1
|
Islam Z, Yamamoto S, Mizoue T, Konishi M, Ohmagari N. Coffee and Green Tea Consumption With the Risk of COVID-19 Among the Vaccine Recipients in Japan: A Prospective Study. J Epidemiol 2024; 34:444-452. [PMID: 38346747 PMCID: PMC11330706 DOI: 10.2188/jea.je20230231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/22/2024] Open
Abstract
BACKGROUND While coffee and green tea have been suggested to have immunoprotective effects, it remains elusive whether they can decrease the risk of coronavirus disease 2019 (COVID-19). OBJECTIVE We prospectively examined the associations of coffee and green tea consumption with the risk of COVID-19 among mRNA vaccine recipients during the epidemic of the Omicron variant. METHODS Participants were 2,110 staff (aged 18 to 76 years) of a large medical facility in Tokyo, who attended a serosurvey in June 2022, predominantly received ≥3 doses of vaccine, and were followed for COVID-19 until December 2022. Coffee and green tea consumption was ascertained via a questionnaire. COVID-19 was identified through the in-house registry. Cox proportional hazards model was used to estimate the hazard ratios (HRs) of COVID-19 across the categories of beverage consumption. RESULTS During 6 months of follow-up, 225 (10.6%) cases of COVID-19 were identified. Contrary to the expectation, higher consumption of coffee was associated with a significant increase in the risk of COVID-19; multivariable-adjusted HRs were 1.00 (reference), 0.92 (95% confidence interval [CI], 0.62-1.35), 1.48 (95% CI, 0.99-2.22), and 1.82 (95% CI, 1.20-2.76) for <1 cup/day, 1 cup/day, 2 cups/day, and ≥3 cups/day, respectively (P trend = 0.003). Green tea consumption was not significantly associated with the risk of COVID-19. The association with coffee was attenuated if serologically detected infection was added to the cases. CONCLUSION In a cohort of Japanese hospital staff who received COVID-19 vaccine, higher consumption of coffee was associated with an increased risk of COVID-19 during the epidemic of the Omicron variant. There was no evidence of a significant association between green tea consumption and COVID-19 risk.
Collapse
Affiliation(s)
- Zobida Islam
- Department of Epidemiology and Prevention, Center for Clinical Sciences, National Center for Global Health and Medicine
| | - Shohei Yamamoto
- Department of Epidemiology and Prevention, Center for Clinical Sciences, National Center for Global Health and Medicine
| | - Tetsuya Mizoue
- Department of Epidemiology and Prevention, Center for Clinical Sciences, National Center for Global Health and Medicine
| | - Maki Konishi
- Department of Epidemiology and Prevention, Center for Clinical Sciences, National Center for Global Health and Medicine
| | - Norio Ohmagari
- Center Hospital of the National Center for Global Health and Medicine
| |
Collapse
|
2
|
Song X, He K, Xu T, Tian Z, Zhang J, He Y, Fang J, Jiang K, Fan X, Tao Y, Jin L. Association of macronutrient consumption quality, food source and timing with depression among US adults: A cross-sectional study. J Affect Disord 2024; 351:641-648. [PMID: 38309482 DOI: 10.1016/j.jad.2024.01.252] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 01/24/2024] [Accepted: 01/26/2024] [Indexed: 02/05/2024]
Abstract
BACKGROUND Growing evidence suggests that meal timing may influence dietary choices and mental health. Thus, this study examined the association between macronutrient consumption quality, food source, meal timing, and depression prevalence in Americans. METHODS 23,313 National Health and Nutrition Survey participants from 2007 to 2016 were included in this cross-sectional study. Macronutrient intake was calculated for all day, dinner, and breakfast and subtypes into 4 classes. Based on the Patient Health Questionnaire, depression was defined as a 9-item score ≥ 10 on the PHQ-9. The correlation between macronutrients and depression prevalence was estimated with multivariable logistic regression models and isocaloric substitution effects. RESULTS Low-quality carbohydrates (OR = 1.54, 95 % CI: 1.11, 2.12) were positively linked to depression compared with the lowest quartile, after adjusting for age and other covariates. In contrast, total high-quality carbohydrate (OR = 0.52, 95 % CI: 0.40, 0.66), total animal protein (OR = 0.60, 95 % CI: 0.45, 0.80), and total vegetable protein (OR = 0.61, 95 % CI: 0.43, 0.85) were negatively associated with depression was negatively associated. Replacing low-quality carbohydrates with high-quality carbohydrates throughout the day reduced the risk of depression by approximately 15 %. LIMITATIONS Cross-sectional data. CONCLUSION All in all, diet plays a crucial role in the prevention and treatment of depression. Especially in terms of macronutrient intake, high-quality, moderate intake can reduce the risk of depression. However, different subtypes of macronutrient consumption may have different effects on depression, so it becomes crucial to carefully consider the selection and combination of macronutrients.
Collapse
Affiliation(s)
- Xingxu Song
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Jilin, Changchun, China.
| | - Kai He
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Jilin, Changchun, China
| | - Tong Xu
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Jilin, Changchun, China.
| | - Zhong Tian
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Jilin, Changchun, China.
| | - Jiaqi Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Jilin, Changchun, China.
| | - Yue He
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Jilin, Changchun, China.
| | - Jiaxin Fang
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Jilin, Changchun, China.
| | - Kexin Jiang
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Jilin, Changchun, China.
| | - Xiaoting Fan
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Jilin, Changchun, China.
| | - Yuchun Tao
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Jilin, Changchun, China.
| | - Lina Jin
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Jilin, Changchun, China.
| |
Collapse
|