Aim This study aimed to determine cross‐sectional relationships between diabetes distress and health‐related variables, and prospective associations between diabetes distress and future glycaemic control (HbA1c) and health status among young adults with early‐onset Type 1 diabetes. Methods Data were collected from a nationwide cohort study of adults whose Type 1 diabetes onset occurred from 0 to 4 years of age during 1993–2002. Questionnaire surveys were conducted in 2012–2013 and 2015–2016 (N = 584). Diabetes distress was assessed via the Problem Areas in Diabetes (PAID) scale (0–100 points), depressive symptoms via the Patient Health Questionnaire‐9 (PHQ‐9) and health status via the 12‐Item Short Form Health Survey (SF‐12) questionnaire. Multivariable linear regression analyses were applied to cross‐sectional and longitudinal data. Results In the cross‐sectional analyses, higher PAID scale total scores (representing higher distress levels) were observed in women than in men and in participants with more severe depressive symptoms. PAID scores were lower in individuals with better physical and mental health. A 1 mmol/mol increase in HbA1c was associated with a 0.28‐point increase [95% confidence interval (95% CI) 0.20, 0.36] in diabetes distress. In longitudinal analyses adjusting for age, sex, socio‐economic index and HbA1c at baseline, a 10‐point higher PAID score at baseline was associated with a 1.82 mmol/mol higher HbA1c level (95% CI 0.43, 3.20) and a 2.48‐point lower SF‐12 mental health score (95% CI −3.55, −1.42) three years later. Conclusions The cross‐sectional and longitudinal analyses results suggest that diabetes distress impairs health‐related outcomes in young adults with early‐onset diabetes.

Background: Older adults show a high variability in cognitive performance that cannot be explained by aging alone. Although research has linked air pollution and noise to cognitive impairment and structural brain alterations, the potential impact of air pollution and noise on functional brain organization is unknown. Objective: This study examined the associations between long-term air pollution and traffic noise with measures of functional brain organization in older adults. We hypothesize that exposures to high air pollution and noise levels are associated with age-like changes in functional brain organization, shown by less segregated brain networks. Methods: Data from 574 participants (44.1% female, 56–85 years of age) in the German 1000BRAINS study (2011–2015) were analyzed. Exposure to particulate matter ( , , and absorbance), accumulation mode particle number ( ), and nitrogen dioxide ( ) was estimated applying land-use regression and chemistry transport models. Noise exposures were assessed as weighted 24-h ( ) and nighttime ( ) means. Functional brain organization of seven established brain networks (visual, sensorimotor, dorsal and ventral attention, limbic, frontoparietal and default network) was assessed using resting-state functional brain imaging data. To assess functional brain organization, we determined the degree of segregation between networks by comparing the strength of functional connections within and between networks. We estimated associations between air pollution and noise exposure with network segregation, applying multiple linear regression models adjusted for age, sex, socioeconomic status, and lifestyle variables. Results: Overall, small associations of high exposures with lesser segregated networks were visible. For the sensorimotor networks, we observed small associations between high air pollution and noise and lower network segregation, which had a similar effect size as a 1-y increase in age [e.g., in sensorimotor network, (95% CI: , 0.009) per 0.3 increase in absorbance and (95% CI: , ) per 1-y age increase]. Conclusion: High exposure to air pollution and noise was associated with less segregated functional brain networks. https://doi.org/10.1289/EHP9737

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