RESUMEN
Objective: To estimate the association between food needs and diabetes outcomes. Research design and methods: Longitudinal cohort study, using a target trial emulation approach. 96,792 adults with type 2 diabetes mellitus who underwent food need assessment in a network of community-based health centers were followed up to 36 months after initial assessment. We used targeted minimum loss estimation to estimate the association between not experiencing food needs, compared with experiencing food needs, and hemoglobin a1c (HbA1c), systolic and diastolic blood pressure (SBP and DBP), and LDL cholesterol. The study period was June 24th, 2016 to April 30th, 2023. Results: We estimated that not experiencing food needs, compared with experiencing food needs, would be associated with 0.12 percentage points lower (95% Confidence Interval [CI] -0.16% to -0.09%, p = < 0.0001) mean HbA1c at 12 months. We further estimated that not experiencing food needs would be associated with a 12-month SBP that was 0.67 mm Hg lower (95%CI -0.97 to -0.38 mm Hg, p < .0001), DBP 0.21 mm Hg lower (95%CI -0.38 to -0.04 mm Hg, p = .01). There was no association with lower LDL cholesterol. Results were similar at other timepoints, with associations for HbA1c, SBP, and DBP of similar magnitude, and no difference in LDL cholesterol. Conclusions: We estimated that not experiencing food needs may be associated with modestly better diabetes outcomes. These findings support testing interventions that address food needs as part of their mechanism of action.
RESUMEN
Functional magnetic resonance imaging (fMRI) has been widely used to identify brain regions linked to critical functions, such as language and vision, and to detect tumors, strokes, brain injuries, and diseases. It is now known that large sample sizes are necessary for fMRI studies to detect small effect sizes and produce reproducible results. Here we report a systematic association analysis of 647 traits with imaging features extracted from resting-state and task-evoked fMRI data of more than 40,000 UK Biobank participants. We used a parcellation-based approach to generate 64,620 functional connectivity measures to reveal fine-grained details about cerebral cortex functional organizations. The difference between functional organizations at rest and during task was examined, and we have prioritized important brain regions and networks associated with a variety of human traits and clinical outcomes. For example, depression was most strongly associated with decreased connectivity in the somatomotor network. We have made our results publicly available and developed a browser framework to facilitate the exploration of brain function-trait association results (http://fmriatlas.org/).
