Carson, April P

ImportanceThere are consistent data demonstrating that socioeconomic disadvantage is associated with risk of premature mortality, but research on the relationship between neighborhood socioeconomic factors and premature mortality is limited. Most studies evaluating the association between neighborhood socioeconomic status (SES) and mortality have used a single assessment of SES during middle to older adulthood, thereby not considering the contribution of early life neighborhood SES.ObjectiveTo investigate the association of life course neighborhood SES and premature mortality.Design, Setting, and ParticipantsThis cohort study included Black and White participants of the multicenter Atherosclerosis Risk in Communities Study, a multicenter study conducted in 4 US communities: Washington County, Maryland; Forsyth County, North Carolina; Jackson, Mississippi; and the northwestern suburbs of Minneapolis, Minnesota. Participants were followed up for a mean (SD) of 18.8 (5.7) years (1996-2020). Statistical analysis was performed from March 2023 through May 2024.ExposureParticipants’ residential addresses during childhood, young adulthood, and middle adulthood were linked with US Census–based socioeconomic indicators to create summary neighborhood SES scores for each of these life epochs. Neighborhood SES scores were categorized into distribution-based tertiles.Main Outcomes and MeasuresPremature death was defined as all-cause mortality occurring before age 75 years. Multivariable-adjusted Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% CIs.ResultsAmong 12 610 study participants, the mean (SD) age at baseline was 62.6 (5.6) years; 3181 (25.2%) were Black and 9429 (74.8%) were White; and 7222 (57.3%) were women. The lowest, compared with the highest tertile, of neighborhood SES score in middle adulthood was associated with higher risk of premature mortality (HR, 1.28; 95% CI, 1.07-1.54). Similar associations were observed for neighborhood SES in young adulthood among women (HR, 1.25; 95% CI, 1.00-1.56) and neighborhood SES in childhood among White participants (HR, 1.25; 95% CI, 1.01-1.56). Participants whose neighborhood SES remained low from young to middle adulthood had an increased premature mortality risk compared with those whose neighborhood SES remained high (HR, 1.25; 95% CI, 1.05-1.49).Conclusions and RelevanceIn this study, low neighborhood SES was associated with premature mortality. The risk of premature mortality was greatest among individuals experiencing persistently low neighborhood SES from young to middle adulthood. Place-based interventions that target neighborhood social determinants of health should be designed from a life course perspective that accounts for early-life socioeconomic inequality.

ImportancePersistent symptoms and disability following SARS-CoV-2 infection, known as post–COVID-19 condition or “long COVID,” are frequently reported and pose a substantial personal and societal burden.ObjectiveTo determine time to recovery following SARS-CoV-2 infection and identify factors associated with recovery by 90 days.Design, Setting, and ParticipantsFor this prospective cohort study, standardized ascertainment of SARS-CoV-2 infection was conducted starting in April 1, 2020, across 14 ongoing National Institutes of Health–funded cohorts that have enrolled and followed participants since 1971. This report includes data collected through February 28, 2023, on adults aged 18 years or older with self-reported SARS-CoV-2 infection.ExposurePreinfection health conditions and lifestyle factors assessed before and during the pandemic via prepandemic examinations and pandemic-era questionnaires.Main Outcomes and MeasuresProbability of nonrecovery by 90 days and restricted mean recovery times were estimated using Kaplan-Meier curves, and Cox proportional hazards regression was performed to assess multivariable-adjusted associations with recovery by 90 days.ResultsOf 4708 participants with self-reported SARS-CoV-2 infection (mean [SD] age, 61.3 [13.8] years; 2952 women [62.7%]), an estimated 22.5% (95% CI, 21.2%-23.7%) did not recover by 90 days post infection. Median (IQR) time to recovery was 20 (8-75) days. By 90 days post infection, there were significant differences in restricted mean recovery time according to sociodemographic, clinical, and lifestyle characteristics, particularly by acute infection severity (outpatient vs critical hospitalization, 32.9 days [95% CI, 31.9-33.9 days] vs 57.6 days [95% CI, 51.9-63.3 days]; log-rank P < .001). Recovery by 90 days post infection was associated with vaccination prior to infection (hazard ratio [HR], 1.30; 95% CI, 1.11-1.51) and infection during the sixth (Omicron variant) vs first wave (HR, 1.25; 95% CI, 1.06-1.49). These associations were mediated by reduced severity of acute infection (33.4% and 17.6%, respectively). Recovery was unfavorably associated with female sex (HR, 0.85; 95% CI, 0.79-0.92) and prepandemic clinical cardiovascular disease (HR, 0.84; 95% CI, 0.71-0.99). No significant multivariable-adjusted associations were observed for age, educational attainment, smoking history, obesity, diabetes, chronic kidney disease, asthma, chronic obstructive pulmonary disease, or elevated depressive symptoms. Results were similar for reinfections.Conclusions and RelevanceIn this cohort study, more than 1 in 5 adults did not recover within 3 months of SARS-CoV-2 infection. Recovery within 3 months was less likely in women and those with preexisting cardiovascular disease and more likely in those with COVID-19 vaccination or infection during the Omicron variant wave.

Background The relationship between mitochondrial DNA copy number (mtDNA CN) and cardiovascular disease remains elusive. Methods and Results We performed cross‐sectional and prospective association analyses of blood‐derived mtDNA CN and cardiovascular disease outcomes in 27 316 participants in 8 cohorts of multiple racial and ethnic groups with whole‐genome sequencing. We also performed Mendelian randomization to explore causal relationships of mtDNA CN with coronary heart disease (CHD) and cardiometabolic risk factors (obesity, diabetes, hypertension, and hyperlipidemia). P <0.01 was used for significance. We validated most of the previously reported associations between mtDNA CN and cardiovascular disease outcomes. For example, 1‐SD unit lower level of mtDNA CN was associated with 1.08 (95% CI, 1.04–1.12; P <0.001) times the hazard for developing incident CHD, adjusting for covariates. Mendelian randomization analyses showed no causal effect from a lower level of mtDNA CN to a higher CHD risk (β=0.091; P =0.11) or in the reverse direction (β=−0.012; P =0.076). Additional bidirectional Mendelian randomization analyses revealed that low‐density lipoprotein cholesterol had a causal effect on mtDNA CN (β=−0.084; P <0.001), but the reverse direction was not significant ( P =0.059). No causal associations were observed between mtDNA CN and obesity, diabetes, and hypertension, in either direction. Multivariable Mendelian randomization analyses showed no causal effect of CHD on mtDNA CN, controlling for low‐density lipoprotein cholesterol level ( P =0.52), whereas there was a strong direct causal effect of higher low‐density lipoprotein cholesterol on lower mtDNA CN, adjusting for CHD status (β=−0.092; P <0.001). Conclusions Our findings indicate that high low‐density lipoprotein cholesterol may underlie the complex relationships between mtDNA CN and vascular atherosclerosis.

OBJECTIVE Given temporal changes in diabetes prevalence and stroke incidence, this study investigated age, race, and sex differences in the diabetes–stroke association in a contemporary prospective cohort, the REasons for Geographic and Racial Differences in Stroke (REGARDS) Study. RESEARCH DESIGN AND METHODS We included 23,002 non-Hispanic black and white U.S. adults aged ≥45 years without prevalent stroke at baseline (2003–2007). Diabetes was defined as fasting glucose ≥126 mg/dL, random glucose ≥200 mg/dL, or use of glucose-lowering medication. Incident stroke events were expert adjudicated and available through September 2017. RESULTS The prevalence of diabetes was 19.1% at baseline. During follow-up, 1,018 stroke events occurred. Among adults aged &lt;65 years, comparing those with diabetes to those without diabetes, the risk of stroke was increased for white women (hazard ratio [HR] 3.72 [95% CI 2.10–6.57]), black women (HR 1.88 [95% CI 1.22–2.90]), and white men (HR 2.01 [95% CI 1.27–3.27]) but not black men (HR 1.27 [95% CI 0.77–2.10]) after multivariable adjustment. Among those aged ≥65 years, diabetes increased the risk of stroke for white women and black men, but not black women (HR 1.05 [95% CI 0.74–1.48]) or white men (HR 0.86 [95% CI 0.62–1.21]). CONCLUSIONS In this contemporary cohort, the diabetes–stroke association varied by age, race, and sex together, with a more pronounced effect observed among adults aged &lt;65 years. With the recent increase in the burden of diabetes complications at younger ages in the U.S., additional efforts are needed earlier in life for stroke prevention among adults with diabetes.

OBJECTIVE Stroke symptoms among individuals reporting no physician diagnosis of stroke are associated with an increased risk of future stroke. Few studies have assessed whether individuals with diabetes or prediabetes, but no physician diagnosis of stroke, have an increased prevalence of stroke symptoms. RESEARCH DESIGN AND METHODS This study included 25,696 individuals aged ≥45 years from the REasons for Geographic And Racial Differences in Stroke (REGARDS) study who reported no history of stroke or transient ischemic attack at baseline (2003–2007). Glucose measurements, medication use, and self-reported physician diagnosis were used to categorize participants into diabetes, prediabetes, or normal glycemia groups. The presence of six stroke symptoms was assessed using a validated questionnaire. RESULTS The prevalence of any stroke symptom was higher among participants with diabetes (22.7%) compared with those with prediabetes (15.6%) or normal glycemia (14.9%). In multivariable models, diabetes was associated with any stroke symptom (prevalence odds ratio [POR] 1.28 [95% CI 1.18–1.39]) and two or more stroke symptoms (1.26 [1.12–1.43]) compared with normal glycemia. In analyses of individual stroke symptoms, diabetes was associated with numbness (1.15 [1.03–1.29]), vision loss (1.52 [1.31–1.76]), half-vision loss (1.54 [1.30–1.84]), and lost ability to understand people (1.34 [1.12–1.61]) after multivariable adjustment. No association was present between prediabetes and stroke symptoms. CONCLUSIONS In this population-based study, almost one in four individuals with diabetes reported stroke symptoms, which suggests that screening for stroke symptoms in diabetes may be warranted.