Sixty-four percent of adults in America drink coffee daily, and caffeine is the main reason people tend to drink coffee habitually. Few studies have examined the association between caffeine and all-cause and cause-specific mortality. The objective of this study was to examine the association between caffeine and all-cause and cause-specific mortality using the National Health and Nutrition Examination Survey (NHANES) 1999–2014 database. The multivariate Cox proportional hazards regression model was used to examine 23,878 individuals 20 years and older. Daily caffeine intake was measured once at baseline. A total of 2206 deaths occurred, including 394 cardiovascular (CVD) deaths and 525 cancer deaths. Compared to those with a caffeine intake of 200 mg/day (HR, 0.67; 95% CI, 0.50–0.88) after adjusting for potential confounders. The HRs for all-cause mortality were significantly lower in the participants with a caffeine intake of 100–200 mg/day (HR, 0.78; 95% CI, 0.67–0.91), and those with a caffeine intake of >200 mg/day (HR, 0.68; 95% CI, 0.60–0.78). Subgroup analyses showed that caffeine may have different effects on all-cause mortality among different age and body mass index (BMI) groups. In conclusion, higher caffeine intake was associated with lower all-cause and CVD mortality.

This study examines the association of sociodemographic risk factors and the comorbidities of COVID-19. Most COVID-19-related studies were conducted in inpatient settings among patients with severe infection during the first and second waves of the pandemic. The third wave with less severe Omicron variant presented a unique opportunity to observe the adult patients treated in outpatient settings. We conducted a cross-sectional study (117 patients aged > 40 years presented with symptomatic COVID-19). We employed the Charlson Comorbidity Index (CCI) to compute comorbidity burden, Medical Outcomes Survey Short form (SF-12) to measure general health, and Self-care Self- Efficacy Scale (SCSES) to assess self-care ability. Fisher’s exact test and analysis of variance (ANOVA) were used to compute the relationship between comorbidities and demographics. This study report focuses on the distribution of the comorbidities and its relationship to demographic variables. The top five comorbidities were hypertension (42%), diabetes (31%), pulmonary disease/asthma (19%), depression (14%), and cancer (11%). Depression was significantly higher among younger age groups (p<0.01) and women (p<0.05). Age (p<0.0001) and income (p<0.01) were the most significantly associated demographics with the comorbidity burden. Incidence of pulmonary disease showed a positive association to educational status (p=0.05). This was the first study to report a significant prevalence of depression among adults with symptomatic COVID-19.