Breakfast skipping and risk of all-cause, cardiovascular and cancer mortality among adults: a systematic review and meta-analysis of prospective cohort studies.
Yanqi WangFengjuan LiXinying LiJun WuXiaojuan ChenYuhao SuTianhang QinXiaoning LiuLei LiangJianping MaPei QinPublished in: Food & function (2024)
Background : Numerous studies reported inconsistent association between breakfast skipping and all-cause, cardiovascular disease (CVD) and cancer mortality. Therefore, we conducted a systematic review and meta-analysis to elucidate these associations. Methods : PubMed, Embase, and Web of Science databases were searched up to July 2023 for prospective cohort studies that assessed the association between breakfast skipping and all-cause, CVD and cancer mortality in general adults. A random effect model was used to estimate the pooled hazard ratio (HR) and 95% confidence intervals (CIs), with subgroup analysis and sensitivity analysis performed. The Newcastle-Ottawa Scale (NOS) was used to assess the study and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) tool was used to assess the risk of bias. Results : The final analysis included 9 cohort studies including 242 095 participants, with 6 studies for all-cause mortality, 4 studies for CVD mortality, and 2 studies for cancer mortality. Compared to regular breakfast consumption, skipping breakfast was associated with a higher risk of all-cause (HR: 1.27, 95% CI, 1.07-1.51, I 2 = 77%), CVD (HR 1.28, 95% CI 1.10-1.50, I 2 = 0), and cancer (HR: 1.34, 95% CI: 1.11-1.61, I 2 = 0%) mortality. Sensitivity analysis revealed inconsistent results in all-cause and CVD mortality. Subgroup analysis showed significant association in studies with larger participants, longer follow-up, adjustments for energy intake, and high-quality articles. GRADE showed very low evidence for all-cause mortality and low evidence for CVD and cancer mortality. Conclusion : The findings underscore the importance of regular breakfast habits for health and longevity. However, these results require careful interpretation due to geographic limitations, potential heterogeneity, and instability.
Keyphrases
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- type diabetes
- childhood cancer
- machine learning
- squamous cell carcinoma
- nitric oxide
- coronary artery disease
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