Study finds link between diet diversity and reduced depression risk in knowledge workers

In a recent article published in BMC Public Health Journal, researchers conducted a multi-center cross‐sectional trial to investigate the association between dietary and sedentary habits outside of work and depressive symptoms in a large cohort of 118,723 knowledge workers in China.

Additionally, they pursued other factors driving depressive symptoms in this group for a more comprehensive systematic review.

Study: Association between dietary diversity, sedentary time outside of work and depressive symptoms among knowledge workers: a multi-center cross-sectional study. Image Credit: JoyStudio/Shutterstock.comStudy: Association between dietary diversity, sedentary time outside of work and depressive symptoms among knowledge workers: a multi-center cross-sectional study. Image Credit: JoyStudio/Shutterstock.com

Background

Studies have found both low-diversity diets and sedentary habits as risk factors for depression.

For instance, a previous study conducted among obese women from disadvantaged communities found that depressive symptoms were associated with diet but not exercise/physical activity.

However, there is a shortage of studies covering a large population of diverse types, including knowledge workers. Moreover, rarely have studies investigated the association of depressive symptoms with sedentary behavior outside of work.

Given the demanding nature of their jobs, knowledge workers, who are now abundant in the current service- and knowledge-based global economy, suffer numerous mental health issues, such as depression.

About the study

In the present study conducted between January 2018 and December 2020, researchers enrolled participants from several hospitals in China based on the following inclusion criteria: 

i) they were aged ≥18 years; 

ii) were knowledge workers as defined by Peter Drucker; 

iii) comprehend and write Chinese; 

iv) provided informed consent for participation; and 

v) provided demographic data and completed all lifestyle/dietary and depressive symptom surveys.

Per the protocol, they also completed an 86-item online survey at the medical center where they were enrolled.

The team analyzed four levels of sedentariness outside of work: less than two, two to four, four to six, and more than six hours every day.

They used the Chinese Food Pagoda as the Dietary Diversity Scale (DDS), where a total score of 1–5, 5-7, and 8-9 indicated insufficient [DDS-1], moderate [DDS-2], and adequate [DDS-3]. 

Notably, the Chinese Food Pagoda classifies foods into nine categories: grains, vegetables, fruits, livestock meat, fish, eggs, dairy products, beans/soy products, and fats, with each food category scored as one point, regardless of the quantity/frequency of the item consumed.

The team noted all participant's self-recall of the food eaten in the last three days. They also carefully noted whether they ate all three meals on time, had midnight snacks, were socially active, smoked, consumed coffee, sugary drinks, and alcohol. 

Further, they used the Patient Health Questionnaire-9 (PHQ-9) to evaluate depressive symptoms, wherein scores ranged between zero and 27, and the higher score indicated more severe depression.

The team performed several statistical tests to determine associations across categorical variables examined in this study, such as the chi-square test to compare different levels of dietary diversity and the presence or absence of depressive symptoms.

They used multilevel binary logistic regression to assess the relationship between demographics (age, gender, etc.), physical activity, sedentary behavior, DDS, and dietary habits.

Finally, they used the Spearman correlation coefficient technique to assess the strength and direction of the relationship between all study variables, where a p-value< 0.05 was considered statistically significant.

Results

The study results suggested that a higher proportion of knowledge workers (participants) reporting diets in the DDS-1 and DDS-2 showed depressive symptoms, while in the DDS-3 group, this relationship was inverse with an odds ratio (OR) of 0.91; 95% confidence interval (CI). 

In general, dietary diversity, especially in certain food groups, can decrease the risk of poor metabolic outcomes by improving the diversity of the gut microbiome.

Thus, increasing the dietary variety may reverse the percentage of depressive symptoms among knowledge workers, too.

Further, the results showed that knowledge workers who did not regularly eat their three meals were at an increased risk of depressive symptoms compared to those who did. Regular diets ensure adequate intake of nutrients, especially folic acid, zinc, and magnesium, which help maintain healthy brain function.

Intriguingly, knowledge workers who never overate showed a lower risk of depressive symptoms.

Furthermore, those who smoked and consumed alcohol in moderation had a lower risk of depressive symptoms in this study. On the contrary, consumption of sugary drinks daily likely exacerbated depressive symptomatology. 

Finally, knowledge workers who never engaged in physical activity had a higher rate of depressive symptoms, which progressed with the extent of their sedentary status.

The ORs for 2–4, 4-6, and >6 hours of sedentariness outside of work were 1.11, 1.21, and 1.49 and 95% CI, respectively.

Conclusions

Overall, a sedentary lifestyle outside of work and poor dietary diversity are risk factors for depressive symptoms for knowledge workers. Additionally, irregular eating and overeating are serious risk factors for depressive symptoms. 

This evidence is preliminary and requires further validation in future studies. Studies using objective indicators to explore the factors contributing to depressive symptoms among knowledge workers may shed more light on the underlying mechanisms governing these associations. 

Meanwhile, it remains crucial to implement interventions to improve knowledge workers' dietary diversity and reduce the time they spend sedentary outside of work.

Journal reference:
Neha Mathur

Written by

Neha Mathur

Neha is a digital marketing professional based in Gurugram, India. She has a Master’s degree from the University of Rajasthan with a specialization in Biotechnology in 2008. She has experience in pre-clinical research as part of her research project in The Department of Toxicology at the prestigious Central Drug Research Institute (CDRI), Lucknow, India. She also holds a certification in C++ programming.

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