Evidence Hub

Association of the dietary phytochemical index with circadian rhythm and mental health in overweight and obese women: A cross-sectional study

Z. Noruzi, Farideh Shiraseb, Atieh Mirzababaei, K. Mirzaei

Clinical Nutrition ESPEN, 2022

13 citations

Abstract

BACKGROUND

Previous studies showed that some dietary indexes are the most important reasons to increase the incidence and spread of mental health disorders and circadian rhythm. We aimed to assess the association between the phytochemical index with circadian rhythm and mental health disorders in obese and overweight women.

METHODS

Participants were selected from different health centers by a multistage cluster random sampling method. Dietary intake was assessed by a semi-quantitative food frequency questionnaire (FFQ) with 147 items. Dietary phytochemical index (DPI) was estimated using the following formula: (daily energy derived from phytochemical-rich foods (kcal)/total daily energy intake (kcal)) × 100. Symptoms of mental health disorders were assessed using a validated depression, anxiety, stress scales (DASS) questionnaire with 21-items. The Circadian rhythm was assessed by the morningness-eveningness questionnaire (MEQ).

RESULTS

The mean age and BMI of our participants were 35.19 and 30.48, kg/m2 respectively. After controlling for potential confounders, women in the highest tertile of phytochemical index (PI) had a lower prevalence of depression (P = 0.023) and would be rarely morning type (OR = 1.044, 95% CI 1-1.090) compared with those in the lowest tertile of the PI. In contrast, there was no association between PI and anxiety (OR = 1.001, 95% CI 0.945-1.060) and stress (OR = 0.992, 95% CI 0.940-1.046).

CONCLUSION

We found that high adherence to PI can decrease…

How strong is the evidence?

Evidence Hub reads this as a cross-sectional, done in people. Its evidence level is 4 of 5 (Low · observational). Observational designs can show an association but not prove cause.

How the five levels of evidence work. The level is assigned automatically from the abstract and can be wrong, so check the paper.

Read the paper

Related studies

Go deeper in Evidence Hub

Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.

Open this study Sign up free