Prescription Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) and Depression among Adults with Inflammatory Chronic Conditions in the United States

Abstract

Background:

The association of prescription NSAIDs to presence of depression among adults with inflammatory chronic conditions in adults with and without depression and seeking care in routine clinical practice remains unknown.

Objective:

We examined the association of prescription NSAIDs to depression among adults with inflammatory chronic conditions in a nationally representative sample of the US non-institutionalized civilian population.

Methods:

We used a retrospective cross-sectional design. Data on 10,713 adults with inflammatory chronic conditions were derived from 2015 Medical Expenditure Panel Survey (MEPS). The dependent variable was the presence or absence of depression and the key independent variable was prescription NSAIDs use. Logistic regression models were used to examine the adjusted associations of prescription NSAIDs to depression. In these regressions, other independent variables (biological, sociocultural, socio-economic, access to healthcare services, medical conditions and treatment factors, behavioural, and environmental factors) that may affect the relationship of prescription NSAIDs to depression were also included. All analyses accounted for the complex survey design of MEPS.

Results:

Overall, 18.2% reported depression. Almost 21% used prescription NSAIDs. In the unadjusted model, prescription NSAIDs use had higher odds of depression (OR=1.59;95%CI=[1.40, 1.82]) as compared to those without NSAIDs. In the fully-adjusted logistic regression model, with controls for other independent variables, adults using prescription NSAIDs had no significant association with depression (AOR=0.97;95%CI=[0.84, 1.13]) compared to those without NSAIDs.

Conclusions:

In this first real-world study of all adults (with and without depression) in the US, we did not observe a statistically significant association of prescription NSAIDs to the presence of depression.

INTRODUCTION

The pathophysiology of depression is evolving[1], however, recent scientific evidence suggest that depression can be due to inflammatory responses and immune dysregulation[2]. The biological link between depression and inflammation has been supported by many studies[3], [4]. Studies have reported elevated blood concentrations of inflammatory biomarkers such as TNF-α, interleukin-6, interleukin 1β, chemokines, C-reactive protein (CRP) and acute phase proteins among patients with major depression[5]–[7], providing indirect evidence of inflammation as a causal pathway. In addition, it has been reported that plasma levels of various cytokines were reduced to normal levels with recovery from depression[8], it is plausible that treatments acting on inflammation, specifically anti-inflammatory drugs may reduce the risk of depression. Thus, emerging research has focused on the role of anti-inflammatory pharmaceutical agents in treating depression.

Many randomized clinical trials (RCTs) have been conducted to study the efficacy of anti-inflammatory drugs on depression. A pooled analysis of data from five placebo-controlled, randomized, multicentre, double-blind trials examined NSAIDs treatment on 1497 patients with osteoarthritis (18–50 years), with or without major depressive disorder concluded that 6-weeks of NSAID treatment reduced depressive symptoms as measured by Patient Health Questionnaire 9[9]. In a systematic review and meta-analysis of 10 RCTs with 4,258 subjects that examined the effect of NSAIDs in reducing depressive symptoms, depression severity and improved remissions concluded that NSAIDs were beneficial[10]. In this review, it was reported that an RCT that evaluated the efficacy of NSAIDs for depressive symptoms in healthy older adults (age ≥ 70 years) demonstrated no reduction in Geriatric Depression Scale[11], suggesting that NSAIDs may not be effective in reducing the risk of depression in adults with and without depression. Similarly, a reanalysis of data from the STAR*D trial suggested that after adjustment for age, sex, race/ethnicity, treatment setting, insurance type and medical comorbidity, NSAIDs were not associated with depression outcomes[12].

While RCTs have provided some evidence on the efficacy of NSAIDs, results from these trials are not generalizable. Many of these trials included adults with depressive symptoms or major depression or specific conditions. For example, Iyengar et al., focused only on patients with osteoarthritis with depression and excluded older adults (age ≥ 50 years) with coronary artery disease and other psychiatric comorbidities.[9] Other RCTs only included adults with psoriasis, osteoarthritis and rheumatoid arthritis.[13], [14] Moreover, Kohler and colleagues in their review of the potential role of anti-inflammatory treatment for depression point to the lack of robust clinical evidence in using NSAIDs in routine clinical practice to combat depression[4]. Thus, the association of prescription NSAIDs to depression in adults with and without depression and seeking care in routine clinical practice remains unknown.

Therefore, the primary objective of this study is to examine the association of prescription NSAIDs to depression in adults of all age groups (≥ 21 years) with a diverse group of inflammatory chronic conditions. We restricted our study sample to those with inflammatory chronic conditions because they are more likely to receive prescription NSAIDs compared to the general population.

To understand factors associated with depression, we adapted determinants of health model as the conceptual framework[15]. The model posits that biological factors (sex and age), sociocultural factors (race/ethnicity and marital status), socio-economic status (income and education), access to healthcare services (insurance coverage and prescription drug coverage), medical conditions and treatment factors (number of chronic conditions, pain, polypharmacy), behavioral (smoking, obesity, and physical activity), and environmental factors (region) can affect an individual’s health (i.e. the presence or absence of depression).

METHODS

Study Design

We adopted a retrospective cross-sectional study design with data from a nationally representative household survey in the United States (US).

Data Source

Our study utilized data from the Medical Expenditure Panel Survey (MEPS), conducted every year since 1996. We used data from the survey year – 2015[16]. MEPS uses a complex sample design to select households and families in the US designed to be representative of the non-institutionalized civilian population. The survey is conducted using face-to-face computer-assisted interviews and collects information on demographics, socioeconomic status, health status, physical and mental health conditions, insurance coverage, health service use, prescription medications, and the cost of healthcare. The medical and mental health conditions are recorded “verbatim and converted to the International Classification of Diseases-9th edition-Clinical Modification (ICD-9-CM) diagnosis codes by professional coders”[17]. MEPS investigators used clinical classification software (CCS) developed by the Agency for Healthcare Research and Quality (AHRQ) to classify ICD-9-CM codes into a manageable number of groups.

Study sample

The study sample consisted of adults (N = 10,713) who were 21 years and older in 2015, with inflammatory chronic conditions, and were observed during the calendar year. We restricted our sample to individuals with one of the following inflammatory chronic conditions: arthritis, asthma, cancer, cardiovascular disease (pulmonary heart disease, congestive heart failure, pericarditis, endocarditis, myocarditis, acute myocardial infarction, cardiac dysrhythmias, cardiac arrest and ventricular fibrillation, and other and ill-defined heart disease), chronic obstructive pulmonary disease (COPD), and diabetes because of the potential to receive prescription NSAIDs as a treatment for their conditions. These inflammatory chronic conditions were identified from the medical encounters using the CCS codes and the designated list of MEPS priority conditions.

Measures

Dependent Variable: presence/absence of depression (Yes/No)

We used the medical conditions file[18] and used the clinical classification code 657 to identify depressive disorders. Adults with at least one healthcare encounter for mood disorders were classified as having depression.

Key independent Variable: Use of prescription NSAIDs (Yes/No):

Prescribed medicine files[19] in MEPS contain information on each unique prescribed medicine, national drug codes, medicine name, days supplied and total expenditure and the type of pharmacies. Each prescription drug is assigned to a 3-level nested therapeutic class based on the propriety software – the Multum Lexicon[20]. We used the second-level therapeutic class codes, to identify prescription NSAIDs. Adults with at least one prescription of NSAIDs during the calendar year were classified as NSAID users.

Other independent variables:

Biological factors comprised sex (men, women) and age in categories (21–44 years, 45–54 years, 55–64 years, 65 and older). Socio-cultural factors included marital status (married, widowed, divorced/separated, and never married) and race/ethnicity (White, African-American, Latino, and other racial minorities). Socioeconomic status included education (less than high school, high school, and above high school) and poverty status measured in terms of the federal poverty line (FPL). We categorized poor as having Federal Poverty Line (FPL) <200%, middle income as those with 200% < FPL < 400% and high income (> 400% FPL).

Access to healthcare services comprised insurance coverage (private, public and uninsured) and prescription drug coverage (yes/no). Medical conditions and treatment factors included the number of inflammatory chronic conditions (ranged from 1 to 6), pain and polypharmacy. Pain was assessed in terms of interference with normal work using one-item from the Short-Form Health Survey version 2 (SF12-v2). It was categorized as little or no pain, moderate pain and severe pain. Based on the most cited definition of polypharmacy[21], it was categorized in to three groups including use of six or more concomitant medications, one to five concomitant medication and no medication use. Behavioral factors included obesity (obese and not obese), physical activity (exercising five times/week and others), and smoking status (yes/no). Environmental factors incorporated geographical region (Northeast, Midwest, South and West).

Statistical analyses

Significant bivariate differences in the association of prescription NSAIDs to depression was tested using Rao-Scott chi-square. We employed multivariable logistic regressions to assess the association of prescription NSAIDs to depression after adjusting for biological, socio-cultural, socio-economic, access to healthcare services, medical conditions and treatment factors, behavioral and external environmental factors. In these analyses, we used appropriate weights (SAQ weight) to account for the non-response bias in the administration of paper questionnaires. We used survey procedures in SAS 9.4 in all our analyses to account for the complex survey design of MEPS (SAS Institute, Inc).

RESULTS

The majority of the population were white (70%), female (55%) and married (58%) (Table 1). Nearly one-third of the sample was 65 years or older. Only 6% were uninsured, however, 45% of the individuals did not have a prescription coverage. Only 12% had less than high school education and nearly 12% had low income (i.e. < 200% FPL).

Table 1:

Characteristics of Adults by Prescription NSAIDs use Medical Expenditure Panel Survey, 2015

		Total		Prescription NSAIDs		No Prescription NSAIDs		Sig
		N	Wt %	N	Wt %	N	Wt %
ALL		10,713	100.0	2,554	100.0	8,159	100.0
Sex								**
	Women	6,223	55.3	1517	20.9	4706	79.1
	Men	4,490	44.7	896	18.2	3594	81.8
Race/Ethnicity								***
	White	5,348	70.0	997	17.7	4351	82.3
	African American	2,168	11.4	574	24.5	1594	75.5
	Latino	2,277	11.6	626	25.3	1651	74.7
	Other race	920	7.0	216	23.1	704	76.9
Age in Years								***
	21–44	2,836	25.7	522	16.6	2314	83.4
	45–54	2,119	18.8	506	20.3	1613	79.7
	55–64	2,464	22.8	643	22.9	1821	77.1
	65+	3,294	32.6	742	19.6	2552	80.4
Marital Status								***
	Married	5,415	58.1	1135	18.6	4280	81.4
	Widowed	1,136	9.5	268	21.0	868	79.0
	Divorced/Separated	2,028	15.8	552	24.4	1476	75.6
	Not Married	2,134	16.6	458	18.3	1676	81.7
Region
	Northeast	1,768	18.6	403	17.3	1365	82.7
	Mid-west	2,218	21.9	469	19.5	1749	80.5
	South	4,114	37.6	914	20.5	3200	79.5
	West	2,613	21.9	627	20.7	1986	79.3
Education								***
	Less than HS	1,968	11.8	589	27.1	1379	72.9
	High School	3,353	30.3	750	19.7	2603	80.3
	Above High School	5,314	57.4	1062	18.2	4252	81.8
Poverty Status								***
	Poor	1,981	11.5	590	28.5	1391	71.5
	Middle income	5,391	45.5	1250	20.7	4141	79.3
	High income	3,341	43.0	573	16.3	2768	83.7
Insurance Coverage								***
	Public	6,179	67.3	1170	17.5	5009	82.5
	Private	3,680	27.0	1112	26.4	2568	24.7
	Uninsured	854	5.7	131	14.3	723	85.7
Prescription Drug Coverage								***
	Yes	5,048	55.3	949	17.4	4099	82.6
	No	5,665	44.7	1464	22.6	4201	77.4
# of Chronic Conditions								***
	1	5,425	49.0	1018	16.7	4407	83.3
	2	3,009	29.8	692	19.1	2317	80.9
	3 or more	2,279	21.2	703	27.6	1576	72.4
Pain
	None/Little	6913	67.2	1178	14.7	5735	85.3	***
	Moderate	1564	14.5	441	26.3	1123	73.7
	Severe	2092	17.3	753	33.5	1339	66.5
Physical Activity								***
	5 times/week	4,749	46.3	964	17.7	3785	82.3
	No physical activity	5,913	53.3	1437	21.4	4476	78.6
Obesity								***
	Yes	4,319	38.0	1144	24.0	3175	76.0
	No	6,239	60.8	1235	17.1	5004	82.9
Smoking Status								*
	Current Smoker	1,765	15.6	441	22.1	1324	77.9
	Other	8,711	82.3	1909	19.1	6802	80.9

Note: Based on 10,713 adults aged 21 years and older, alive during the calendar and with at least one of the following conditions: arthritis, asthma, cancer, COPD, diabetes, heart diseases. Significant group differences in characteristics by prescription NSAIDs use was based on chi-square tests.

HS: High School; Sig: Significance; Wt: Weighted COPD: Chronic Obstructive Pulmonary Disease

^***p < .001;

^**.001 ≤ p < .01;

^*.01 ≤ p < .05.

Overall, 21% reported using prescription NSAIDs (Table 1). Approximately 32% reported pain interference with normal work. We observed that 33% adults with severe pain and 26% adults with moderate pain used prescription NSAIDs. Among the inflammatory chronic conditions, adults with COPD used the highest percentage of NSAIDs (23.5%), followed by arthritis (23.2%), diabetes (22.2%), cardiovascular disease (21.1%), asthma (20.4%), and cancer (18%). We observed statistically significant differences among individuals using prescription NSAIDs and not using prescription NSAIDs. A higher percentage of women than men (20.9% vs 18.3%) used prescription NSAIDs. A higher percentage of those living in poverty (28.5% vs 16.3%), current smokers (22.1% versus 19.1%), obese (24% vs 17.1%) reported using prescription NSAIDs compared to those with high income, former/never smokers, not obese.

Table 2 displays the sample and their weighted percentages by the presence and absence of depression. Overall, 18% reported depression. A significantly higher percentage of adults (23.9% vs 16.3%) who used prescription NSAIDs reported depression compared to those who did not use prescription NSAIDs. Among the inflammatory chronic conditions, those with COPD had the highest percentage of self-reported depression (24%), followed by diabetes (21%), asthma (21%), arthritis (20%), cardiovascular diseases (20%), and cancer (16%). Further, 31% adults with severe pain and 22.4% adults with moderate pain reported depression. With closer examination of polypharmacy variable, we found that adults using prescription NSAIDs had significantly higher use of polypharmacy (40.5% vs. 23.6%) as compared to adults without prescription NSAIDs use.

Table 2:

Characteristics of Adults by Depression Medical Expenditure Panel Survey, 2015

		Total		Depression		No Depression		Sig
		N	Wt %	N	Wt %	N	Wt %
ALL		10,713	100.0	1,854	100.0	8,559	100.0
Sex								***
	Women	6,223	55.3	1291	21.7	4932	78.3
	Men	4,490	44.7	563	13.0	3927	87.0
Race/Ethnicity								***
	White	5,348	70.0	1104	19.6	4244	80.4
	African American	2,168	11.4	284	12.7	1884	87.3
	Latino	2,277	11.6	352	15.0	1925	85.0
	Other race	920	7.0	114	12.5	806	87.5
Age in Years								***
	21–44	2,836	25.7	506	18.3	2330	81.7
	45–54	2,119	18.8	362	17.8	1757	82.2
	55–64	2,464	22.8	514	21.2	1950	78.8
	65+	3,294	32.6	472	15.0	2822	85.0
Marital Status								***
	Married	5,415	58.1	755	15.1	4660	84.9
	Widowed	1,136	9.5	224	22.1	912	77.9
	Divorced/Separated	2,028	15.8	471	24.3	1557	75.7
	Not Married	2,134	16.6	404	18.8	1730	81.2
Region
	Northeast	1,768	18.6	340	17.7	1428	82.3
	Mid-west	2,218	21.9	436	19.2	1782	80.8
	South	4,114	37.6	644	17.2	3470	82.8
	West	2,613	21.9	434	17.7	2179	82.3
Education
	Less than HS	1,968	11.8	324	16.4	1644	83.6
	High School	3,353	30.3	577	18.4	2776	81.6
	Above High School	5,314	57.4	941	17.7	4373	82.3
Poverty Status								***
	Poor	1,981	11.5	499	28.7	1482	71.3
	Middle income	5,391	45.5	918	18.6	4473	81.4
	High income	3,341	43.0	437	14.1	2904	85.9
Insurance Coverage								***
	Public	6,179	67.3	911	15.9	5268	84.1
	Private	3,680	27.0	848	23.5	2832	76.5
	Uninsured	854	5.7	95	13.4	759	86.6
Prescription Drug Coverage								***
	Yes	5,048	55.3	731	15.9	4317	84.1
	No	5,665	44.7	1123	20.2	4542	79.8
# of Chronic Conditions								***
	1	5,425	49.0	713	14.3	4712	85.7
	2	3,009	29.8	545	18.3	2464	81.7
	3 or more	2,279	21.2	596	25.3	1683	74.7
Pain
	None/Little	6913	67.2	857	13.5	6056	86.5	***
	Moderate	1564	14.5	333	22.4	1231	77.6
	Severe	2092	17.3	637	30.7	1455	69.3
Physical Activity								***
	5 times/week	4,749	46.3	633	13.8	4116	86.2
	No physical activity	5,913	53.3	1214	21.3	4699	78.7
Obesity								***
	Yes	4,319	38.0	865	21.0	3454	79.0
	No	6,239	60.8	967	15.8	5272	84.2
Smoking Status								***
	Current Smoker	1,765	15.6	454	26.7	1311	73.3
	Other	8,711	82.3	1367	16.2	7344	83.8

Note: Based on 10,713 adults aged 21 years and older, alive during the calendar and with at least one of the following conditions: arthritis, asthma, cancer, COPD, diabetes, heart diseases. Significant group differences in characteristics by prescription NSAIDs use was based on chi-square tests.

HS: High School; Sig: Significance; Wt: Weighted COPD: Chronic Obstructive Pulmonary Disease

^***p < .001;

^**.001 ≤ p < .01;

^*.01 ≤ p < .05.

The unadjusted odds ratios (UOR) indicated that compared to adults who did not use prescription NSAIDs, those who used prescription NSAIDs had higher odds of depression. (UOR = 1.59; 95%CI = 1.40, 1.82) (Table 3). After adjusting for polypharmacy, the AOR reduced substantially and was no more statistically significant (AOR = 1.13; 95% CI = 0.98, 1.31). With the addition of pain to the model, the AOR reduced further (AOR = 1.05; 95% CI = 0.91, 1.20). In the fully-adjusted model, (biological, sociocultural, socio-economic, access to healthcare services, medical conditions and treatment factors, behavioral and environmental factors), those using prescription NSAIDs had no significant association with depression (AOR = 0.97; 95% CI = 0.84, 1.13). Adults with polypharmacy were almost three times as likely to report depression as those without polypharmacy (AOR= 2.80, 95% CI = 2.37, 3.30). The AORs of other independent variables in the fully adjusted model are represented in Table 4.

Table 3:

Odds Ratios, Adjusted Odds Ratios (AOR) and 95% Confidence Intervals (CI) of Prescription NSAIDs from Multivariable Logistic Regressions on Depression among adults (>=21), Medical Expenditure Panel Survey, 2015

		Depression
Model 1- Unadjusted
		OR	95%CI	sig
Prescription NSAIDs
	NSAIDs	1.59	[1.40, 1.82]	***
	No NSAIDs(Reference)
Model 2- Adjusted for polypharmacy
		AOR	95%CI	sig
Prescription NSAIDs
	NSAIDs	1.13	[0.98, 1.31]
	No NSAIDs(Reference)
Model 3- Adjusted for polypharmacy and pain
		AOR	95%CI	sig
Prescription NSAIDs
	NSAIDs	1.05	[0.91, 1.20]
	No NSAIDs(Reference)
Model 4- Adjusted for polypharmacy, pain, age, sex, race/ethnicity, medical conditions, education, poverty status, marital status, insurance coverage,physical activity, smoking status, obesity, and region.
		AOR	95%CI	sig
Prescription NSAIDs
	NSAIDs	0.97	[0.84, 1.13]
	No NSAIDs(Reference)

Based on 10,713 adults aged 21 years and older, alive during the calendar and with at least one of the following conditions: arthritis, asthma, cancer, COPD, diabetes, heart diseases. Asterisks represent significant group differences by prescription NSAIDs in depression based on multivaiable logistic regression on Depression.

Sig: Significance

^***p < .001;

^**.001 ≤ p < .01;

^*.01 ≤ p < .05.

Table 4:

Adjusted Odds Ratios and 95% Confidence Intervals from Multivariable Logistic Regression on Prescription NSAIDs use (Reference = No NSAIDs) Among Individuals of 21 years and older Medical Expenditures Panel Survey, 2015

		NSAIDs use
		AOR	95%CI	sig
Sex
	Male
	Female	1.61	[1.42, 1.82]	***
Race/Ethnicity
	White	2.04	[1.62, 2.56]	***
	African American
	Latino	1.50	[1.13, 1.98]	**
	Other Race	1.19	[0.82, 1.74]
Age in Years
	21–44	2.37	[1.89, 2.99]	***
	45–54	1.83	[1.45, 2.31]	***
	55–64	1.97	[1.59, 2.45]	***
	65,+
Marital status
	Married
	Never married	1.19	[1.00, 1.41]
	Separated/Divorce	1.36	[1.14, 1.62]	***
	Widowed	1.35	[1.05, 1.72]	*
Region
	Northeast	0.98	[0.75, 1.27]
	Mid-west	0.94	[0.72, 1.22]
	South	0.81	[0.64, 1.03]
	West
Education
	Less than high school	0.57	[0.46, 0.71]	***
	High School	0.83	[0.72, 0.94]	**
	Above High School
Poverty Status
	Poor	1.86	[1.42, 2.43]	***
	Middle Income	1.21	[0.99, 1.47]
	High Income
Insurance Coverage
	Public
	Private	1.15	[0.90, 1.47]
	Uninsured	0.90	[0.65, 1.25]
Prescription Coverage
	Yes
	No	1.02	[0.80, 1.31]
Smoking Status
	Other
	Current smoker	1.69	[1.41, 2.02]	***
Physical Activity
	Moderate to Vigorous 5 times/week
	No Physical Activity	1.35	[1.17, 1.56]	***
Obesity
	Not obese
	Obese	1.13	[0.97, 1.32]
Number of Chronic Conditions
	1
	2	1.02	[0.87, 1.18]
	3 or more	1.01	[0.84, 1.21]
Pain
	None/Little
	Moderate	1.44	[1.16 , 1.79]
	Severe	1.72	[1.41 , 2.09]
Polypharmacy
	6 or more medications	2.80	[2.37 , 3.30]
	1 – 6 medications
	No or NSAIDs medications	0.30	[0.22 , 0.40]

Note: Based on 10,713 adults aged 21 years and old, alive during 2015 and with at least one of the following conditions: arthritis, asthma, cancer, copd, diabetes, heart diseases. Asterisks represent significant group differences by type of treatment compared to the reference group based on multivariable logistic regression. The reference group for the dependent variable in the multivariable logistic regression was “No NSAIDs use”.

AOR: Adjusted odds ratio; CI: Confidence Interval; Sig: significance.

^***p< .001;

^**.001 ≤ p < .01;

^*.01 ≤ p <.05

DISCUSSION

Consistent with the literature, we found that depression was reported by 1 in 5 adults with inflammatory chronic conditions.[22]–[24]. We also found that one in five adults used prescription NSAIDs. As we restricted our sample to those with inflammatory chronic conditions, it is difficult to compare rates of NSAIDs use in our study with other published studies. However, routine prescription NSAIDs was reported by 9.5% of adults in a study using data from the National Health and Nutrition Examination Survey (NHANES)[25].

In the unadjusted model, adults using prescription NSAIDs were more likely to report depression compared to those without depression, whereas in the fully adjusted model, there was no statistically significant association of prescription NSAIDs use to depression. This finding is consistent with several published studies reporting no significant benefit of NSAID in depression.[11], [12], [26], [27] Our findings also contradicts several published results from RCTs.[28], [29] However, our study findings are not strictly comparable to these RCTs because they included adults with depression or depressive symptoms; our study evaluated the odds of depression in adults with inflammatory chronic conditions.

It is plausible that those using prescription NSAIDs may experience severe pain. This is also reflected in our study where more than 50% of the adults using NSAIDs had moderate to severe pain as compared to only 27% adults who are not using NSAIDs. Adults using NSAIDs may also be using concomitant medications such as corticosteroids, statins that may increase their vulnerability for depression. Again, this can be seen in our study where adults with prescription NSAIDs had significantly higher polypharmacy rates. There is also some evidence that corticosteroids may lower serotonin levels and may lead to depression[30]. Moreover, we found that 33% of adults with polypharmacy reported depression that is much higher than the national average.[31]–[33] This finding is consistent with a recently published study using data from the NHANES, that reported adults using 3 or more concurrent medications with depression as an adverse effect were more likely to report depression as compared to adults not using such medications (15% vs 4.7%)[34]. Based on the adjusted model, polypharmacy demonstrated having significant influence on the association of prescription NSAIDs to depression. Given the well-established association between polypharmacy and depression where polypharmacy increases the risk to depression, our findings in the model could be plausible.[34]–[36]

Although NSAIDs are beneficial in treating pain and inflammation their possible adverse effects should also be considered. It is well documented that NSAIDs have gastrointestinal and cardiovascular adverse effects including peptic ulceration, thrombosis, myocardial infarction, hypertension, atherosclerosis, and various other vascular events [37]–[39]. These side effects can lead to depression[40]–[42].

Associations of other variables in the study (sex, age, race, poverty status, smoking status, exercise, obesity, insurance coverage) with depression were consistent with other published studies[43]–[50]. Additionally, pain interference with normal work and number of chronic conditions were also consistent with published literature[22], [23], [51].

Our study had many strengths; to date, ours is the first real world population-based study of all adults (with or without depression) to analyze the association of prescription NSAIDs to depression in the United States. We used a nationally representative sample with a large sample size, real-world practice setting, and a comprehensive list of independent variables that may affect depression. There were also some limitations. First of all, the study finding cannot be used to establish a causal relationship because the study design is retrospective, observational, and cross-sectional. This study did not include over-the-counter NSAIDs in the analysis because MEPS did not collect information on over-the-counter drugs, unless prescribed. We did not adjust for severity of inflammatory chronic conditions, which may have affected the relationship of prescription NSAIDs to depression. The study variables were based on the self-reported data which is collected by MEPS and is subject to reporting bias. Finally, our study had several biases and errors inherently associated with the secondary data that includes sampling and non-sampling errors, data editing errors, measurement errors and inter-rater bias.

To conclude, our study findings suggest that adults with inflammatory chronic conditions and using prescription NSAIDs had no significant association with depression compared to those who did not use prescription NSAIDs. Future population-based studies using a prospective study design, including disease severity and over-the-counter NSAIDs are needed to confirm or refute the observed association of prescription NSAIDs to depression from our study.

Author Biographies

Nazneen Fatima Shaikh is a PhD student in Health Services and Outcomes Research program at School of Pharmacy, West Virginia University. She received her BPharm from Bombay College of Pharmacy, India and prior to that completed her DPharm from KMK pharmacy polytechnic, India. Nazneen’s research interests include pharmacoeconomics, epidemiology, patient reported outcomes and health outcomes research studies on mental illness, oncology and medication use. She is actively involved in the International Society for P harmacoeconomics and Outcomes Research (ISPOR) Student Network and is currently the president-elect for WVU ISPOR Student Chapter.

Dr. Usha Sambamoorthi is the interim-chair and Professor in the Department of Pharmaceutical Systems and Policy, WVU School of Pharmacy. She is also the director of the graduate program in Health Services and Outcomes Research. Dr. Sambamoorthi received her master’s and doctorate degree in economics from the University of Madras, India. Her areas of research interest include big-data/machine learning in HSOR, health economics, global health, healthcare in individuals with co-occurring physical and mental illnesses and healthcare disparities by gender, race/ethnicity, age, and disability.