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Objectives Adiposity may have a role in the risk of dementia. Fewer studies have focused on the relationship between change in adiposity and cognitive decline. Our study aimed to explore the association between the change in adiposity and cognitive function in Black and White older adults. Methods The participants were 12,204 older adults without cognitive impairment (62.8 ± 8.0 years) in the United States. The percent body mass index change (%BMI change) and percent waist circumference change (%WC change) were measured at 2 in-home visits (first: 2003–2007, second: 2013–2016). Cognitive status was assessed by the Six-Item Screener annually. Memory and executive function were measured by word list learning, MOCA recall and orientation, and letter and animal fluency every 2 years. Logistic regression or linear regression models were used to estimate the relationship between percent change in adiposity and cognitive function. Results After 12.7 ± 1.7 years, a greater decrease in %BMI change or %WC change was significantly associated with a higher risk of cognitive impairment. Compared to older adults with −5% ≤ change ≤ 5% from baseline, a significantly higher risk of cognitive impairment and greater loss in memory and executive function were found among those who experienced more than a 10% decline in %BMI change or %WC change. Older adults who experienced a 5%–10% decrease in %BMI change had a higher risk of cognitive impairment and greater loss of memory compared to those with −5% ≤ change ≤ 5%. Discussion A greater decrease in %BMI (>5%) and %WC (>10%) change was associated with greater cognitive loss observed over time. [ABSTRACT FROM AUTHOR]

ObjectiveTo assess whether there are differences in the strength of association with incident stroke for specific periods of life in the Stroke Belt (SB).MethodsThe risk of stroke was studied in 24,544 black and white stroke-free participants, aged 45+, in the Reasons for Geographic and Racial Differences in Stroke study, a national population-based cohort enrolled 2003-2007. Incident stroke was defined as first occurrence of stroke over an average 5.8 years of follow-up. Residential histories (city/state) were obtained by questionnaire. SB exposure was quantified by combinations of SB birthplace and current residence and proportion of years in SB during discrete age categories (0-12, 13-18, 19-30, 31-45, last 20 years) and entire life. Proportional hazards models were used to establish association of incident stroke with indices of exposure to SB, adjusted for demographic, socioeconomic (SES), and stroke risk factors.ResultsIn the demographic and SES models, risk of stroke was significantly associated with proportion of life in the SB and with all other exposure periods except birth, ages 31-45, and current residence. The strongest association was for the proportion of the entire life in SB. After adjustment for risk factors, the risk of stroke remained significantly associated only with proportion of residence in SB in adolescence (hazard ratio 1.17, 95% confidence interval 1.00-1.37).ConclusionsChildhood emerged as the most important period of vulnerability to SB residence as a predictor of future stroke. Improvement in childhood health circumstances should be considered as part of long-term health improvement strategies in the SB.

BackgroundDiabetes prevalence and incidence vary by neighborhood socioeconomic environment (NSEE) and geographic region in the United States. Identifying modifiable community factors driving type 2 diabetes disparities is essential to inform policy interventions that reduce the risk of type 2 diabetes. ObjectiveThis paper aims to describe the Diabetes Location, Environmental Attributes, and Disparities (LEAD) Network, a group funded by the Centers for Disease Control and Prevention to apply harmonized epidemiologic approaches across unique and geographically expansive data to identify community factors that contribute to type 2 diabetes risk. MethodsThe Diabetes LEAD Network is a collaboration of 3 study sites and a data coordinating center (Drexel University). The Geisinger and Johns Hopkins University study population includes 578,485 individuals receiving primary care at Geisinger, a health system serving a population representative of 37 counties in Pennsylvania. The New York University School of Medicine study population is a baseline cohort of 6,082,146 veterans who do not have diabetes and are receiving primary care through Veterans Affairs from every US county. The University of Alabama at Birmingham study population includes 11,199 participants who did not have diabetes at baseline from the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study, a cohort study with oversampling of participants from the Stroke Belt region. ResultsThe Network has established a shared set of aims: evaluate mediation of the association of the NSEE with type 2 diabetes onset, evaluate effect modification of the association of NSEE with type 2 diabetes onset, assess the differential item functioning of community measures by geographic region and community type, and evaluate the impact of the spatial scale used to measure community factors. The Network has developed standardized approaches for measurement. ConclusionsThe Network will provide insight into the community factors driving geographical disparities in type 2 diabetes risk and disseminate findings to stakeholders, providing guidance on policies to ameliorate geographic disparities in type 2 diabetes in the United States. International Registered Report Identifier (IRRID)DERR1-10.2196/21377

Background: The work environment can contribute to the risk of cardiovascular diseases (CVD) including stroke. Our objective was to identify occupations with elevated risk of stroke within the Reasons for Geographic and Racial Differences in Stroke (REGARDS) cohort. Methods: We analyzed incident stroke outcomes (ischemic and hemorrhagic strokes) from 2003 to 2020 and employment characteristics of 13,659 adults aged ≥45 years enrolled in a national population‐based cohort study. Using a modified Poisson regression approach, we estimated the relative risks (RRs) and the associated 95% confidence intervals (CI) of stroke in relation to years of employment within each occupation coded using the US Census two‐digit Standard Occupation Code. Models were adjusted for Framingham Stroke Risk Score, region, race, age, and body mass index. We conducted stratified analysis by sex, employment time period (pre‐1975 vs. post‐1975), and region. Results: Workers in the following occupations had a greater risk of stroke with longer duration of employment (per decade): protective service (RR: 2.35, 95% CI: 1.11, 4.97), food preparation and service (RR: 1.51, 95% CI: 1.05, 2.19), and transportation and material moving (RR: 1.30, 95% CI: 1.00, 1.69). The stroke risk in these occupations was disproportionately elevated in men, and differed by region and employment time period. Conclusions: Longer employment in protective service, food preparation and serving, and transportation and materials moving occupations may increase the risk of stroke. Surveillance may uncover specific work‐related risk factors in these occupations, leading to interventions to reduce the burden of stroke among US workers. [ABSTRACT FROM AUTHOR]