Skip to main content
PMC home page
PLOS ONE logoLink to PLOS ONE
. 2024 May 8;19(5):e0302637. doi: 10.1371/journal.pone.0302637

Adults with depressive symptoms have lower odds of dietary supplement use

Shakila Meshkat 1, Vanessa K Tassone 1, Hilary Pang 2, Michelle Wu 1, Hyejung Jung 3, Wendy Lou 3, Venkat Bhat 1,2,4,5,*
Editor: Jenny Wilkinson6
PMCID: PMC11078386  PMID: 38718014

Abstract

Objective

In this study, we aim to evaluate dietary supplement and complementary and alternative medicine (CAM) use in individuals with depressive symptoms. Furthermore, we conducted a comparative analysis of the usage of these agents among individuals with depressive symptoms, differentiating between those who were using antidepressants and those who were not. Additionally, we compared individuals with depressive symptoms who were not using antidepressants with participants who did not have depressive symptoms as well as individuals with depressive symptoms who were using antidepressants with individuals without depressive symptoms.

Method

The National Health and Nutrition Examination Survey 2007–2018 data was collected. Depressive symptoms were assessed using patient health questionnaire-9. Dietary supplement and antidepressants use was evaluated using Dietary Supplement Use and Prescription Medications Questionnaires.

Results

31,445 participants, with 2870 (8.05%) having depressive symptoms were included. Participants with depressive symptoms had significantly lower odds of dietary supplement use compared with those without depressive symptoms (aOR = 0.827, 95% CI: 0.700,0.977, p = 0.026). Participants with depressive symptoms who were using antidepressants had significantly higher odds of dietary supplement (aOR = 1.290, 95% CI: 1.038,1.604, p = 0.022) compared with participants with depressive symptoms who were not using antidepressants. Furthermore, Participants with depressive symptoms who weren’t using antidepressants had significantly lower odds of dietary supplement use (aOR = 0.762, 95% CI: 0.632,0.918, p = 0.005) compared with participants without depressive symptoms. In individuals with treated depressive symptoms compared to those without depressive symptoms, CAM use was significantly lower (aOR = 0.763, 95% CI = 0.598,0.973, p = 0.030).

Conclusion

Individuals with depressive symptoms have lower odds of dietary supplement use. Further studies are needed to replicate these findings and examine the underlying mechanisms for this association.

1. Introduction

Major depressive disorder (MDD) is among the leading causes of disability with a prevalence of 280 million globally [1]. MDD is not a single, homogeneous disorder but a complex phenomenon with many subtypes and probably several etiologies [2]. It also involves connections with other psychiatric and somatic disorders, a propensity for episodic and frequently progressive mood disturbances, a range of symptomatology from moderate to severe symptoms with or without psychotic aspects, and variances in symptomatology [3]. Depression is associated with increased morbidity and mortality rates with treatment involving adherence to psychotherapy and/or medication [1, 2]. Numerous pathways, such as synaptic transmission, the monoamine hypothesis, neurotransmitter concentrations, transporters for neurotransmitter reuptake, and neurotransmitter receptors have been identified as being involved in the pathophysiology of depression [4]. Additionally, nutrition may play a significant role in depression prevention, with involvement with the gut microbiome [5]. Nutritional deficiencies can have an impact on brain functioning, leading to mood disorders such as depression, dysthymia, and anxiety disorders [6]. Additionally, depression has been linked to deficits in several vitamins such as vitamin D, folic acid, vitamin B12, niacin, and vitamin C [7].

Dietary supplements are chemical substances such as minerals, vitamins, and anti- oxidants, which are part of normal nutrition but also can be added to normal nutrition in the shape of more or less pure substances [8]. Despite the fact that dietary supplements are not recommended for individuals who are healthy and consume a well-balanced and nutritionally adequate diet, the industry generates an annual revenue of 1.2 billion USD [9]. Additionally, it is estimated that approximately 29.2% of people in the United States (US) use at least one dietary supplement [8]. Dietary supplement use is more common in women and people with healthy lifestyles and reduces risk of chronic medical conditions [10, 11]. As more is learned about the therapeutic effects of dietary components, dietary supplements are increasingly being developed for the treatment of specific medical conditions including mental disorders. However, there are limited studies on examining the utilization of dietary supplements in people with depression at the population-level.

Complementary and alternative medicine (CAM) refers to a diverse range of medical and healthcare systems, practices, and products that are currently not included in conventional medicine [12]. Depression is one of the 10 most frequent indications for using CAM since it is often undertreated and under diagnosed [13]. Despite the advantages associated with CAM, such as a lower incidence of adverse events, reported efficacy, a comprehensive perspective on individual problems, and dissatisfaction with traditional care, the quality of CAM recommendations for depression has been noted to be generally lower [14]. Herbal agents, exercise, and dietary supplements are mostly used as CAM by depressed individuals [15]. While different agents are used in depression as CAM, there is limited evidence regarding the use of each agent in individuals with depression.

Given the widespread use of CAM and dietary supplements, we aim to investigate 1) the association between use of these supplement agents and depressive symptom severity, 2) if individuals with depressive symptoms use these agents more than individuals without depressive symptoms, 3) if individuals with depressive symptoms who use antidepressants use these agents more than individuals with depressive symptoms who do not use antidepressants, 4) if individuals with depressive symptoms who do not use antidepressants use these agents more than individuals without depressive symptoms, and 5) if individuals with depressive symptoms who use antidepressants use these agents more than individuals without depressive symptoms.

2. Method

2.1. Study population and design

We used data from the National Health and Nutrition Examination Surveys (NHANES) 2007–2018. NHANES contains cross sectional population based data that was conducted by the US National Center for Health Statistics (NCHS), Center for Disease Control and Prevention (CDC). NHANES is a survey based nationally data from civilian non-institutionalized populations aged 18–80 years in 50 states of the United States that has complex, multistage, probability sampling design. The data is collected through in-home interviews using computer-assisted personal interviews conducted at home and physical examinations performed at mobile examination centers (MEC). Socio-demographic, nutritional, and health-related inquiries were addressed during in-home interviews. Anthropometric, blood pressure, urine, blood, and hearing tests, as well as health status evaluations, were done at the MEC. Before conducting in-home interviews and the MEC examinations, participants would need to sign consent forms [16]. The survey procedure has been approved by the NCHS Research Ethics Review Board. NHANES data is collected annually and released every two years. Additional details about methods and sampling are presented on the CDC website: https://wwwn.cdc.gov/nchs/nhanes/. We included male and female older than 18 years old who completed the Mental Health—Depression Screener (items DPQ010 to DPQ090), Dietary Supplement Use questionnaire and Prescription Medications—Drug Information Questionnaire.

2.2. Exposure variables

Depressive symptoms were assessed using the Patient Health Questionnaire-9 (PHQ-9). PHQ-9 is a self-administered questionnaire widely used for making criteria-based diagnoses of depressive symptoms in accordance with the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition for MDD [17]. On a scale of 0 to 3, participants rated each question as per the frequency of their symptoms during the previous two weeks, with 0 being not at all and 3 being experienced nearly every day. While a score of less than 10 shows no depressive symptoms, a score of 10 or higher suggests presence of depressive symptoms [18]. Several studies have confirmed the reliability and validity of PHQ-9 [17, 19].

Antidepressants use was evaluated using Prescription Medications—Drug Information Questionnaire. Prescription medications were classified by NHANES based on the three-level nested therapeutic classification scheme from Cerner Multum’s Lexicon (https://www.cerner.com/solutions/drug-database). Antidepressants were selected by a second-level category identifier of “249” (https://wwwn.cdc.gov/Nchs/Nhanes/1999-2000/RXQ_DRUG.htm). Binary variables were then constructed for depressive symptoms treatment, where “treated” indicates anyone with depressive symptoms and currently on any class of antidepressants and “untreated” for those diagnosed with depressive symptoms but not taking any class of antidepressants. Depressive symptoms severity was defined as just the raw PHQ-9 score, where a higher score indicates more depressive symptoms.

2.3. Outcome variable

Dietary supplements use during the past 30 days was self reported, including vitamin B1, B2, B3 (Niacin), B6, B12, C, K, D, folic acid, folate, choline, calcium, phosphorus, magnesium, iron, zinc, copper, sodium, potassium, selenium, vitamin E, omega-3 fatty acids, and multivitamins. Dietary supplement use was binary and was considered “Yes” if individuals were taking any of the previously listed supplements as well as answered “Yes” to DSD010 “Any dietary supplements taken?”, and “No” otherwise. Selected CAM agents were: folate, magnesium, vitamin B6, B9, D, zinc, selenium, and omega-3 fatty acids. In this study, CAM was defined as a binary variable of “Yes” if any of the above CAM agents were taken or if an individual participated in >150 minutes of physical activity a week, and “No” otherwise. We also categorized supplements into vitamin B family (vitamin B1, B2, niacin, folate, B12, folic acid), fat-soluble vitamins (D, E, K) and water-soluble vitamins (vitamin C, B1, B2, B3, folate, folic acid). These were all binary variables that were dichotomized into “Yes” or “No” for specific vitamin-class use, with “No” set as the reference category. Individual vitamin use was kept continuous in their respective units. Note that while the majority of the vitamin and supplements information comes from the Dietary Supplement Use 30-Day—Total Dietary Supplements Questionnaire, information on vitamin E, omega 3 fatty-acids, and multivitamin use had to be extracted from the Prescription Medications questionnaire and thus details on exact amounts taken per individual was not available.

2.4. Covariates

In order to minimize confounding bias, covariates were included. Covariates included age, race, sex, diabetes, hypertension, chronic kidney disease, congestive heart failure, and liver disease. Age was continuous and gender was binary (male, female). All other health indicator variables were binary where “Yes” indicates presence of the disease and “No” otherwise. In models where depressive symptoms are treated as a binary variable, depressive symptoms severity (total PHQ-9 score) was included as a control.

2.5. Statistical analysis

All statistical analyses were performed using R v 4.2.2 and the package “survey” to account for MEC survey weights (https://wwwn.cdc.gov/nchs/nhanes/tutorials/weighting.aspx). Survey weights were divided by the number of cycles included to account for the merging of cycles, as recommended by NHANES. Categorical variables were described as raw frequency and weighted percent in the study population demographic characteristics table, while continuous variables were described as weighted mean and standard deviation (SD). A chi-square test of independence was used to check for statistically significant (p-value ≤ 0.05) differences in categorical demographic characteristics among the depressive symptoms groups, and a t-test was used to test for differences in continuous variables. Multivariable logistic regression was used to test the relationship between dietary supplement and CAM use with depressive symptoms, depressive symptoms severity, treated vs. untreated depressive symptoms, and untreated depressive symptoms vs. no depressive symptoms. The same methodology was applied with the use of vitamin classes as the outcome variable. Multiple linear regression was used to look at the association between individual vitamins and depressive symptoms, depressive symptoms severity, treated vs. untreated depressive symptoms, and untreated vs. no depressive symptoms. To account for multiple testing, statistical significance was adjusted using Bonferroni’s correction for the individual vitamins models and the vitamin class models. Missing values were excluded from the analyses.

3. Results

3.1. Study sample

Data from a total of 59,842 individuals aged 18 to 80 years were collected from the 2007–2018 NHANES cycles. The study population consisted of 31,445 individuals (Fig 1), of which 2870 (8.05%) reported depressive symptoms, 15518 (54.32%) reported using dietary supplements, and 22332 used CAM (76.42%). The mean age of the study population was 46.66 (SD = 17.50), and 15958 (51.13%) were females. Table 1 presents the demographic characteristics for the study population and any significant differences among covariates.

Fig 1. Participant inclusion flowchart.

Fig 1

Open in a new tab

Table 1. Demographics of study sample.

Characteristic Total Depressive symptoms No-depressive symptoms P value
Sample size 31445 2870 28575
Age (mean, SD) 46.66 (17.50) 46.13 (16.43) 46.71 (17.59) 0.227
Sex (n, %) <0.001
Female 15958 (51.13) 1827 (64.16) 14131 (49.98)
Male 15487 (48.87) 1043 (35.84) 14444 (50.02)
Race (n, %) <0.001
Mexican American 4857 (8.71) 440 (8.29) 4417 (8.74)
Other Hispanic 3280 (5.82) 397 (8.09) 2883 (5.62)
Non-Hispanic White 12864 (66.66) 1190 (62.94) 11674 (66.98)
Non-Hispanic Black 6786 (11.16) 613 (13.20) 6173 (10.98)
Other race—including multi-racial 3658 (7.66) 230 (7.48) 3428 (7.68)
Diabetes—Yes (n, %) 4042 (9.69) 570 (15.61) 3472 (9.17) <0.001
Hypertension—Yes (n, %) 8903 (25.56) 1148 (37.26) 7755 (24.53) <0.001
Chronic Kidney Disease—Yes (n, %) 1016 (2.65) 207 (6.60) 809 (2.30) <0.001
Congestive Heart Failure—Yes (n, %) 965 (2.37) 189 (5.69) 776 (2.08) <0.001
Liver Disease—Yes (n, %) 1257 (3.69) 255 (8.36) 1002 (3.28) <0.001
Dietary supplement use (n, %) 15518 (54.32) 1368 (53.40) 14150 (54.40) 0.470
CAM use (n, %) 22332 (76.42) 1762 (66.34) 20570 (77.30) 0.062
Vitamin B family (n, %) 10230 (36.28) 810 (31.11) 9420 (36.73) <0.001
Water-soluble vitamins (n, %) 10777 (38.19) 831 (31.93) 9946 (38.74) <0.001
Fat-soluble vitamins (n, %) 11054 (39.24) 881 (33.43) 10173 (39.75) <0.001
Treated depressive symptoms 910 (36.53) 910 (36.53) N/A N/A
Open in a new tab

Note: All percentages, means and SDs are using survey weights. P values are from t-tests for weighted continuous variables and chi-squared tests for weighted categorical variables.

3.2. Dietary supplement use

In adjusted models, participants with depressive symptoms had significantly lower odds of dietary supplement use in comparison with those without depressive symptoms. The adjusted model showed that those with depressive symptoms have 17.3% lower odds of using dietary supplement compared to those without depressive symptoms (adjusted odds ratio [aOR] = 0.827, 95% CI: 0.700, 0.977, p = 0.026). However, depressive symptoms severity did not show this pattern (Table 2). Conversely, between treated and untreated individuals with depressive symptoms, those who were treated had statistically significant higher odds of using dietary supplements compared to those who were not treated (aOR = 1.290, 95% CI: 1.038,1.604, p = 0.022) (Table 3). For patients with untreated depressive symptoms, odds of dietary supplement use was significantly lower compared to those without depressive symptoms (aOR = 0.762, 95% CI: 0.632,0.918, p = 0.005) (Table 3). No statistically significant association was seen between those with treated depressive symptoms versus no depressive symptoms in terms of dietary supplement usage (Table 3).

Table 2. Unadjusted and adjusted ORs for associations between dietary supplement and complementary and alternative medicine use and depressive symptoms.

Exposure group OR (95% CI) P value aOR (95% CI) P value
Dietary supplement
Depressive symptoms vs. No depressive symptoms 0.960 (0.859,1.074) 0.475 0.8272 (0.700,0.977) 0.026*
Depressive symptoms severity 1.001 (0.994,1.009) 0.727 0.998(0.990,1.007) 0.702
Complementary and alternative medicine
Depressive symptoms vs. No depressive symptoms 0.579 (0.521,0.642) <0.001* 0.831(0.710,0.974) 0.023*
Depressive symptoms severity 0.960 (0.952,0.968) <0.001* 0.966(0.957,0.974) <0.001*
Open in a new tab

Note. aOR = adjusted odds ratio. Covariates in the adjusted model include age, gender, diabetes, hypertension, chronic kidney disease, congestive heart failure, and liver disease. Statistical significance of p < 0.05 is indicated by *.

Table 3. Unadjusted and adjusted ORs for associations between dietary supplement and complementary and alternative medicine use and depressive symptoms treatments.

Outcome N OR (95% CI) P value aOR (95% CI) P value
Dietary supplement
Treated vs. Untreated depressive symptoms 2843 1.663 (1.354,2.041) <0.001* 1.290 (1.038,1.604) 0.022*
Untreated depressive symptoms vs. No depressive symptoms 30508 0.805 (0.704,0.920) 0.002* 0.762(0.632,0.918) 0.005*
Treated depressive symptoms vs. No depressive symptoms 29485 1.338 (1.121,1.596) 0.001* 0.850 (0.678,1.065) 0.155
Complementary and alternative medicine
Treated vs. Untreated depressive symptoms 2843 0.959 (0.772,1.191) 0.700 0.917(0.731,1.150) 0.450
Untreated depressive symptoms vs. No depressive symptoms 30508 0.589 (0.523,0.663) <0.001* 0.869(0.728,1.037 0.118
Treated depressive symptoms vs. No depressive symptoms 29485 0.565 (0.468,0.682) <0.001* 0.763 (0.598,0.973) 0.030*
Open in a new tab

Note. aOR = adjusted odds ratio. Covariates in the adjusted model include age, gender, diabetes, hypertension, chronic kidney disease, congestive heart failure, and liver disease. Statistical significance of p < 0.05 is indicated by *.

3.3. Complementary and alternative medicine

Participants with depressive symptoms had lower odds of CAM use in comparison with those without depressive symptoms (aOR = 0.831, 95% CI: 0.710, 0.977, p = 0.026). Moreover, participants with more severe depressive symptoms had significantly lower odds of CAM use in comparison with those milder depressive symptoms (aOR = 0.966, 95% CI: 0.957, 0.974, p = <0.001) (Table 2). Between treated and untreated individuals with depressive symptoms though, odds of CAM use was not statistically significantly different than those with treated depressive symptoms compared to those with untreated depressive symptoms (Table 3). Results were also not significant when comparing those with untreated depressive symptoms to those without depressive symptoms (Table 3). In those with treated depressive symptoms compared to no depressive symptoms, CAM use was lower in comparison (aOR = 0.763, 95% CI = 0.598,0.973, p = 0.030) (Table 3).

3.4. Vitamins

There were no significant changes in vitamin usage between those who reported depressive symptoms compared to those who did not report depressive symptoms, or in terms of increasing depressive symptoms severity (S1 Table). Individuals with depressive symptoms had statistically significantly lower odds of taking vitamin B Family or water soluble vitamins (aOR = 0.794, 95% CI: 0.662, 0.953, p = 0.0141; aOR = 0.790, 95% CI: 0.661, 0.943, p = 0.010) and the odds of taking any vitamin class were decreased for each one point increase in PHQ-9 score and was statistically significant (S2 Table). Between those treated and untreated for depressive symptoms, the results were not statistically significant for any individual vitamin but was significant for the fat-soluble vitamin class, where those who were treated for depressive symptoms had 1.339 odds of taking a fat-soluble vitamin (Table 3 and S4 Table). For those with untreated depressive symptoms, compared to those with no depressive symptoms, the results were not statistically significant for any individual vitamins, but use of a vitamin B class supplement was statistically lower (aOR = 0.774, 95% CI: 0.631,0.950, p = 0.015) (Table 3 and S4 Table). Comparing those with treated depressive symptoms to no depressive symptoms, no statistically significant differences were seen in individual vitamins or vitamin classes (Table 3 and S4 Table).

4. Discussion

Several randomized clinical trials have indicated the efficacy of dietary supplement inducing vitamin D, B12, magnesium, zinc for reducing depression symptoms [19–24]. Vitamin B family and omega 3, which are precursors to neurotransmitters, are among the most common nutritional deficiencies in individuals with mood disorders [25]. There is evidence that high fish oil consumption can result in low incidence of mental disorders [26]. Our results suggested that individuals with depressive symptoms have lower odds of supplement consumption compared with individuals without depressive symptoms. Taking dietary supplements can indicate various health-related behaviors, as individuals who use supplements are generally less inclined to consume excessive alcohol, smoke, or be overweight [27]. Additionally, they are more prone to participate in physical activities and adopt a more vegetarian eating pattern and to consume more fruits and vegetables [27]. Within the National Diet and Nutrition Survey of British Adults survey, it was observed that individuals who consumed dietary supplements surprisingly displayed higher recorded nutrient intakes solely from food sources compared to those who didn’t take supplement [28]. This phenomenon, known as the ’inverse supplement hypothesis,’ suggests that the individuals who are most inclined to use dietary supplements may actually be the ones who require them the least [27, 28]. Previous studies have reported that depression is associated with sedentary lifestyle and lower physical activity [29]. Our findings suggest that supplement users are less likely to have depressive symptoms than non-supplement users. Additionally, it is noteworthy to consider that participants with chronic diseases in this study exhibited higher levels of depressive symptoms. The use of CAM and dietary supplements among these individuals may introduce interactions with their chronic disease medications, which could contribute to the observed depressive symptomatology. Future research should delve deeper into these potential interactions to better understand their impact on mental health outcomes.

Our findings indicate that participants with depressive symptoms who use antidepressants have higher odds of dietary supplement compared with participants with depressive symptoms who do not use antidepressants. This may be due to the potential to self-treat with a range of dietary supplements. Previous studies have demonstrated the possibility of self-medication with over-the-counter (OTC) medicines, CAM and dietary supplements [30, 31]. Additionally, the use of herbal remedies and OTC for self-medication is prevalent among individuals suffering from anxiety and depression [32]. This further implies that the general population may have some level of dissatisfaction with their Western medical treatment, albeit indirectly [30]. This is also in line with prior work that around thirty percent of individuals older than 65 years old may utilize OTC medications alongside their prescribed medicines [30]. We also hypothesize that the higher odds of supplement use in individuals with treated depressive symptoms compared to individuals with untreated depressive symptoms may be due to antidepressants adverse events. An increasing number of studies have shown that antidepressants can induce nutritional depletion and deficiency [33–35]. Hence, individuals might consider utilizing dietary supplements to address the potential effects of antidepressants on their vitamin levels. Finally, the lower odds of dietary supplements use in participants with depressive symptoms who do not use antidepressants may be due their lack of insight or less compliance to antidepressants therapy. Moreover, various factors are involved in supplements and CAM use including reported effectiveness, accessibility, decreased adverse effects, dissatisfaction with current medical treatment, income level, education level, culture. There may also be a selection bias towards using supplements and CAM in people with less severe depression, as people with more severe depression may rely on more biological/interventional treatments such as medication and electroconvulsive therapy [36].

Our study’s findings suggested a notable difference in CAM usage between individuals with treated depressive symptoms and those without. This indicated that individuals with treated depressive symptoms may be less inclined to turn to CAM therapies compared to individuals without depressive symptoms. One possibility is that individuals receiving antidepressant treatment for depressive symptoms, may feel that these conventional methods are sufficient for managing their symptoms. They might prioritize the guidance of healthcare professionals and evidence-based antidepressants over CAM approaches. Additionally, the stigma often associated with mental health conditions such as depressive symptoms could play a role. Some individuals might be more comfortable discussing and seeking treatment for their depressive symptoms within the context of traditional healthcare settings, rather than exploring CAM options. Further research should explore the reason for this phenomenon.

It is essential to take into consideration the strengths and limitations inherent in this study. The understanding of the measurement error structure and validity of the NHANES dietary supplements collection methods is currently limited. Conducting validation studies would be necessary to comprehend the extent and types of errors, such as random and systematic errors. Potential sources of measurement error include several factors: 1) participants’ recall errors when reporting all dietary supplement consumed, typical dosage, and frequency within the past 30 days; 2) inaccuracies when interviewers transcribe information from the product label during data collection; 3) misidentification of the reported product with the actual formulation used by the participant; 4) errors during the entry of product label information into the database; and 5) discrepancies between the labeled ingredient amounts and the actual content consumed. Future research endeavors may involve assessing the NHANES dietary supplement collection methods as well as alternative approaches for gathering information on dietary supplement use in surveys and studies. In addition, regarding the definition of depressive symptoms, our study employed the PHQ-9 as a screening tool. While deemed acceptable for screening, it’s crucial to acknowledge that the PHQ-9 serves as a screening tool rather than a standardized diagnostic tool. Consequently, individuals identified as MDD through screening, who remain untreated, may not necessarily require antidepressants, potentially not reflecting true MDD cases. Furthermore, the tool might not distinctly capture the level of depressive symptoms, representing a limitation in our study.

The strength of our study is that NHANES is a survey that encompasses a representative sample of the noninstitutionalized population in the US, which adds to its credibility, however it is important to note a limitation. The data utilized in our analysis only extends up to the year 2018 due to the unique circumstances presented by the COVID-19 pandemic and its impact on mental health. This time frame limitation may impact the generalizability of our findings. Finally, it is not possible to completely dismiss the potential influence of self-selection bias, whereby individuals who are more health-conscious may have exhibited greater interest in participating in NHANES [37].

In conclusion, our results indicated significantly lower odds of dietary supplement use in individuals with depressive symptoms compared to adults not reporting depressive symptoms. Notably, individuals receiving treatment for depression demonstrated increased usage of dietary supplements, particularly fat-soluble vitamins such as vitamin D compared with those with depressive symptoms who were not taking antidepressants. Conversely, those with untreated depressive symptoms had lower odds of CAM use compared with participants without depressive symptoms. These findings suggest that treatment may influence supplement intake, especially for essential vitamins. Further replication and validation is needed along with definitive studies to further evaluate the underlying reasons for this phenomenon among individuals with depression. Healthcare providers should engage in discussions regarding the potential benefits of dietary supplements and CAM with patients experiencing depressive symptoms, particularly those not undergoing treatment. Clinicians should consider the impact of treatment on vitamin intake, specifically fat-soluble vitamins, and potentially monitor or recommend appropriate supplementation for individuals with depressive symptoms to ensure adequate nutritional support.

Supporting information

S1 Table. Adjusted coefficient estimates (aCoef. Estm) for associations between individual vitamin use and depressive symptoms risk or depressive symptoms severity.

(DOCX)

pone.0302637.s001.docx (9.4KB, docx)
S2 Table. Adjusted ORs for associations between various vitamin classes and depressive symptoms risk or depressive symptoms severity.

(DOCX)

pone.0302637.s002.docx (8.5KB, docx)
S3 Table. Adjusted Coef. Estm for associations between individual vitamin use and depressive symptoms treatments.

(DOCX)

pone.0302637.s003.docx (9.5KB, docx)
S4 Table. Adjusted ORs for associations between various vitamin classes and alternative medicine use and depressive symptoms treatments.

(DOCX)

pone.0302637.s004.docx (8.6KB, docx)

Data Availability

The data underlying the results presented in the study are available from https://wwwn.cdc.gov/nchs/nhanes/Default.aspx. We used data from 2005-2006 through 2017-2018 survey cycle datasets.

Funding Statement

The authors received no specific funding for this work.

References

  • 1.Depression, Accessed March 16, 2023. https://www.who.int/news-room/fact-sheets/detail/depression
  • 2.Belmaker RH, Agam G. Major depressive disorder. New England Journal of Medicine. 2008. Jan 3;358(1):55–68. doi: 10.1056/NEJMra073096 [DOI] [PubMed] [Google Scholar]
  • 3.Solomon DA, Keller MB, Leon AC, Mueller TI, Lavori PW, Shea MT, et al. Multiple recurrences of major depressive disorder. American Journal of Psychiatry. 2000. Feb 1;157(2):229–33. doi: 10.1176/appi.ajp.157.2.229 [DOI] [PubMed] [Google Scholar]
  • 4.Fekadu N, Shibeshi W, Engidawork E. Major depressive disorder: pathophysiology and clinical management. J Depress Anxiety. 2017;6(1):255–7. [Google Scholar]
  • 5.Kaner G, Soylu M, Yüksel N, Inanç N, Ongan D, Başmısırlı E. Evaluation of nutritional status of patients with depression. BioMed research international, vol. 2015, Article ID 521481, 9 pages, 2015. doi: 10.1155/2015/521481 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Harbottle L, Schonfelder N. Nutrition and depression: A review of the evidence. Journal of Mental Health. 2008. Jan 1;17(6):576–87. [Google Scholar]
  • 7.Tiemeier H, Van Tuijl HR, Hofman A, Meijer J, Kiliaan AJ, Breteler MM. Vitamin B12, folate, and homocysteine in depression: the Rotterdam Study. American Journal of Psychiatry. 2002. Dec 1;159(12):2099–101. doi: 10.1176/appi.ajp.159.12.2099 [DOI] [PubMed] [Google Scholar]
  • 8.Balluz LS, Kieszak SM, Philen RM, Mulinare J. Vitamin and mineral supplement use in the United States: results from the third National Health and Nutrition Examination Survey. Archives of Family Medicine. 2000. Mar 1;9(3):258. [DOI] [PubMed] [Google Scholar]
  • 9.Gariballa S, Forster S. Effects of dietary supplements on depressive symptoms in older patients: a randomised double-blind placebo-controlled trial. Clinical nutrition. 2007;26(5):545–51. doi: 10.1016/j.clnu.2007.06.007 [DOI] [PubMed] [Google Scholar]
  • 10.Kirk SF, Cade JE, Barrett JH, Conner M. Diet and lifestyle characteristics associated with dietary supplement use in women. Public health nutrition. 1999. Jan;2(1):69–73. doi: 10.1017/s1368980099000099 [DOI] [PubMed] [Google Scholar]
  • 11.De Jong N, Ocke MC, Branderhorst HA, Friele R. Demographic and lifestyle characteristics of functional food consumers and dietary supplement users. British Journal of Nutrition. 2003. Feb;89(2):273–81. doi: 10.1079/BJN2002772 [DOI] [PubMed] [Google Scholar]
  • 12.The National Center for Complementary and Alternative Medicine Clearinghouse website: http://nccam.nih.gov/health (Accessed March 19, 2023).
  • 13.Freeman MP. Complementary and alternative medicine (CAM): considerations for the treatment of major depressive disorder. The Journal of clinical psychiatry. 2009. Nov 15;70(suppl 5):3533. doi: 10.4088/JCP.8157su1c.01 [DOI] [PubMed] [Google Scholar]
  • 14.Ng JY, Nazir Z, Nault H. Complementary and alternative medicine recommendations for depression: a systematic review and assessment of clinical practice guidelines. BMC complementary medicine and therapies. 2020. Dec;20(1):1–5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Wu P, Fuller C, Liu X, Lee HC, Fan B, Hoven CW, et al. Use of complementary and alternative medicine among women with depression: results of a national survey. Psychiatric Services. 2007;58(3):349–56. doi: 10.1176/ps.2007.58.3.349 [DOI] [PubMed] [Google Scholar]
  • 16.Zipf G, Chiappa M, Porter KS, Ostchega Y, Lewis BG, Dostal J. National Health and Nutrition Examination Survey: Plan and Operations, 1999–2010. Vital Health Stat. 2013;1(56):37. [PubMed] [Google Scholar]
  • 17.Kroenke K, Spitzer RL, Williams JB. The PHQ‐9: validity of a brief depression severity measure. Journal of general internal medicine. 2001. Sep;16(9):606–13. doi: 10.1046/j.1525-1497.2001.016009606.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Kroenke K, Spitzer RL. The PHQ-9: a new depression diagnostic and severity measure. Psychiatric annals. 2002. Sep 1;32(9):509–15. [Google Scholar]
  • 19.Costantini L, Pasquarella C, Odone A, Colucci ME, Costanza A, Serafini G, et al. Screening for depression in primary care with Patient Health Questionnaire-9 (PHQ-9): A systematic review. Journal of affective disorders. 2021. Jan 15;279:473–83. doi: 10.1016/j.jad.2020.09.131 [DOI] [PubMed] [Google Scholar]
  • 20.Hoffmann K, Emons B, Brunnhuber S, Karaca S, Juckel G. The role of dietary supplements in depression and anxiety-a narrative review. Pharmacopsychiatry. 2019;52(6):261–279. doi: 10.1055/a-0942-1875 [DOI] [PubMed] [Google Scholar]
  • 21.Syed EU, Wasay M, Awan S. Vitamin B12 supplementation in treating major depressive disorder: a randomized controlled trial. Open Neurol J. 2013;7(1):44–48. doi: 10.2174/1874205X01307010044 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Wang J, Um P, Dickerman BA, Liu J. Zinc, magnesium, selenium and depression: a review of the evidence, potential mechanisms and implications. Nutrients. 2018;10(5):1–19. doi: 10.3390/nu10050584 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Bell IR, Edman JS, Morrow FD, Marby DW, Mirages S, Perrone G, et al. B Complex vitamin patterns in geriatric and young adult inpatients with major depression. J Am Geriatr Soc. 1991;39:252–7. doi: 10.1111/j.1532-5415.1991.tb01646.x [DOI] [PubMed] [Google Scholar]
  • 24.Tanskanen A, Hibbeln JR, Hintikka J, Haatainen K, Honkalampi K, Viinamaki H. Fish consumption, depression, and suicidality in a general population. Arch Gen Psychiatry. 2001;58:512–3. doi: 10.1001/archpsyc.58.5.512 [DOI] [PubMed] [Google Scholar]
  • 25.Janicak PG, Lipinski, Davis JM, Comaty JE, Waternaux C, Cohen B, et al. S-adenosylmethionine in depression: A literature Review and preliminary report. Ala J Med Sci. 1988;25:306–13. [PubMed] [Google Scholar]
  • 26.Assisi A, Banzi R, Buonocore C, Capasso F, Di Muzio V, Michelacci F, et al. Fish oil and mental health: the role of n-3 long-chain polyunsaturated fatty acids in cognitive development and neurological disorders. International clinical psychopharmacology. 2006. Nov 1;21(6):319–36. doi: 10.1097/01.yic.0000224790.98534.11 [DOI] [PubMed] [Google Scholar]
  • 27.Conner M, Kirk SF, Cade JE, Barrett JH. Why do women use dietary supplements? The use of the theory of planned behaviour to explore beliefs about their use. Social science & medicine. 2001. Feb 1;52(4):621–33. doi: 10.1016/s0277-9536(00)00165-9 [DOI] [PubMed] [Google Scholar]
  • 28.Gregory J, Foster K, Tyler H, Wiseman M. The dietary and nutritional survey of British adults. HMSO Publications Centre; 1990. [Google Scholar]
  • 29.Piotrowski MC, Lunsford J, Gaynes BN. Lifestyle psychiatry for depression and anxiety: Beyond diet and exercise. Lifestyle Medicine. 2021. Jan;2(1):e21. [Google Scholar]
  • 30.Goh LY, Vitry AI, Semple SJ, Esterman A, Luszcz MA. Self-medication with over-the-counter drugs and complementary medications in South Australia’s elderly population. BMC Complementary and Alternative Medicine. 2009. Dec;9(1):1–0. doi: 10.1186/1472-6882-9-42 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Eichhorn T, Greten HJ, Efferth T. Self-medication with nutritional supplements and herbal over-thecounter products. Natural Products and Bioprospecting. 2011. Oct;1:62–70. [Google Scholar]
  • 32.Saeed SA, Bloch RM, Antonacci DJ. Herbal and dietary supplements for treatment of anxiety disorders. American family physician. 2007. Aug 15;76(4):549–56. [PubMed] [Google Scholar]
  • 33.Felípez L, Sentongo TA. Drug-induced nutrient deficiencies. Pediatric Clinics. 2009. Oct 1;56(5):1211–24. doi: 10.1016/j.pcl.2009.06.004 [DOI] [PubMed] [Google Scholar]
  • 34.Shi H, Wang B, Xu X. Antidepressant effect of vitamin D: a literature review. Neuropsychiatry. 2017;7(4):337–41. [Google Scholar]
  • 35.Wakeman M. A literature review of the potential impact of medication on vitamin D status. Risk management and healthcare policy. 2021. Aug 14:3357–81. doi: 10.2147/RMHP.S316897 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Ashraf H, Salehi A, Sousani M, Sharifi MH. Use of complementary alternative medicine and the associated factors among patients with depression. Evidence-Based Complementary and Alternative Medicine. 2021. Mar 27;2021. doi: 10.1155/2021/6626394 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Bernstein OM, Vegetabile BG, Salazar CR, Grill JD, Gillen DL. Adjustment for biased sampling using NHANES derived propensity weights. Health Services and Outcomes Research Methodology. 2023. Mar;23(1):21–44. [Google Scholar]

Decision Letter 0

Jenny Wilkinson

5 Dec 2023

PONE-D-23-21189Adults with Depression Have Lower Odds of Dietary Supplement UsePLOS ONE

Dear Dr. Bhat,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Jan 12 2024 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Jenny Wilkinson, PhD

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at 

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and 

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. Thank you for stating the following in the Competing Interests section: 

"I have read the journal's policy and the authors of this manuscript have the following

competing interests: VB is supported by an Academic Scholar Award from the

University of Toronto Department of Psychiatry and has received research support

from the Canadian Institutes of Health Research, Brain & Behavior Foundation, Ontario

Ministry of Health Innovation Funds, Royal College of Physicians and Surgeons of

Canada, Department of National Defence (Government of Canada), New Frontiers in

Research Fund, Associated Medical Services Inc. Healthcare, American Foundation

for Suicide Prevention, Roche Canada, Novartis, and Eisai."

Please confirm that this does not alter your adherence to all PLOS ONE policies on sharing data and materials, by including the following statement: ""This does not alter our adherence to  PLOS ONE policies on sharing data and materials.” (as detailed online in our guide for authors http://journals.plos.org/plosone/s/competing-interests).  If there are restrictions on sharing of data and/or materials, please state these. Please note that we cannot proceed with consideration of your article until this information has been declared. 

Please include your updated Competing Interests statement in your cover letter; we will change the online submission form on your behalf.

Additional Editor Comments:

Thank you for your submission. Reviews are now complete and reviewers comments are provided. Both reviewers have highlighted significant areas for review in the work particularly around the use, analysis and interpretation of the data and have provided suggestions for improvements. you are invited to consider these comments and provide a significant revision of your work to address the concerns raised by the reviewers.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: No

Reviewer #2: No

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: No

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: This manuscript utilized data from NHANES 2005-2018 to address the question whether adults with depression use nutritional supplements to a different degree than non-depressed adults. This is an interesting question as there is evidence that supplement use can be used successfully as adjunct therapy in depression. Using this large, representative sample is a strength of the study; however, researchers are limited to the data collected to direct their question. My main concern with this work is how the outcome variables were defined (part 2.3). The investigators defined dietary supplement use by reporting individual nutrient use: B1, B2, B3, B6, B12, vitamins C, K, and D, folic acid, folate choline, calcium, P, Mg, Fe, Zn, Cu, Na, K, Se, and caffeine. Additionally, nutrients were grouped as water soluble vitamins, fat soluble vitamins, and B vitamins. CAM was defined as folate, Mg, B6, B9, D, Zn, and Se. Hence, there is tremendous overlap in the data presented, and the results, thus, are convoluted and repetitive. Also, it is unclear if multivitamin/mineral use is included in all of these categories, or if only individual supplementation is examined. A more systematic approach (with no overlap) would produce more useful, meaningful results. Often multivitamin/mineral use is separated from single nutrient supplementation. In addition to a multivitamin/mineral supplement, the top 3-5 supplements could be investigated (with an ‘other’ group). For fat soluble vitamins, only D and K are examined – yet E is one of the leading individual nutrients supplemented in the US. The omega 3 fats are also at the top of the list of supplemented nutrients and are not examined in this report (although mentioned in the discussion). Why is caffeine in this analysis? Furthermore, there is no data presented on caffeine as well as several other nutrients listed above. If variables are stated as outcomes in the methods section, they need to be reported in the results section.

In the text, CAM is defined (lines 79-86) as a range of medical and healthcare systems, practices, and products – including herbal agents, and exercise. Yet, in methods CAM is defined as folate, Mg, B6, B9 (which is folate – thus repetitive), D, Zn, and Se. There is no justification for this definition of CAM and it is not consistent with the accepted definition of CAM. See: https://www.cancer.gov/about-cancer/treatment/cam Also, the authors discuss the use of OTC – yet they did not look at these data in the NHANES data set. The authors need to be more cautious in their approach to the research question.

Since herbal agents, exercise, and omega 3 fats are in the NHANES data set, it is unclear why these variables were not assessed in this investigation.

Other concerns:

• The introduction is sourced mainly from reviews and websites. There is only a cursory overview of the topic with little primary research cited. Depending on second-hand sources to such a large degree lowers the confidence of the reader for accepting the rational provided to justify the investigation. Include primary data in the introduction to support statements.

• Line 71: what is meant by ‘regular’ diet?

• Section 2.1: provide citations for the characteristics of NHANES data.

• Line 105: ‘need to sign’ to replace ‘have to sign’

• Line 123: what is “249” – there is no definition or citation.

• Throughout the text, do not capitalize nutrients – these are not proper nouns.

• Line 145: provide a citation

• All tables should have a legend to explain the presentation of the data and the p value.

• Table 1: For ‘sex’ add a line for male data (similar to how there is a line for each component of ‘race’).

• Table 1: the final 6 lines need to be reconsidered as discussed above. (similar comment for tables 4-6)

• Line 213: replace ‘levels’ with ‘usage’

• Discussion: the first paragraph can be deleted as it is a repeat of the results.

• Line 316: need to add ‘compared to adults not reporting depression’. The comparison group needs to be identified.

Reviewer #2: Thank you for the opportunity to review this paper

1. The authors referenced line 81 to justify CAM's indication for depression, citing source number 14. However, upon further examination of this source, it does not distinctly indicate the role of CAM in treating depression. Referencing the article by Ng, J.Y., Nazir, Z. & Nault, H. (2020) on "Complementary and alternative medicine recommendations for depression: a systematic review and assessment of clinical practice guidelines," it was observed that the quality of CAM recommendations was generally lower. Therefore, it is crucial to narrow down the scope of CAM that has proven to be beneficial for depression.

2. In reference to line 99 mentioning the use of NHANES data covering participants from 20 to 80 years old, a 2020 US report highlights varying prevalence rates of depression across age groups, with the highest among 18–24 years (21.5%) and the lowest among those ≥65 years (14.2%). However, the data analyzed in this study covers adults from 18 to 80 years old (line 166). Clarification is needed regarding the real age range within this dataset. Additionally, it's important to note that this dataset only covers information until 2018, which presents a limitation. The reason for not utilizing more current NHANES data should be addressed.

3. Concerning the definition of MDD, the use of PHQ-9 (with a sensitivity and specificity cutoff of 10 at more than 85%) is deemed acceptable as a screening tool rather than a standardized diagnostic tool. However, it should be acknowledged that individuals screened as MDD and remaining untreated might not necessarily require antidepressants, potentially not reflecting true MDD cases. Furthermore, the tool might not distinctly capture the level of depression, which should be highlighted as a limitation.

4. Further examination of the CAM definition reveals that it encompasses more than just dietary supplements, contradicting the initial understanding. Notably, at line 133, B6, vitamin D, and Zinc are also considered part of CAM. To maintain consistency throughout the manuscript, a single term, preferably "dietary supplement," should be used instead of alternating between CAM and dietary supplement. Please refer to reference at question 1 for the various definition of CAM

5. Certain variables within the NHANES dataset might act as confounders. For instance, the presence of chronic diseases like diabetes could influence the decision to take dietary supplements rather than using them specifically for treating depression. It's essential to explore whether the authors investigated other potential covariates or confounders that are available in the dataset.

6. The method for defining depression severity is unclear. Specifically, how did the authors delineate the severity using the raw total score of PHQ-9? What cutoffs were employed to categorize mild, moderate, and severe depression? Line 155 mentions analyzing depression severity using logistic regression. Clarification is needed on the cutoffs and grouping used for the analysis of dietary supplement and depression severity.

7. Due to the unclear definition of certain variables, it would be inappropriate to draw conclusions solely based on the results.

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

**********

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2024 May 8;19(5):e0302637. doi: 10.1371/journal.pone.0302637.r002

Author response to Decision Letter 0

22 Jan 2024

Response to reviewers

Reviewer #1: This manuscript utilized data from NHANES 2005-2018 to address the question whether adults with depression use nutritional supplements to a different degree than non-depressed adults. This is an interesting question as there is evidence that supplement use can be used successfully as adjunct therapy in depression. Using this large, representative sample is a strength of the study; however, researchers are limited to the data collected to direct their question.

My main concern with this work is how the outcome variables were defined (part 2.3). The investigators defined dietary supplement use by reporting individual nutrient use: B1, B2, B3, B6, B12, vitamins C, K, and D, folic acid, folate choline, calcium, P, Mg, Fe, Zn, Cu, Na, K, Se, and caffeine. Additionally, nutrients were grouped as water soluble vitamins, fat soluble vitamins, and B vitamins. CAM was defined as folate, Mg, B6, B9, D, Zn, and Se. Hence, there is tremendous overlap in the data presented, and the results, thus, are convoluted and repetitive. Also, it is unclear if multivitamin/mineral use is included in all of these categories, or if only individual supplementation is examined.

A more systematic approach (with no overlap) would produce more useful, meaningful results. Often multivitamin/mineral use is separated from single nutrient supplementation. In addition to a multivitamin/mineral supplement, the top 3-5 supplements could be investigated (with an ‘other’ group). For fat soluble vitamins, only D and K are examined – yet E is one of the leading individual nutrients supplemented in the US. The omega 3 fats are also at the top of the list of supplemented nutrients and are not examined in this report (although mentioned in the discussion).

Why is caffeine in this analysis? Furthermore, there is no data presented on caffeine as well as several other nutrients listed above. If variables are stated as outcomes in the methods section, they need to be reported in the results section.

Response: Thank you for your valuable feedback. We appreciate the insightful comments provided by Reviewer #1. In response to your concerns, we have made several revisions to enhance the clarity and relevance of our study.

1. Multivitamin/Mineral Use: We have incorporated 'multivitamin/mineral use' into our dietary supplement analysis, providing a more comprehensive perspective on supplement intake.

2. Inclusion of Missing Nutrients: Based on your suggestion, we have expanded our analysis to include Vitamin E and Omega-3 Fatty Acids.

3. Exclusion of Caffeine: We acknowledge the oversight and have removed caffeine from the analysis.

4. Refinement of CAM Definition: To address the issue of repetitiveness, we have redefined CAM based on the available NHANES data. We acknowledge the absence of other CAM agents including herbal agents data and, unfortunately, NHANES does not provide this information. The revised definition of CAM now includes: ‘’Selected CAM agents were: folate, magnesium, vitamin B6, B9, D, zinc, selenium, and omega-3 fatty acids. In this study, CAM was defined as a binary variable of “Yes” if any of the above CAM agents were taken or if an individual participated in >150 minutes of physical activity a week, and “No” otherwise.’’

In the text, CAM is defined (lines 79-86) as a range of medical and healthcare systems, practices, and products – including herbal agents, and exercise. Yet, in methods CAM is defined as folate, Mg, B6, B9 (which is folate – thus repetitive), D, Zn, and Se. There is no justification for this definition of CAM and it is not consistent with the accepted definition of CAM. See: https://www.cancer.gov/about-cancer/treatment/cam Also, the authors discuss the use of OTC – yet they did not look at these data in the NHANES data set. The authors need to be more cautious in their approach to the research question.

Since herbal agents, exercise, and omega 3 fats are in the NHANES data set, it is unclear why these variables were not assessed in this investigation.

Response: Thank you for bringing these concerns to our attention. We have redefined CAM based on the available NHANES data. We acknowledge the absence of other CAM agents including herbal agents data and, unfortunately, NHANES does not provide this information. The revised definition of CAM now includes: ‘’Selected CAM agents were: folate, magnesium, vitamin B6, B9, D, zinc, selenium, and omega-3 fatty acids. In this study, CAM was defined as a binary variable of “Yes” if any of the above CAM agents were taken or if an individual participated in >150 minutes of physical activity a week, and “No” otherwise.’’

Thank you for providing clarification on the dataset limitations related to OTC medications. We want to acknowledge your comment and clarify that the NHANES dataset specifically includes information on prescribed medications only, and unfortunately, OTC data is not available.

Other concerns:

• The introduction is sourced mainly from reviews and websites. There is only a cursory overview of the topic with little primary research cited. Depending on second-hand sources to such a large degree lowers the confidence of the reader for accepting the rational provided to justify the investigation. Include primary data in the introduction to support statements.

Response: Thank you for your comment. We have incorporated the original studies as references in the introduction section.

• Line 71: what is meant by ‘regular’ diet?

Response: Thank you for your comment. In the context of our statement, a "regular" diet refers to a balanced and nutritionally adequate diet that provides essential nutrients in appropriate proportions. We revised that section of the manuscript.

‘’Despite the fact that dietary supplements are not recommended for individuals who are healthy and consume a well-balanced and nutritionally adequate diet, the industry generates an annual revenue of 1.2 billion USD.’’

• Section 2.1: provide citations for the characteristics of NHANES data.

Response: Thank you for your comment. We added a citation for the characteristics of NHANES data.

‘’​​Zipf G, Chiappa M, Porter KS, Ostchega Y, Lewis BG, Dostal J. National Health and Nutrition Examination Survey: Plan and Operations, 1999–2010. Vital Health Stat. 2013;1(56):37.’’

• Line 105: ‘need to sign’ to replace ‘have to sign’

Response: We appreciate your keen observation. In response to your comment, we have made the suggested change, replacing 'have to sign' with 'need to sign'.

• Line 123: what is “249” – there is no definition or citation.

Response: Thank you for your comment. 249 is how NHANES coded antidepressants in the Prescription Medications - Drug Information Questionnaire questionnaire. We added ‘’https://wwwn.cdc.gov/Nchs/Nhanes/1999-2000/RXQ_DRUG.htm’’ to the methods section for further clarification.

• Throughout the text, do not capitalize nutrients – these are not proper nouns.

Response: Thank you for your comment. In response to your feedback, we have made the necessary corrections in the revised manuscript to ensure that nutrients are not capitalized

• Line 145: provide a citation

Response: Thank you for your comment. We provide citations for line 145 in the revised manuscript.

• All tables should have a legend to explain the presentation of the data and the p value.

Response: Thank you for your comment. We added legends to all tables to further explain the data.

• Table 1: For ‘sex’ add a line for male data (similar to how there is a line for each component of ‘race’).

Respons: Thank you for your comment. In response to your comment, we have added a dedicated line in Table 1, providing a more comprehensive presentation of both male and female participant numbers.

• Table 1: the final 6 lines need to be reconsidered as discussed above. (similar comment for tables 4-6)

Response: Thank you for your comment. We redefined these variables in the revised manuscript.

• Line 213: replace ‘levels’ with ‘usage’

Response: Thank you for your comment. In response to your comment, we have made the suggested change, replacing 'levels' with '‘usage’'.

• Discussion: the first paragraph can be deleted as it is a repeat of the results.

Response: Thank you for your comment. We deleted the first paragraph of discussion in the revised manuscript.

• Line 316: need to add ‘compared to adults not reporting depression’. The comparison group needs to be identified.

Response: Thank you for your comment. In response to your comment, we have revised the sentence on line 316 to explicitly state, ‘’In conclusion, our results indicated significantly lower odds of dietary supplement use in individuals with depressive symptoms compared to adults not reporting depressive symptoms.’’

\fReviewer #2: Thank you for the opportunity to review this paper

1. The authors referenced line 81 to justify CAM's indication for depression, citing source number 14. However, upon further examination of this source, it does not distinctly indicate the role of CAM in treating depression. Referencing the article by Ng, J.Y., Nazir, Z. & Nault, H. (2020) on "Complementary and alternative medicine recommendations for depression: a systematic review and assessment of clinical practice guidelines," it was observed that the quality of CAM recommendations was generally lower. Therefore, it is crucial to narrow down the scope of CAM that has proven to be beneficial for depression.

Response: We appropriate the reviewer for their insightful comment. We revised that section based on your feedback: ‘’Despite the advantages associated with CAM, such as a lower incidence of adverse events, reported efficacy, a comprehensive perspective on individual problems, and dissatisfaction with traditional care, the quality of CAM recommendations for depression has been noted to be generally lower.’’

2. In reference to line 99 mentioning the use of NHANES data covering participants from 20 to 80 years old, a 2020 US report highlights varying prevalence rates of depression across age groups, with the highest among 18–24 years (21.5%) and the lowest among those ≥65 years (14.2%). However, the data analyzed in this study covers adults from 18 to 80 years old (line 166). Clarification is needed regarding the real age range within this dataset. Additionally, it's important to note that this dataset only covers information until 2018, which presents a limitation. The reason for not utilizing more current NHANES data should be addressed.

Response: Thank you for your insightful comment. We have addressed the concern about the age range in the revised manuscript, providing clarification on the NHANES data source. The corrected statement now reads:

‘’NHANES is a survey based on nationally representative data from civilian, non-institutionalized populations aged 18-80 years across 50 states of the United States, utilizing a complex, multistage, probability sampling design.’’

Furthermore, we acknowledge the limitation associated with the dataset's timeframe, as it covers information up to 2018. In the revised manuscript, we have explicitly mentioned the reason for not utilizing more recent NHANES data. Due to the unprecedented impact of the COVID-19 pandemic on mental health and depression, we made the decision to focus on data up to 2018 to maintain consistency and reliability in our analysis.

‘’The strength of our study is that NHANES is a survey that encompasses a representative sample of the noninstitutionalized population in the US, which adds to its credibility, it is important to note a limitation. The data utilized in our analysis only extends up to the year 2018 due to the unique circumstances presented by the COVID-19 pandemic and its impact on mental health. This time frame limitation may impact the generalizability of our findings.’’

3. Concerning the definition of MDD, the use of PHQ-9 (with a sensitivity and specificity cutoff of 10 at more than 85%) is deemed acceptable as a screening tool rather than a standardized diagnostic tool. However, it should be acknowledged that individuals screened as MDD and remaining untreated might not necessarily require antidepressants, potentially not reflecting true MDD cases. Furthermore, the tool might not distinctly capture the level of depression, which should be highlighted as a limitation.

Response: Thank you for your insightful comment. We appreciate the importance of clarifying the nature of the PHQ-9 as a screening tool. To accurately reflect this distinction, we have modified instances of 'depression' to 'depressive symptoms' throughout the manuscript, including the title. Additionally, we have incorporated this clarification into the limitation section of the manuscript to transparently communicate the nature of our assessment tool and its implications for the study's findings:

‘’In addition, regarding the definition of depressive symptoms, our study employed the PHQ-9 as a screening tool, utilizing a sensitivity and specificity cutoff of 10 at more than 85%. While deemed acceptable for screening, it's crucial to acknowledge that the PHQ-9 serves as a screening tool rather than a standardized diagnostic tool. Consequently, individuals identified as MDD through screening, who remain untreated, may not necessarily require antidepressants, potentially not reflecting true MDD cases. Furthermore, the tool might not distinctly capture the level of depressive symptoms, representing a limitation in our study.’’

4. Further examination of the CAM definition reveals that it encompasses more than just dietary supplements, contradicting the initial understanding. Notably, at line 133, B6, vitamin D, and Zinc are also considered part of CAM. To maintain consistency throughout the manuscript, a single term, preferably "dietary supplement," should be used instead of alternating between CAM and dietary supplement. Please refer to reference at question 1 for the various definition of CAM.

Response: Thank you for your comment. We have redefined CAM based on the available NHANES data. We acknowledge the absence of other CAM agents including herbal agents data and, unfortunately, NHANES does not provide this information. The revised definition of CAM now includes: ‘’Selected CAM agents were: folate, magnesium, vitamin B6, B9, D, zinc, selenium, and omega-3 fatty acids. In this study, CAM was defined as a binary variable of “Yes” if any of the above CAM agents were taken or if an individual participated in >150 minutes of physical activity a week, and “No” otherwise.’’

5. Certain variables within the NHANES dataset might act as confounders. For instance, the presence of chronic diseases like diabetes could influence the decision to take dietary supplements rather than using them specifically for treating depression. It's essential to explore whether the authors investigated other potential covariates or confounders that are available in the dataset.

Response: Thank you for your comment. In response, we have expanded our analysis by incorporating additional covariates (chronic diseases). The updated set of covariates now includes age, gender, diabetes, hypertension, chronic kidney disease, congestive heart failure, and liver disease.

6. The method for defining depression severity is unclear. Specifically, how did the authors delineate the severity using the raw total score of PHQ-9? What cutoffs were employed to categorize mild, moderate, and severe depression? Line 155 mentions analyzing depression severity using logistic regression. Clarification is needed on the cutoffs and grouping used for the analysis of dietary supplement and depression severity.

Response: Thank you for your comment. We did not categorize depressive symptoms severity into mild/moderate/severe due to small sample sizes. We added ‘’Depressive symptoms severity was defined as just the raw PHQ-9 score, where a higher score indicates more depressive symptoms.’’ to further clarity how we defined depressive symptoms severity.

7. Due to the unclear definition of certain variables, it would be inappropriate to draw conclusions solely based on the results.

Response: Thank you for your insightful comment. In response, we have taken steps to enhance the clarity of our study by redefining certai

Attachment

Submitted filename: Response letter.docx

pone.0302637.s005.docx (294.5KB, docx)

Decision Letter 1

Jenny Wilkinson

15 Feb 2024

PONE-D-23-21189R1Adults with Depressive Symptoms Have Lower Odds of Dietary Supplement UsePLOS ONE

Dear Dr. Bhat,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. The comments of the reviewers are attached for your information, these comments are seeking clarity on some aspects of your study and provided suggestions from strengthening the work.

Please submit your revised manuscript by Mar 31 2024 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Jenny Wilkinson, PhD

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Additional Editor Comments:

Thank you for your responses and revisions to the manuscript. Once reviewer has provided some further comments in relation to the revisions and you are invited to provide a response to these comments.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Partly

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: No

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: (No Response)

Reviewer #2: Thank you for the opportunity to review this revision. I have some concern regarding methodology, result and discussion

1. It is still essential to use the recent data. If the authors are concern about the COVID, it can be adjusted with statistical method treating COVID as confounding or making a subgroup analysis of this nested data for more relevant and novel result

2. Table 1 one elaborates on the characteristic of the participants. It is obvious that those people with chronic disease tend to have depressive symptom, However it was not briefly discussed in the result and discussion section. Just add some statement that using CAM and dietary supplement may also have interaction with the chronic disease medication

3. It It will be more meaningful to classify the severity of disease rather than using the raw score of the PHQ9 so the aOR would be more meaningful to translate. As a reader will prefer to see the aOR of severity level rather than aOR for each 1 unit of PHQ9. Table 2,4 and 5 on depressive severity have aOR of around 0.9 which is quite smaller. To accommodate this, logistic regression is preferred. We might see more meaningful association of particular CAM and supplement such as vitamin D

4. Also the authors talked about depressive symptoms which is treated as binary using cutoff of 10 (<10 is no and >10 is yes). Why didn't the authors used logistic regression for table 4 and 6 and just present the odd ratio of table 5 and 7 to make the manuscript more concise without abundant coefficients tables?

5. In characteristic table 1, age was not different between group, but race was different. Why the adjusted model did not use race but put age instead?

6. Is it still fall into study objective if the authors compare the treated individual vs non depressive individual, which is missing in the manuscript?

7. Again, this manuscript reveals that adult with depressive symptoms have lower use of cam and supplement, although in the introduction, some CAMs are not clinically recommended. Looking at table 6 and 7 the intake of fat soluble vitamin which also cover vitamin D was significantly higher in treated depressive individual Which is good. With these conflicting results, what would be the final conclusion and recommendations?

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

**********

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2024 May 8;19(5):e0302637. doi: 10.1371/journal.pone.0302637.r004

Author response to Decision Letter 1

3 Apr 2024

Response to reviewers

1. It is still essential to use the recent data. If the authors are concern about the COVID, it can be adjusted with statistical method treating COVID as confounding or making a subgroup analysis of this nested data for more relevant and novel result.

Response: Thank you for your valuable feedback. We appreciate your suggestion regarding adjusting for COVID effects using statistical methods. However, the data is not avaible (please see: 2019-2020:not representative- https://wwwn.cdc.gov/nchs/nhanes/continuousnhanes/default.aspx?BeginYear=201; 2017-March 2020 Pre-pandemic: Not completed- https://wwwn.cdc.gov/nchs/nhanes/continuousnhanes/default.aspx?Cycle=2017-2020;" https://wwwn.cdc.gov/nchs/nhanes/continuousnhanes/default.aspx?Cycle=2017-2020; 2021-2023:Not available- https://wwwn.cdc.gov/nchs/nhanes/continuousnhanes/default.aspx?Cycle=2017-2020). Furthermore, we believe that adjusting for all potential COVID effects might not be feasible due to several reasons. Firstly, the NHANES dataset does not include specific questions regarding the history of COVID-19 infection or treatments received. Secondly, COVID-19 has had multifaceted impacts on health outcomes, including indirect effects on lifestyle, mental health, and healthcare access, which are not easily quantifiable within the NHANES dataset. Additionally, using data after the COVID-19 period might introduce further challenges. Post-COVID data may be confounded by temporal changes in lifestyle and health-seeking behavior, limited availability of such data depending on the timing of the study, continued uncertainty and variability of pandemic effects, potential shifts in dietary patterns during the pandemic, the profound impact of the pandemic on mental health, and ethical considerations surrounding research conducted immediately after a major global health crisis.

2. Table 1 one elaborates on the characteristic of the participants. It is obvious that those people with chronic disease tend to have depressive symptom, However it was not briefly discussed in the result and discussion section. Just add some statement that using CAM and dietary supplement may also have interaction with the chronic disease medication.

Response: Thank you for your comment. We added ‘’Additionally, It is noteworthy to consider that participants with chronic diseases in this study exhibited higher levels of depressive symptoms. The use of CAM and dietary supplements among these individuals may introduce interactions with their chronic disease medications, which could contribute to the observed depressive symptomatology. Future research should delve deeper into these potential interactions to better understand their impact on mental health outcomes.’’ to the discussion section.

3. It It will be more meaningful to classify the severity of disease rather than using the raw score of the PHQ9 so the aOR would be more meaningful to translate. As a reader will prefer to see the aOR of severity level rather than aOR for each 1 unit of PHQ9. Table 2,4 and 5 on depressive severity have aOR of around 0.9 which is quite smaller. To accommodate this, logistic regression is preferred. We might see more meaningful association of particular CAM and supplement such as vitamin D

Response: Thank you for your comment. We first categorized depressive symptoms into 'Yes (at risk)' and 'No,' in hopes of simplifying the understanding of the risk of depressive symptoms and CAM intake. We agree that additional insight can be drawn with severity of disease though it was not possible to run such models reliably due to the small number of individuals in some of our categories. Instead we had included the PHQ9 as a continuous score to allow us to observe trends without losing statistical power that may have happened when dichotomizing our depressive symptom scores.

4. Also the authors talked about depressive symptoms which is treated as binary using cutoff of 10 (<10 is no and >10 is yes). Why didn't the authors used logistic regression for table 4 and 6 and just present the odd ratio of table 5 and 7 to make the manuscript more concise without abundant coefficients tables?

Response: Thank you for your comment. We would like to clarify that we did not use logistic regression for Table 4 and 6 as the outcome was specific vitamin intake (ex. mg, mcg) which were treated as continuous variables. Linear regressions were used for each vitamin intake where depressive symptoms were included as one of the covariates. Based on your comment, we moved tables 4-7 to supplementary materials to avoid having abundant tables.

5. In characteristic table 1, age was not different between group, but race was different. Why the adjusted model did not use race but put age instead?

Response: Thank you for your comment. We added ethnicity to covariates and re-analyzed the data.

6. Is it still fall into study objective if the authors compare the treated individual vs non depressive individual, which is missing in the manuscript?

Response: Thank you for your comment. We compare the treated individual vs non depressive individual analysis results to the revised manuscript.

‘’No statistically significant association was seen between those with treated depressive symptoms versus no depressive symptoms in terms of dietary supplement usage (Table 3).’’

‘’In those with treated depressive symptoms compared to no depressive symptoms, CAM use was lower in comparison (aOR = 0.763, 95% CI = 0.598,0.973, p = 0.030) (Table 3).’’

We also added ‘’Our study's findings suggested a notable difference in CAM usage between individuals with treated depressive symptoms and those without. This indicated that individuals with treated depressive symptoms may be less inclined to turn to CAM therapies compared to individuals without depressive symptoms. One possibility is that individuals receiving antidepressant treatment for depressive symptoms, may feel that these conventional methods are sufficient for managing their symptoms. They might prioritize the guidance of healthcare professionals and evidence-based antidepressants over CAM approaches. Additionally, the stigma often associated with mental health conditions such as depressive symptoms could play a role. Some individuals might be more comfortable discussing and seeking treatment for their depressive symptoms within the context of traditional healthcare settings, rather than exploring CAM options. Further research should explore the reason for this phenomenon.’’ to the discussion section of the revised manuscript.

7. Again, this manuscript reveals that adult with depressive symptoms have lower use of cam and supplement, although in the introduction, some CAMs are not clinically recommended. Looking at table 6 and 7 the intake of fat soluble vitamin which also cover vitamin D was significantly higher in treated depressive individual Which is good. With these conflicting results, what would be the final conclusion and recommendations?

Response: Thank you for your comment. Based on your comment we added ‘’In conclusion, our results indicated significantly lower odds of dietary supplement use in individuals with depressive symptoms compared to adults not reporting depressive symptoms. Notably, individuals receiving treatment for depression demonstrated increased usage of dietary supplements, particularly fat-soluble vitamins such as vitamin D compared with those with depressive symptoms who were not taking antidepressants. Conversely, those with untreated depressive symptoms had lower odds of CAM use compared with participants without depressive symptoms. These findings suggest that treatment may influence supplement intake, especially for essential vitamins. Further replication and validation is needed along with definitive studies to further evaluate the underlying reasons for this phenomenon among individuals with depression. Healthcare providers should engage in discussions regarding the potential benefits of dietary supplements and CAM with patients experiencing depressive symptoms, particularly those not undergoing treatment. Clinicians should consider the impact of treatment on vitamin intake, specifically fat-soluble vitamins, and potentially monitor or recommend appropriate supplementation for individuals with depressive symptoms to ensure adequate nutritional support.’’ to the revised manuscript.

Attachment

Submitted filename: Response to reviewers.docx

pone.0302637.s006.docx (10KB, docx)

Decision Letter 2

Jenny Wilkinson

10 Apr 2024

Adults with Depressive Symptoms Have Lower Odds of Dietary Supplement Use

PONE-D-23-21189R2

Dear Dr. Bhat,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice will be generated when your article is formally accepted. Please note, if your institution has a publishing partnership with PLOS and your article meets the relevant criteria, all or part of your publication costs will be covered. Please make sure your user information is up-to-date by logging into Editorial Manager at Editorial Manager® and clicking the ‘Update My Information' link at the top of the page. If you have any questions relating to publication charges, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Jenny Wilkinson, PhD

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Thank you for your responses to reviewer's comments. These and the manuscript revisions have satisfactorily addressed the reviewer concerns.

Reviewers' comments:

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Table. Adjusted coefficient estimates (aCoef. Estm) for associations between individual vitamin use and depressive symptoms risk or depressive symptoms severity.

    (DOCX)

    pone.0302637.s001.docx (9.4KB, docx)
    S2 Table. Adjusted ORs for associations between various vitamin classes and depressive symptoms risk or depressive symptoms severity.

    (DOCX)

    pone.0302637.s002.docx (8.5KB, docx)
    S3 Table. Adjusted Coef. Estm for associations between individual vitamin use and depressive symptoms treatments.

    (DOCX)

    pone.0302637.s003.docx (9.5KB, docx)
    S4 Table. Adjusted ORs for associations between various vitamin classes and alternative medicine use and depressive symptoms treatments.

    (DOCX)

    pone.0302637.s004.docx (8.6KB, docx)
    Attachment

    Submitted filename: Response letter.docx

    pone.0302637.s005.docx (294.5KB, docx)
    Attachment

    Submitted filename: Response to reviewers.docx

    pone.0302637.s006.docx (10KB, docx)

    Data Availability Statement

    The data underlying the results presented in the study are available from https://wwwn.cdc.gov/nchs/nhanes/Default.aspx. We used data from 2005-2006 through 2017-2018 survey cycle datasets.

    Articles from PLOS ONE are provided here courtesy of PLOS

    RESOURCES