Incident Benzodiazepine and Z-Drug Use and Subsequent Risk of Serious Infections

Abstract

Background and Objectives

Animal studies have suggested a link between benzodiazepine and related Z-drug (BZDR) use and immune dysfunction. Corresponding evidence in humans is limited and focuses mainly on pneumonia. This study aimed to assess the association of incident BZDR use with subsequent development of serious infections.

Methods

This Swedish register-based study included a population-based demographically matched cohort, a co-twin control cohort, and an active comparator cohort. Out of 7,362,979 individuals aged below 65 years who were BZDR naïve by 2007, 713,896 BZDR recipients with incident dispensation of any BZDRs between 2007 and 2019 were 1:1 matched to 713,896 nonrecipients from the general population; 9197 BZDR recipients were compared with their 9298 unexposed co-twins/co-multiples; and 434,900 BZDR recipients were compared with 428,074 incident selective serotonin reuptake inhibitor (SSRI) recipients. The outcomes were identified by the first inpatient or specialist outpatient diagnosis of serious infections in the National Patient Register, or death from any infections recorded as the underlying cause in the Cause of Death Register. Cox proportional hazards regression models were fitted and controlled for multiple confounders, including familial confounding and confounding by indication. To study a possible dose–response association, the cumulative dosage of BZDRs dispensed during the follow-up was estimated for each BZDR recipient and modeled as a time-varying exposure with dose categories in tertiles [≤ 20 defined daily doses (DDDs), > 20 DDDs ≤ 65, and > 65 DDDs). The risk of infections was assessed in BZDR recipients within each category of the cumulative BZDR dosage compared to their demographically matched nonrecipients.

Results

In the demographically matched cohort (average age at incident BZDR use 42.8 years, 56.9% female), the crude incidence rate of any serious infections in BZDR recipients and matched nonrecipients during 1-year follow-up was 4.18 [95% confidence intervals (CI) 4.13–4.23] and 1.86 (95% CI 1.83–1.89) per 100 person-years, respectively. After controlling for demographic, socioeconomic, clinical, and pharmacological confounders, BZDR use was associated with 83% relative increase in risk of any infections [hazard ratio (HR) 1.83, 95% CI 1.79–1.89]. The risk remained increased, although attenuated, in the co-twin cohort (HR 1.55, 95% CI 1.23–1.97) and active comparator cohort (HR 1.33, 95% CI 1.30–1.35). The observed risks were similar across different types of initial BZDRs and across individual BZDRs, and the risks increased with age at BZDR initiation. We also observed a dose–response association between cumulative BZDR dosage and risk of serious infections.

Conclusions

BZDR initiation was associated with increased risks of serious infections, even when considering unmeasured familial confounding and confounding by indication. The exact pathways through which BZDRs may affect immune function, however, remain unclear. Further studies are needed to explore the neurobiological mechanisms underlying the association between BZDR use and serious infections, as it can lead to safer therapeutic strategies for patients requiring BZDR.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40263-024-01108-w.

Key Summary Points

This nationwide register-based study triangulated several design approaches and reported incident use of benzodiazepines and related Z-drugs (BZDR) to be associated with 33–83% relative increase in risk of developing serious infections, both viral and bacterial, within 1 year after the treatment was initiated.

The increased risk of serious infections was observed across different initial BZDRs types and across individual BZDRs, with a dose–response association between the cumulative BZDR dosage and infection risk.

The risk of developing infections increased with age of BZDR initiation, particularly among those who initiated BZDR treatment at age 35 years and older.

Introduction

Benzodiazepines (BZD) are widely prescribed for the management of anxiety, insomnia, epilepsy and seizure disorders, alcohol withdrawal, and, in some situations, as adjuvant therapy for depression and bipolar disorder [1–3], while BZD-related Z-drugs (i.e., zolpidem, zopiclone, zaleplon, and eszopiclone) are indicated for insomnia. Although their clinical effectiveness has been well established, BZD and the related Z-drugs (hereafter “BZDR” if mentioned together) are also associated with a range of adverse effects, including developing tolerance and dependence [4], psychomotor impairment [5–8], and cognitive decline [9, 10]. The possible effects of some BZDR drugs on the immune system have been proposed by animal models [11–14] but received little attention in humans [15]. Increased risk of infections (mainly focusing on pneumonia) in BZDR users compared with nonusers has been observed in different populations (e.g., the general population, patients with Parkinson’s disease, Alzheimer disease, stroke, and trauma) [16–19]. A recent meta-analysis reported an overall 25% increased risk of pneumonia in relation to BZDR use but highlighted methodological limitations in individual studies, including the lack of control for confounding by indication [16]. A handful of studies have investigated the association between Z-drugs and the risk of infections, with inconsistent findings and often insufficient statistical power for the analyses of individual drugs [20–22]. Thus, to gain better insight on the safety profile of BZDR, there is a clear need to further understand the association between BZDR use and the subsequent development of a broader spectrum of infections. Ideally, studies should focus on different drugs and employ rigorous pharmacoepidemiological designs that can control for important confounders, including shared familial factors and confounding by indication.

In this nationwide register-based study, we examined the risk of serious infections from viral and bacterial pathogens in association with incident BZDR use in individuals aged 0 to 65 years. We used multiple study designs and analytical strategies [23, 24] to mitigate the impact of familial confounding and confounding by indication. We also explored the role of drug type and dosage on the associations of interest.

Methods

The study was approved by the Swedish Ethical Review Authority (reference number 2020-06540). The requirement for informed consent was waived because the study is register-based, and all individual data were de-identified.

Study Population

The Swedish nationwide health and administrative registers were linked via the unique personal identification number [25], with data available from inception dates of the registers to 31 December 2020 (Note S1). To ensure that all study participants had a similar opportunity to utilize Swedish healthcare services under the study period, the study population was identified from the Prescribed Drug Register (PDR) [26] and consisted of individuals who (1) had at least one dispensation record of any prescribed medication in 2007–2019 (n = 10,703,848) and (2) were BZDR naïve by 1 January 2007 (i.e., had no dispensation records of any BZDRs during a 1.5-year washout period from the PDR inception on 1 July 2005 and throughout 2006) and did not receive their first BZDR dispensation after 31 December 2019 (to allow for a 12-month follow-up before the study end on 31 December 2020) (n = 9,754,184). The study population was restricted to individuals without a lifetime diagnosis of epilepsy because of a complex relationship between epilepsy (one of indications for BZDs) and infections, particularly central nervous system infections [27]. Also, to enable the distinction between singletons and multiple births, we further restricted the study population to individuals born in Sweden with available linkages to biological mothers. Following these restrictions, 7,362,979 individuals remained available for constructing the study cohorts.

Study Design and Measures of BZDR Use

We compared incident BZDR recipients and individuals unexposed to BZDR using the triangulating design approach [23, 24]: (1) a demographically matched cohort, (2) a co-twin control cohort, and (3) an active comparator cohort. The demographically matched and active comparator cohorts included only singletons.

For all three cohorts, incident BZDR recipients were defined as those who had their first dispensation of any BZDR in 2007–2019, while the unexposed individuals were selected separately for each cohort, as described below. BZDR dispensation records were collected from the PDR using the Anatomical Therapeutic Chemical (ATC) codes for benzodiazepine derivatives in anxiolytics (N05BA), hypnotics/sedatives (N05CD), antiepileptics (N03AE), and Z-drugs (N05CF) (Table S1).

The construction of the three cohorts, together with the number of included and excluded individuals, is visualized in Fig. 1 and reported in Table S2. First, in the demographically matched cohort, incident BZDR recipients were 1:1 randomly matched to individuals from the study population who had no BZDR dispensations before or on the index date (i.e., when the exposed individuals were dispensed their first BZDR). Matching was performed by year and month of birth, sex, and county of residence in Sweden at the index date’s year. Second, to control for unmeasured familial confounding [28], we constructed a co-twin cohort of discordantly exposed twins or other multiple birth individuals, e.g., triplets by means of the Multi-Generation Register [29]. Multiple birth individuals were considered exposed if they were either the only or the first in the family to dispense their first BZDR prescription. Third, we created an active comparator cohort [30] where selective serotonin reuptake inhibitors (SSRIs) were chosen as a comparator, in line with prior literature [31, 32]. This approach helped reduce the potential for confounding by indication due to a partial overlap in psychiatric indications between BZDRs and SSRIs (e.g., anxiety disorders). Other measured covariates were balanced between BZDR recipients and SSRI recipients via the inverse probability of treatment weighting (IPTW) [33] method. Incident SSRI recipients were selected using the PDR records with N06AB ATC-codes (Table S1) if any SSRIs were dispensed for the first time in 2007–2019. Individuals with simultaneous first BZDR and first SSRI dispensations were excluded. Also, incident BZDR recipients were restricted to those with no SSRIs dispensed during the washout period (while incident SSRI recipients by default had no BZDR dispensations in the washout period, according to our study population definition). The index dates for BZDR recipients and SSRI recipients were defined separately as the dates of the first dispensation of the corresponding drugs.

Fig. 1.

Study population and the selection of the exposed individuals (BZDR recipients) and controls for each design. Detailed information on inclusion and exclusion criteria with the numbers of individuals included/excluded at the stage when each criterion was applied is reported in Table S2 (of the EMS). *Washout period refers to 1.5-year time period between 1 July 2005 (i.e., inception of the Prescribed Drug Register) and 31 December 2006. ^†At least one co-sibling from a multiple birth family did not have BZDR dispensation before and on the date when their exposed co-sibling(s) were dispensed the first BZDR (i.e., at least one co-sibling is unexposed and at least one is exposed). ^‡Incident BZDR-recipients without precedent incident dispensation of SSRI (i.e., “BZDR first”). ^§Incident SSRI-recipients without precedent incident dispensation of BZDR (i.e., “SSRI first”). **The additional exclusion criteria are the same for all three cohorts and refer to (i) age ≥ 65 years at the index date or death before the index date, (ii) in-hospital stay for > 90 days between 1 July 2005 and the index date, (iii) having emigrated/re-immigrated between 2005 and the index date, and (iv) having records of any infections in the National Patient Register during 2 years prior to the index date. ^††Refers to the incident BZDR recipients who were dispensed any SSRI for the first time during a 1.5-year washout period or after 31 December 2019 (i.e., in 2020). ^‡‡If the same person was simultaneously (co-incidentally) dispensed the first BZDR and the first SSRIs at the same date. ^§§ BZDR recipients and SSRI recipients were included only if all information on the covariates used for the inverse probability of treatment weighting (IPTW) were available (i.e., a “complete case scenario”). BZDR benzodiazepines and related Z-drugs; IPTW inverse probability of treatment weighting; PDR Prescribed Drug Register; SSRI selective serotonin reuptake inhibitors

In all three cohorts, BZDR recipients and their counterparts were considered to be eligible for analyses if they were (1) alive and aged below 65 years at the index date, (2) residing in Sweden (i.e., not emigrated/re-immigrated) between 2005 and the index date, (3) not hospitalized for more than 90 days between the start of washout period and the index date (to further clarify the exposure status since the PDR does not cover in-hospital medication use), and (4) free from any serious infections during 2 years before the index date, according to the National Patient Register. We focused on individuals aged below 65 years to reduce age-related differences in pharmacokinetics and pharmacodynamics of BZDRs (e.g., in older patients, BZDRs have prolonged elimination half‐lives, which could lead to accumulation of the drugs) [34, 35]. As a result, the final analytical sample of (1) the demographically matched cohort included 713,896 pairs of BZDR recipients and matched unexposed individuals, for whom information on matching variables was available; (2) the co-twin cohort comprised 9197 BZDR recipients and their 9298 unexposed co-twins (of which 98.8% were twin pairs and the rest were other multiple-birth siblings) from 9189 discordantly exposed families; and (3) the active comparator cohort incorporated 434,900 BZDR recipients and 428,074 SSRI recipients with complete information on all covariates used for weighting in IPTW (Fig. 1 and Table S2).

Definition of Serious Infections

We defined outcomes as the first record of any infection which required an inpatient or specialist outpatient care and was recorded as the main or secondary diagnosis in the National Patient Register, or as death due to any infection which was considered the underlying death cause in the Cause of Death Register. The diagnoses in question and the corresponding International Classification of Diseases, Tenth Edition (ICD-10) codes are reported in Table S3. To assess the risk of infections in proximity to initiation of BZDR treatment and in line with prior studies [16], the outcomes were collected if they occurred within 12 months after the index date. We constructed outcome variables as “any serious infections,” “viral infections,” “bacterial infections,” and “mixed and others,” with the latter referring to simultaneously recorded viral and bacterial infections or to infections with unknown origin. The outcome definition did not include cases of COVID-19 infection.

Covariates

We collected demographic data (birth year and month, sex, county of residence at the index date), socioeconomic characteristics (household disposable income the year before the index date), calendar year of the index date, history of psychiatric and somatic diagnoses before the index date (with ICD-10 codes for the diagnoses listed in Table S4), and records of other medications dispensed within 3 months prior to the index date (with ATC-codes listed in Table S1). Also, to rule out a general susceptibility to infectious diseases, we collected data on history of inpatient and specialist outpatient diagnoses of any infections recorded before 2-year infection-free period that preceded the index date (using the same ICD-10 codes from the National Patient Register as for the outcomes).

Statistical Analysis

We used Cox proportional hazards regression models with the days since the index date as the underlying time scale. In all three cohorts, BZDR recipients and their unexposed counterparts were followed-up from the index date until the date of outcome event, emigration, death other than by infection, end of a 12-month follow-up period, or end of study on 31 December 2020, whichever came first. Unexposed individuals in the demographically matched and co-twin cohorts as well as BZDR recipients and SSRI recipients in the active comparator cohort were additionally censored at the date they changed the exposure status, if such change occurred during the follow-up. The hazard ratio and 95% confidence intervals were estimated for any serious infections and, separately, for viral, bacterial, and mixed/other infections. For each cohort, baseline crude models were followed by models adjusted for all study covariates. For the demographically matched and co-twin cohorts, the covariates included in the fully adjusted model are listed in Tables S5 and S6, respectively. For the active comparator cohort, individuals were weighted by the inverse of the predicted probability of their observed exposure to incident BZDR or SSRI use conditional on all potential confounders listed in Table S7. We truncated stabilized weights at the 1st and 99th percentiles to minimize impact of extreme values [33, 36]. The use of the inverse probability of treatment weighting resulted in balanced covariates between BZDR recipients and SSRI recipients (all standardized differences were < 0.05 [36]; Table S7). In all three cohorts, the main analyses were followed by an exploratory analysis where models were stratified by sex.

A series of additional analyses were performed in the demographically matched cohort with “any serious infections” as the outcome of interest. First, we re-ran the main analysis with the exposure subdivided by the type of the initial BZDR (as anxiolytics, hypnotics/sedatives, antiepileptics, Z-drugs, based on their ATC codes, or as poly-BZDRs, if more than one BZDR was dispensed at the treatment initiation). Second, we further subdivided the exposure by the specific initial BZDR drug. Third, exposure to incident BZDR use was categorized according to the cumulative dosage [measured by the defined daily dose (DDD)], for which we additionally collected information on all BZDR dispensations under the follow-up for each BZDR recipient. Cumulative dosage was assessed as a time-varying exposure and categorized based on tertiles into ≤ 20 DDDs, > 20 DDDs ≤ 65, and > 65 DDDs (Note S2 provides the details). Lastly, we assessed the effect modification by age at the index date. We modeled age using restricted cubic splines with 5 knots placed at 5, 27.5, 50, 72.5, and 95 quantiles and added an interaction term between exposure and the splined age to the fully adjusted model.

For all tests, we employed two-tailed significance set at p < 0.05. Data management and analyses were performed using SAS, version 9.4 (SAS Institute Inc).

Patient Involvement

No patients were involved in setting the research question or the outcome measures, nor were they involved in the design and implementation of the study. As this is a register-based study based on de-identified data, there are no plans to disseminate the results of the research directly to study participants. The study is co-authored by researchers affiliated to the Stockholm Health Care Services, Region Stockholm, where results will be widely disseminated. Dissemination to the broader Swedish population will be achieved through media outreach on publication of this study.

Results

In all three study cohorts—the demographically matched, co-twin control, and active comparator cohorts—more than half of the BZDR recipients were female (56.9% of 713,896, 58.6% of 9197, and 54.4% of 434,900, respectively), and the mean age at BZDR initiation was 42.8, 41.9, and 45.6 years, respectively (Table 1). Compared with the nonrecipients, in the demographically matched cohort, higher proportions of BZDR recipients had history of psychiatric and somatic disorders, other medication dispensations, and lower household income (all p-values < 0.01; Table S5). Similar differences were observed in the co-twin cohort (Table S6). In the active comparator cohort, all characteristics were balanced after applying IPTW (Table S7).

Table 1.

General characteristics of BZDR-recipients and nonrecipients in each study cohort

	BZDR-recipients	Nonrecipientsa
Demographically matched cohort
Included individuals, n	713,896	713,896
Female, n (%)	406,397 (56.9)	406,397 (56.9)
Age at the index date (years), mean ± SD	42.8 ± 14.1	42.8 ± 14.1
Follow-up (days), mean ± SD	347 ± 68	355 ± 52
Co-twin control cohortb
Included individuals, n	9197	9298
Female, n (%)	5385 (58.6)	4735 (50.9)
Age at the index date (years), mean ± SD	41.9 ± 15.5	41.9 ± 15.5
Follow-up (days), mean ± SD	346 ± 70	354 ± 52
SSRI active comparator cohortc
Included individuals, n	434,900	428,074
Female, n (%)	236,610 (54.4)	264,900 (61.9)
Age at the index date (years), mean ±SD	45.6 ± 13.0	34.4 ± 13.2
Follow-up (days), mean ± SD	331 ± 115	334 ± 89

BZDR benzodiazepines and benzodiazepine-related Z-drugs; SD standard deviation; SSRI selective serotonin reuptake inhibitors

^aFor the demographically matched cohort: individuals who were not dispensed BZDRs before or on the index date and matched to BZDR recipients by year and month of birth, sex, and county of residence in Sweden at the index date’s year. For the co-twin control cohort: co-multiple(s) who were not dispensed BZDRs before and on the index date. For the active comparator cohort: incident SSRI recipients with the first SSRI dispensation in 2007–2019

^bAmong the individuals who comprised the co-twin control cohort, 98.8% were twin pairs and the rest were other multiple-birth siblings (e.g., triplet, etc.)

^cCharacteristics are presented for unweighted sample of exposed and unexposed individuals

Demographically Matched Cohort

In the demographically matched cohort, during the 1-year follow-up 28,354 incident diagnoses of any serious infections were recorded among 713,896 BZDR recipients, and 12,904 infection cases were found among 713,896 matched nonrecipients, resulting in crude incidence rates of 4.18 [95% confidence intervals (CI) 4.13–4.23] and 1.86 (95% CI 1.83–1.89) per 100 person-years, respectively (Table 2). Over 80% of the outcome cases corresponded to bacterial infections (i.e., 23,021 and 10,623 cases of bacterial infections among BZDR recipients and nonrecipients, respectively). While the absolute risks of infections in exposed and unexposed individuals were fairly low, there was an over two-fold relative increase in risk of any infections in BZDR recipients compared with matched individuals [hazard ratio (HR) 2.25, 95% CI 2.20–2.29]. After controlling for all covariates, the risk estimates were slightly attenuated, but remained increased (HR 1.83, 95% CI 1.79–1.89). Similar results were observed in fully-adjusted model for viral (HR 2.00, 95% CI 1.88–2.14), bacterial (HR 1.79, 95% CI 1.74–1.85), and mixed/other infections (HR 3.29, 95% CI 2.32–4.67); although the latter results should be interpreted with caution due to more limited power. In the sex-stratified analysis, the risk of any infections remained increased in all BZDR recipients, with stronger increase among male (HR 2.09, 95% CI 1.99–2.19) than that in female (HR 1.71, 95% CI 1.66–1.77) (p < 0.001 for interaction [37]) (Table S8).

Table 2.

Hazard ratios (95% confidence intervals) for the risk of developing serious infections among BZDR recipients in comparison to nonrecipients

	Cases of infections (crude incidence rate per 100 person-years)			Baseline model (unadjusted)	Fully adjusted model
	BZDR recipients		Nonrecipients	HR (95% CI)	HR (95% CI)
Demographically matched
Infection (any)	28,354 (4.18)		12,904 (1.86)	2.25 (2.20–2.29)	1.83 (1.79–1.89)a
Viral infection	5043 (0.75)		2188 (0.32)	2.40 (2.28–2.52)	2.00 (1.88–2.14)a
Bacterial infection	23,021 (3.40)		10,623 (1.53)	2.21 (2.16–2.27)	1.79 (1.74–1.85)a
Mixed and other	290 (0.04)		93 (0.01)	3.33 (2.61–4.23)	3.29 (2.32–4.67)a
Co-twin control
Infection (any)	344 (3.95)		181 (2.01)	1.94 (1.62–2.33)	1.55 (1.23–1.97)b
Viral infection	57 (0.67)		32 (0.36)	1.92 (1.23–2.98)	3.68 (1.40–9.63)b
Bacterial infection	284 (3.27)		149 (1.66)	1.94 (1.59–2.37)	1.45 (1.10–1.90)b
Mixed and other	3 (0.04)		0 (0.00)	NA	NA
SSRI active comparator
Infection (any)	15,756 (4.00)		12,660 (3.23)	1.23 (1.21–1.26)	1.33 (1.30–1.35)c
Viral infection	2799 (0.72)		2037 (0.53)	1.37 (1.29–1.45)	1.42 (1.36–1.47)c
Bacterial infection	12,807 (3.26)		10,554 (2.70)	1.20 (1.17–1.24)	1.31 (1.28–1.33)c
Mixed and other	150 (0.04)		69 (0.02)	2.16 (1.62–2.87)	2.09 (1.68–2.59)c

BZDR benzodiazepines and benzodiazepine-related Z-drugs; CI confidence interval; HR: hazard ratio; NA not applicable; SSRI selective serotonin reuptake inhibitors

^aStratified by the matching identifiers (birth year and month, sex, and residence at the index date’s year) and adjusted for calendar year of the index date, family disposable income, history of psychiatric and somatic diagnoses ever before the index date (substance use disorders, schizophrenia, bipolar disorders, depression, anxiety disorders, obsessive–compulsive disorders, stress-related disorders, dissociative, somatoform, and other neurotic disorders, mental retardation, autism spectrum disorders, attention-deficit/hyperactivity disorders, disruptive behavior disorders, any cardiovascular disorders, diabetes mellitus, asthma, any autoimmune diseases, nonorganic sleep disorders and insomnias, chronic pain of different origins, and Alzheimer’s disease), and concomitant medication, defined as dispensations within 3 months prior to the index date (selective serotonin reuptake inhibitors, psychostimulants, mood stabilizers, antipsychotics, nonbenzodiazepine antiepileptics, nonbenzodiazepine anxiolytics, hypnotics, and sedatives, nonopioid analgesics, opioids), and history of infection hospitalization or specialized outpatient care prior to 2-year infection-free period

^bStratified by family identification number (which was created to link multiple birth siblings within family) and adjusted for all above-mentioned covariates (as for the demographically matched cohort), and for sex and the residence at the cohort entry of each multiple birth co-sibling

^cCovariates are balanced via IPTW (same covariates as for the demographically matched cohort)

Co-Twin Control Cohort

In the co-twin-control cohort, 344 and 181 cases of any serious infections were identified among 9197 multiple birth BZDR recipients and their 9298 unexposed co-twins, respectively, with corresponding incidence rates of 3.95 (95% CI 3.55–4.39) and 2.01 (95% CI 1.73–2.32) per 100 person-years (Table 2). In the fully adjusted model, a 1.5-times greater risk of any infections was observed among BZDR recipients compared with their unexposed co-twins (HR 1.55, 95% CI 1.23–1.97). The increased risk was also evident for viral (HR 3.68, 95% CI 1.40–9.63) and bacterial infections (HR 1.45, 95% CI 1.10–1.90). In this cohort, the sex-stratified analysis was underpowered (Table S8).

Active Comparator Cohort

In the active comparator cohort, 15,756 individuals out of 434,900 incident BZDR recipients and 12,660 individuals out of 428,074 incident SSRI recipients developed any infections under study, with corresponding incidence rates of 4.00 (95% CI 3.94–4.06) and 3.23 (95% CI 3.18–3.29) per 100 person-years, respectively (Table 2). After controlling for all covariates balanced by IPTW, BZDR recipients were at 1.3-time greater risk of any infections compared to SSRI recipients (HR 1.33, 95% CI 1.30–1.35). Similar increase in risks of viral and bacterial infections (HR 1.42, 95% CI 1.36–1.47 and HR 1.31, 95% CI 1.28–1.33, respectively) were observed. Further, the increase in risk of any infections among males with BZDR use compared with males with SSRI use (HR 1.48, 95% CI 1.44–1.53) was stronger than the corresponding measures among females (HR 1.23, 95% CI 1.20–1.25) (p < 0.001 for interaction) (Table S8).

Additional Analyses

The additional analyses assessed the association between BZDR properties and any infections in the demographically matched cohort. Among 713,896 BZDR recipients, Z-drugs were the most common initial BZDR used by 60.9% (n = 435,015) of recipients, while 3.7% (n = 26,219) of BZDR recipients used more than one BZDR drug at treatment initiation (Table S9). The relative increase in risk of any infections was found for all types of initial BZRDs, varying from HR of 1.79 (95% CI 1.71–1.86) among those initially dispensed BZD-anxiolytic to HR of 2.46 (95% CI 2.00–3.04) in individuals initially dispensed BZD-hypnotic/sedative. The hazard ratio for individuals simultaneously dispensed multiple BZDRs was 2.50 (95% CI 2.23–2.80). Further subdivision of exposure by specific initial drugs showed that zopiclone (37.7%, n = 269,456), zolpidem (22.6%, n = 161,617), and oxazepam (21.5%, n = 153,544) were three most common initially dispensed BZDR (Table S10). The risk of infections remained increased across all initial drugs, varying from HR of 1.55 (95% CI 1.14–2.12) in individuals with zaleplon as the initial drug to HR of 5.97 (95% CI 3.96–8.99) among those with lorazepam. The only exception was triazolam, for which no association with the outcome was observed, but this analysis was based on a small number of exposed individuals.

Next, the assessment of cumulative dosage of BZDR use during the follow-up (as time-varying exposure) showed a relative increase in outcome risk within each cumulative dosage category (Fig. 2). The hazard ratio for any serious infections increases from HR of 1.56 (95% CI 1.51–1.61) among BZDR recipients with the cumulative dosage of ≤ 20 DDD to HR of 1.97 (95% CI 1.83–2.05) for the cumulative dosage of > 20 DDD ≤ 65, and to HR of 3.94 (95% CI 3.72–4.17) for the cumulative dosage of > 65 DDD. Figure 2 footnotes provide the corresponding risk estimates for viral and bacterial outcomes.

Fig. 2.

Hazard ratios and 95% confidence intervals for association between time-varying exposure to cumulative dosage of BZDR used during the follow-up and outcomes in incident BZDR recipients compared with matched nonrecipients from the demographically matched cohort. Hazard ratios and 95% confidence intervals are retrieved from the fully adjusted model. For any serious infections, the hazard ratio (HR) of 1.56 [95% confidence interval (CI) 1.51–1.61] was estimated for association with the cumulative BZDR dosage of ≤ 20 DDD; HR of 1.97 (95% CI 1.83–2.05) was estimated for association with > 20 DDD ≤ 65, and HR of 3.94 (95% CI 3.72–4.17) for association with the cumulative dosage of > 65 DDD. For viral infections, the corresponding hazard ratios were 1.70 (95% CI 1.58–1.83) for the cumulative BZDR dosage of ≤ 20 DDD, 2.14 (95% CI 1.93–2.37) for > 20 DDD ≤ 65, and 4.60 (95% CI 4.00–5.30) for > 65 DDD. For bacterial infection, the corresponding hazard ratios were 1.52 (95% CI 1.47–1.58) for the cumulative BZDR dosage of ≤ 20 DDD, 1.93 (95% CI 1.84–2.02) for > 20 DDD ≤ 65, and 3.79 (95% CI 3.56–4.04) for > 65 DDD. BZDR benzodiazepines and benzodiazepine-related Z-drugs; DDD defined daily dosage

Finally, we explored the risk of serious infections as a function of the exposed individual’s age at the index date. The associations remained strong in all ages, with the magnitude of associations particularly growing with increased age at the index date among those who initiated BZDR treatment at age 35 years and older (Fig. 3).

Fig. 3.

Association between incident use of BZDR and any serious infections by age at the index date in incident BZDR recipients compared with matched nonrecipients from the demographically matched cohort. Age at the index date was modeled into restricted cubic spline with five knots placed at 5, 27.5, 50, 72.5 and 95 quantiles. Age-varying hazard ratios were subsequently predicted using Cox models, where interaction term between incident BZDR use and the age spline was included. BZDR benzodiazepines and benzodiazepine-related Z-drugs

Discussion

Principal Findings

In this nationwide register-based study on individuals aged up to 65 years, incident use of BZDRs was associated with an increased risk of serious infections within 1 year after the treatment was initiated. Despite having fairly low absolute risk of developing the outcomes, incident BZDR recipients had 83% higher risk of any serious infections compared with nonrecipients (100% and 79% increased risks of viral and bacterial infections, respectively), even after controlling for demographic, socioeconomic, clinical, and pharmacological confounders. Further control for familial confounding (in the co-twin control cohort) and confounding by indication (in the active comparator cohort) slightly attenuated all estimates (55% and 33% increased risks of any serious infections in the co-twin and active comparator cohorts, respectively). The corresponding risk estimates for viral infections were slightly higher than that for bacterial infections. The association of BZDR use with infections was stronger among male than in female. Furthermore, the increase in risk of any infections maintained across all types of initial BZDRs and across different individual BZDR. Further analyses indicated that, while the risk for infections was already present at the lower cumulative dosage of ≤ 20 DDD, a clear dose–response relationship was observed whereby higher cumulative doses were associated with higher risks. Finally, the risk of any infections increased with age among those who initiated BZDR treatment at age 35 years and older.

Strengths and Limitations

The strengths of the study included the use of the nationwide Swedish registers with comprehensive and standardized data collection, which enabled generalizable results to the entire population and minimized selection and reporting bias. Recall bias was avoided as BZDR dispensations (which were collected regardless of indication, except for epilepsy) and outcome diagnoses were gathered independently and prospectively. We used multiple designs to mitigate  shared familial confounders and confounding by indication. Furthermore, the large sample size enabled fine-grained analyses of specific drugs.

Several study limitations should also be acknowledged. First, we used BZDR dispensation records as a proxy for medication use because data on actual consumption were unavailable. However, based on prior literature [38], we assumed that the majority of BZDR recipients used the medication in proximity to the dispensation date. Second, confounding by clinical indications that are different in BZDR and SSRIs (e.g., insomnia) could have biased the results since SSRI was chosen as the active comparator due to the overlap in psychiatric indications. Still, we expect that the use of IPTW carefully balanced the large set of measured confounders for BZDR and SSRI recipients, including a wide spectrum of clinical conditions, and thus minimized the risk of confounding by indication. Third, our study focused on severe, potentially life threatening, infections. Milder infections treated in primary care settings were not included in the analyses, though arguably their clinical relevance is more limited. Fourth, despite our comprehensive approach to control confounding, residual confounders, including lifestyle factors (e.g., smoking, physical activity, alcohol intake) could still partially account for the observed associations. Finally, although we controlled for the history of substance use disorder via adjustment or IPTW, data on recreational and illegal BZDR use were unavailable to us, which could have biased the observed associations if such use was present and unequally distributed between the exposure categories.

Comparison with Other Studies

The general scarcity of evidence on the topic precluded us from finding a direct comparison for our results, which was particularly true for our findings from the co-twin and active comparator cohorts and for the results within outcome subgroups of viral and bacterial infections. Overall, the observed relative increase in risk of any serious infection in BZDR recipients was in line with prior literature, although the existing studies varied in the magnitude of associations due to different patient characteristics and assessment of BZDRs and infections. A recent meta-analysis of ten observational studies involving about 120,000 pneumonia cases (with nine studies on the general populations and one based on patients with Alzheimer disease) reported 25% relative increase in outcome risk among BZDR-recipients of all ages compared with nonrecipients, while in a subgroup of four studies on BZDR recipients aged below 65 years, as in our cohorts, the corresponding increase in pneumonia risk was 80% [16]. For a broader spectrum of infections, a retrospective cohort study of 33,260 trauma patients reported 22–43% increased odds of developing infectious complications, such as pneumonia, wound infection, soft tissue infections, and sepsis, associated with BZD use (Z-drugs not included) [19]. Further, a meta-analysis of randomized controlled trials including 6614 participants on Z-drugs versus 3326 participants receiving placebo and risk of any infections varied in its pooled results depending on Z-drug used from no associations to 99% increase in outcome risk [21]. However, in all the above-mentioned studies, limited information on the etiology of infection impeded a corresponding comparison for our findings within outcome subgroups.

Our results on the types of initial BZDRs concurred with findings from a previous nested case–control study where the increased risk of pneumonia hospitalization was observed among current users of BZD-hypnotics, BZD-anxiolytics, and Z-drugs, with the strongest increase related to BZD-hypnotic use [39]. Likewise, pooled results from the meta-analysis reported both BZDs and Z-drugs to be associated with an increased risk of pneumonia [16]. Furthermore, our findings of all initial BZDRs being associated with increased risk of any infections is consistent with previous research reporting moderate differences in risks of pneumonia in association with different individual BZDs and/or Z-dugs [16, 21, 39, 40]; yet the variations in the choice of drugs in each study precluded the direct comparison. Additionally, the observed dose-response relation between the cumulative BZDR dosage and the risk of infections reflected findings from other studies, despite variations in methodology for measuring the dosage [18, 39]. Finally, consistent with our observations of a J-curve association between BZDR initiation at different ages and the risk of any infections, a similar pattern was reported for BZDR users in different age groups and influenza-like illness-related pneumonia risk [40]. Our findings of male and female with BZDR use having an increased risk of infections, with stronger increase among male, were supported by previous results on BZDR use and pneumonia hospitalization [39] and on BZD use and post-stroke pneumonia [18].

Meaning of the Study

Our combined results suggest that incident BZDR use is an independent risk factor for the development of serious infections. While our study cannot directly address the biological mechanisms behind the observed risks, one plausible hypothesis is BZDRs can suppress immune surveillance through modulating central and peripheral gamma-aminobutyric acid type A (GABA_A) receptors on immune cells. These may result in impaired cytokine production and secretion, inhibited phagocytosis function, and suppressed T cell proliferation [11, 12, 41–43]. The hypothesis stems from animal models where exposure to BZDs (mainly diazepam) in rodents was linked to increased susceptibility to viral infection [11, 12], developing secondary bacterial infection in animals infected with virus [11], and to increased mortality from various bacterial infections [11, 13, 14]. Immune cell expression of GABA_A receptors is also reported in human research, making the abovementioned mechanisms plausible for humans [11, 43]. Other existing explanations postulate that BZDR users could more likely experience gastroesophageal reflux [44] and sleep apnea [45], which in turn may pose a higher risk of infections [46, 47].

Findings related to BZDR pharmacological profile suggest the observed associations likely represent a “class effect” given the comparable increase in outcome risks across BZD-anxiolytics, BZD-hypnotics/sedatives, BZD-antiepileptics, and Z-drugs used at treatment initiation, and across the specific initial BZDRs. Our findings, although similar to those of prior pharmacoepidemiological research [16, 21, 39, 40], could not support results of some in vitro studies reporting alprazolam and triazolam potentiated the immune response [48, 49] due to low number of exposed and underpowered analysis. It is worth noting the large increase in risk of infections amongst individuals initiating treatment with multiple BZDRs simultaneously, a pattern of BZDR use that is discouraged in clinical guidelines [50–52]. This finding, together with the observed dose-response relation between cumulative BZDR dosage and infection risk, underscores the importance of raising awareness among clinicians, in particular in healthcare settings where BZDRs are commonly prescribed, on making a balanced risk–benefit decision upon initiation BZDR treatment.

Conclusions

In this nationwide study, the initiation of BZDR use in individuals aged up to 65 years was associated with increased risks of serious infections, including infections of bacterial and viral origins. The observed associations were not entirely explained by the influence of clinical, pharmacological, and socioeconomic confounders; shared familial factors; and confounding by indication, suggesting that incident use of BZDRs may be an independent risk factor for the development of serious infections. Further studies are needed to uncover the precise neurobiological mechanisms. While the absolute risks were small, the assessed outcomes represent serious conditions that require hospitalization or specialist outpatient care. The findings highlight the importance of raising clinical awareness to make evidence-based decisions on BZDR treatment initiation.

Supplementary Information

Below is the link to the electronic supplementary material.

Funding

Open access funding provided by Karolinska Institute.

Declarations

Funding

The study was supported by grants from the Swedish Research Council (grant No 2019-01408, AS), Region Stockholm (ALF Medicine; grant nos. 20190379 and RS2020-0731, AS), Karolinska Institutet (KID funding; grant no. 2021-00505, AS, and research funding; grant no. FS-2022:0010, AS). The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, or approval of the manuscript; and decision to submit the manuscript for publication.

Conflicts of Interest

Prof Mataix-Cols receives royalties for contributing articles to UpToDate, Inc, and is part owner of Scandinavian E-Health AB, all outside the submitted work. The other authors have no conflicts of interest to declare in relation to this work.

Ethics Approval

The study was approved by the Swedish Ethical Review Authority (reference number 2020-06540).

Consent to Participate

The requirement for informed consent was waived because the study is register-based, and all individual data were de-identified.

Consent to Publish

Not applicable.

Data Availability

Sharing individual-level data are restricted by Swedish data protection laws, therefore the data underlying our findings cannot be made publicly accessible. The data for this study were made available to the authors by ethical approval and were sourced from several registers held by the Swedish governmental agencies. For data access inquiries, the researchers may apply through the Swedish Ethical Review Authority (www.etikprovningsmyndigheten.se) and the primary data owners as the National Board of Health and Welfare (www.socialstyrelsen.se) and Statistics Sweden (www.scb.se), in accordance with Swedish law.

Code Availability

The code used for analyses are available from the corresponding author upon reasonable request.

Authors Contributions

Conceptualization and methodology: AS, DMC, XW, and KI. Formal analysis: XW. Interpretation of data and critical revision of the manuscript for important intellectual content: all authors. Original draft preparation: AS and XW. Funding acquisition: AS. Supervision: AS, DMC, ZC, and NJ-L. Final manuscript approval: all authors. All authors have read and approved the final submitted manuscript, and agree to be accountable for the work.