Population-Based Data Supporting Escitalopram as a Safer Antidepressant with Lower Mortality and Fewer Side Effects Compared to Other Medications

Population-Based Data Supporting Escitalopram as a Safer Antidepressant with Lower Mortality and Fewer Side Effects Compared to Other Medications | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 13 March 2026 V1 Latest version Share on Population-Based Data Supporting Escitalopram as a Safer Antidepressant with Lower Mortality and Fewer Side Effects Compared to Other Medications Authors : Zerui You , Tuzhi Wang , Lutong Gan , Simeng Feng , and Jiyang Pan 0000-0003-2802-0137 [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.177343055.52470991/v1 146 views 68 downloads Contents Abstract ABSTRACT Key Points Plain Language Summary INTRODUCTION DISCUSSION CONCLUSION References Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Purpose: This study aimed to compare the long-term safety profiles of different antidepressants. Methods: We utilized integrated databases, the National Health and Nutrition Examination Survey (NHANES) 2005-2018, to investigate the relationship between various antidepressants and health outcomes. Overall, 11 antidepressants were included in the main analysis, each used by at least 100 individuals with an average medication of over 40 months. Hazard ratios (HRs) and restricted mean survival time (RMST) were estimated to quantify differences in survival outcomes. Depression was assessed using the Patient Health Questionnaire-9. Results: A total of 5077 participants with depression were included. After adjustment, all antidepressants use had a trend toward increased long sleep duration risk (odds ratio [OR] range, 1.84-3.72; all p < 0.05) and reduced suicidal ideation risk (OR range, 0.25-0.47; all p < 0.05), except for mirtazapine. Users of bupropion, citalopram, duloxetine, sertraline, fluoxetine, and venlafaxine had higher obesity risk (OR range, 1.26-1.44; all p < 0.05). Only bupropion and escitalopram users were at lower risk for all-cause mortality, with an adjusted hazard ratio (aHR) of 0.66 (95% CI, 0.45 - 0.97; p = 0.036) for bupropion and 0.68 (95% CI, 0.47 - 0.93; p = 0.019) for escitalopram. Escitalopram users showed the most significant survival benefit (RMST difference, 30.1 [95% CI, 25.2-35.0] months; p < 0.001). Conclusions: Real-world evidence indicates that antidepressants have an extensive impact on overall health. Escitalopram is linked to reduced all-cause mortality risk and improved survival outcomes, suggesting its potential as a better treatment option for depression. Text: 3507 words Abstract: 250 words Table: 3 Figures: 2 Population-Based Data Supporting Escitalopram as a Safer Antidepressant with Lower Mortality and Fewer Side Effects Compared to Other Medications Author list : Zerui You a ; Tuzhi Wang a ; Lutong Gan a ; Simeng Feng a ; Jiyang Pan a * ; a Sleep Medicine Centre, First Affiliated Hospital of Jinan University, Guangzhou, 510632, P.R. China * Corresponding author: Jiyang Pan, M.D., Sleep Medicine Centre, First Affiliated Hospital of Jinan University, Guangzhou, Guangdong Province, 510632, P.R. China E-mail: [email protected] Tel.: +86 18675872910 ABSTRACT Purpose: This study aimed to compare the long-term safety profiles of different antidepressants. Methods: We utilized integrated databases, the National Health and Nutrition Examination Survey (NHANES) 2005-2018, to investigate the relationship between various antidepressants and health outcomes. Overall, 11 antidepressants were included in the main analysis, each used by at least 100 individuals with an average medication of over 40 months. Hazard ratios (HRs) and restricted mean survival time (RMST) were estimated to quantify differences in survival outcomes. Depression was assessed using the Patient Health Questionnaire-9. Results: A total of 5077 participants with depression were included. After adjustment, all antidepressants use had a trend toward increased long sleep duration risk (odds ratio [OR] range, 1.84-3.72; all p < 0.05) and reduced suicidal ideation risk (OR range, 0.25-0.47; all p < 0.05), except for mirtazapine. Users of bupropion, citalopram, duloxetine, sertraline, fluoxetine, and venlafaxine had higher obesity risk (OR range, 1.26-1.44; all p < 0.05). Only bupropion and escitalopram users were at lower risk for all-cause mortality, with an adjusted hazard ratio (aHR) of 0.66 (95% CI, 0.45 - 0.97; p = 0.036) for bupropion and 0.68 (95% CI, 0.47 - 0.93; p = 0.019) for escitalopram. Escitalopram users showed the most significant survival benefit (RMST difference, 30.1 [95% CI, 25.2-35.0] months; p < 0.001). Conclusions: Real-world evidence indicates that antidepressants have an extensive impact on overall health. Escitalopram is linked to reduced all-cause mortality risk and improved survival outcomes, suggesting its potential as a better treatment option for depression. Keywords: Antidepressant, NHANES, Mortality, Escitalopram Key Points • This real-world study analyzed data from 5077 participants with depression in the NHANES database (2005–2018) to evaluate the long-term health outcomes associated with 11 different antidepressants. • Most antidepressants were linked to an increased risk of long sleep duration and obesity, and a reduced risk of suicidal ideation. • Escitalopram and bupropion were associated with a significantly lower risk of all-cause mortality. • Escitalopram users experienced the most pronounced survival benefit, with a restricted mean survival time (RMST) difference of 30.1 months compared to non-users. Plain Language Summary This study used real-world data from a large U.S. health survey to examine the long-term effects of commonly prescribed antidepressants on overall health and survival. The researchers analyzed information from over 5,000 adults with depression who had been taking one of 11 different antidepressants for an average of more than three years. The findings show that while most antidepressants were linked to a higher risk of obesity and longer sleep duration, they were also associated with a lower risk of suicidal thoughts. Importantly, two medications—escitalopram and bupropion—were linked to a lower risk of death from any cause. Escitalopram, in particular, showed the strongest association with improved survival, suggesting it may offer advantages as a treatment option for depression. This real-world evidence illuminates the complex risk-benefit landscape of antidepressant use, demonstrating that treatment choice may have profound implications not only for mental health but also for critical physical health outcomes and long-term survival. INTRODUCTION Depression is a prevalent mental health disorder among the US population, carrying substantial social and economic burdens. Despite the wide range of treatment options for depression, including both pharmacological and psychotherapeutic approaches, antidepressants are routinely prioritized[1]. This preference is mainly due to their accessibility, the breadth of symptoms they address, and the perceived efficacy in managing symptoms. However, many antidepressants are associated with a range of documented side effects. A study found that 63% of patients reported experiencing side effects during a follow-up period of 1 to 2 years related to antidepressant treatment[2]. Reviews have determined that long-term use of selective serotonin reuptake inhibitors (SSRIs) is associated with adverse effects, including self-harm and suicide, weight gain and obesity, sleep disturbances, and others[3–5]. Therefore, although antidepressants are vital for managing depression, their potential side effects necessitate careful consideration. Understanding the long-term side effects associated with different classes of antidepressants could provide valuable insights. Antidepressants could attenuate the deleterious outcomes of depression, including an increased prevalence of disturbed sleep, suicide, cardiovascular diseases (CVD), and premature mortality[6–9]. Scherrer and his colleagues found that all classes of antidepressants were associated with a reduced risk of all-cause mortality, with hazard ratios (HRs) ranging from 0.50 to 0.66[10]. Similarly, Haukka et al. showed that ongoing antidepressant use was associated with significantly lower all-cause mortality compared to those with only one prior prescription[11]. However, another study yielded contradictory results, suggesting that the risks of mortality were substantially higher in older individuals using antidepressants[12]. Such discrepancies might be ascribed to the heterogeneity of antidepressants[13]. Tricyclic antidepressants (TCAs) are known to have pharmacological properties that can precipitate life-threatening arrhythmias and orthostatic hypotension and prolong QT-interval, with a higher risk of cardiovascular disease[14]. At the same time, SSRIs could reduce this risk through attenuation of serotonin-mediated platelet activation in addition to treatment of depression itself[15,16]. Consequently, the ambiguity necessitates additional validation of both all-cause and cardiovascular mortality associated with antidepressants. However, to the best of our knowledge, no recent studies have examined the influence of antidepressants on mortality risk among U.S. adults， particularly using the National Health and Nutrition Examination Survey (NHANES) mortality data. In light of these existing knowledge gaps, there is an urgent need to re-examine the beneficial pattern and the mortality risk associated with different antidepressants among adults with depressive symptoms. The chronicity of depression makes it challenging to observe mortality outcomes directly; therefore, we aimed to address this challenge by exploring the real-world data from NHANES. Hence, the objectives of the current study were to (1) identify differences in side effects among various antidepressants, such as short or long sleep duration, suicidal ideation, and obesity, and (2) examine the relation between antidepressant use and both cardiovascular disease (CVD) and all-cause mortality. As an exploratory objective, we evaluated different antidepressants in depression patients, hypothesizing that, despite their side effects, their use would be associated with increased survival time, based on the U.S. National Health and Nutrition Examination Survey (NHANES) data, controlling for socio-demographic, lifestyle, and health status variables. Study population This cross-sectional study was designed using data from the 2005–2018 NHANES, which was conducted by the National Center for Health Statistics (NCHS) to assess the health and dietary conditions of the U.S. population. The NCHS Research Ethics Review Board approved the NHANES protocol. Informed written consent was obtained from all participants. Further information regarding the NHANES initiative is available on the official website of the Centers for Disease Control and Prevention (CDC). The participants were evaluated for eligibility based on the following conditions: (1) aged 18 years or above; (2) diagnosed with depression (currently using antidepressants or exhibiting depressive symptoms); (3) with the documented history of medication usage; (4) completed data available for relevant covariates, such as educational attainment, smoking, and alcohol consumption. In total, 5,077 individuals were included in the final analysis, as illustrated in Fig. 1. Methods of Depression Assessment and Suicidal Ideation Depression participants were defined as having depressive symptoms or currently taking antidepressants from NHANES medication data. The 9-item Patient Health Questionnaire (PHQ-9) was employed to evaluate depressive symptomatology. It is widely recognized as a reliable and valid tool for depression screening, with scores ranging from 0 to 27, where higher scores indicate greater severity. A PHQ-9 score of ≥10 shows high sensitivity and specificity for major depressive disorder when compared to clinical criteria[17]. Suicidal ideation was assessed through Item 9 of the PHQ-9, specifically regarding “thoughts that you would be better off dead or thoughts of self-harm.” For analysis, scores exceeding 0 (i.e., occurring on several days or more) were interpreted as indicative of suicidality. Medication for Depression Participants were inquired about their use of prescribed medications during the past month via self-report, with NHANES interviewers corroborating medication consumption. Those who affirmed usage were instructed to present the medication containers or prescription list to the interviewer or verbally disclose the names of the medications. Approximately 75% of the prescribed medications were verified through direct observation by the interviewer. This study primarily concentrated on the utilization of pharmacological agents for the treatment of depression, encompassing the active antidepressants evaluated in double-blind, randomized controlled trials (RCTs), all second-generation antidepressants sanctioned by regulatory authorities in the United States, Europe, or Japan, and the rescue medications prescribed for depressive disorders[1]. A total of 21 antidepressants were systematically examined within the NHANES medication dataset (Table S1). Of these, one was not detected, and nine antidepressants were excluded from the analysis due to inadequate sample sizes (< 30 users). Ultimately, 11 antidepressants were retained for inclusion in the subsequent analyses, each used by a minimum of 100 individuals who had been on these medications for an average duration exceeding 40 months. Taking into account the real-world complexity of medication and drug combinations for patients with depression, the main analysis included participants who received the specific type of antidepressant, including those on multiple antidepressant therapies. The sensitivity analysis focused on regimens involving a single antidepressant without other types of antidepressants. Assessment of the side effects Based on the contents of NHANES data, three long-term side effects of antidepressants were considered: sleep duration (both short and long sleep duration), and obesity. Sleep duration was evaluated utilizing the NHANES questionnaire via a questionnaire administered by trained interviewers, facilitated by a computer-assisted personal interview system. Participants also provided self-reported data on their habitual sleep duration during weekdays, measured in hours. Sleep duration was characterized as short sleep duration (< 7 hours) and long sleep duration (9 hours or more) referenced to normal sleep (7-8 hours)[18]. Obesity was defined as a body mass index (calculated as weight in kilograms divided by height in meters squared) of 30 or greater. Mortality outcomes of the study population All-cause mortality was sourced from the US National Death Index (NDI) search, maintained by the CDC (https://www.cdc.gov/nchs/data-linkage/mortality-public.htm). The NDI was run on all clinical trial participants at biennial to triennial intervals. The follow-up period for each participant was computed from the enrollment date until either the date of death or December 31, 2019, which corresponded to the most recent update of the NDI database. Cardiovascular mortality was determined utilizing the International Classification of Diseases 10th revision (ICD-10) diagnostic classifications (codes I00-I09, I11, I13, I20-I51, I60-I69). Covariates Continuous covariates included age at interview and the income level, which was defined by the ratio of household income to poverty (PIR). Race/ethnicity, education level (less than 9th grade, 9th to 11th grade, high school diploma recipient, some college or Associate of Arts degree holder, college graduate or above), body mass index (BMI) group (underweight, normal weight, overweight, obesity), marital status (single or non-single), smoking status (never/former/current), alcohol status (yes/no), cardiovascular disease (CVD) history (yes/no), stroke history (yes/no), and diabetes mellitus (yes/no) were used as categorical variables. The BMI was defined as body weight (kg)/height 2 (m 2 ) and categorized according to the World Health Organization classification: underweight (BMI < 18.5), normal weight (BMI 18.5 to < 25), overweight (BMI 25 to < 30), and obesity (BMI ≥30). Marital status was classified into two groups: single (widowed, divorced, or separated) or non-single (married or living with a partner). Smoking status was classified as never (smoked <100 cigarettes), former (not currently smoking but smoked ≥100 cigarettes), and current smoking (≥ 100 cigarettes and currently smoking every day or on some days). Alcohol use was categorized into two categories: never drinking and ever or current drinking. CVD history was defined as a self-reported history of coronary heart disease and heart failure. Diabetes mellitus and stroke history were determined based on self-reported diagnoses provided by medical professionals. Statistical Analysis Continuous variables were summarized as mean and standard deviation (SD) or median with interquartile range (IQR), whereas categorical variables were reported as frequency and proportion. The characteristics were compared using the appropriate statistical tests, including the independent Student’s t-test, Mann-Whitney U test, or Chi-squared test. Logistic regression analysis was conducted to examine the effect of antidepressants on sleep duration, suicide ideation, and obesity. The Cox regression model calculated hazard ratios (HR) and 95% confidence interval (CI). The impact of antidepressant use on all-cause mortality was evaluated through incremental adjustments for covariates across various models. Crude model was a univariate model. Model I was adjusted for all demographic covariates, and Model II was adjusted for all demographic covariates and the history of heart disease and the presence of diabetes to explore stability. Statistical computations were performed using the “survey” package in R software (version 4.0.4). We used restricted mean survival time (RMST), a robust summary measure, to interpret as the mean time free from an outcome event adjusted for loss to follow-up, reflecting the area under the survival curve[19–21]. RMST difference (absolute survival benefit) reflects that participants will live longer (positive) or shorter (negative), with its magnitude representing the size of average gain or lost in life expectancy within prespecific time (τ). The prespecific time was set at the maximum follow-up period in each group. We quantified the survival benefits of antidepressant therapies compared with non-users by using RMST difference. The adjusted RMST difference (adjusted for all covariates) between groups in the restricted mean survival time is reported. All analyses and models were conducted using R (version 4.3.2). The significance level was set at p < 0.05. RESULTS Population characteristics The number of participants with depression from NHANES 2005–2018 was 5077. Of these, 3251(64.0%) are currently taking antidepressants, while 1,826 (36.0%) are not. Demographic and clinical characteristics are summarized in Table 1. Among the total participants, 3295 (64.9%) were female, 2851 (56.2%) were non-Hispanic White, and the median age of participants was 52.0 years. Participants with antidepressants were significantly older at evaluation than those without antidepressants (median age, 55.0 vs 47.0 years; p<0.001). Compared to non-users, participants with antidepressants were more likely to be female, white, obese, high-income, never smokers, and have lower physical activity, college education or greater, and a higher prevalence of diabetes mellitus. Effects of antidepressants on sleep duration, obesity, and suicidal ideation Of the eleven antidepressants selected for the main analysis, the most commonly used were sertraline (17.6% of total antidepressant users, 573 participants), citalopram (14.5%, 473 participants), bupropion (12.9%, 420 participants), and others. All antidepressants had an average medication duration of over 40 months, with fluoxetine users having the longest mean duration (77.9 months) and mirtazapine users having the shortest mean duration (40.2 months). More data on user number and mean duration of other medications are presented in Figure 2A-B. Participants had a mean BMI of 30.8, with 48% classified as obese (2438 participants, Table S2). The mean sleep duration for all participants was 7.04 hours, accompanied by a mean PHQ score of 9.10. In contrast, non-users had a mean sleep duration of 6.50 hours and a mean PHQ score of 13.88. Compared with non-users, all antidepressant users included demonstrated a significant decrease in PHQ score (all t < -9.58, all p 4.45, all p<0.001), which suggests an association between antidepressant use and improvements in depressive symptoms and sleep duration. In multivariable logistic regression, compared with non-users, participants with whichever antidepressants had a trend for decreased risk of short sleep duration (different antidepressants: odds ratio [OR] range, 0.43-0.59; all p<0.01) and increased risk of long sleep duration (OR range, 1.84-3.72; all p<0.05) at the same time after adjusting for demographic covariates in the model (Table 2). Except for mirtazapine, participants using other antidepressants had a reduced risk of experiencing suicidal ideation (OR range, 0.25-0.47; all p<0.001). Additionally, participants using various antidepressants, including bupropion, citalopram, duloxetine, sertraline, fluoxetine, and venlafaxine, had higher obesity risk (OR range, 1.26-1.44; all p<0.05). Mortality and survival Over an average follow-up period of 87.6 months, there were 700 all-cause deaths. Crude models (unadjusted models) linked most antidepressants, including amitriptyline, citalopram, mirtazapine, paroxetine, sertraline, and trazodone, with higher all-cause mortality (Fig 2C and Table S3). However, after adjusting for potential confounders, only bupropion and escitalopram were associated with a reduced risk of all-cause mortality. The adjusted hazard ratios (aHR) were 0.66 (95% CI, 0.45-0.97; p = 0.036) for bupropion and 0.68 (95% CI, 0.47-0.93; p = 0.019) for escitalopram, while no significant association was found for other antidepressants regarding all-cause mortality (Table 3). Additionally, all antidepressants were not associated with cardiovascular mortality (Table S4). Adjusting for potential confounders in a multivariable model and relative to the participants without antidepressants, survival differences ranged from -1.7 to 30.1 months at each maximum follow-up period. Except for bupropion and duloxetine, the differences in survival outcomes among antidepressants were significantly longer than non-users (adjusted RMST difference range, 3.5-30.1 months, all p < 0.001). Escitalopram users showed the longest survival difference, with an adjusted RMST difference of 30.1 months (95% CI, 25.2-35.0; p < 0.001; Table 3), with no observed increase in obesity risk. Sensitivity analysis The sensitivity analysis took part in participants who used only one kind of antidepressant. Our observations revealed trends consistent with those found in the primary analysis when comparing participants with and without antidepressants (Tables S5-9). Only escitalopram users, compared to participants without antidepressants, showed a lower risk for all-cause mortality, with aHR of 0.69 (95% CI, 0.48-0.99; p = 0.046). Additionally, the adjusted RMST difference became longer at 30.9 months (95% CI, 25.3-36.5; p < 0.001; Table S7). DISCUSSION Most antidepressants were associated with reduced suicidal ideation and increased risk of long sleep duration, and some were associated with increased risk of obesity. Among the eleven antidepressants assessed, only bupropion and escitalopram were associated with a reduced risk of all-cause mortality after adjusting for confounders. Escitalopram users exhibited the most significant survival benefit, with no associated obesity risk. We initially found that many antidepressants were all associated with a higher risk of all-cause mortality. However, most associations became statistically insignificant after adjusting for socio-demographic factors. These results suggested that the observed correlation between antidepressants and elevated mortality may stem from confounding factors such as unhealthy lifestyle behaviors and CVD history, which are known contributors to increased mortality. For example, a study on patients with chronic kidney disease found that elevated depressive symptoms were linked to a higher risk of hospitalization and mortality, regardless of antidepressant treatment status[22]. Evidence suggests that it is the depression itself, or the residual symptoms following treatment, that are responsible for the elevated mortality rather than the antidepressants[23]. These findings imply that the severity of depression and its associated health complications may contribute more to mortality risk than antidepressants[24]. It is noteworthy that escitalopram is associated with a reduced risk of all-cause mortality, and the increase in RMST was almost 30 months after adjustments of covariates. However, according to evidence from randomized controlled trials (RCTs), escitalopram had been found to be associated with a decreased risk of major adverse cardiac events, but not all-cause mortality, in patients suffering from depression and acute coronary syndrome[25]. Similarly, Angermann et al. found no evidence supporting that escitalopram reduces all-cause mortality or hospitalization in patients with chronic systolic heart failure and depression[26]. The discrepancy between our results and the previous studies may be due to the diverse study populations. Thus, the mortality benefit of escitalopram is open to debate. Taken together, the comprehensive rise in mortality in depressed patients can be attributed to the disease itself rather than to antidepressants. Larger studies are needed to confirm the mortality benefits of the drugs. We also found that, compared to non-users, all eleven antidepressants were associated with longer sleep duration and reduced suicidal ideation. Our data showed that the use of antidepressants may lead to an increase in sleep duration. Ramic et al. conducted a prospective cross-sectional study that included over 500 patients with depression treated with antidepressants[27], and the somatic side effects reported tiredness in 45% of subjects. Additionally, the side effects of SSRIs, including both increased and decreased sleep, were correlated with treatment duration in subjects. Other real-world data shows that sleepiness is one of the most common side effects reported by SSRI users[28]. Garfield et al. also found that increased duration of sleep was one of the drug-placebo side-effect differences in SSRIs[29]. These findings suggest that antidepressants may increase sleep duration, which is a common side effect in this population. Previous data demonstrate that patients with major depressive disorder (MDD) aged 25 years and older have more suicidal thoughts when using any antidepressant, but suicidal thoughts tend to improve over time with medication[30]. Our results supported and aligned with this prior finding, suggesting that the long-term use of all kinds of antidepressants could mitigate suicidal ideation and reduce their frequency in adults with depression. Our data revealed that the mean BMI of US adults with depression came to 30.8 kg/m2, with 48% classified as obese, higher than the 40% observed in the general population[31]. This disparity highlights a potential association between depression and obesity. Epidemiological evidence and biological mechanisms provide substantial evidence for a link between depression and obesity[32]. The odds ratios of depression among the obese ranged from 1.23 to 1.41 in pooled cross-sectional studies. All of these results call for a more integrated treatment approach to depression and obesity, one that addresses both conditions simultaneously rather than in isolation. Some antidepressants in our data, including bupropion, citalopram, duloxetine, sertraline, fluoxetine, and venlafaxine, were associated with an increased risk of obesity. The somatic side effects reported swelling in 10% of subjects treated with antidepressants[27]. In another 10-year longitudinal study, the risk of obesity was associated with antidepressant type, particularly SSRIs, with venlafaxine significantly linked to an increased risk[33]. This result aligns with our findings, suggesting the risk of obesity needs to be incorporated into consideration in the long-term use of antidepressants. Previous results evidenced that bupropion was associated with a greater risk of weight loss in long-term treatment[29]. However, our findings indicated that bupropion was associated with obesity. This difference in results may be due to the different calculation methods for the weight. Previous studies have focused on individual weight changes[34], while our cross-sectional study looked at obesity risk at the population level. Although bupropion is often linked to modest weight loss[35], the reduction is typically tiny (about 5-10% of total body weight) [36,37], which may be only a few pounds[38,39]. Among patients receiving antidepressants, those who smoked and started bupropion gained an average weight of 2.2 pounds, compared to those using fluoxetine[39]. Additionally, Fiedorowicz and his colleagues found that patients with MDD using bupropion-containing medications were significantly more likely to experience weight gain at week 24 compared to those not using bupropion [40]. These results highlight the importance of study design and methodology in interpreting the effects of antidepressants on weight, particularly when comparing individual weight changes versus population-level obesity risks. Different lines of evidence support that population-based investigations may offer useful insights into antidepressants, aiding in the identification of side effects, risk factors, and long-term effects. One strength of our investigation is that a nationally representative sample with the longitudinal design was used, in which eleven antidepressants were assessed. However, our study findings should be interpreted considering the following limitations. First, in real-world conditions, patients may be taking multiple antidepressants. Therefore, we attempted to exclude the influence of multiple antidepressants in the sensitivity analysis, specifically by analyzing the effects of using a single antidepressant. The results were largely consistent. Second, the antidepressant use was assessed only at baseline, without accounting for dynamic changes during the follow-up phase. However, these participants have generally been using the same antidepressant for several years, suggesting that their medication history is relatively stable. Third, the reliance on self-reported data for variables such as suicidal ideation (assessed with a single item), sleep duration, CVD, and diabetes introduces potential recall bias and limits the nuanced assessment of severity. Finally, although the multivariable analysis was adjusted for socio-demographic variables and a history of CVD and diabetes, the possibility of residual confounding cannot be entirely excluded. CONCLUSION Real-world evidence indicated that all antidepressants exerted long-term side effects, including an extension of sleep duration, with some also associated with an increased risk of obesity. Only two antidepressants, including bupropion and escitalopram, were associated with a reduction in all-cause mortality. Escitalopram users exhibited a significant survival benefit, with no observed increase in obesity risk. Declaration of Interest Statement The authors have no actual or potential conflicts of interest to declare. Data Availability Statement All relevant data are presented in this paper. The NHANES data utilized in the current study can be accessed through the CDC website: https://wwwn.cdc.gov/nchs/nhanes/Default.aspx. Authorship contribution statement Zerui You: Conceptualization, Methodology, Data extraction, Statistical analysis, Writing-original draft, Writing-review & editing. Tuzhi Wang, Lutong Gan, Simeng Feng: Conceptualization, Methodology. Jiyang Pan: Conceptualization, Funding acquisition, Investigation, Supervision, Project administration. All authors have read and agreed to the published version of the manuscript. Funding This work was funded by National Key R&D Program of China (Grant No.: 2022YFC2503902), and Guangzhou Key Laboratory for Germ-free animals and Microbiota Application (Grant No.: 202201020381). Ethical Statement The study protocols (Protocol Nos. 2011–17 and 2018–01) received approval from the NCHS Institutional Review Board (IRB), and written informed consent was obtained from all participants before enrollment (https://www.cdc.gov/nchs/nhanes/irba98.htm). Acknowledgments No. Figure legends Fig 1. Flowchart of participants included in this study. Abbreviation: NHANES, National Health and Nutrition Examination Survey; PIR, family poverty income ratio; BMI, body mass index. Figure 2. Medications information and association between antidepressants and all-cause mortality. A The number of people using different antidepressants. B The mean medication duration of different antidepressants. C Association between antidepressants and all-cause mortality. 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Obesogenic Medications and Weight Gain Over 24 Weeks in Patients with Depression: Results from the GUIDED Study. Psychopharmacol Bull. 2021 Nov;51(4):8–30. Google Scholar Information & Authors Information Version history V1 Version 1 13 March 2026 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords antidepressant escitalopram mortality nhanes Authors Affiliations Zerui You The First Affiliated Hospital of Jinan University View all articles by this author Tuzhi Wang The First Affiliated Hospital of Jinan University View all articles by this author Lutong Gan The First Affiliated Hospital of Jinan University View all articles by this author Simeng Feng The First Affiliated Hospital of Jinan University View all articles by this author Jiyang Pan 0000-0003-2802-0137 [email protected] The First Affiliated Hospital of Jinan University View all articles by this author Metrics & Citations Metrics Article Usage 146 views 68 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Zerui You, Tuzhi Wang, Lutong Gan, et al. Population-Based Data Supporting Escitalopram as a Safer Antidepressant with Lower Mortality and Fewer Side Effects Compared to Other Medications. Authorea . 13 March 2026. 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