Background: Results from observational and genetic epidemiological studies suggest that lower serum homocysteine levels are associated with lower incidence of cardiovascular disease (CVD). Numerous randomized controlled trials have investigated the efficacy of lowering homocysteine with folic acid supplementation for CVD risk, but conflicting results have been reported. Methods and Results: Three bibliographic databases (Medline, Embase, and the Cochrane Database of Systematic Reviews) were searched from database inception until December 1, 2015. Of the 1933 references reviewed for eligibility, 30 randomized controlled trials involving 82 334 participants were included in the final analysis. The pooled relative risks of folic acid supplementation compared with controls were 0.90 (95% CI 0.84–0.96; P =0.002) for stroke, 1.04 (95% CI 0.99–1.09; P =0.16) for coronary heart disease, and 0.96 (95% CI 0.92–0.99; P =0.02) for overall CVD. The intervention effects for both stroke and combined CVD were more pronounced among participants with lower plasma folate levels at baseline (both P <0.02 for interaction). In stratified analyses, a greater beneficial effect for overall CVD was seen in trials among participants without preexisting CVD ( P =0.006 for interaction) or in trials with larger reduction in homocysteine levels ( P =0.009 for interaction). Conclusions: Our meta‐analysis indicated a 10% lower risk of stroke and a 4% lower risk of overall CVD with folic acid supplementation. A greater benefit for CVD was observed among participants with lower plasma folate levels and without preexisting CVD and in studies with larger decreases in homocysteine levels. Folic acid supplementation had no significant effect on risk of coronary heart disease.

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OBJECTIVE To cross-sectionally and prospectively investigate the association between irregular sleep patterns, a potential marker for circadian disruption, and metabolic abnormalities. RESEARCH DESIGN AND METHODS In the Multi-Ethnic Study of Atherosclerosis, participants completed 7-day actigraphy at exam 5 (2010–2013) and were prospectively followed throughout exam 6 (2016 to 2017). Sleep regularity was quantified by the 7-day SD of actigraphy-assessed sleep duration and sleep onset timing. Metabolic abnormalities were defined by 1) the National Cholesterol Education Program Adult Treatment Panel III criteria and 2) a data-driven clustering of metabolic factors. RESULTS In the exam 5 cross-sectional analysis adjusted for sociodemographic and lifestyle factors (n = 2,003), every 1-h increase in the sleep duration SD was associated with 27% (95% CI 1.10, 1.47) higher odds of metabolic syndrome, and every 1-h increase in the sleep timing SD was associated with 23% (95% CI 1.06, 1.42) higher odds. The associations remained significant with additional adjustment for sleep-related factors including sleep duration. In the prospective analysis (n = 970), the corresponding fully adjusted odds ratio (OR) was 1.27 (95% CI 0.97, 1.65) for sleep duration and 1.36 (1.03, 1.80) for sleep timing. Compared with the cluster of few metabolic changes, every 1-h increase in sleep variability was associated with almost doubled odds for the cluster characterized by incidence of multiple metabolic abnormalities (OR 1.97 [95% CI 1.18, 3.30] for sleep duration and OR 2.10 [95% CI 1.25, 3.53] for sleep timing). CONCLUSIONS Increased variability in sleep duration and timing was associated with higher prevalence and incidence of metabolic abnormalities even after consideration of sleep duration and other lifestyle factors.

OBJECTIVE: Multiple lines of evidence support a complex relationship between obstructive sleep apnea (OSA) and diabetes. However, no population-based study has evaluated the potential bidirectional association between these two highly prevalent disorders. RESEARCH DESIGN AND METHODS: We followed 146,519 participants from the Nurses' Health Study (NHS; 2002–2012), Nurses’ Health Study II (NHSII; 1995–2013), and Health Professionals Follow-up Study (HPFS; 1996–2012) who were free of diabetes, cardiovascular disease, and cancer at baseline. Cox proportional hazards models were used to estimate hazard ratios (HRs) for developing diabetes according to OSA status. In parallel, we used similar approaches to estimate risk of developing OSA according to diabetes status among 151,194 participants free of OSA, cardiovascular disease, and cancer at baseline. In all three cohorts, diagnoses of diabetes and OSA were identified by validated self-reports. RESULTS: Similar results were observed across the three cohorts. In the pooled analysis, 9,029 incident diabetes cases were identified during follow-up. After accounting for potential confounders, the HR (95% CI) for diabetes was 2.06 (1.86, 2.28) comparing those with versus without OSA. The association was attenuated but remained statistically significant after further adjusting for waist circumference and BMI (HR 1.37 [95% CI 1.24, 1.53]), with the highest diabetes risk observed for OSA concomitant with sleepiness (1.78 [1.13, 2.82]). In the second analysis, we documented 9,364 incident OSA cases during follow-up. Compared with those without diabetes, the multivariable HR (95% CI) for OSA was 1.53 (1.32, 1.77) in individuals with diabetes. Adjustment for BMI and waist circumference attenuated the association (1.08 [1.00, 1.16]); however, an increased risk was observed among those with diabetes who used insulin compared with those without diabetes (1.43 [1.11, 1.83]), particularly among women (1.60 [1.34, 1.89]). CONCLUSIONS: OSA is independently associated with an increased risk of diabetes, whereas insulin-treated diabetes is independently associated with a higher risk of OSA, particularly in women. Clinical awareness of this bidirectional association may improve prevention and treatment of both diseases. Future research aimed at elucidating the mechanisms that underlie each association may identify novel intervention targets.