Next Article in Journal
Chebulic Acid Prevents Hypoxia Insult via Nrf2/ARE Pathway in Ischemic Stroke
Previous Article in Journal
Examining the Composition of the Oral Microbiota as a Tool to Identify Responders to Dietary Changes
Previous Article in Special Issue
Association between the Preoperative C-Reactive Protein-to-Albumin Ratio and the Risk for Postoperative Pancreatic Fistula following Distal Pancreatectomy for Pancreatic Cancer
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Nutritional Impact and Eating Pattern Changes in Schizophrenic Spectrum Disorders after Health Education Program on Symbiotic Dietary Modulation Offered by Specialised Psychiatric Nursing–Two-Arm Randomised Clinical Trial

1
Córdoba-South Community Mental Health Unit, Mental Health Clinical Management Unit, Reina Sofia University Hospital, C/Huelva s/n, 14013 Cordoba, Spain
2
Department of Nursing, Pharmacology and Physiotherapy, University of Cordoba, Avd Menéndez Pidal s/n, 14004 Cordoba, Spain
3
Lifestyles, Innovation and Health (GA-16), Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Avd Menéndez Pidal s/n, 14004 Cordoba, Spain
4
Department of Nursing and Nutrition, Biomedicine Sciences and Health Faculty, European University of Madrid, C/Tajo s/n, Villaviciosa de Odon, 28670 Madrid, Spain
*
Author to whom correspondence should be addressed.
Nutrients 2022, 14(24), 5388; https://doi.org/10.3390/nu14245388
Submission received: 18 November 2022 / Revised: 14 December 2022 / Accepted: 16 December 2022 / Published: 19 December 2022
(This article belongs to the Special Issue Clinical Nutrition for Prevention and Treatment of Chronic Diseases)

Abstract

:
Background: The traditional therapeutic approach has perceived the role of nutrition as a minor intervention in psychiatry. The microbiota–gut–brain axis theory evidences the influence of dietary and nutritional patterns on mental health. Aims: To evidence the impact of dietary advice on increasing symbiotic intake on nutritional status and dietary habits in individuals with schizophrenia spectrum disorders. Methods: Randomised clinical trial (two-arm, double-blind, balanced-block, six-month intervention) in 50 individuals diagnosed with schizophrenia spectrum disorders. The control group received conventional dietary advice on an individual basis. A personal nutritional education programme was established in the intervention group (IG) to increase prebiotic and probiotic intake through dietary advice (dairy and fermented foods, green leafy vegetables, high-fibre fruit, whole grains, etc.). Data on nutritional status and dietary habits were collected (baseline and six months). The degree of dietary adherence to the recommended patterns was recorded weekly. Anthropometric parameters were also analysed monthly. Results: Finally, 44 subjects completed the follow-up. All participants exceeded the dietary reference intakes. The overall and intra-group analysis showed a statistically significant (p < 0.05) reduction in macro and micronutrient intakes with a closer approximation to the recommended dietary intakes, except for polyunsaturated fatty acids, oligosaccharides, polysaccharides and dietary fibre. After six months of intervention, statistical differences (p < 0.001) were found in all variables of the anthropometric profile in the IG, as well as an increase in the consumption of foods with a high symbiotic content (at baseline and six months). Likewise, a reduction in eggs, meat, fish, sugars and ultra-processed foods was evident, leading to significant intra-group differences (p < 0.05). Conclusions: Implementing conventional nutritional education strategies and specific nutritional advice with a symbiotic effect improves the dietary-nutritional profile in patients with schizophrenia spectrum disorders. Furthermore, it highlights the nutritional impact on mental health, stating itself as adjuvant therapy for physical health and lifestyle improvement.

1. Introduction

Historical evolution has evidenced the role of nutritional psychiatry as a minor intervention in the traditional therapeutic conception of Mental Health [1,2]. However, the advances in the last decade, mainly associated with the development of holobiont theory and metagenomics [2,3], as well as the detection of new dietary patterns of poor nutritional quality in different Western societies [1,3,4], have highlighted the influence exerted by the dietary and nutritional pattern on the functioning of the Central Nervous System (CNS) [5]. Furthermore, the possible mechanisms or aetiological pathways of psychiatric disorders have been established [2,3,5], especially in severe and long-term mental disorders (LTMD), such as schizophrenia [5]. Consequently, the “Microbiota–Gut–Brain Axis” concept has emerged. This term refers to the bidirectional communication pathway between the CNS, the gastrointestinal tract, and the microbiota (IM) [4,6]. Its determinant role in the organism’s normal functioning has been defined: development and maturation of the CNS, nutrition and metabolism, immune response or systemic inflammation [7,8,9,10,11]. Thus, according to low-grade systemic inflammation theory, when the state of dysbiosis appears, a cascade of pro-inflammatory agents can modify both the integrity and the permeability of enterocytes [3,9,10]. This response triggers the release of pro-inflammatory cytokines (tumour necrosis factor-alpha or interleukins type 6 or 1ß) [2,8,10], leading to synergies between inflammation, increased oxidative stress and energy imbalance [8]. These reactions result in homeostatic disturbances and neuropsychiatric dysfunction [9,11,12].
Dysregulation of the microbiota–gut–brain axis is determined by the acquisition of unhealthy lifestyles [1,5] based on poor nutritional quality dietary patterns and inadequate physical activity performance, which are especially common in LTMD [4,13,14,15]. Likewise, the current adoption of social distancing and home quarantine strategies established by the different governments within the global SARS-CoV-2 pandemic [16,17] promotes the acquisition of unhealthy habits in the vulnerable population, worsening previous pathogenic states [14].

Background

Concerning mental problems, the evidence shows a high rate of disability and morbidity and mortality (up to 20% higher) [16,17,18,19], being especially significant in LTMD [3,5,15,18,19]. Furthermore, these figures are closely linked to the development of Metabolic Syndrome (MetS) [2,4,15,16,17,18,19], considered a determining factor in the patient’s physical health and tripling the incidence of cardio-metabolic diseases [17,18,19,20]. Finally, the main etiopathogenic determinants of MetS and the level of neuro-functional disability in the psychiatric population are linked to the characteristics of the disease, the exclusive psychopharmacological approach, and resistance to optimal care in terms of physical health and lifestyles [17,18,19,21].
Despite the magnitude and severity of the problem, interventions aimed at modifying nutritional patterns and eating behaviours play a minority role in the routine clinical practice of psychiatric healthcare professionals [4,15,16,21,22]. The evidence establishes high levels of malnutrition and the acquisition of unhealthy dietary habits in LTMD (far from the dietary reference standard) [4,15,22], based on the consumption of ultra-processed foods with high energy and glycaemic index and low consumption of fibre, fruit and vegetables [14,17,22,23,24]. Thus, the persistence of dietary patterns of low nutritional quality in the target population leads to a higher propensity for dysbiosis and, consequently, to a state of low-grade systemic inflammation. This state determines a higher risk of cardio-metabolic and psychopathological dysfunction that conditions the level of neuronal plasticity and cognitive performance [1,5,12].
In response to the evidence described above, there is currently a growing effort to develop and implement dietary interventions focused on modulating the gut microbiota in psychotic disorders through the use of “psychobiotics” [5,11,12,13] in the form of nutraceuticals. This term refers to a set of symbiotic substances (prebiotics and probiotics) whose administration leads to health benefits in psychiatric patients [5,10,11,25]. Probiotics include micro-organisms from the intestinal biota, which benefit the host when administered in adequate amounts (notably the genera Lactobacillus and Bifidobacterium, among others) [8,10,25,26]. On the other hand, prebiotics is non-digestible dietary fibre (fructo- and oligosaccharides, inulin or pectins) [2,5], which promote optimal growth and the development of probiotics in the gastrointestinal tract, reducing pathogenic microbiota [8,9,26].
In short, the future of the new models of care in Mental Health is determined by the approach to nutritional factors and the detection of unhealthy dietary habits [1,6,10,23,24]. This fact is conditioned by the appropriate use of nutritional counselling in the multifactorial approach to the psychiatric patient, representing the cornerstone in achieving optimal and cost-effective health outcomes for the health system [27,28].
For all the above, this study aimed to evaluate the impact of nutritional counselling to follow a high-symbiotic diet in patients diagnosed with a schizophrenia spectrum disorder and in the context of confinement and social restriction due to the SARS-CoV-2 pandemic.

2. Materials and Methods

2.1. Study Design

A 6-month, double-blind, two-arm, parallel-arm, balanced-block, randomised clinical trial was conducted on patients diagnosed with schizophrenia spectrum disorders (without distinction by type). The study design is shown in Figure 1.

2.2. Population Eligibility Criteria

The sample was selected from the referral Psychiatry Service from June 2020 to February 2021. Inclusion criteria were: (1) patients diagnosed on the spectrum of schizophrenia (without distinction by type), according to criteria DSM-5 and/or ICD-11; (2) age between 18–65 years; (3) absence of gastrointestinal comorbidity that contraindicates the use of prebiotics and/or probiotics (intolerance, explosive diarrhoea, acute abdominal pain, etc.); (4) to show clinical stability for six months before the beginning of the study (absence of psychiatric hospitalisation, maintenance of the level of functionality, and lack of social and occupational absenteeism); (5) to manifest agreement to participate in the study and to sign of informed consent. Reasons for exclusion of participants were: (1) suffering from a somatic or neurocognitive condition that prevented participation and collaboration in compliance with the protocol; (2) standardised dietary planning not modulated by the study population (catering, institutional or collective feeding, etc.); (3) refusal to participate in the study.

2.3. Sample Size

The researchers estimated a 22 individuals sample size to assess the efficacy of the intervention (11 for the control group (CG) and 11 for the intervention group (IG), with a power of 80% and safety of 95%, expecting a risk/prevalence difference of 63% post-intervention [29]. Finally, the sample was increased by more than 50% to minimise the effect of possible losses, obtaining a final size of 50 individuals (25 for the CG and 25 for the IG). Randomisation was performed according to the anthropometric analysis results, allowing the prevalence of MetS in both groups to be balanced.

2.4. Intervention

The CG consisted of those participants who received conventional dietary advice [30] on an individual basis. Similarly, the IG intervention was developed individually through intensive nutritional intervention [31] (designed and supervised by registered dietitians) from specialised nurses on psychiatric care and based on counselling for the increasing consumption of food with high prebiotic and probiotic content. In both allocation groups, visually supportive educational resources were used during the consultations [32]. The study was initiated with focus groups that improved the set dietary-nutritional intervention, ensuring its correct adaptation according to the study population. The research project was also presented to the referred psychiatry service staff. Subsequently, a 6-month dietary-nutritional education programme was implemented, associated with two months of educational reinforcement every 15 days for the IG and monthly for the CG. During the intervention phase, the anthropometric status (weight, body mass index—BMI, waist-to-height ratio—WHtR-, and waist circumference) was determined monthly, as well as the dietary-nutritional pattern using a validated Food Frequency Questionnaire (FFQ) for the Spanish population [33], focusing on those food groups and main dishes with the most significant symbiotic impact, at baseline and six months after the intervention. Finally, to assess the degree of adherence to the established dietary plan, a weekly record was kept of the main dishes and foods consumed with a prebiotic and probiotic effect (fermented foods, whole grains, green leafy vegetables, fruit, etc.).

2.5. Data Analysis

The data were described using means and standard deviation for quantitative variables and frequencies and percentages for qualitative variables. The Kolmogorov-Smirnov test was used to assess normality in quantitative variables. The Student’s t-test for paired data, Mann-Whitney U test and repeated-means ANOVA were used to analyse the relationship between quantitative variables. Similarly, the association between qualitative variables was determined by Chi-square (Fisher or Yates corrections) and McNemar’s test. Non-parametric versions of the tests described above were performed if homoscedasticity criteria were not met. A probability of alpha error of less than 5% (p < 0.05) and a confidence interval of 95% were accepted during the analysis. Finally, SPSS (version 25.0) and EPIDAT (version 4.2) software were used for computing these tests. Similarly, the Nutriplato 2.0 (version 4.6) software tool [34] was used in the FFQ analysis.

3. Results

During recruitment, the eligible population was 50 subjects. Six participants were excluded during the intervention phase, resulting in 21 subjects in the CG and 23 in the IG. The flow chart of the participants is shown in Figure 2.
Thirty-two men (72.7%) and 12 women (27.3%) participated, with 49.2 ± 11.9 years on average. The primary psychiatric diagnosis was schizophrenia [37 (84.1%)], with a mean duration of illness of 21.6 ± 12.4 years. Drug use was reported by 29 smokers (65.9%), ten subjects who used cannabis (22.7%) and 6 participants who reported drinking alcohol (13.6%) regularly. Regarding the number of subjects with associated cardio-metabolic risk factors, 17 subjects showed dyslipidaemia (38.6%), ten high blood pressure (22.7%), and seven suffered from diabetes mellitus (15.9%). Moreover, 27 participants (61.4%) knew how to cook and were responsible for it.
Finally, the baseline analysis of the dependent variables showed significant differences in sugars and ultra-processed products and the mean calculation (weekly, monthly and quarterly) of the main foods and dishes consumed with high symbiotic value. Table 1 and Table 2 show the baseline characteristics of the independent and dependent variables, respectively, showing homogeneity between the two allocation groups.
Table 3 shows the changes in outcome variables at baseline and six months of intervention in CG and IG, respectively. The overall analysis showed that almost all participants significantly exceeded the Recommended Daily Allowances (% RDA), except for the vitamin D variable, were lower than recommended throughout the intervention phase. Likewise, the overall analysis showed a significant improvement (p < 0.05) in all macronutrient and micronutrient profile variables, except for polyunsaturated fatty acids, oligosaccharides, polysaccharides, dietary fibre, copper, manganese, biotin, ascorbic acid and vitamin D.
Similarly, the overall analysis of weekly, monthly and quarterly records of consumption of foods with high symbiotic content showed statistically significant differences, with a subsequent decrease and increase in consumption coinciding with the implementation of social distancing and confinement measures in the SARS-CoV-2 era.
Regarding the intra-group analysis of macronutrients between the CG and IG, we observed concordance with those results obtained from the global analysis, obtaining statistically significant differences in all variables, except for polyunsaturated fatty acids oligosaccharides, polysaccharides and dietary fibre. However, the intra-group analysis of micronutrients showed statistically significant differences in the IG for phosphorus, sodium, iron, zinc, thiamin, vitamin B12 and vitamin E.
Similarly, in terms of weekly consumption by food group in the IG, there was a reduction in protein consumption of eggs, meat and fish, and sugars and ultra-processed foods, compared to the increase obtained in the CG. This fact is related to the non-statistical significance at the global level. In addition, there was an increase in the consumption of dairy products, legumes and cereals between the two allocation groups and a decrease in the intake of fruit, vegetables and greens. However, these variations were not significant. Finally, anthropometric variables improved significantly (p < 0.001) in the IG, while waist circumference increased in the CG. These modifications did not lead to significant differences in the number of antipsychotics and dosage prescribed.
Regarding the global inter-group analysis at baseline and at six months of intervention, except for the improvement observed in the consumption of sugars and ultra-processed food (p < 0.05) in IG, no statistically significant results were shown for the rest of the dependent variables.

4. Discussion

This study focuses on the nutritional impact of a high symbiotic dietary modulation throughout health education intervention by specialised psychiatric nurses in patients suffering from schizophrenia spectrum disorder, reducing macro and micronutrient intake towards a closer approximation to the % RDA between allocation groups. However, the findings confirm the results described by Gill R et al. (2021). They found that implementing an intensified educational approach does not yield significant benefits compared to a conventional dietary-nutritional intervention in schizophrenic disorders [24].
On the other hand, from our perspective, we consider that the statistically significant intra-group differences are a reason for not reaching inter-group statistical results, a condition supported by the significance reached for the overall analysis of the group. However, the results obtained reflect a clinically significant trend toward healthier nutritional patterns in the IG, compared to the increased consumption of ultra-processed, higher energy and higher glycaemic index foods in the CG [4,15,16,35,36], a highly prevalent condition in the target population (p < 0.05) [20,32]. The scientific evidence supports and clarifies the results obtained, with an increase in dietary habits of low nutritional quality in psychotic disorders (up to 60%) [21,32,36]. These patterns exceed % RDA [35,36] and are characterised by a higher intake of refined carbohydrates, saturated fats, sodium and phosphorus, as well as a lower intake of vitamin D, calcium, potassium, iron, polyunsaturated fatty acids, fruit and vegetables and, therefore, lower intake of dietary fibre (among others) [1,4,15,16,22,35,36,37,38,39,40,41,42]. In this regard, according to Gill R et al. (2021), Stefańska E et al. (2019) and Kowalski K et al. (2022), low adherence to Mediterranean dietary patterns leads to a higher propensity for nutritional deficiencies [24,36,41] and, consequently, a higher risk of exacerbation of underlying cardio-metabolic and neuropsychiatric disorders [39,40,41].
Undoubtedly, the improvement of the anthropometric profile (in all variables) and, therefore, the significant decrease in the risk of MetS in the GI (p < 0.05) after intensive dietary advice with high prebiotic and probiotic content is noteworthy. Similar findings were obtained by Sugawara et al. (2018) and Caemmerer et al. (2012) [29,42]. Again, the results presented in the present study support the meta-analysis developed by Teasdale et al. (2017), showing that non-pharmacological interventions focused on improving the dietary-nutritional pattern are established as coadjuvant therapies for metabolic abnormalities [43], relevant to improving the lifestyles of the target population [1,4,15,23,35]. Concerning the level of compliance and results obtained in both allocation groups, it is essential to highlight the contextual framework of the global SARS-CoV-2 pandemic in which this clinical trial was conducted. Solé et al. (2021) indicated that most preliminary studies during the current pandemic have focused on psychological distress in the general population [14], with limited evidence regarding the dietary pattern followed in patients with schizophrenia spectrum disorders. Likewise, the particular vulnerability of the target population in this context of confinement and the global pandemic [14,16,17] stands out. This population has limited the acquisition of coping strategies, which has encouraged the development of unhealthy lifestyles [14,15,16,17,23,39], where hypercaloric dietary patterns and the restriction of physical activity stand out [23,24,40,41]. For these reasons, the effectiveness of the intervention may have been reduced. Thus, according to Stefánska et al. (2019), Stefánska et al. (2017), and Cheikl et al. (2021), poor sun exposure during states of confinement and the characteristics of schizophrenic disorder in terms of social restriction has made it challenging to achieve optimal vitamin D results in line with % RDA [35,36,40].
As established by Costa et al. (2019) and Giannouli (2017), the high prevalence of morbidity and mortality in LTMD is not only determined by the nutritional outcome and dysmetabolic status but also by the aetiological condition that derives from it [23,44]. In this sense, cultural, cognitive-emotional or spiritual factors stand out as aspects to be considered when elucidating which ones behave as protective or risk agents in the prediction of morbidity and mortality in the psychiatric population [44,45], especially in contexts of social restriction [14,17,40].
Thus, risk behaviours associated with the consumption of intoxicants, such as alcohol, tobacco or cannabis (among others), are a proven condition related to the factors above (cultural, cognitive, etc.) [44], with an impact on unhealthy lifestyles [23,28,39,40] and the development of disruptive behaviours [44,45]. However, despite the particular vulnerability of the psychiatric population to states of confinement [14,17,18], the latter has been postulated as a protective factor against the development of harmful habits with marked social content, such as substance consumption, among which alcohol consumption stands out. This fact has made it possible to minimise the potential impact of alcohol intake on the results obtained regarding the nutritional and cardio-metabolic profile.
However, despite the significant difficulties of intervention in the schizophrenic population [1,17,32], this study highlights the feasibility of high-symbiotic dietary intervention on cardio-metabolic health and marked improvement of the nutritional profile, different from the current evidence available in confinement settings [16,18,24,38]. Longitudinal studies are needed to demonstrate the impact of hygienic-dietary measures on the macro and micronutrient profile in the psychiatric population [17,41].
The available evidence shows that clinical trials with dietary approaches in the absence of psychopharmacological treatment are limited [38], show marked heterogeneity and lack methodological rigour [5,10]. However, as Stefánska et al. (2019) and Dabke et al. (2019) point out, the association of the individual nutritional programme with a symbiotic approach may have a high synergistic impact on the improvement of dysmetabolic states [35,46], a highly prevalent condition in the population studied [17,18,20].
Finally, according to Balanzá (2017), the role of advanced practice nurses stands out as the cornerstone of the multidisciplinary approach and the main person responsible for the dietary advice offered [5]. Likewise, psychiatric nurses are the leading active players in the emotional and cognitive regulation associated with the dietary patterns established as part of the care provided to the psychiatric population [28,32].

Limitations

The main limitations of this study are related to the sample size and the participants’ loss or lack of cooperation during the intervention phase. However, this limited and heterogeneous sample size could explain the scarce significant differences between macro and micronutrient profile variables and weekly consumption by food group. Thus, significant intra-group differences meant that no inter-group statistical results were achieved. Finally, since the authors followed the usual procedures for sample size estimation, it is possible that the risk/prevalence difference between IG and CG was overestimated (63%).
The results obtained may be linked to the difficulty of using FFQ in assessing the dietary-nutritional pattern. This fact is based on the low degree of dietary knowledge and food responsibility, psychopathological state and, therefore, possible associated neurocognitive impairment in the population under study, which may result in overestimated data relating to the RDAs [1,35].
Likewise, the non-inclusion of biochemical parameters in this manuscript may be a potential limitation, preventing the comparison of nutritional and cardio-metabolic results (blood glucose, lipid profile, etc.). The reason for not including these data was that the main objective was to assess the intervention’s efficacy in modifying this population’s dietary patterns with such particular characteristics. However, readers interested in this type of information can consult a recent paper in which these results have been included [47].
It would be relevant to know the psychopathological impact of increased consumption of prebiotics and probiotics on psychiatric disorders, of particular interest in LTMD. To this end, using Visual Evoked Potentials (VEP) is an effective diagnostic technique in analysing the neurophysiology of subjective disorders and interruption of functional recovery in psychopathological worsening, common in schizophrenia [48]. Unfortunately, this test could not be applied during the development of the trial, so subsequent studies that included it could provide more information on this vital topic.
It is essential to note that this study was conducted during the SARS-CoV-2 pandemic, making it difficult to achieve the proposed intervention, especially in acquiring and strengthening healthy lifestyles. Furthermore, it is necessary to consider the inherent characteristics of the subjects under study, a population that is particularly vulnerable to change, especially in a context of confinement and a global pandemic [14,17].
Finally, the scarcity of existing research on nutritional patterns and dietary habits in subjects diagnosed with schizophrenia makes it difficult to contrast the results obtained in different healthcare settings.

5. Conclusions

The development of a dietary-nutritional education programme in patients diagnosed with schizophrenia spectrum disorders and based on dietary advice by psychiatric nurses has not shown significant differences from conventional health education models, both being proposed as effective interventions in improving the nutritional pattern and dietary habits of the population under study. However, implementing a dietary-nutritional intervention with a high symbiotic content improves cardio-metabolic outcomes effectively in a global pandemic such as SARS-CoV-2. Furthermore, despite the inherent lifestyle dysfunctionalities of the target population, prebiotics and probiotics have been shown to offer a relevant and promising solution in different settings. Finally, further studies with larger sample sizes and outside the context of pandemics and confinement are needed to assess better the efficacy of these interventions.

Author Contributions

Investigation, A.S.-J., M.R.-S. and G.M.-R.; methodology, M.R.-S., M.G.-R., R.M.-L. and G.M.-R.; writing—review & editing, A.S.-J., M.R.-S. and G.M.-R. All authors have read and agreed to the published version of the manuscript.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Institutional Review Board Statement

The study was conducted respecting the fundamental principles established in the Declaration of Helsinki (1964), the Council of Europe Convention on Human Rights and Biomedicine (1997), and the UNESCO Universal Declaration on the Human Genome and Human Rights (1997). Research also followed the requirements established by Spanish legislation (Organic Law 3/2018 of 5 December and Law 41/2002 of 14 November). The referral Research Ethics Committee approved the study in November 2019 (reg. 468) and retrospectively registered on the Clinical Trials platform: clinicaltrials.gov (ID: NCT04366401; First Submission: 28 April 2020; First Registration: 9 September 2020; URL: https://register.clinicaltrials.gov/prs/app/action/LoginUser?ts=1&cx=-jg9qo4 [accessed on 9 September 2022]). All the information analysed by the principal investigator of this study was subject to the maintenance of professional secrecy. In any case, each participant was assigned a code as a register, where all the relative data were typed anonymously, limiting access to the database only to personnel linked to the development of the study, with the prior authorisation of the researcher responsible for the study.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study. Written informed consent has been obtained from the patient(s) to publish this paper.

Data Availability Statement

The collected data that support the findings of this study are available on reasonable request from the corresponding author.

Acknowledgments

This publication is partially funded by the XXVII Nursing Research Grant of the Illustrious Official College of Nursing of Córdoba, Spain.

Conflicts of Interest

The authors declare that they have no competing interest.

Trial Registration

The referral Research Ethics Committee approved the study protocol in November 2019 (reg. 468) and retrospectively registered at clinicaltrials.gov (NCT0436366401. First Submitted: 28 April 2020).

References

  1. Aucoin, M.; LaChance, L.; Cooley, K.; Kidd, S. Diet and Psychosis: A Scoping Review. Neuropsychobiology 2020, 79, 20–42. [Google Scholar] [CrossRef] [PubMed]
  2. Icaza, M.E. Gut microbiota in health and disease. Rev. Gastroenterol. Mex. 2013, 78, 240–248. [Google Scholar] [CrossRef] [Green Version]
  3. Castillo, F.; Marzo, M.E. Role of the gut microbiota in the development of various neurological diseases. Neurol. Sci. 2019, 37. [Google Scholar] [CrossRef]
  4. Henderson, D.C.; Borba, C.P.; Daley, T.B.; Boxill, R.; Nguyen, D.D.; Culhane, M.A.; Louie, P.; Cather, C.; Eden Evins, A.; Freudenreich, O.; et al. Dietary intake profile of patients with schizophrenia. Ann. Clin. Psychiatry 2006, 18, 99–105. [Google Scholar] [CrossRef] [PubMed]
  5. Balanzá, V. Nutritional supplements in psychotic disorders. Actas Esp. Psiquiatr. 2017, 45, 16–25. [Google Scholar]
  6. Gómez, A.E. Nutrición y enfermedad mental. Esquizofrenia y ácidos grasos omega 3. Farm. Prof. 2007, 21, 60–63. [Google Scholar]
  7. Salagre, E.; Vieta, E.; Grande, I. The visceral brain: Bipolar disorder and microbiota. Rev. Psiquiatr. Salud Ment. 2017, 10, 67–69. [Google Scholar] [CrossRef]
  8. Soria, V.; Uribe, J.; Salvat, N.; Palao, D.; Menchón, J.M.; Labad, J. Psychoneuroimmunology of mental disorders. Rev. Psiquiatr. Salud Ment. 2018, 11, 115–124. [Google Scholar] [CrossRef]
  9. Wang, H.; Wang, Y.P. Gut microbiota-brain axis. Chin. Med. J. 2016, 129, 2373–2380. [Google Scholar] [CrossRef]
  10. Cepeda, V.; Mondragón, A.; Lamas, A.; Miranda, J.M.; Cepeda, A. Use of prebiotics and probiotics in the management of anxiety. Farm. Comunit. 2019, 11, 30–40. [Google Scholar] [CrossRef]
  11. Patra, S. Psychobiotics: A paradigm shift in psychopharmacology. Indian J. Pharm. 2016, 48, 469–470. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  12. Andreo, P.; García, N.; Sánchez, E.P. La microbiota intestinal y su relación con las enfermedades mentales a través del eje microbiota-intestino-cerebro. Rev. Dis. Clin. Neurol. 2017, 4, 52–58. [Google Scholar]
  13. Forsythe, P.; Kunze, W.; Bienestock, J. Moody microbes or fecal phrenology: What do we know about the microbiota-gutbrain axis? BMC Med. 2016, 14, 58. [Google Scholar] [CrossRef] [PubMed]
  14. Solé, B.; Verdolini, N.; Amoretti, S.; Montejo, L.; Rosa, A.R.; Hogg, B.; Garcia-Rizo, C.; Mezquida, G.; Bernardo, M.; Martinez-Aran, A.; et al. Effects of the COVID-19 pandemic and lockdown in Spain: Comparison between community controls and patients with a psychiatric disorder. Preliminary results from the BRIS-MHC STUDY. J. Affect. Disord. 2021, 281, 13–23. [Google Scholar] [CrossRef]
  15. Baker, A.L.; Kay-Lambkin, F.J.; Richmond, R.; Filia, S.; Castle, D.; Williams, J.; Thornton, L. Healthy lifestyle intervention for people with severe mental disorders. Ment. Health Subst. Use 2011, 4, 144–157. [Google Scholar] [CrossRef] [Green Version]
  16. Muhammad, D.G.; Abubakar, I.A. COVID-19 lockdown may increase cardiovascular disease risk factors. Egypt. Heart J. 2021, 73, 2. [Google Scholar] [CrossRef]
  17. Bennett, G.; Young, E.; Butler, I.; Coe, S. The Impact of Lockdown During the COVID-19 Outbreak on Dietary Habits in Various Population Groups: A Scoping Review. Front. Nutr. 2021, 8, 626432. [Google Scholar] [CrossRef] [PubMed]
  18. Sánchez, M.L.; González, J.; Martínez, M.C. Metabolic control and prolactin in severe mental illness. Nursing interventions. Rev. Enferm Salud Ment. 2018, 9, 24–28. [Google Scholar] [CrossRef] [Green Version]
  19. Franch, C.M.; Molina, V.; Franch, J.I. Determinants of metabolic risk in atypical antipsychotic treatment. Rev. Psiquiatr. Salud Ment. 2016, 23, 87–130. [Google Scholar] [CrossRef] [Green Version]
  20. Franch, C.M.; Molina, V.; Franch, J.I. Metabolic syndrome and atypical antipsychotics: Possibility of prediction and control. Rev. Psiquiatr. Salud Ment. 2017, 10, 38–44. [Google Scholar] [CrossRef]
  21. Ocando, L.; Roa, A.; León, M.; González, R. Atypical antipsychotics and their role in the development of metabolic disease. Rev. Iberoam. Hipert. 2018, 13, 44–51. [Google Scholar]
  22. Gurusamy, J.; Gandhi, S.; Damodharan, D.; Ganesan, V.; Palaniappan, M. Exercise, diet and educational interventions for metabolic syndrome in persons with schizophrenia: A systematic review. Asian J. Psychiatr. 2018, 36, 73–85. [Google Scholar] [CrossRef] [PubMed]
  23. Costa, R.; Teasdale, S.; Abreu, S.; Bastos, T.; Probst, M.; Rosenbaum, S.; Ward, P.B.; Corredeira, R. Dietary Intake, Adherence to Mediterranean Diet and Lifestyle-Related Factors in People with Schizophrenia. Issues Ment. Health Nurs. 2019, 40, 851–860. [Google Scholar] [CrossRef] [PubMed]
  24. Gill, R.; Tyndall, S.F.; Vora, D.; Hasan, R.; Megna, J.L.; Leontieva, L. Diet Quality and Mental Health Amongst Acute Inpatient Psychiatric Patients. Cureus 2021, 13, e12434. [Google Scholar] [CrossRef]
  25. Kali, A. Psychobiotics: An emerging probiotic in psychiatric practice. Biomed. J. 2016, 3, 223–224. [Google Scholar] [CrossRef] [Green Version]
  26. Sarkar, A.; Lehto, S.M.; Harty, S.; Dinan, T.G.; Cryan, J.F.; Burnet, P. Psychobiotics and the Manipulation of Bacteria–Gut–Brain Signals. Trends Neurosci. 2016, 39, 763–781. [Google Scholar] [CrossRef] [Green Version]
  27. Mörkl, S.; Wagner-Skacel, J.; Lahousen, T.; Lackner, S.; Holasek, S.J.; Bengesser, S.A.; Painold, A.; Holl, A.K.; Reininghaus, E. The Role of Nutrition and the Gut-Brain Axis in Psychiatry: A Review of the Literature. Neuropsychobiology 2018. ahead of print. [Google Scholar] [CrossRef] [PubMed]
  28. Blomqvist, M.; Ivarsson, A.; Carlsson, I.M.; Sandgren, A.; Jormfeldt, H. Health Effects of an Individualized Lifestyle Intervention for People with Psychotic Disorders in Psychiatric Outpatient Services: A TwoYear Follow-up. Issues Ment. Health Nurs. 2019, 40, 839–850. [Google Scholar] [CrossRef] [Green Version]
  29. Sugawara, N.; Sagae, T.; Yasui-Furukori, N.; Yamakazi, M.; Shimoda, K.; Mori, T.; Sugai, T.; Matsuda, H.; Suzuki, Y.; Ozeki, Y.; et al. Effects of nutritional education on weight change and metabolic abnormalities among patients with schizophrenia in Japan: A randomized controlled trial. J. Psychiatr. Res. 2018, 97, 77–83. [Google Scholar] [CrossRef]
  30. Andalusian Regional Ministry of Health. Dietary Advice in Primary Care. Plan for the Promotion of Physical Health and Balanced Diet 2004–2008. 2010. Available online: https://www.juntadeandalucia.es/export/drupaljda/Guia_Consejo_Dietetico_AP_2005_imp2010.pdf (accessed on 18 February 2020).
  31. Andalusian Regional Ministry of Health. Guide to Intensive Dietetic Counselling in Primary Health Care. Plan for the Promotion of Physical Health and Balanced Diet 2004–2008. 2007. Available online: https://www.repositoriosalud.es/handle/10668/1220 (accessed on 20 February 2020).
  32. Sevillano, A.; Molina, G.; García, J.A.; García, M.; Molina, R.; Romero, M. Efficacy of nutrition education for the increase of symbiotic intake on nutritional and metabolic status in schizophrenic spectrum disorders: A two-arm protocol. Front. Nutr. 2022, 9, 912783. [Google Scholar] [CrossRef]
  33. Martín, J.M.; Boyle, P.; Gorgojo, L.; Maisonneuve, P.; Fernández, J.C.; Salvini, S.; Willett, W.C. Development and validation of a food frequency questionnaire in Spain. Int. J. Epidemiol. 1993, 22, 512–519. [Google Scholar] [CrossRef] [PubMed]
  34. Moreno-Rojas, R.; Pérez-Rodríguez, F.; Cámara Martos, F. Nutriplato 2.0 web para valoración de recetas y platos, de libre uso. XVI J. Nac. Nutr. Práctica. 2012, 32, 29–58. [Google Scholar]
  35. Stefańska, E.; Wendołowicz, A.; Lech, M.; Konarzewska, B.; Zapolska, J.; Waszkiewicz, N.; Ostrowska, L. Does the usual dietary intake of schizophrenia patients require supplementation with vitamins and minerals? Psychiatr. Pol. 2019, 53, 599–612. [Google Scholar] [CrossRef] [PubMed]
  36. Stefańska, E.; Wendołowicz, A.; Konarzewska, B.; Waszkiewicz, N.; Ostrowska, L. The assessment of satisfaction of energy demand and of chosen macro- and micro-element content in the daily food rations of women diagnosed with schizophrenia with varied nutritional states. Psychiatr. Pol. 2019, 53, 613–628. [Google Scholar] [CrossRef]
  37. Adamowicz, K.; Kucharska-Mazur, J. Dietary Behaviors and Metabolic Syndrome in Schizophrenia Patients. J. Clin. Med. 2020, 9, 537. [Google Scholar] [CrossRef]
  38. Stefańska, E.; Lech, M.; Wendołowicz, A.; Konarzewska, B.; Waszkiewicz, N.; Ostrowska, L. Eating habits and nutritional status of patients with affective disorders and schizophrenia. Psychiatr. Pol. 2017, 51, 1107–1120. [Google Scholar] [CrossRef]
  39. Zurrón, P.; Casaprima, S.; García, L.; García-Portilla, M.P.; Junquera, R.; Canut, M.T.L. Eating and nutritional habits in patients with schizophrenia. Rev. Psiquiatr. Salud Ment. 2019, S1888–9891, 30098–30099. [Google Scholar] [CrossRef]
  40. Cheikh, L.; Hashim, M.; Mohamad, M.N.; Hassan, H.; Ajab, A.; Stojanovska, L.; Jarrar, A.H.; Hasan, H.; Abu Jamous, D.O.; Saleh, S.T.; et al. Dietary Habits and Lifestyle During Coronavirus Pandemic Lockdown: Experience from Lebanon. Front. Nutr. 2021, 8, 730425. [Google Scholar] [CrossRef]
  41. Kowalski, K.; Bogudzińska, B.; Stańczykiewicz, B.; Piotrowski, P.; Bielawski, T.; Samochowiec, J.; Szczygieł, K.; Plichta, P.; Misiak, B. The Deficit Schizophrenia Subtype Is Associated with Low Adherence to the Mediterranean Diet: Findings from a Case-Control Study. J. Clin. Med. 2022, 11, 568. [Google Scholar] [CrossRef]
  42. Caemmerer, J.; Correll, C.U.; Maayan, L. Acute and maintenance effects of non-pharmacologic interventions for antipsychotic associated weight gain and metabolic abnormalities: A meta-analytic comparison of randomized controlled trials. Schizophr. Res. 2012, 140, 159–168. [Google Scholar] [CrossRef]
  43. Teasdale, S.B.; Ward, P.B.; Rosenbaum, S.; Samaras, K.; Stubbs, B. Solving a weighty problem: Systematic review and meta-analysis of nutrition interventions in severe mental illness. Br. J. Psychiatry 2017, 210, 110–118. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  44. Giannouli, V. Ethnicity, mortality, and severe mental illness. Lancet Psychiatry 2017, 4, 517. [Google Scholar] [CrossRef] [Green Version]
  45. Giannouli, V. Violence in severe mental illness: Is cognition missing in the associations with ethnicity, cannabis and alcohol? Australas. Psychiatry 2017, 25, 633. [Google Scholar] [CrossRef] [PubMed]
  46. Dabke, K.; Hendrick, G.; Devkota, S. The gut microbiome and metabolic syndrome. J. Clin. Investig. 2019, 129, 4050–4057. [Google Scholar] [CrossRef] [PubMed]
  47. Sevillano-Jiménez, A.; Romero-Saldaña, M.; García-Mellado, J.A.; Carrascal-Laso, L.; García-Rodríguez, M.; Molina-Luque, R.; Molina-Recio, G. Impact of high prebiotic and probiotic dietary education in the SARS-CoV-2 era: Improved cardio-metabolic profile in schizophrenia spectrum disorders. BMC Psychiatry 2022, 22, 781. [Google Scholar] [CrossRef]
  48. Saiz, J.; Vega, D.C.; Sánchez, P. Bases Neurobiológicas de la Esquizofrenia. Clín. Salud. 2010, 21, 235–254. [Google Scholar]
Figure 1. Study Design. * Data collected at baseline and six months of intervention: (1) Nutritional profile. ** Data collected at baseline and monthly during the intervention: (1) Anthropometric data (weight, height, Body Mass Index—BMI, waist circumference and waist-to-height ratio—WHtR-); (2) R-24 (weekly determination of foods with high symbiotic content in adherence to established dietary plan).
Figure 1. Study Design. * Data collected at baseline and six months of intervention: (1) Nutritional profile. ** Data collected at baseline and monthly during the intervention: (1) Anthropometric data (weight, height, Body Mass Index—BMI, waist circumference and waist-to-height ratio—WHtR-); (2) R-24 (weekly determination of foods with high symbiotic content in adherence to established dietary plan).
Nutrients 14 05388 g001
Figure 2. CONSORT flow diagram.
Figure 2. CONSORT flow diagram.
Nutrients 14 05388 g002
Table 1. Sample characteristics (independent variables): Baseline.
Table 1. Sample characteristics (independent variables): Baseline.
Variables Total
(n = 44)
Control Group
(n = 21)
Intervention Group
(n = 23)
p
Socio-demographic variables
Sex
Men32 (72.7%)14 (31.8%)18 (40.9%)0.388
Women12 (27.3%)7 (15.9%)5 (11.4%)
Age (years) 49.2 (11.2)48.8 (13.8)49.5 (10.1)0.897
Household composition
Individual12 (27.3%)5 (11.4%)7 (15.9%)0.893
Horizontal3 (6.8%)1 (2.3%)2 (4.5%)
Complete3 (6.8%)1 (2.3%)2 (4.5%)
Family home7 (15.9%)4 (9.1%)3 (6.8%)
Supervised flat19 (43.2%)10 (22.7%)9 (20.5%)
Economic level
High6 (13.6%)3 (6.8%)3 (6.8%)0.651
Medium26 (59.1%)11 (25%)15 (34.1%)
Low12 (27.3%)7 (15.9%)5 (11.4%)
Education level
Uneducated4 (9.1%)2 (4.5%)2 (4.5%)0.590
Primary19 (43.2%)11 (25%)8 (18.2%)
Secondary17 (38.6%)7 (15.9%)10 (22.7%)
University4 (9.1%)1 (2.3%)3 (6.8%)
Area of residence
Urban38 (86.4%)18 (40.9%)20 (45.5%)1.00
Rural6 (13.6%)3 (6.8%)3 (6.8%)
Clinical Variables
Psychiatric diagnosis
Schizophrenia37 (84.1%)19 (43.2%)18 (40.9%)0.419
Schizoaffective Disorder5 (11.4%)1 (2.3%)4 (9.1%)
Delusional Disorder2 (4.5%)1 (2.3%)1 (2.3%)
Duration of illness (years)21.6 (12.4)22.5 (12.6)20.9 (12.5)0.715
Age at first hospitalisation (years)31.4 (11)31.4 (11.4)31.4 (10.7)0.572
Consumption of toxics
No15 (34.1%)5 (11.4%)10 (22.7%)0.169
Yes29 (65.9%)16 (36.4%)13 (29.5%)
Type of toxics
Alcohol6 (13.6%)3 (6.8%)3 (6.8%)0.775
Tobacco29 (65.9%)15 (34%)14 (31.8%)
Cocaine3 (6.8%)1 (2.3%)2 (4.5%)
Opioids2 (4.6%)1 (2.3%)1 (2.3%)
Amphetamines3 (6.8%)2 (4.5%)1 (2.3%)
Cannabis10 (22.7%)5 (11.6%)5 (11.3%)
Cardio-metabolic condition
No24 (54.5%)11 (25%)13 (29.5%)0.783
Yes20 (45.5%)10 (22.7%)10 (22.7%)
Type Cardio-metabolic condition
AHT10 (22.7%)6 (13.6%)4 (9.1%)0.407
DM7 (15.9%)5 (11.3%)2 (4.5%)
Hyperlipemia17 (38.6%)8 (18.1%)9 (20.4%)
Therapeutic Variables
Reason for Change: Antipsychotic Treatment
Unchanged31 (70.5%)16 (51.6%)15 (48.4%)0.660
Lack of efficiency5 (11.4%)1 (2.3%)4 (9.1%)
Tolerability/safety issues2 (4.5%)1 (2.3%)1 (2.3%)
Patient’s own choice3 (6.8%)1 (2.3%)2 (4.5%)
Other: Clinical improvement3 (6.8%)2 (4.5%)1 (2.3%)
Tolerability and Modulation of Dietary and Nutritional Patterns
Culinary knowledge and food responsibility
Can cook and he/she is in charge of it27 (61.4%)9 (20.5%)18 (40.9%)0.004
Can cook but he/she is not in charge of it6 (13.6%)2 (4.5%)4 (9.1%)
Cannot cook and he/she is not in charge of it11 (25%)10 (22.7%)1 (2.3%)
AHT: Arterial hypertension; DM: diabetes mellitus.
Table 2. Sample characteristics (dependent variables): Baseline.
Table 2. Sample characteristics (dependent variables): Baseline.
VariablesTotal
(n = 44)
Control
Group
(n = 21)
Intervention Group
(n = 23)
p
Macronutrients (RDA)
Energy (%)177.4 (48.4)182 (47.3)173.2 (50.1)0.329
Proteins (g)432 (152.5)443.2 (159.6)421.9 (148.6)0.597
Lipids (g)207.8 (63.1)212.4 (68.2)203.5 (59.4)0.716
Saturated fatty acids (g) 392.3 (222.2)414.9 (260.6)371.7 (183.9)0.698
Monounsaturated fatty acids (g)147.7 (60.9)140.9 (63.6)154 (59)0.613
Polyunsaturated fatty acids (g) 138.9 (103.7)145.1 (131.3)133.2 (72.8)0.716
Cholesterol (mg)247.2 (135.8)224.6 (70.3)267.9 (175)0.787
Carbohydrates (g)159.6 (53.4)161.8 (48.2)157.5 (58.7)0.518
Oligosaccharides (g)
Polysaccharides (g)
303.4 (205.7)342.7 (203.8)267.5 (205.2)0.088
123.2 (74.6)139.8 (87.2)108 (58.8)0.378
Fibre (g)215.1 (124.8)196 (130.5)232.5 (119.5)0.245
Micronutrients (RDA)
Ca (mg)181.1 (68.8)194.1 (64.7)169.2 (71.2)0.124
Mg (mg)292.8 (95.4)285.3 (88.8)299.7 (102.6)0.823
P (mg)352.9 (107.7)372.7 (123.5)334.8 (89.9)0.209
Na (mg)310.8 (93.6)320.9 (112.4)301.5 (73.7)0.630
K (mg)236 (83.8)232.4 (90.2)239.2 (79.5)0.664
Fe (mg)216 (70.5)211.1 (64.1)220.5 (77.1)0.953
Cu (mg)173.7 (91.2)170 (118.9)177 (58.1)0.184
Zn (mg)260.4 (101.3)251.2 (83.4)268.7 (116.6)0.916
Mn (mg)714.7 (595.6)575.9 (360.2)841.3 (735)0.264
I (ug)252.7 (102.1)278.4 (120.9)229.2 (76.7)0.177
Se (mg)501.4 (229)471 (203)529.2 (251.7)0.518
Thiamine (mg)261.4 (81.4)261 (74.1)261.7 (89.2)0.769
Riboflavin (mg)289.2 (92.7)299.5 (92.1)279.8 (94.4)0.226
Niacin (mg)388.5 (116.3)392.7 (113)384.7 (121.6)0.503
Pantothenic acid (mg)97.3 (44.6)103.6 (46.9)91.6 (42.7)0.329
Vit B6 (mg)314.1 (105.7)305.5 (94.4)321.9 (116.7)0.842
Biotin (ug)117.7 (76.2)135.7 (87.3)101.2 (61.7)0.162
Folic Acid (ug)205.4 (81.4)199.1 (86.1)211.2 (78.4)0.565
Vit B12 (ug)636.2 (273.9)657.5 (321.6)616.6 (227.5)0.842
Ascorbic Acid (mg)451.6 (244.3)431.2 (248.7)470.2 (244.2)0.647
Vit A (ug)239.5 (93.4)250.7 (86.9)229.3 (99.8)0.549
Vit D (ug)64.9 (65.9)69.5 (80.5)60.6 (50.6)0.897
Vit E (mg)228.5 (143.7)191.8 (100.7)262.1 (169.4)0.065
Food Group: Weekly Consumption
Dairy Products (n°. consumed/week)21.2 (13)22.7 (14.9)19.9 (11.1)0.487
Eggs, Meats and Fish (n°. consumed/week)23.3 (9.3)21.8 (10.9)24.6 (7.5)0.188
Vegetables (n°. consumed/week)25.3 (12.9)23.7 (14.2)26.8 (11.8)0.188
Fruits (n°. consumed/week)22.4 (17.7)19 (18.4)25.4 (16.8)0.086
Legumes and Cereals (n°. consumed/week)6.6 (4.9)5.9 (3.9)7.2 (5.7)0.687
Sugars and ultra-processed products (n°. consumed/week)53.9 (22.4)45.5 (14.9)61.6 (25.4)0.03
Weekly food record
R24-weekly (n°. of symbiotic foods consumed/week)24.4 (7.8)20.6 (7.8)27.8 (6.2)0.001
R24-monthly (n°. of symbiotic foods consumed/week)97.7 (31.4)82.6 (31.3)111.4 (25)0.001
R24-trimestral (n°. of symbiotic foods consumed/week)293.1 (94.3)247.9 (94.1)334.3 (75)0.001
Anthropometric Profile
Weight (kg)81.4 (17.6)76.6 (18)85.7 (16.3)0.086
Waist circumference (cm)101.9 (17)97.6 (21)105.7 (11.5)0.312
BMI (kg/m2)28.5 (5)27.5 (5.2)29.5 (4.8)0.307
WHtR0.6 (0.1)0.6 (0.1)0.6 (0.0)0.518
Height (cm)168.5 (9.2)166.4 (10.7)170.3 (7.4)0.245
Therapeutic Variables
N of associated antipsychotic1.3 (0.5)1.3 (0.5)1.3 (0.4)0.597
DDD antipsychotics (mg)271.4 (242.5)286.7 (222.3)257.4 (242.5)0.458
RDA: Recommended Dietary Allowance; Ca: calcium; Mg: magnesium: P: phosphorus; Na: sodium; K: potassium; Fe: iron; Cu: copper; Zn: zinc; Mn: manganese; I: iodine; Se: selenium; Vit.B6: vitamin B6; Vit.B12: vitamin B12; Vit.A: vitamin A; Vit.D: vitamin D; Vit.E: vitamin E; Food Group-Weekly Consumption: Calculation of average consumption of main foods (weekly) by food group; Weekly food record: weekly determination of foods with high symbiotic content in adherence to established dietary plan; R24-weekly: average (weekly) calculation of the main foods and dishes consumed according to the established dietary plan; R24-monthly: average (monthly) calculation of the main foods and dishes consumed according to the established dietary plan; R24-quarterly: average (quarterly) calculation of the main foods and dishes consumed according to the established dietary plan BMI: body mass index; WHtR: waist-to-height ratio; Antipsychotic DDD: defined daily dose antipsychotics.
Table 3. Modifications in allocation groups: control group and experimental group.
Table 3. Modifications in allocation groups: control group and experimental group.
Total (n = 44)Control Group (n = 21)Intervention Group (n = 23)p *p **
VariablesBasal6 MonthspBasal6 MonthspBasal6 Monthsp
Macronutrients (RDA)
Energy (%)177.4 (48.4)128.2 (31.7)<0.001182 (47.3)130.9 (37.8)0.001173.2 (50.1)125.8 (25.4)<0.0010.3290.647
Proteins (g)432 (152.5)328.4 (116.7)<0.001443.2 (159.6)311.1 (134.1)0.003421.9 (148.6)344.2 (98.6)0.0110.5970.209
Lipids (g)207.8 (63.1)143.2 (39.2)<0.001212.4 (68.2)149.6 (47)0.002203.5 (59.4)137.3 (30.2)<0.0010.7160.245
Saturated fatty acids (g) 392.3 (222.2)251.6 (93.8)<0.001414.9 (260.6)252.4 (99.4)0.002371.7 (183.9)250.9 (90.7)0.0080.6980.897
Monounsaturated fatty acids (g)147.7 (60.9)108.7 (40.2)<0.001140.9 (63.6)103.1 (35.9)0.006154 (59)113.9 (43.9)0.0180.6130.418
Polyunsaturated fatty acids (g) 138.9 (103.7)120.6 (115.8)0.264145.1 (131.3)144.6 (160)0.985133.2 (72.8)98.7 (43.3)0.0950.7160.733
Cholesterol (mg)247.2 (135.8)173.1 (80.7)0.001224.6 (70.3)160.1 (76.7)0.002267.9 (175)185 (84.2)0.0270.7870.285
Carbohydrates (g)159.6 (53.4)118.7 (35.2)<0.001161.8 (48.2)120.3 (38.5)0.003157.5 (58.7)117.3 (32.6)0.0040.5180.897
Oligosaccharides (g)303.4 (205.7)204.8 (98.6)0.005342.7 (203.8)214 (113.4)0.015267.5 (205.2)196.5 (84.6)0.1340.0880.805
Polysaccharides (g)123.2 (74.6)96.6 (40.7)0.019139.8 (87.2)89.1 (44.4)0.003108 (58.8)103.5 (36.6)0.7620.3780.177
Fibre (g)215.1 (124.8)185.8 (111)0.229196 (130.5)175.8 (116.8)0.560232.5 (119.5)194.8 (107.3)0.2880.2450.431
Micronutrients (RDA)
Ca (mg)181 (68.8)142 (56)0.004194.1 (64.7)142.8 (64.6)0.02169.2 (71.2)141.3 (48.2)0.0990.1240.751
Mg (mg)292.8 (95.4)238.2 (102.7)0.002285.3 (88.8)220.2 (116.8)0.013299.7 (102.6)254.7 (87.3)0.070.8230.118
P (mg)352.9 (107.7)270.9 (77.8)<0.001372.7 (123.5)265.6 (88.2)0.003334.8 (89.9)275.7 (68.6)0.0090.2090.318
Na (mg)310.8 (93.6)201 (60.7)<0.001320.9 (112.4)200.5 (67.6)0.001301.5 (73.7)201.5 (55.2)<0.0010.6300.860
K (mg)236 (83.8)195.5 (84.4)0.007232.4 (90.2)178.4 (87.7)0.03239.2 (79.5)211 (80.1)0.1200.6640.136
Fe (mg)216 (70.5)169.5 (57.6)<0.001211.1 (64.1)166.9 (66.3)0.008220.5 (77.1)171.8 (49.8)0.0030.9530.953
Cu (mg)173.7 (91.2)154.8 (73.8)0.170170 (118.9)133.9 (74.5)0.132177 (58.1)173.8 (69.3)0.8290.1840.08
Zn (mg)260.4 (101.3)202.3 (76.4)0.003251.2 (83.4)206.3 (96.5)0.118268.7 (116.6)198.6 (53.9)0.0130.9160.565
Mn (mg)714.7 (595.6)632.8 (437.2)0.413575.9 (360.2)495.5 (376.9)0.290841.3 (735)758.3 (458.3)0.6480.2640.028
I (ug)252.7 (102.1)194.9 (91.9)0.009278.4 (120.9)204.2 (114.7)0.061229.2 (76.7)186.4 (66.3)0.0630.1770.953
Se (mg)501.4 (229)392.4 (147.6)0.004471 (203)360.4 (136.2)0.034529.2 (251.7)421.6 (154.4)0.0550.5180.162
Thiamine (mg)261.4 (81.4)209.6 (65.2)<0.001261 (74.1)203.5 (76.8)0.006261.7 (89.2)215.2 (53.7)0.0240.7690.503
Riboflavin (mg)289.2 (92.7)237.2 (72)0.005299.5 (92.1)230.3 (79.9)0.019279.8 (94.4)243.5 (65)0.1350.2260.534
Niacin (mg)388.5 (116.3)318 (98.4)0.001392.7 (113)295.9 (114.4)0.002384.7 (121.6)338.1 (78.3)0.1040.5030.107
Pantothenic acid (mg)97.3 (44.6)82.3 (32.2)0.051103.6 (46.9)73 (29.4)0.01991.6 (42.7)90.8 (32.8)0.9290.3290.08
Vit B6 (mg)314.1 (102.7)262.9 (97.8)0.007305.5 (94.4)244.2 (104.5)0.025321.9 (116.7)279.9 (90.2)0.1280.8420.155
Biotin (ug)117.7 (76.2)104.6 (73.6)0.363135.7 (87.3)93.5 (62.3)0.07101.2 (61.7)114.7 (82.7)0.4290.1620.296
Folic Acid (ug)205.4 (81.4)174.8 (69.9)0.02199.1 (86.1)158.3 (64.7)0.057211.2 (78.4)189.9 (72.4)0.1950.5650.142
Vit. B12 (ug)636.2 (273.9)475.6 (198.3)0.002657.5 (321.6)449.5 (183.2)0.021616.6 (227.5)499.4 (212.3)0.040.8420.549
Ascorbic Acid (mg)451.6 (244.3)429 (206.7)0.529431.2 (248.7)383.2 (226.1)0.292470.2 (244.2)470.8 (287.3)0.9920.6470.254
Vit. A (ug)239.5 (93.4)219 (80.1)0.212250.7 (86.9)208.6 (75.7)0.079229.3 (99.8)228.6 (84.4)0.9740.5490.366
Vit. D (ug)64.9 (65.9)52.4 (56.1)0.1369.5 (80.5)56.4 (78.4)0.20160.6 (50.6)48.8 (23.1)0.3610.8970.445
Vit. E (mg)228.5 (143.7)156.4 (52.8)0.002191.8 (100.7)146.9 (64.3)0.059262.1 (169.4)165.1 (39.1)0.0140.0650.062
Food Group: Weekly Consumption
Dairy Products (n°. consumed/week)21.3 (13)22.4 (11.9)0.62522.7 (14.9)24.4 (13.8)0.67019.9 (11.1)20.5 (9.8)0.8220.4870.316
Eggs, Meats and Fish (n°. consumed/week)23.3 (9.3)20 (7.6)0.09721.8 (10.9)22.1 (8.7)0.92724.6 (7.5)18.1 (5.9)0.0090.1880.09
Vegetables (n°. consumed/week)25.3 (12.9)23.8 (11.1)0.51723.7 (14.2)23 (12.9)0.84826.8 (11.8)24.6 (9.4)0.4070.1880.284
Fruits (n°. consumed/week)22.4 (17.7)18.2 (14.4)0.07419 (18.4)15.3 (14)0.27625.4 (16.8)20.8 (14.6)0.1650.0860.148
Legumes and Cereals (n°. consumed/week)6.6 (4.9)7.2 (4.2)0.3805.9 (3.9)6.4 (2.5)0.5627.2 (5.7)7.9 (5.2)0.5220.6870.661
Sugars and ultra-processed products (n°. consumed/week)53.9 (22.4)57.4 (28.4)0.50545.5 (14.9)67.2 (34.1)0.00661.6 (25.4)48.4 (18.5)0.030.030.037
Weekly food record
R24-weekly (n°. of symbiotic foods consumed/week)24.4 (7.8)--20.6 (7.8)--27.8 (6.2)--0.001-
R24-monthly (n°. of symbiotic foods consumed/week)97.7 (31.4)--82.6 (31.3)--111.4 (25)--0.001-
R24- quarterly (n°. of symbiotic foods consumed/week)293.1 (94.3)--247.9 (94.1)--334.3 (75)--0.001-
Anthropometric Profile
Weight (kg)81.4 (17.6)78.7 (16.2)<0.00176.6 (18)75.8 (17.7)0.38285.7 (16.3)81.3 (14.6)<0.0010.0860.275
Waist circumference (cm)101.9 (17)101.6 (12.5)0.89897.6 (21)101.2 (13.5)0.322105.7 (11.5)102.1 (11.7)<0.0010.3970.981
BMI (kg/m2)28.5 (5)27.6 (4.7)<0.00127.5 (5.2)27.2 (5.3)0.32329.5 (4.8)27.9 (4.3)<0.0010.3070.869
WHtR0.6 (0.09)0.6 (0.07)0.9320.6 (0.12)0.6 (0.08)0.3450.6 (0.06)0.6 (0.06)<0.0010.5970.378
Therapeutic Variables
N° of associated antipsychotic1.3 (0.5)1.2 (0.4)0.2621.38 (0.49)1.28 (0.46)0.3291.3 (0.47)1.26 (0.44)0.5750.5970.855
DDD antipsychotics (mg)271.4 (242.5)241.2 (226.7)0.108286.7 (222.3)260.5 (221.5)0.230257.4 (263.7)247.4 (225.9)0.3010.4580.789
p: intragroup statistical significance; p *: baseline intergroup statistical significance; p **: 6 months intergroup statistical significance; RDA: Recommended Dietary Allowance Ca: calcium; Mg: magnesium: P: phosphorus; Na: sodium; K: potassium; Fe: iron; Cu: copper; Zn: zinc; Mn: manganese; I: iodine; Se: selenium; Vit.B6: vitamin B6; Vit.B12: vitamin B12; Vit.A: vitamin A; Vit.D: vitamin D; Vit.E: vitamin E; Food Group-Weekly Consumption: Calculation of average consumption of main foods (weekly) by food group; Weekly food record: weekly determination of foods with high symbiotic content in adherence to established dietary plan; R24-weekly: average (weekly) calculation of the main foods and dishes consumed according to the established dietary plan; R24-monthly: average (monthly) calculation of the main foods and dishes consumed according to the established dietary plan R24-quarterly: average (quarterly) calculation of the main foods and dishes consumed according to the established dietary plan BMI: body mass index; WHtR: waist-to-height ratio; Antipsychotic DDD: defined daily dose antipsychotics.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Sevillano-Jiménez, A.; Romero-Saldaña, M.; García-Rodríguez, M.; Molina-Luque, R.; Molina-Recio, G. Nutritional Impact and Eating Pattern Changes in Schizophrenic Spectrum Disorders after Health Education Program on Symbiotic Dietary Modulation Offered by Specialised Psychiatric Nursing–Two-Arm Randomised Clinical Trial. Nutrients 2022, 14, 5388. https://doi.org/10.3390/nu14245388

AMA Style

Sevillano-Jiménez A, Romero-Saldaña M, García-Rodríguez M, Molina-Luque R, Molina-Recio G. Nutritional Impact and Eating Pattern Changes in Schizophrenic Spectrum Disorders after Health Education Program on Symbiotic Dietary Modulation Offered by Specialised Psychiatric Nursing–Two-Arm Randomised Clinical Trial. Nutrients. 2022; 14(24):5388. https://doi.org/10.3390/nu14245388

Chicago/Turabian Style

Sevillano-Jiménez, Alfonso, Manuel Romero-Saldaña, María García-Rodríguez, Rafael Molina-Luque, and Guillermo Molina-Recio. 2022. "Nutritional Impact and Eating Pattern Changes in Schizophrenic Spectrum Disorders after Health Education Program on Symbiotic Dietary Modulation Offered by Specialised Psychiatric Nursing–Two-Arm Randomised Clinical Trial" Nutrients 14, no. 24: 5388. https://doi.org/10.3390/nu14245388

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop