSRIs may reflect the availability of several generic options with a wide range of indications and a favorable profile regarding adverse effects.26
Overall, trends in analgesic use were stable; however, there was marked heterogeneity by class. COX-2 inhibitors decreased, likely a result of rofecoxib being taken off the market in 2004.27 On the other hand, use of narcotic analgesics rose from 1999–2000 to 2011–2012: while their increasing use may raise concern about the potential misuse/abuse of these drugs, it should be noted that use leveled off after 2003–2004. This flattening trend may reflect increased awareness of prescription opioid drug misuse/abuse,28 although under-reporting of these drugs may have increased with awareness regarding their potential for abuse.
Use of sex hormones decreased substantially among women, due to the decrease in non-contraceptive hormones following the release of results from the Women’s Health Initiative Hormone Therapy Trial.10,29 This decrease is notable, as conjugated estrogens once represented the most commonly used prescription drug.11
As the prevalence of diabetes increased,30 use of anti-diabetic drugs also increased, driven by a sharp rise in use of insulin and biguanides. Accordingly, metformin, considered a first-line agent in the treatment of diabetes,31 is now the 5th most commonly used drug. Use of thiazolidinediones decreased in recent years, likely owing to the concern regarding the link between rosiglitazone and risk of cardiovascular events.32
Despite certain PPIs becoming available over-the-counter (OTC), use of prescription PPIs increased, a trend which would be likely even more marked if we were able to account for OTC use. The increase in prescription PPIs may, in part, reflect the availability of more affordable, varied options for PPIs following the loss of patent protection for omeprazole in 2001 and subsequent market entry of esomeprazole. It remains unclear how use of prescription PPIs will be affected long-term by increasing availability of OTC PPIs.
Use of anti-convulsants increased over the study period. Several anti-convulsants are cross-classified in other drug classes (e.g., benzodiazapines), and it is likely that these alternative indications are, in part, driving the observed increase in use.
A significant joinpoint was observed for use of adrenergic bronchodilators in 2007–2008, after which use leveled off. It is possible that this pattern may, in part, reflect the 2005 US Food and Drug Administration’s Public Health Advisory regarding use of long-acting beta-2-adrenergic agonists. The sharp early increase in use of bronchodilator combinations may reflect other market forces, including direct-to-consumer advertising (DCTA), which peaked in the mid-2000s.33,34 The impact of DCTA is particularly relevant to bronchodilator combinations, as the popular combination, Advair, was ranked as one of the top drugs in terms of DCTA in 2010.34 Even so, a recent study found little evidence of association between DCTA and Advair prescriptions, and it therefore seems unlikely that DCTA alone is responsible.35
Lastly, use of muscle relaxants increased over the study period. Although the reasons underlying this increase are unclear, there has been discussion about the potential for misuse/abuse of one of the more commonly used muscle relaxants, carisoprodol. In 2011, the Drug Abuse Warning Network released a report showing an increase in emergency department visits associated with carisoprodol between 2004 and 2009,36 and in 2012, the Drug Enforcement Administration classified this drug as a controlled substance. Notably, however, in our data, the sharpest increase in prevalence of use of muscle relaxants was observed before 2003–2004, with no significant change observed thereafter.
The increases in any prescription drug use and polypharmacy are not explained by changes in the age distribution of the population. An alternative explanation for the observed increase in prescription drug use might be large-scale policy changes, including the implementation of Medicare Part D. However, the increase in prescription drug use was not just observed among those adults ages ≥65y, but also among adults ages 40–64y. Furthermore, Medicare Part D went into effect in 2006, and for many of the drug classes discussed, the sharpest increase occurred before 2006.
It is unclear if this pattern, with the sharpest increases observed early in the study period, reflects a saturation of the market, the peak of DCTA in the mid-2000s,34 or lagged effects resulting from the increase in obesity in the population. Eight of the ten most commonly used drugs in 2011–2012 are used to treat components of the cardiometabolic syndrome, including hypertension, diabetes and dyslipidemia. Another is a proton-pump inhibitor used for gastroesophageal reflux, a condition more prevalent among overweight/obese individuals.37 Thus, the increase in use of some agents may reflect the growing need for treatment of complications associated with the increase in overweight and obesity.
While patterns in prescription drug use were generally comparable across age, sex, and race/ethnicity, some differences were observed, with the most marked being that any prescription drug use was substantially lower for Mexican-Americans than non-Hispanic whites. As the Mexican American population is younger than the non-Hispanic white population,38 we conducted age-adjusted analyses and found that a marked difference between groups persisted, although the difference attenuated somewhat. Further adjustment for insurance status did not entirely account for the difference in any prescription use, although it is possible that prescription drug coverage may better account for the observed pattern. An alternative explanation may be the Hispanic paradox, where despite lower socioeconomic status, individuals of Hispanic descent have better than expected health status, which would likely result in less use of prescription medications.39 The reasons underlying these differences are likely multifactorial, meriting further investigation.
We have provided a comprehensive picture of prescription drug use in the US adult population using nationally-representative data. Prescription drug use was assessed at an in-home interview where containers were seen for 84% of drugs, giving confidence to participants’ self-reported use. Further, NHANES has a high response rate, reducing concern about bias. Even so, this study has several limitations. First, recall of intermittently used drugs may be more prone to measurement error than drugs used daily. Second, we are unable to capture OTC drug use, and some trends, such as the decrease in anti-histamines, reflect the availability of certain drugs becoming available OTC. Third, this survey was conducted among non-institutionalized adults; thus, results do not capture use among adults living in nursing homes and should only be generalized to the community-dwelling US adult population. Lastly, certain drugs may fall into more than one class and some drugs may be taken for off-label use, and therefore the classifications of drugs do not perfectly align with reasons for use.
CONCLUSIONS
In this nationally-representative survey, significant increases in overall prescription drug use and polypharmacy were observed. These increases persisted even after accounting for changes in the age distribution of the population. Trends were notable for specific categories of drugs, with the prevalence of use increasing in most, but not all, drug classes.
Supplementary Material
Acknowledgments
This work was conducted with support from the National Cancer Institute of the National Institutes of Health (E.D. Kantor supported by T32 CA 009001) and the National Institute of Diabetes and Digestive and Kidney Diseases of the National Institutes of Health (A.T. Chan supported by K24 DK098311). J.S. Haas is supported by Harvard Catalyst – The Harvard Clinical and Translational Science Center (National Center for Research Resources and the National Center for Advancing Translational Sciences, National Institutes of Health Award UL1 TR001102) and financial contributions from Harvard University and its affiliated academic healthcare centers. The content is solely the responsibility of the authors and does not necessarily represent the official views of Harvard Catalyst, Harvard University and its affiliated academic healthcare centers, or the National Institutes of Health.
Footnotes
All authors contributed to the i) conception or design and/or acquisition, analysis, or interpretation of data, as well as ii) drafting of the manuscript and/or critical revision of the manuscript for important intellectual content, and iii) statistical analysis, administrative technical, or material support, supervision/other support. E.D. Kantor (Harvard T.H. Chan School of Public Health) and C.D. Rehm (Friedman School of Nutrition Science and Policy) conducted analyses, had full access to all of the data in this study, and take responsibility for the integrity of the data and the accuracy of the data analysis.
The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of the manuscript. A.T Chan has consulted for Pfizer Inc., Bayer Healthcare, and Pozen Inc.; all other authors (E.D. Kantor, C.D. Rehm, J.S Haas, and E.L. Giovannucci) have no conflict of interest to declare.
References
- 1.Schumock GT, Li EC, Suda KJ, et al. National trends in prescription drug expenditures and projections for 2014. Am J Health Syst Pharm. 2014;71:482–499. doi: 10.2146/ajhp130767. [DOI] [PubMed] [Google Scholar]
- 2.Gu Q, Dillon CF, Burt VL. Prescription drug use continues to increase: U.S. prescription drug data for 2007–2008. NCHS Data Brief. 2010;42:1–8. [PubMed] [Google Scholar]
- 3.Stagnitti MN. Statistical brief 180: the top five outpatient prescription drugs ranked by total expense for children, adults, and the elderly, 2004. Medical Expenditure Panel Survey website. 2007 Available: http://www.meps.ahrq.gov/mepsweb/data_files/publications/st180/stat180.pdf. Accessed March 29, 2015.
- 4.Thielke SM, Simoni-Wastila L, Edlund MJ, et al. Age and sex trends in long-term opioid use in two large American health systems between 2000 and 2005. Pain Med. 2010;11:248–256. doi: 10.1111/j.1526-4637.2009.00740.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Bertisch SM, Herzig SJ, Winkelman JW, Buettner C. National use of prescription medications for insomnia: NHANES 1999–2010. Sleep. 2014;37:343–349. doi: 10.5665/sleep.3410. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Chong Y, Fryer CD, Gu Q. Prescription sleep aid use among adults: United States, 2005–2010. NCHS Data Brief. 2013;127:1–8. [PubMed] [Google Scholar]
- 7.Ford ES, Mannino DM, Wheaton AG, et al. Trends in the use, sociodemographic correlates, and undertreatment of prescription medications for chronic obstructive pulmonary disease among adults with chronic obstructive pulmonary disease in the United States from 1999 to 2010. PloS One. 2014;9:e95305. doi: 10.1371/journal.pone.0095305. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Gu Q, Paulose-Ram R, Dillon C, Burt V. Antihypertensive medication use among US adults with hypertension. Circulation. 2006;113:213–221. doi: 10.1161/CIRCULATIONAHA.105.542290. [DOI] [PubMed] [Google Scholar]
- 9.Gu Q, Paulose-Ram R, Burt VL, Kit BK. Prescription cholesterol-lowering medication use in adults aged 40 and over: United States, 2003–2012. NCHS Data Brief. 2014;177:1–8. [PubMed] [Google Scholar]
- 10.Jewett PI, Gangnon RE, Trentham-Dietz A, Sprague BL. Trends of postmenopausal estrogen plus progestin prevalence in the United States between 1970 and 2010. Obstet Gynecol. 2014;124:727–733. doi: 10.1097/AOG.0000000000000469. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Kaufman DW, Kelly JP, Rosenberg L, Anderson TE, Mitchell AA. Recent patterns of medication use in the ambulatory adult population of the United States: the Slone survey. JAMA. 2002;287:337–344. doi: 10.1001/jama.287.3.337. [DOI] [PubMed] [Google Scholar]
- 12.Paulose-Ram R, Jonas BS, Orwig D, Safran MA. Prescription psychotropic medication use among the U.S. adult population: results from the third National Health and Nutrition Examination Survey, 1988–1994. J Clin Epidemiol. 2004;57:309–317. doi: 10.1016/j.jclinepi.2003.05.001. [DOI] [PubMed] [Google Scholar]
- 13.Qato DM, Alexander GC, Conti RM, Johnson M, Schumm P, Lindau ST. Use of prescription and over-the-counter medications and dietary supplements among older adults in the United States. JAMA. 2008;300:2867–2878. doi: 10.1001/jama.2008.892. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Yoon SS, Gu Q, Nwankwo T, Wright JD, Hong Y, Burt V. Trends in blood pressure among adults with hypertension: United States, 2003 to 2012. Hypertension. 2015;65:54–61. doi: 10.1161/HYPERTENSIONAHA.114.04012. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.National Center for Health Statistics. Health, United States, 2013: With Special Feature on Prescription Drugs. Hyattsville, MD: 2014. [PubMed] [Google Scholar]
- 16.National Center for Health Statistics. NHANES 2003–2004 Public Data General Release File Documentation. Hyattsville, MD: National Center for Health Statistics; 2005. http://www.cdc.gov/nchs/data/nhanes/nhanes_03_04/general_data_release_doc_03-04.pdf. Accessed March 28, 2015. [Google Scholar]
- 17.Viktil KK, Blix HS, Moger TA, Reikvam A. Polypharmacy as commonly defined is an indicator of limited value in the assessment of drug-related problems. Br J Clin Pharmacol. 2007;63:187–195. doi: 10.1111/j.1365-2125.2006.02744.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Johnson CL, Paulose-Ram R, Ogden CL, et al. National Health and Nutrition Examination Survey: Analytic guidelines, 1999–2010. National Center for Health Statistics. Vital Health Stat. 2(161):2013. [PubMed] [Google Scholar]
- 19.Clegg LX, Hankey BF, Tiwari R, Feuer EJ, Edwards BK. Estimating average annual per cent change in trend analysis. Stat Med. 2009;28:3670–3682. doi: 10.1002/sim.3733. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Kim HJ, Fay MP, Feuer EJ, Midthune DN. Permutation tests for joinpoint regression with applications to cancer rates. Stat Med. 2000;19:335–351. doi: 10.1002/(sici)1097-0258(20000215)19:3<335::aid-sim336>3.0.co;2-z. [DOI] [PubMed] [Google Scholar]
- 21.National Center for Health Statistics. NHANES Response Rates and Population Totals. Hyattsville, MD: National Center for Health Statistics; http://www.cdc.gov/nchs/nhanes/response_rates_cps.htm. Accessed March 28, 2015. [Google Scholar]
- 22.Chobanian AV, Bakris GL, Black HR, et al. The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report. JAMA. 2003;289:2560–2572. doi: 10.1001/jama.289.19.2560. [DOI] [PubMed] [Google Scholar]
- 23.James PA, Oparil S, Carter BL, et al. 2014 evidence-based guideline for the management of high blood pressure in adults: report from the panel members appointed to the Eighth Joint National Committee (JNC 8) JAMA. 2014;311:507–520. doi: 10.1001/jama.2013.284427. [DOI] [PubMed] [Google Scholar]
- 24.Stone NJ, Robinson JG, Lichtenstein AH, et al. 2013 ACC/AHA guideline on the treatment of blood cholesterol to reduce atherosclerotic cardiovascular risk in adults: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol. 2014;63:2889–2934. doi: 10.1016/j.jacc.2013.11.002. [DOI] [PubMed] [Google Scholar]
- 25.Blumner KH, Marcus SC. Changing perceptions of depression: ten-year trends from the general social survey. Psychiatr Serv. 2009;60:306–312. doi: 10.1176/ps.2009.60.3.306. [DOI] [PubMed] [Google Scholar]
- 26.Goodnick PJ, Goldstein BJ. Selective serotonin reuptake inhibitors in affective disorders–I. Basic pharmacology. J Psychopharmacol. 1998;12(3 Suppl B):S5–20. doi: 10.1177/0269881198012003021. [DOI] [PubMed] [Google Scholar]
- 27.Ross JS, Madigan D, Hill KP, Egilman DS, Wang Y, Krumholz HM. Pooled analysis of rofecoxib placebo-controlled clinical trial data: lessons for postmarket pharmaceutical safety surveillance. Arch Intern Med. 2009;169:1976–1985. doi: 10.1001/archinternmed.2009.394. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Manchikanti L, Helm S, 2nd, Fellows B, et al. Opioid epidemic in the United States. Pain Physician. 2012;15(3 Suppl):ES9–38. [PubMed] [Google Scholar]
- 29.Rossouw JE, Anderson GL, Prentice RL, et al. Risks and benefits of estrogen plus progestin in healthy postmenopausal women: principal results From the Women’s Health Initiative randomized controlled trial. JAMA. 2002;288:321–333. doi: 10.1001/jama.288.3.321. [DOI] [PubMed] [Google Scholar]
- 30.Selvin E, Parrinello CM, Sacks DB, Coresh J. Trends in prevalence and control of diabetes in the United States, 1988–1994 and 1999–2010. Ann Internal Med. 2014;160:517–525. doi: 10.7326/M13-2411. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Bennett WL, Wilson LM, Bolen S, et al. Oral Diabetes Medications for Adults With Type 2 Diabetes: An Update. Rockville, MD: Agency for Healthcare Research and Quality; Mar, 2011. (Comparative Effectiveness Review No. 27. AHRQ Publication No. 11-EHC038-EF). www.effectivehealthcare.ahrq.gov/reports/final.cfm. Accessed July 24, 2015. [PubMed] [Google Scholar]
- 32.Nissen SE, Wolski K. Effect of rosiglitazone on the risk of myocardial infarction and death from cardiovascular causes. N Engl J Med. 2007;356:2457–2471. doi: 10.1056/NEJMoa072761. [DOI] [PubMed] [Google Scholar]
- 33.Donohue JM, Cevasco M, Rosenthal MB. A decade of direct-to-consumer advertising of prescription drugs. N Engl J Med. 2007;357:673–681. doi: 10.1056/NEJMsa070502. [DOI] [PubMed] [Google Scholar]
- 34.Kornfield R, Donohue J, Berndt ER, Alexander GC. Promotion of prescription drugs to consumers and providers, 2001–2010. PloS One. 2013;8(3):e55504. doi: 10.1371/journal.pone.0055504. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Daubresse M, Hutfless S, Kim Y, et al. Effect of Direct-to-Consumer Advertising on Asthma Medication Sales and Healthcare Use. Am J Respir Crit Care Med. 2015;192:40–46. doi: 10.1164/rccm.201409-1585OC. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Substance Abuse and Mental Health Services Administration. Center for Behavioral Health Statistics and Quality The DAWN Report: ED Visits Involving the Muscle Relaxant Carisoprodol. Rockville, MD: Oct, 2011. http://oas.samhsa.gov/2k11/DAWN071/WEB_DAWN_071_HTML.pdf. Accessed July 25, 2015. [Google Scholar]
- 37.Jacobson BC, Somers SC, Fuchs CS, Kelly CP, Camargo CA., Jr Body-mass index and symptoms of gastroesophageal reflux in women. N Engl J Med. 2006;354:2340–2348. doi: 10.1056/NEJMoa054391. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Perez AD, Hirschman C. The Changing Racial and Ethnic Composition of the US Population: Emerging American Identities. Popul Dev Rev. 2009;35:1–51. doi: 10.1111/j.1728-4457.2009.00260.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Sorlie PD, Backlund E, Johnson NJ, Rogot E. Mortality by Hispanic status in the United States. JAMA. 1993;270:2464–2468. [PubMed] [Google Scholar]
- 40.Klein RJ, Proctor SE, Boudreault MA, Turczyn KM. Healthy People 2010 criteria for data suppression. Hyattsville, Maryland: National Center for Health Statistics; Jun, 2002. (Healthy People 2010 Statistical Notes, Number 24). [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.