Metabolik Sendromlu Bireylerde Diyet İnflamatuar İndeks Skoru, Depresyon ve Kronotip Arasındaki İlişkinin Belirlenmesi: Bir Eğitim Araştırma Hastanesi Örneği

Year 2024, Volume: 8 Issue: 2, 171 - 179, 30.08.2024

Kübra Ahıskalıoğlu , Emre Batuhan Kenger

Abstract

Amaç: Bu çalışma, metabolik sendromlu bireylerde diyet inflamatuar indeks skoru, depresyon ve kronotip arasındaki ilişkinin belirlenmesi amacıyla yapılmıştır.
Gereç ve Yöntemler: Bu çalışmaya 100 metabolik sendromlu birey dahil edilmiştir. Katılımcıların, depresyon, stres ve anksiyete durumlarını değerlendirmek için Depresyon-Anksiyete Stres Ölçeği ölçeği, kronotiplerini belirlemek için sabahçıl-akşamcıl anketi ve Dİİ'lerini belirlemek için üç günlük besin tüketim kaydı yöntemi kullanılmıştır.
Bulgular: Katılımcıların %53'ü kadın ve %47'si erkektir. Depresyon (10,64±3,91), anksiyete (10,38±3,51) ve stres skorları (13,12±3,89) "akşamcıl tip" grupta anlamlı şekilde yüksek çıkmıştır. Kadın katılımcıların depresyon skorları (9.68 ± 4.39) erkeklere (8.00 ± 3.35) göre anlamlı olarak daha yüksek bulunmuştur (p:0.033). Diyet inflamatuar indeks skorları incelendiğinde, kadınların daha pro-inflamatuar (3, 23 ± 5,69) bir beslenme tarzına sahip oldukları belirlenmiştir. Ayrıca, depresyon skoru ile karbonhidrat tüketimi arasında pozitif (r: 0.264; p: 0.002), protein yüzdesi ile ise negatif yönde (r:-0.336; p:0.001) korelasyon saptanmıştır.
Sonuç: Çalışma, metabolik sendromlu bireylerin çoğunluğunun akşamcıl tipte olduğunu ve bu bireylerin depresyon, anksiyete ve stres açısından risk altında olduğunu göstermiştir. Ayrıca bireylerin pro-inflamatuar bir beslenme tarzına sahip olduğu saptanmıştır. Metabolik sendromlu bireylerin tedavisinde kronotiplerinin belirlenmesi, beslenme alışkanlıklarının ve psikolojik durumlarının değerlendirilmesi önerilmektedir.

Keywords

Diyet İnflamatuar İndeksi, Depresyon ve Anksiyete, Kronotip, Metabolik Sendrom

Determining The Relationship Between Diet Inflammatory Index Score, Depression and Chronotype In Individuals with Metabolic Syndrome: An Example of a Training and Research Hospital

Abstract

Aim: This study aimed to examine the relationship between the depression, chronotype and Dietary Inflammatory Index score in individuals diagnosed with metabolic syndrome.
Material and Methods: This study included 100 individuals with metabolic syndrome. The Depression-Anxiety Stress Scale was utilized to assess the depression, stress, and anxiety levels of the participants. Chronotypes were determined using the Morningness-Eveningness Questionnaire, and the Dietary Inflammatory Index (DII) was calculated based on a three-day food consumption record.
Results: Of the participants, 53% were women and 47% were men. The depression (10.64±3.91), anxiety (10.38±3.51), and stress (13.12±3.89) scores were significantly higher in the "evening type" group. Female participants had significantly higher depression scores (9.68±4.39) compared to male participants (8.00±3.35) (p=0.033). Analysis of the Dietary Inflammatory Index (DII) scores revealed that women had a more pro-inflammatory diet (3.23±5.69). Additionally, a positive correlation was observed between depression scores and carbohydrate consumption (r=0.264, p=0.002), while a negative correlation was found with the percentage of protein intake (r=-0.336, p=0.001).
Conclusion: The study revealed that the majority of individuals with metabolic syndrome exhibit an evening chronotype and are at increased risk for depression, anxiety, and stress. Additionally, it was found that these individuals tend to follow a pro-inflammatory diet. Therefore, it is recommended that the treatment of individuals with metabolic syndrome includes the assessment of their chronotypes, nutritional habits, and psychological states.

Keywords

Chronotype, Dietary Inflammatory Index, Depression and Anxiety, Metabolic Syndrome

Ethical Statement

Informed consent in writing was obtained from all participants. Permission was received from Istanbul Bahçeşehir University Ethics Committee to conduct the research (approval number 2023-/03, dated 30.03.2023) and the study was conducted in accordance with the principles of the Declaration of Helsinki.

References

• 1. Gurka MJ, Guo Y, Filipp SL, DeBoer MD. Metabolic syndrome severity is significantly associated with future coronary heart disease in Type 2 diabetes. Cardiovasc Diabetol. 2018;17(1):1- 9.
• 2. Bovolini A, Garcia J, Andrade MA, Duarte JA. Metabolic Syndrome Pathophysiology and Predisposing Factors. Int J Sports Med. 2021;42(3):199-214.
• 3. Akeren Z, Kaya O. Üniversite Öğrencilerinde Günlük Alınan Besin Öğeleri Dağılımının ve Metabolik Sendrom Riskinin Belirlenmesi: Bayburt Üniversitesi Örneği. Turk J Diab Obes. 2023;7(3):231-9.
• 4. Eftekharzadeh A, Khamseh ME, Farshchi A, Malek M. The association between subclinical hypothyroidism and metabolic syndrome as defined by the ATP III criteria. Metab Syndr Relat Disord. 2016; 14(3), 137-144.
• 5. Saklayen MG. The Global Epidemic of the Metabolic Syndrome. Curr Hypertens Rep. 2018;20(2):12.
• 6. Waters H, Graf M. America’s obesity crisis. The Health and Economic Costs of Excess Weight. Santa Monica, California: Milken Institute; 2018.
• 7. Emiral GO, Tozun M, Atalay BI, Goktas S, Dagtekin G, Aygar H, et al. Assessment of Knowledge of Metabolic Syndrome and Health Literacy Level among Adults in Western Turkey. Niger J Clin Pract.2021; 24(1): 28-37.
• 8. Laclaustra M, Corella D, Ordovas JM. Metabolic syndrome pathophysiology: the role of adipose tissue. Nutr Metab Cardiovasc Dis. 2007;17(2):125-139.
• 9. McCracken E, Monaghan M, Sreenivasan S. Pathophysiology of the metabolic syndrome. Clin Dermatol. 2018;36(1):14-20.
• 10. Esser N, Legrand-Poels S, Piette J, Scheen AJ, Paquot N. Inflammation as a link between obesity, metabolic syndrome and type 2 diabetes. Diabetes Res Clin Pract. 2014;105(2):141-150.
• 11. Torres S, Fabersani E, Marquez A, Gauffin-Cano P. Adipose tissue inflammation and metabolic syndrome. The proactive role of probiotics. Eur J Nutr. 2019;58(1):27-43.
• 12. Taylor VH, Macqueen GM. The Role of Adipokines in Understanding the Associations between Obesity and Depression. J Obes. 2010;2010:748048.
• 13. Balkoca F, Cubukcu M, Şimşek Yurt N. The Relationship Between Obesity with Depression and Anxiety Levels: a Cross-Sectional, Case-Control Study. Turk J Diab Obes. 2023;7(2):152-8.
• 14. Tuna S, Özden F, Yeniçeri N, Şahin C. Comparison of Cognitive Reserve, Depression and Anxiety in Patients with Diabetes Mellitus. Turk J Diab Obes. 2024;8(1):1-5.
• 15. Al-Khatib Y, Akhtar MA, Kanawati MA, Mucheke R, Mahfouz M, AlNufoury M. Depression and Metabolic Syndrome: A Narrative review. Cureus. 2022;14(2).
• 16. Jagannath A, Taylor L, Wakaf Z, Vasudevan SR, Foster RG. The genetics of circadian rhythms, sleep and health. Hum Mol Genet. 2017;26(R2)
• 17. Skene DJ, Skornyakov E, Chowdhury NR, Gajula RP, Middleton B, Satterfield BC, et al. Separation of circadian- and behavior- driven metabolite rhythms in humans provides a window on peripheral oscillators and metabolism. Proc Natl Acad Sci USA. 2018;115(30):7825-7830.
• 18. Alberti KGM, Zimmet P, Shaw J. The metabolic syndrome—a new worldwide definition. Lancet. 2005;366(9491):1059-1062.
• 19. Faul F, Erdfelder E, Lang AG, Buchner A. G* Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods. 2007;39(2), 175- 191.
• 20. Kenđel Jovanović G, Pavičić Žeželj S, Klobučar Majanović S, Mrakovcic‐Sutic I, Šutić I. Metabolic syndrome and its association with the Dietary Inflammatory Index (DII)® in a Croatian working population. J Hum Nutr Diet. 2020;33(1):128-137.
• 21. Pündük Z, Gür H, Ercan İ. Sabahçıl-akşamcıl anketi Türkçe uyarlamasında güvenilirlik çalışması. Turk Psikiyatri Derg. 2005;16:40-5.
• 22. Sariçam H. The psychometric properties of Turkish version of Depression Anxiety Stress Scale-21 (DASS-21) in health control and clinical samples. J Cogn Behav Psychother Res. 2018;7(1):19.
• 23. Shivappa N, Godos J, Hébert JR, Wirth MD, Piuri G, Speciani AF, et al. Designing and developing a literature-derived, population- based dietary inflammatory index. Public Health Nutr. 2014;17(8):1689-1696.
• 24. Yu JH, Yun CH, Ahn JH, Suh S, Cho HJ, Lee SK, et al. Evening chronotype is associated with metabolic disorders and body composition in middle-aged adults. J Clin Endocrinol Metab. 2015;100(4):1494-1502.
• 25. Vera B, Dashti HS, Gómez-Abellán P, Hernández-Martínez AM, Esteban A, Scheer FA, et al. Modifiable lifestyle behaviors, but not a genetic risk score, associate with metabolic syndrome in evening chronotypes. Sci Rep. 2018;8(1):945.
• 26. Kahl KG, Greggersen W, Schweiger U, Cordes J, Balijepalli C, Lösch C, et al. Prevalence of the metabolic syndrome in unipolar major depression. Eur Arch Psychiatry Clin Neurosci. 2012;262(4):313-320.
• 27. Vancampfort D, Correll CU, Wampers M, Sienaert P, Mitchell AJ, De Herdt A, et al. Metabolic syndrome and metabolic abnormalities in patients with major depressive disorder: a meta- analysis of prevalences and moderating variables. Psychol Med. 2014;44(10):2017-2028.
• 28. Muhammad HFL, van Baak MA, Mariman EC, Sulistyoningrum DC, Huriyati E, Lee YY, et al. Dietary Inflammatory Index Score and Its Association with Body Weight, Blood Pressure, Lipid Profile, and Leptin in Indonesian Adults. Nutrients. 2019;11(1):148.
• 29. Salari-Moghaddam A, Keshteli AH, Afshar H, Esmaillzadeh A, Adibi P. Association between dietary inflammatory index and psychological profile in adults. Clin Nutr. 2019;38(5):2360- 2368.
• 30. Salgado-Delgado R, Tapia Osorio A, Saderi N, Escobar C. Disruption of circadian rhythms: a crucial factor in the etiology of depression. Depress Res Treat. 2011;2011:839743.
• 31. Gao Q, Sheng J, Qin S, Zhang L. Chronotypes and affective disorders: A clock for mood?. Brain Sci Adv. 2019;5(3):145-160.
• 32. McClung CA. Circadian genes, rhythms and the biology of mood disorders. Pharmacol Ther. 2007;114(2):222-232.
• 33. Karimbeiki R, Alipoor E, Yaseri M, Shivappa N, Hebert JR, HosseinzadehAttar MJ. Association between the dietary inflammatory index and obesity in otherwise healthy adults: Role of age and sex. Int J Clin Pract. 2021;75(10)
• 34. Shi J, Liang Z, Zhang X, Ren S, Cheng Y, Liu Y, et al. Association of physical activity and dietary inflammatory index with overweight/obesity in US adults: NHANES 2007-2018. Environ Health Prev Med. 2023;28:40.
• 35. Ruiz-Canela M, Zazpe I, Shivappa N, Hébert JR, Sanchez-Tainta A, Corella D, et al. Dietary inflammatory index and anthropometric measures of obesity in a population sample at high cardiovascular risk from the PREDIMED (PREvencion con DIeta MEDiterranea) trial. Br J Nutr. 2015;113(6):984-995.
• 36. Khanna P, Aeri BT. Association of quantity and quality of protein intake with depression and anxiety symptoms among adolescent boys and girls (13–15 years) studying in public schools of Delhi. J Nutr Sci Vitaminol. 2020;66(Supplement)
• 37. Clemente-Suárez VJ, Mielgo-Ayuso J, Martín-Rodríguez A, Ramos-Campo DJ, Redondo-Flórez L, Tornero-Aguilera JF. The burden of carbohydrates in health and disease. Nutrients. 2022;14(18):3809.
• 38. Yao S, Zhang M, Dong SS, Wang JH, Zhang K, Guo J, et al. Bidirectional two-sample Mendelian randomization analysis identifies causal associations between relative carbohydrate intake and depression. Nat Hum Behav. 2022;6(11):1569-1576.
• 39. Nanri A, Eguchi M, Kuwahara K, Kochi T, Kurotani K, Ito R, et al. Macronutrient intake and depressive symptoms among Japanese male workers: the Furukawa Nutrition and Health Study. Psychiatry Res. 2014;220(1-2):263-268.
• 40. Li X, Chen M, Yao Z, Zhang T, Li Z. Dietary inflammatory potential and the incidence of depression and anxiety: a meta- analysis. J Health Popul Nutr. 2022;41(1):24.