Author contributions
S. M. F.: study concept and design; acquisition, analysis or interpretation of data; drafting of the manuscript; statistical analysis. B. K. K.: study concept and design; acquisition, analysis or interpretation of data; critical revision of the manuscript for important intellectual content; administrative, tech-nical or material support. S. L. L.: study concept and design; acquisition, analysis or interpretation of data; critical revision of the manuscript for important intellectual content; administrative, technical or material support. L. A. H.: study concept and design; acquisition, analysis or interpretation of data; critical revision of the manuscript for important intellectual content; administrative, technical or material support. Q. G.: acquisition, analysis or interpretation of data; critical revision of the manuscript for important intellectual content; administrative, technical or material support.
The objectives of this study were: to examine trends in the use of prescription antibiotics overall and by population subgroups between 1999 and 2012; and to examine trends in the use of categories of antibiotics and individual antibiotics.
Use of antibiotics was examined among 71444 participants in the nationally representative National Health and Nutrition Examination Survey (NHANES; 1999–2012). Use of an antibiotic in the past 30 days was the main outcome variable. Analyses of trends were conducted overall and separately by population subgroups (i.e. age, sex, race/Hispanic origin, health insurance status and respiratory conditions) across four time periods (1999–2002, 2003–06, 2007–10 and 2011–12).
The percentage of the US population that used a prescription antibiotic in the past 30 days significantly declined from 6.1% in 1999–2002 to 4.1% in 2011–12 (
Overall, there was a significant decline in the use of antibiotics between 1999–2002 and 2011–12. Due to concerns about antimicrobial resistance, it is important to continue monitoring the use of antibiotics.
Antimicrobial resistance threatens health professionals’ ability to effectively treat infectious diseases.
Reporting of antibiotic prescribing in the USA has previously been based on analyses of pharmacy dispensing data (including the IMS Health Xponent database) or data from the National Ambulatory Medical Care Survey (NAMCS) and the National Hospital Ambulatory Medical Care Survey (NHAMCS).
Data from the National Health and Nutrition Examination Survey (NHANES) can build on these studies and provide more details about trends in the use of antibiotics. NHANES collects information about prescription medication use from a nationally representative sample of the US non-institutionalized population through direct observation of medication containers in the home or by self- and proxy-reported medication use. The study also collects detailed information about people’s demographic characteristics and their health, which can allow researchers to examine trends in antibiotic use among population subgroups.
In this study, we examined trends in the use of antibiotics overall and by population subgroups between 1999–2002 and 2011–12 using NHANES data. We also examined trends in the use of categories of antibiotics and individual antibiotics.
Data for this analysis come from the NHANES, a continuous, crosssectional survey conducted by the National Center for Health Statistics (NCHS), CDC. A complex, multistage probability sampling design was used to generate a representative sample of the civilian, non-institutionalized US population.
Data on prescription medications used in the past 30 days were collected through direct abstraction from prescription medication containers. During the household interview, respondents aged ≥16 years were asked: ‘In the past 30 days, have you used or taken medication for which a prescription is needed?’ For respondents under the age of 16 or those that could not respond to the question, a proxy responded. Those who answered affirmatively were asked to give their prescription medication containers to the interviewer and report details related to its use (i.e. duration of use). An interviewer took the container and recorded the exact product name from its label. If the container was not available, the partici-pant verbally reported this information. In most instances, interviewers saw the medicine container for each antibiotic used (70% of antibiotic containers in 1999–2002, 76% in 2003–06, 70% in 2007–10 and 72% in 2011–12). Collection methodology was similar for all NHANES cycles. Further details of prescription medication data collection in NHANES 1999–2012 are available elsewhere.
All the drug names reported were converted into a standard generic drug name for the data release and a therapeutic drug class was assigned based on the Multum Lexicon Drug Database.
In addition to examining the overall trend in antibiotic use, we examined trends among several subpopulations, including: age groups (0–1 year, 2–5 years, 6–11 years, 12–17 years, 18–39 years, 40–59 years and ≥60 years), self-identified race/Hispanic origin (non-Hispanic black, non-Hispanic white, Mexican American and other), sex (male and female), health insurance status (have health insurance and do not have health insurance). Respiratory tract infections (acute and chronic) are a leading indication for antibiotic prescribing in the ambulatory setting, and the use of antibiotics among people with these infections has been examined in prior research.
Statistical analyses were conducted using the survey (SVY) commands in Stata 12.1 to adjust for differential probabilities of selection and the complex sampling design.
We generated estimates of the percentage of the US non-institutionalized population who used an antibiotic in the past 30 days overall and among the subpopulations mentioned above. In addition, we examined trends in the use of different categories of antibiotics and three individual antibiotics. We tested for the presence of linear trends using orthogonal contrast matrices generated using Stata’s ‘contrast’ command, adjusted for the uneven midpoints of the time periods used in the analysis (three 4 year periods and one 2 year period). For all tests, a signifiance level of 0.05 was utilized. We also reported the absolute change in percentage between the first and last time periods examined (i.e. 1999–2002 and 2011–12).
The percentage of the US population that used a prescription antibiotic in the past 30 days declined significantly from 6.1% in 1999–2002 to 4.1% in 2011–12 (
A significant decline in antibiotic use occurred for both males and females. The magnitude of the decline was greater for males (2.4%) compared with females (1.6%), and in the most recent period examined females continued to use more antibio-tics than males (4.9% compared with 3.2%). Use of antibiotics declined among non-Hispanic white and non-Hispanic black per-sons; however, their use remained relatively stable among Mexican American persons. The decline was greater among non-Hispanic white persons compared with non-Hispanic black persons (2.0% compared with 1.2%).
Use of antibiotics declined among persons with health insurance and those without health insurance. The magnitude of the decline was greater for people without health insurance compared with those with health insurance (2.3% compared with 1.9%). Among persons who currently had asthma, there was a significant decline in the use of antibiotics and an absolute percentage change of 2.6%. There was no change in use for those who currently had chronic bronchitis and/or ever had emphysema.
Among the categories of antibiotics examined, there were significant declines in the use of penicillins, cephalosporins and macrolide derivatives (
The CDC has identified antibiotic resistance as a top public health concern and has promoted adherence to appropriate prescribing guidelines since the mid-1990s.
From 1999–2002 to 2011–12, when the CDC programmes were active and when the pneumococcal conjugative vaccines PCV7 and PCV13 became available (2000 and 2010, respectively),
Although the declines in overall antibiotic use were statistically significant, the magnitudes of the declines ranged from 1.2 to 6.8 percentage points, indicating that the decline in antibiotic use is not universal among all subpopulations. The largest decline occurred among children under the age of 2 years, where the percentage of antibiotic users declined almost by half. Antibiotic use among this group is of great interest due to their high use of antibiotics and because the CDC had focused on educating parents of young children about appropriate uses of antibiotics.
The assessment of categories of antibiotics and individual drugs revealed that the decline in the use of antibiotics was not concentrated among one category of antibiotics. Significant declines were reported for three categories (penicillins, cephalos-porins and macrolide derivatives). Among individual antibiotics, there was a significant decline in the use of amoxicillin, which mir-rors findings from studies of their use in ambulatory settings.
This study has several limitations. First, we cannot determine whether the decline in the use of antibiotics was for appropriate or inappropriate uses. Due to the relatively small number of persons taking some of the categories of antibiotics, some of the CIs were wide and may have resulted in a lack of power to identify significant covariate effects and linear trends. Caution should be exercised when conducting inference for prevalence estimates based on small numbers of outcomes or means based on small sample sizes. Our prevalence rate is based on use within the past 30 days and variation may exist between this study and others that examined antibiotic use using different time periods (i.e. past week and past 2 weeks). In addition, due to most regi-mens of antibiotics lasting 10–14 days, respondents may have used them within the past 30 days, but could have forgotten they took them or discarded their containers. Thus, the prevalence rates reported may be a conservative estimate of antibiotic use. Finally, we cannot determine which factors were responsible for the decline in antibiotic use during the time periods examined.
The strengths of this study are that the data come from a large, nationally representative sample of the US population, that the data include detailed demographic and health information, which allowed us to assess use of antibiotics across several population subgroups, and that we were able to examine trends in the use of categories of antibiotics and also individual antibiotics. In addition, data on prescription medication use come primarily from observing respondents’ medication containers (not selfreport) and include antibiotics prescribed across multiple healthcare settings.
This study revealed that there has been a significant decline in the use of antibiotics among the US non-institutionalized population during the past 13 years. This decline was found among numerous population subgroups of interest (e.g. children under the age of 2 years and people with asthma), but for some subpopulations no decline was found. Declines were also observed among different categories of antibiotics. Due to concerns about the threat of antimicrobial resistance, it is important to continue monitoring the use of antibiotics.
We would like to thank Dr Kathryn S. Porter for conceptualizing the study and for providing comments and suggestions on earlier versions of the manuscript.
Funding
All data used in this study were collected by the NCHS, CDC. This study was carried out as part of our routine work.
Disclaimer
The findings and conclusions in this article are those of the authors and not necessarily those of the CDC.
Transparency declarations
None to declare.
Use of prescription antibiotics
| 1999–2002 | 2003–06 | 2007–10 | 2011–12 | Absolute percentage | ||||||
|---|---|---|---|---|---|---|---|---|---|---|
| % (95% CI) | % (95% CI) | % (95% CI) | % (95% CI) | |||||||
| Overall | 20814 | 6.1 (5.4–6.8) | 20347 | 5.6 (5.0–6.3) | 20577 | 4.2 (3.8–4.7) | 9706 | 4.1 (3.6–4.6) | <0.001 | 2.0 |
| Age groups (years) | ||||||||||
| 0–1 | 1635 | 15.5 (12.9–18.7) | 1690 | 10.9 (9.0–13.1) | 1532 | 11.7 (9.5–14.5) | 620 | 8.7 (6.7–11.2) | 0.001 | 6.8 |
| 2–5 | 1801 | 9.1 (7.2–11.4) | 1975 | 7.3 (5.3–10.0) | 1893 | 7.1 (5.4–9.4) | 973 | 6.6 (3.3–12.6) | 0.34 | 2.5 |
| 6–11 | 2345 | 6.1 (4.3–8.6) | 2176 | 5.8 (4.3–7.9) | 2510 | 4.8 (3.6–6.3) | 1325 | 2.7 (1.5–4.8) | 0.01 | 3.4 |
| 12–17 | 3722 | 8.0 (6.5–9.9) | 3412 | 7.8 (6.5–9.3) | 1971 | 4.8 (3.4–6.7) | 968 | 5.1 (2.8–9.3) | 0.05 | 2.9 |
| 18–39 | 4736 | 6.0 (4.9–7.3) | 4797 | 5.4 (4.4–6.6) | 4576 | 4.5 (3.7–5.5) | 2250 | 4.7 (3.9–5.8) | 0.04 | 1.3 |
| 40–59 | 2934 | 5.0 (3.9–6.3) | 2865 | 4.8 (4.1–5.7) | 3906 | 3.0 (2.5–3.6) | 1801 | 3.0 (2.0–4.5) | 0.01 | 2.0 |
| ≥60 | 3641 | 4.3 (3.5–5.1) | 3432 | 4.4 (3.8–5.1) | 4189 | 3.1 (2.5–3.9) | 1769 | 3.5 (2.4–5.0) | 0.11 | 0.8 |
| Sex | ||||||||||
| male | 10144 | 5.6 (4.8–6.6) | 9989 | 4.5 (3.9–5.3) | 10268 | 4.0 (3.5–4.6) | 4831 | 3.2 (2.5–4.1) | <0.001 | 2.4 |
| female | 10670 | 6.5 (5.8–7.2) | 10358 | 6.6 (5.8–7.4) | 10309 | 4.4 (3.9–5.0)** | 4875 | 4.9 (4.0–5.9) | <0.001 | 1.6 |
| Race/Hispanic origin | ||||||||||
| non-Hispanic white | 7909 | 6.9 (5.9–8.0) | 8014 | 6.2 (5.5–7.0) | 8489 | 4.9 (4.3–5.5) | 2964 | 4.9 (4.0–5.9) | <0.001 | 2.0 |
| non-Hispanic black | 4853 | 4.4 (3.7–5.2) | 5321 | 4.3 (3.4–5.4) | 4147 | 3.7 (3.2–4.4) | 2667 | 3.2 (2.6–4.0) | 0.02 | 1.2 |
| Mexican American | 6126 | 3.9 (3.4–4.6) | 5352 | 3.9 (3.2–4.7) | 4519 | 3.2 (2.5–4.1) | 1345 | 3.8 (2.7–5.4) | 0.23 | 0.1 |
| Health insurance status | ||||||||||
| no insurance | 3915 | 4.4 (3.2–6.1) | 3610 | 3.6 (2.7–4.7) | 3989 | 2.9 (2.3–3.7) | 1692 | 2.1 (1.5–3.1) | 0.003 | 2.3 |
| have insurance | 16524 | 6.4 (5.7–7.3) | 16564 | 6.0 (5.3–6.7) | 16555 | 4.5 (4.0–5.1) | 7995 | 4.5 (3.8–5.2) | <0.001 | 1.9 |
| Respiratory conditions | ||||||||||
| asthma | 784 | 7.8 (5.6–10.9) | 1709 | 9.0 (6.9–11.6) | 1698 | 5.7 (4.4–7.4) | 877 | 5.2 (3.5–7.8) | 0.02 | 2.6 |
| chronic bronchitis | 417 | 7.9 (5.0–12.2) | 443 | 10.4 (7.3–14.7) | 555 | 6.6 (4.5–9.7) | 204 | 6.3 (3.8–10.1) | 0.28 | 1.6 |
Interview sample weights were utilized to adjust for differential probabilities of selection and the complex sampling design.
Respondents were asked: ‘In the past 30 days, have you used or taken medication for which a prescription is needed?’.
Topical antibiotics are excluded from this analysis.
Test for an overall linear trend using Stata’s ‘contrast’ command.
Age-adjusted to the 2000 US Census population using age groups 0–1 year, 2–5 years, 6–11 years, 12–17 years, 18–39 years, 40–59 years and ≥60 years.
Estimates for persons of other race/ethnicity groups are not provided separately, but members of this group are included in total estimates.
Currently have asthma. Question restricted to respondents aged ≥1 year. Data available from 2001 to 2012.
Currently have chronic bronchitis. Question restricted to respondents aged ≥20 years. Data available from 1999 to 2012.
Ever had emphysema. Question restricted to respondents aged ≥20 years. Data available from 1999 to 2012.
Statistically significant differences between 1999–2002 and 2003–06 estimates (
Statistically significant differences between 2003–06 and 2007–10 estimates (
Statistically significant differences between 2007–10 and 2011–12 estimates (
!Estimate does not meet standard of statistical reliability and precision (relative standard error .>30% and <40%).
Use of antibiotics by category and individual antibiotics in the past 30 days among US children and adults, NHANES 1999–2012
| 1999–2002 | 2003–06 | 2007–10 | 2011–12 | Absolute | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| % (95% CI) | % (95% CI) | % (95% CI) | % (95% CI) | ||||||||
| Antibiotic categories | 20814 | 20347 | 20577 | 9706 | |||||||
| penicillins | 2.7 (2.3–3.2) | 2.3 (1.9–2.7) | 1.6 (1.4–1.8) | 1.7 (1.3–2.2) | <0.001 | 1.0 | |||||
| cephalosporins | 0.9 (0.7–1.1) | 0.7 (0.6–0.9) | 0.6 (0.4–0.8) | 0.5 (0.3–0.8) | 0.02 | 0.4 | |||||
| macrolide derivatives | 0.8 (0.6–1.1) | 0.9 (0.7–1.1) | 0.5 (0.4–0.6) | 0.5 (0.3–0.8) | 0.01 | 0.3 | |||||
| tetracyclines | 0.7 (0.6–0.9) | 0.7 (0.5–0.9) | 0.7 (0.5–0.9) | 0.7 (0.5–1.1) | 0.99 | 0.0 | |||||
| sulphonamides | 0.4 (0.3–0.5) | 0.4 (0.2–0.5) | 0.4 (0.3–0.5) | 0.3 (0.2–0.5) | 0.44 | 0.1 | |||||
| quinolones | 0.4 (0.3–0.5) | 0.5 (0.4–0.7) | 0.4 (0.3–0.6) | 0.3 (0.2–0.6) | 0.58 | 0.1 | |||||
| urinary anti-infectives | 0.2 (0.2–0.3) | 0.3 (0.2–0.4) | 0.2 (0.1–0.3) | 0.2 (0.2–0.4) | 0.78 | 0.0 | |||||
| lincomycin derivatives | 0.1 (0.1–0.2) | 0.2 (0.1–0.3) | 0.1 (0.1–0.2) | 0.1 (0.1–0.3) | 0.86 | 0.0 | |||||
| miscellaneous antibiotics | 0.2 (0.1–0.3) | 0.2 (0.1–0.3) | 0.1 (0.04–0.1) | 0.2 (0.01–0.04) | 0.55 | 0.0 | |||||
| Individual antibiotics | |||||||||||
| amoxicillin | 2.3 (1.9–2.8) | 1.9 (1.5–2.3) | 1.3 (1.1–1.6) | 1.4 (1.1–1.9) | 0.001 | 0.9 | |||||
| cefalexin | 0.5 (0.4–0.7) | 0.4 (0.3–0.5) | 0.4 (0.3–0.5) | 0.4 (0.2–0.7)! | 0.22 | 0.1 | |||||
| azithromycin | 0.3 (0.2–0.5) | 0.5 (0.4–0.6) | 0.4 (0.3–0.5) | 0.5 (0.3–0.8) | 0.54 | 0.2 | |||||
Interview sample weights were utilized to adjust for differential probabilities of selection and the complex sampling design. Respondents were asked: ‘In the past 30 days, have you used or taken medication for which a prescription is needed?’
Topical antibiotics are excluded from this analysis.
Test for an overall linear trend using Stata’s ‘contrast’ command.
Level 2 drug categories from the Multum Lexicon Drug Database. Glycopeptide antibiotics are not shown due to only three respondents indicating that they used them.
Antibiotics in this category include chloramphenicol and metronidazole.
Includes multi-ingredient drugs that contain amoxicillin.
Statistically significant differences between 1999–2002 and 2003–06 estimates (
Statistically significant differences between 2003–06 and 2007–10 estimates (
Statistically significant differences between 2007–10 and 2011–12 estimates (
!Estimate does not meet standard of statistical reliability and precision (relative standard error >.30% and ,<40%).
!!Estimate does not meet standard of statistical reliability and precision (relative standard error >.40% and ,<50%).