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1.
JAMA Netw Open ; 7(4): e244602, 2024 Apr 01.
Article in English | MEDLINE | ID: mdl-38607629

ABSTRACT

Importance: Although cardiovascular disease (CVD) is a known risk factor for depression, evidence is lacking regarding whether and to what extent a spouse's CVD is associated with the subsequent mental health of individuals. Objective: To examine the association between CVD onset in spouses and subsequent depression. Design, Setting, and Participants: This cohort study examined 277 142 matched married couples enrolled in the Japan Health Insurance Association health insurance program between April 2015 and March 2022, covering approximately 40% of the working-age population in Japan. Index individuals (primary insured) whose spouses (dependent) experienced incident CVD between April 2016 and March 2022 were 1:1 matched to controls whose spouses did not experience CVD. Matching was based on age, sex, income, or the onset date of the spouses' CVD. Data analysis was conducted from April 2016 to March 2022. Exposure: Spousal onset of CVD between fiscal years 2016 and 2021. The International Statistical Classification of Diseases and Related Health Problems, Tenth Revision codes were used to identify the composite CVD outcomes (stroke, heart failure, and myocardial infarction). Main Outcomes and Measures: Multivariate Cox proportional hazards models were used to investigate the association between spouses' new-onset CVD and individuals' depression, adjusting for sociodemographic characteristics and comorbidities of index individuals (diabetes, hypertension, and CVD) and spouses (diabetes, hypertension, and depression). Subgroup analyses were conducted according to sex, age, income levels, and history of CVD. Results: Among 277 142 matched pairs of married couples, 263 610 (95.1%) had a male index individual; the mean (SD) age of index individuals was 58.2 (10.2) years. A new onset of depression was observed in 4876 individuals (1.8%). In multivariable Cox models, there was an association between the spouse's CVD and the individuals' depression (hazard ratio, 1.13 [95% CI, 1.07-1.20]). The subgroup analysis found no evidence of heterogeneity in sex, age, income level, or CVD history. The results were consistent when additionally adjusted for health behaviors (smoking, alcohol consumption, physical activity, and use of antihypertensive drugs) and objectively measured physical health conditions (body mass index, blood pressure, cholesterol levels, glucose levels, and estimated glomerular filtration rate) (hazard ratio, 1.16 [95% CI, 1.06-1.28]). Conclusions and Relevance: In this nationwide cohort study of matched couples, a spouse's onset of CVD was associated with an increased risk of an individual's depression. These findings highlight the importance of preventive care for mental health disorders in individuals whose spouses experience incident CVD.


Subject(s)
Diabetes Mellitus , Hypertension , Myocardial Infarction , Humans , Male , Middle Aged , Spouses , Cohort Studies , Depression/epidemiology
2.
Nat Commun ; 15(1): 1214, 2024 Feb 09.
Article in English | MEDLINE | ID: mdl-38331890

ABSTRACT

The optimal interval between the first and second doses of COVID-19 mRNA vaccines has not been thoroughly evaluated. Employing a target trial emulation approach, we compared the effectiveness of different interdose intervals among >6 million mRNA vaccine recipients in Georgia, USA, from December 2020 to March 2022. We compared three protocols defined by interdose interval: recommended by the Food and Drug Administration (FDA) (17-25 days for Pfizer-BioNTech; 24-32 days for Moderna), late-but-allowable (26-42 days for Pfizer-BioNTech; 33-49 days for Moderna), and late ( ≥ 43 days for Pfizer-BioNTech; ≥50 days for Moderna). In the short-term, the risk of SARS-CoV-2 infection was lowest under the FDA-recommended protocol. Longer-term, the late-but-allowable protocol resulted in the lowest risk (risk ratio on Day 120 after the first dose administration compared to the FDA-recommended protocol: 0.83 [95% confidence interval: 0.82-0.84]). Here, we showed that delaying the second dose by 1-2 weeks may provide stronger long-term protection.


Subject(s)
COVID-19 , United States , Humans , COVID-19/prevention & control , COVID-19 Vaccines , SARS-CoV-2/genetics , Georgia , RNA, Messenger
3.
Mayo Clin Proc Innov Qual Outcomes ; 7(4): 203-211, 2023 Aug.
Article in English | MEDLINE | ID: mdl-37304061

ABSTRACT

Objective: To examine differences in the association between educational attainment and mortality by the presence of diabetes and diabetic retinopathy (DR)-a major complication of diabetes. Patients and Methods: We used a nationally representative sample of 54,924 US adults aged 20 years or older with diabetes from the National Health and Nutrition Examination Survey 1999-2018 and its mortality data through 2019. We applied the multivariable Cox proportional hazard models to investigate the associations between educational attainment (low, less than high school; middle, high school; and high, more than high school) and all-cause mortality according to diabetes status: nondiabetes, diabetes without DR, and diabetes with DR. Differences in the survival rate by educational attainment were evaluated using the slope inequality index (SII). Results: Among the 54,924 participants (mean age, 49.9 years), adults in the low educational group reported an increased risk of all-cause mortality compared with those of the high educational group in any diabetes status (nondiabetes-hazard ratio [HR], 1.69; 95% CI, 1.56-1.82; diabetes without DR-HR, 1.61; 95% CI, 1.37-1.90; diabetes with DR-HR, 1.43; 95% CI, 1.10-1.86). SIIs among the diabetes without DR group and diabetes with DR group were 22.17 and 20.87 per 1000 person-years, respectively, which were 2 times greater than those among the nondiabetes group (SII=9.94). Conclusion: The differences in the mortality risks owing to the educational attainment increased by the presence of diabetes regardless of the complication of DR. Our findings indicate that prevention of diabetes itself is critical to mitigate health disparities by socioeconomic status such as education status.

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