Abstract
Our objective was to describe the use of medications associated with weight change among US adults with overweight/obesity, including anti-obesity medications (AOMs), weight-loss-promoting and weight-gain-promoting medications. We performed a cross-sectional analysis of data from the nationwide All of Us Research Programme. We included adults with measured body mass index (BMI) ≥ 27 kg/m2 enrolled between 2018 and 2022 across the United States. We used linked electronic health record data to determine medication use ±12 months of BMI measure. Our 132 057 participants had mean age 54 years and mean BMI 34 kg/m2; 60% of participants were women, 62% White, and 32% Black. Only 1% used any AOM, and 14% used at least one weight-loss-promoting medication. We found that 36% used at least one weight-gain-promoting medication, and approximately 20% used multiple weight-gain-promoting medications. While AOMs are underutilized by participants with overweight/obesity, weight-gain-promoting medication use is common. Our results raise concern about potential iatrogenic weight gain from medications. Future research is needed to estimate the long-term effect of weight-gain-promoting medications on weight status and determine whether weight-loss benefits occur with their discontinuation. Clinician education on AOMs and weight-loss-promoting medications may be needed to increase their use.
| Original language | English (US) |
|---|---|
| Article number | e12609 |
| Journal | Clinical obesity |
| Volume | 13 |
| Issue number | 5 |
| DOIs | |
| State | Published - Oct 2023 |
Keywords
- anti-obesity agents
- body weight changes
- drug side effects
- obesity
ASJC Scopus subject areas
- Endocrinology, Diabetes and Metabolism
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In: Clinical obesity, Vol. 13, No. 5, e12609, 10.2023.
Research output: Contribution to journal › Article › peer-review
}
TY - JOUR
T1 - Use of medications associated with weight change among participants in the All of Us research programme
AU - Almazan, Erik
AU - Schwartz, Jessica L.
AU - Gudzune, Kimberly A.
N1 - Funding Information: Erik Almazan was supported by the Johns Hopkins School of Medicine Dean's Office. Jessica L. Schwartz was supported by the National Heart, Lung, and Blood Institute (T32HL007180, PI: Maruthur). Kimberly A. Gudzune is funded by a grant from the National Institute of Mental Health (P50MH115842) and National Heart, Lung and Blood Institute (UH3HL155801). The All of Us Research Programme is supported by the National Institutes of Health, Office of the Director through multiple mechanisms (Regional Medical Centers: 1 OT2 OD026549; 1 OT2 OD026554; 1 OT2 OD026557; 1 OT2 OD026556; 1 OT2 OD026550; 1 OT2 OD 026552; 1 OT2 OD026553; 1 OT2 OD026548; 1 OT2 OD026551; 1 OT2 OD026555; IAA #: AOD 16037. Federally Qualified Health Centers: HHSN 263201600085U. Data and Research Center: 5 U2C OD023196. Biobank: 1 U24 OD023121. The Participant Center: U24 OD023176. Participant Technology Systems Center: 1 U24 OD023163. Communications and Engagement: 3 OT2 OD023205; 3 OT2 OD023206. Community Partners: 1 OT2 OD025277; 3 OT2 OD025315; 1 OT2 OD025337; 1 OT2 OD025276). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. We conducted a cross-sectional analysis of data from the All of Us Research Programme, which is a precision-medicine initiative sponsored by the National Institutes of Health (NIH).21 Since 2018, the Programme has collected data from volunteer participants across the nation. Any person residing within the United States is eligible to participate, and the Programme actively recruits participants from populations historically underrepresented in medical research. All data are volunteered by participants who are ≥18 years of age, able to provide informed consent and live in a US territory at the time of enrolment. The Programme includes data from multiple sources including electronic health records (EHR), anthropometrics and surveys. EHR data are standardized using the Observational Medical Outcomes Partnership (OMOP) Common Data Model, and includes information such as medications and diagnoses. For anthropometrics, height and weight is specifically measured for the Programme by the participant or partnering health organizations, and BMI is calculated from this measurement. Upon enrolment, the baseline survey includes information on demographics as well as health and lifestyle. Additional details on the data curation process are publicly available at https://allofus.nih.gov/. For this study, we used the ‘All of Us Controlled Tier Dataset v6’, which contains EHR, anthropometric and survey data collected between May 2018 and February 2022. We included adults with BMI ≥27 kg/m2 (overweight or greater) calculated from their most recent weight measurement, as this group represents a population where weight reduction would likely be recommended, AOM use may be indicated and avoiding weight-gain-promoting medications would be recommended.3,6,7 We excluded individuals who were deceased or lacked information on age, sex or race/ethnicity. Given that an individual's weight may change over time, we limited extraction of most data elements within ±12 months of their last weight measurement. The National Institutes of Health's All of Us Research Programme Institutional Review Board approved the protocol and materials for the All of Us Research Programme.22 The Johns Hopkins School of Medicine Institutional Review Board approved this study. We conducted a cross-sectional analysis of data from the All of Us Research Programme, which is a precision-medicine initiative sponsored by the National Institutes of Health (NIH).21 Since 2018, the Programme has collected data from volunteer participants across the nation. Any person residing within the United States is eligible to participate, and the Programme actively recruits participants from populations historically underrepresented in medical research. All data are volunteered by participants who are ≥18 years of age, able to provide informed consent and live in a US territory at the time of enrolment. The Programme includes data from multiple sources including electronic health records (EHR), anthropometrics and surveys. EHR data are standardized using the Observational Medical Outcomes Partnership (OMOP) Common Data Model, and includes information such as medications and diagnoses. For anthropometrics, height and weight is specifically measured for the Programme by the participant or partnering health organizations, and BMI is calculated from this measurement. Upon enrolment, the baseline survey includes information on demographics as well as health and lifestyle. Additional details on the data curation process are publicly available at https://allofus.nih.gov/. For this study, we used the ‘All of Us Controlled Tier Dataset v6’, which contains EHR, anthropometric and survey data collected between May 2018 and February 2022. We included adults with BMI ≥27 kg/m2 (overweight or greater) calculated from their most recent weight measurement, as this group represents a population where weight reduction would likely be recommended, AOM use may be indicated and avoiding weight-gain-promoting medications would be recommended.3,6,7 We excluded individuals who were deceased or lacked information on age, sex or race/ethnicity. Given that an individual's weight may change over time, we limited extraction of most data elements within ±12 months of their last weight measurement. The National Institutes of Health's All of Us Research Programme Institutional Review Board approved the protocol and materials for the All of Us Research Programme.22 The Johns Hopkins School of Medicine Institutional Review Board approved this study. Our primary outcomes were use of anti-obesity, weight-loss-promoting and weight-gain-promoting medications, which were all derived from EHR data. We first created rosters of relevant medications for each of these groups (Table S1). For AOMs, we identified medications approved by the FDA for weight reduction during the study period based on prior studies and through the online FDA database.7–11,16 Some identified medications were FDA approved for short-term use (Benzphetamine, Diethylpropion, Phendimetrazine, Phentermine), while others were approved for long-term use (Liraglutide, Lorcaserin [approved only from 2012 to 2020], Naltrexone–Bupropion, Orlistat, Phentermine–Topiramate, Semaglutide). Liraglutide and Semaglutide were approved for both Type 2 diabetes mellitus and obesity; however, we were unable to distinguish between prescriptions for these two indications in the dataset. Therefore, we allocated all prescriptions for Liraglutide and Semaglutide as weight-loss-promoting medications rather than AOMs. Of note, we also identified two medications approved for other obesity indications—one medication was approved for treatment of certain types of rare genetic obesity (Setmelanotide) and another was approved for treatment of binge eating disorder (Lisdexamfetamine). We did not include these medications as AOMs, given that their specific treatment indications do not include common obesity. Therefore, we included eight medications in our final list of AOMs. For weight-loss-promoting medications, we identified medications based on guidelines that included a variety of medications such as anticonvulsants, antidepressants and medications to treat Type 2 diabetes mellitus.3 We used the same approach for weight-gain-promoting medications, and identified medications within anticonvulsants, antidepressants, atypical antipsychotics, beta-blockers, contraceptives, corticosteroids and medications to treat Type 2 diabetes mellitus.3–5,17,18 Of note, we identified that some included medications were available as single agents or offered in combination with other medications (Table S2). We allocated components of combination medications to either weight-loss-promoting or weight-gain-promoting, as appropriate, in the estimates (Table S3). We then identified participants with use of these medications documented in the EHR. Within the dataset, drug exposures are defined as an EHR entry for the start date of a prescription, the fill date of a prescription or the administration date of a medication. We limited the sample to only oral formulations of medications (with the exception of insulins and glucagon-like peptide-1 [GLP-1] receptor agonists), as the weight change effect of other preparations (e.g., topical, ophthalmic, intravenous, etc.) has not been well characterized. We defined use of each medication if exposure to that drug occurred within ±12 months of their last weight measurement. We also individually calculated the number of participants with use of any anti-obesity, weight-loss-promoting, and weight-gain-promoting medications by identifying participants with a drug exposure to at least one medication in the relevant category. Finally, we individually determined counts of weight-loss-promoting and weight-gain-promoting medications by adding the number of drug exposures to unique medications in each category. To characterize the sample included in this study, we examined other measures available in the dataset. We identified several weight-related comorbidities, including Type 2 diabetes mellitus, within ±12 months of their last weight measurement,2,6 which were derived from EHR data using the relevant 10th International Statistical Classification of Diseases and Related Health Problems (ICD-10) diagnostic codes. We also used data from two surveys in the dataset—The Basics and Overall Health questionnaires—collected within ±36 months of their last weight measurement. Specifically, we examined educational attainment, annual household income, health insurance status and self-reported health status from these questionnaires. All analyses were conducted with Python 3 (Python Software Foundation, Wilmington, DE). We conducted descriptive analyses of all variables and report means and proportions, as appropriate. We examined measures in the overall sample, as well as limited to participants with overweight (BMI ≥27 kg/m2 and <30 kg/m2) and participants with obesity (BMI ≥ 30 kg/m2). Additionally, we examined measures among a subset of participants with Type 2 diabetes mellitus. Data visualization was completed with Microsoft Excel version 16.70 (Microsoft Corporation, Redmond, WA). Funding Information: Erik Almazan was supported by the Johns Hopkins School of Medicine Dean's Office. Jessica L. Schwartz was supported by the National Heart, Lung, and Blood Institute (T32HL007180, PI: Maruthur). Kimberly A. Gudzune is funded by a grant from the National Institute of Mental Health (P50MH115842) and National Heart, Lung and Blood Institute (UH3HL155801). The Research Programme is supported by the National Institutes of Health, Office of the Director through multiple mechanisms (Regional Medical Centers: 1 OT2 OD026549; 1 OT2 OD026554; 1 OT2 OD026557; 1 OT2 OD026556; 1 OT2 OD026550; 1 OT2 OD 026552; 1 OT2 OD026553; 1 OT2 OD026548; 1 OT2 OD026551; 1 OT2 OD026555; IAA #: AOD 16037. Federally Qualified Health Centers: HHSN 263201600085U. Data and Research Center: 5 U2C OD023196. Biobank: 1 U24 OD023121. The Participant Center: U24 OD023176. Participant Technology Systems Center: 1 U24 OD023163. Communications and Engagement: 3 OT2 OD023205; 3 OT2 OD023206. Community Partners: 1 OT2 OD025277; 3 OT2 OD025315; 1 OT2 OD025337; 1 OT2 OD025276). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. All of Us Funding Information: Kimberly A. Gudzune serves as the medical director for the American Board of Obesity Medicine, has a research grant from Novo Nordisk and is a paid consultant to Eli Lilly. Jessica L. Schwartz is a co‐investigator on a research grant from Novo Nordisk. All other authors declare no conflicts of interest. Publisher Copyright: © 2023 World Obesity Federation.
PY - 2023/10
Y1 - 2023/10
N2 - Our objective was to describe the use of medications associated with weight change among US adults with overweight/obesity, including anti-obesity medications (AOMs), weight-loss-promoting and weight-gain-promoting medications. We performed a cross-sectional analysis of data from the nationwide All of Us Research Programme. We included adults with measured body mass index (BMI) ≥ 27 kg/m2 enrolled between 2018 and 2022 across the United States. We used linked electronic health record data to determine medication use ±12 months of BMI measure. Our 132 057 participants had mean age 54 years and mean BMI 34 kg/m2; 60% of participants were women, 62% White, and 32% Black. Only 1% used any AOM, and 14% used at least one weight-loss-promoting medication. We found that 36% used at least one weight-gain-promoting medication, and approximately 20% used multiple weight-gain-promoting medications. While AOMs are underutilized by participants with overweight/obesity, weight-gain-promoting medication use is common. Our results raise concern about potential iatrogenic weight gain from medications. Future research is needed to estimate the long-term effect of weight-gain-promoting medications on weight status and determine whether weight-loss benefits occur with their discontinuation. Clinician education on AOMs and weight-loss-promoting medications may be needed to increase their use.
AB - Our objective was to describe the use of medications associated with weight change among US adults with overweight/obesity, including anti-obesity medications (AOMs), weight-loss-promoting and weight-gain-promoting medications. We performed a cross-sectional analysis of data from the nationwide All of Us Research Programme. We included adults with measured body mass index (BMI) ≥ 27 kg/m2 enrolled between 2018 and 2022 across the United States. We used linked electronic health record data to determine medication use ±12 months of BMI measure. Our 132 057 participants had mean age 54 years and mean BMI 34 kg/m2; 60% of participants were women, 62% White, and 32% Black. Only 1% used any AOM, and 14% used at least one weight-loss-promoting medication. We found that 36% used at least one weight-gain-promoting medication, and approximately 20% used multiple weight-gain-promoting medications. While AOMs are underutilized by participants with overweight/obesity, weight-gain-promoting medication use is common. Our results raise concern about potential iatrogenic weight gain from medications. Future research is needed to estimate the long-term effect of weight-gain-promoting medications on weight status and determine whether weight-loss benefits occur with their discontinuation. Clinician education on AOMs and weight-loss-promoting medications may be needed to increase their use.
KW - anti-obesity agents
KW - body weight changes
KW - drug side effects
KW - obesity
UR - http://www.scopus.com/inward/record.url?scp=85165383526&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85165383526&partnerID=8YFLogxK
U2 - 10.1111/cob.12609
DO - 10.1111/cob.12609
M3 - Article
C2 - 37455380
AN - SCOPUS:85165383526
SN - 1758-8103
VL - 13
JO - Clinical obesity
JF - Clinical obesity
IS - 5
M1 - e12609
ER -