Yasmin Mossavar-Rahmani

The favorable meal timing for glycemic control in individuals with diabetes remains unclear. The primary aim of this study was to evaluate the prospective association of meal timing with hemoglobin A1C (HbA1c) in individuals with diabetes. The secondary aim was to evaluate associations of meal timing with other cardiovascular disease (CVD) risk factors, including triglycerides, low-density and high-density lipoprotein cholesterol (LDL-C, HDL-C), and systolic and diastolic blood pressure (SBP, DBP). This cohort study included participants with diabetes at baseline (2008-2011) and attending visit 2 examination (2014-2017). Baseline dietary intakes were assessed using two 24-hour dietary recalls. Linear regression was performed to estimate prospective associations of energy intake (EI) and glycemic load (GL) at each meal timing with HbA1c and other CVD risk factors at visit 2. This study included 1,740 participants (mean age: 52.8 years; 59.2% female). Meal timings were associated with HbA1c and CVD risk factors, but in different directions and varied by sex and antidiabetic medication use. For HbA1c, there were generally inverse associations with morning meals, particular early-morning meal (6:00-8:59 AM) in males [EI: percent change, -2.86 (95% CI, -5.48 to -0.17)] and late-morning meal (9:00-11:59 AM) in individuals without antidiabetic medication use [EI: -2.83 (-5.49 to -0.09); GL: -3.31 (-6.46 to -0.05)]. For triglyceride, inverse associations were found for early-morning meals, whereas positive associations were found for afternoon meals (12:00-5:59 PM) in females and individuals without antidiabetic medication use. For LDL-C, positive associations were found for evening meals (6:00-11:59 PM) in individuals without antidiabetic medication use. There were overall positive associations of afternoon meal with SBP and DBP. A greater proportion of daily energy intake or glycemic load consumed during morning meals was associated with lower HbA1c levels and more favorable cardiovascular risk factor profiles in individuals with diabetes. Medication use and sex should be considered when discussing potential meal-timing recommendations.

Background : Physical activity (PA) may be a modifiable factor for chronic kidney disease (CKD) prevention, but evidence specific to Hispanic/Latino populations is limited. Our objective was to examine associations between PA type/volume with changes in kidney function among Hispanic/Latino adults. Methods : We included participants (mean age: 41.6 years, 55.2% women) in the Hispanic Community Health Study/Study of Latinos with complete data. PA was measured using both 7-day accelerometry and the Global Physical Activity Questionnaire. Primary outcomes were percent change in estimated glomerular filtration rate (eGFR) and percent change in urine albumin-to-creatinine ratio over a mean of 6.1 years (N = 7071); incident CKD was the secondary outcome (N = 7177). Results : The mean eGFR change was −3.6 mL/min/1.73 m ² , and mean urine albumin-to-creatinine ratio change was 4.0 mg/g. In multivariable-adjusted models accounting for demographic, occupational, and clinical factors, neither accelerometer-measured light PA or moderate to vigorous PA (MVPA) nor self-reported MVPA were significantly associated with changes in eGFR, urine albumin-to-creatinine ratio, or incident CKD ( P > .05). Diabetes status significantly modified associations between eGFR percent change and accelerometer-measured light PA (interaction P < .01), MVPA (interaction P = .02), and self-reported total MVPA (interaction P = .03). Among individuals with diabetes, higher self-reported total MVPA was associated with higher eGFR change (0.12% per 15 min/d; 95% CI, 0.02–0.22), whereas greater accelerometer-measured MVPA was linked to higher CKD risk (incidence rate ratio: 1.12; 95% CI, 1.02–1.23). Among those without diabetes, associations were inverse with 95% CIs that overlapped the null. Conclusions : PA types/volumes were not associated with kidney function decline or CKD incidence, though diabetes status may modify these relationships.

The burden of diabetes has disproportionately impacted Hispanic/Latino residents in the United States, with diet recognized as a major modifiable risk factor. Outcome-dependent dietary patterns provide insight into what foods may be associated with the increased severity and progression of diabetes. However, the ethnic and geographical heterogeneity of US Hispanic/Latino adults makes it difficult to identify and distinguish differences within their diet as risk increases. Supervised robust profile clustering (sRPC) is a flexible joint model that can identify dietary patterns associated with diabetes, while partitioning out those defined by their ethnicity and geography. However, sRPC has only been applied to binary outcomes. We extend the existing model to develop the ordinal sRPC. Using baseline dietary data (2008-2011) from the Hispanic Community Health Study/Study of Latinos, we illustrate the utility of our model to identify dietary patterns associated with the three-levels of diabetes status (i.e. normal, pre-diabetes, diabetes). Simulation studies confirmed that ordinal sRPC improved identification and characterization of these patterns compared to a standard supervised latent class model. Results indicated that participants who had greater consumption of fruits, snack foods, and refined grain breads may be more likely to be associated with an increasing severity of diabetes status.

BACKGROUND: Consistent evidence suggests diabetes-protective effects of dietary fiber intake. However, the underlying mechanisms, particularly the role of gut microbiota and host circulating metabolites, are not fully understood. We aimed to investigate gut microbiota and circulating metabolites associated with dietary fiber intake and their relationships with type 2 diabetes (T2D). METHODS: This study included up to 11 394 participants from the HCHS/SOL (Hispanic Community Health Study/Study of Latinos). Diet was assessed with two 24-hour dietary recalls at baseline. We examined associations of dietary fiber intake with gut microbiome measured by shotgun metagenomics (350 species/85 genera and 1958 enzymes; n=2992 at visit 2), serum metabolome measured by untargeted metabolomics (624 metabolites; n=6198 at baseline), and associations between fiber-related gut bacteria and metabolites (n=804 at visit 2). We examined prospective associations of serum microbial-associated metabolites (n=3579 at baseline) with incident T2D over 6 years. RESULTS: We identified multiple bacterial genera, species, and related enzymes associated with fiber intake. Several bacteria (eg, Butyrivibrio , Faecalibacterium ) and enzymes involved in fiber degradation (eg, xylanase EC3.2.1.156) were positively associated with fiber intake, inversely associated with prevalent T2D, and favorably associated with T2D-related metabolic traits. We identified 159 metabolites associated with fiber intake, 47 of which were associated with incident T2D. We identified 18 of these 47 metabolites associated with the identified fiber-related bacteria, including several microbial metabolites (eg, indolepropionate and 3-phenylpropionate) inversely associated with the risk of T2D. Both Butyrivibrio and Faecalibacterium were associated with these favorable metabolites. The associations of fiber-related bacteria, especially Faecalibacterium and Butyrivibrio , with T2D were attenuated after further adjustment for these microbial metabolites. CONCLUSIONS: Among United States Hispanics/Latinos, dietary fiber intake was associated with favorable profiles of gut microbiota and circulating metabolites for T2D. These findings advance our understanding of the role of gut microbiota and microbial metabolites in the relationship between diet and T2D.

Background: The Hispanic Community Health Study/Study of Latinos (HCHS/SOL) showed that self‐reported cognitive decline (SCD) is associated with objectively assessed cognition. In HCHS/SOL, sleep phenotypes using empirically derived latent class/cluster analyses are associated with brain vascular outcomes. Since these measures may predict cognitive decline and dementia, we examined the associations between sleep phenotypes, SCD and mild cognitive impairment (MCI) among a diverse sample of Hispanics/Latinos living in the United States.Method: HCHS/SOL is prospective cohort study designed using a multisite (Bronx, NY, Chicago, IL, Miami, FL, San Diego, CA) multistage probability sample. SCD was measured as part of SOL‐INCA, an HCHS/SOL ancillary study. SOL‐INCA obtained repeated cognitive tests, seven‐years apart and the Everyday Cognition Short Form (ECog‐12). The ECog‐12 is a self‐rated questionnaire of current multiple cognitively relevant functional abilities compared to 10‐years ago administered to 5,563 SOL‐INCA participants aged ≥ 50 years. We used latent class analysis using 15 common sleep related symptoms, home sleep apnea test and four comorbidities to derive three sleep phenotypes: (1) Minimally Symptomatic group (49.6%), (2) Disturbed Sleep group (17.1%), and (3) Daytime Sleepiness group (33.3%). We used survey regression to evaluate associations between visit‐1 sleep phenotypes and the ECog‐12 (linear) cognitive domains (memory, language, executive function, and global) and MCI (logistic) using the minimally symptomatic sleep group as the reference. Models were adjusted for age, education, sex, background, field center, insurance, body mass index, cigarette use, alcohol use, cardiovascular disease, language preference, and respiratory event index.Result: Average age was 64.34±8.25 years and 55% were female. In fully adjusted models, participants with disturbed sleep had worse global cognition β = 0.18 [0.14;0.22], memory β = 0.21 [0.16;0.26], language β = 0.23 [0.17;0.29], and executive function β = 0.16 [0.12;0.21]. Compared to the reference, we observed stronger associations in participants with daytime sleepiness; global cognition β = 0.22 [0.16;0.27], memory β = 0.26 [0.19;0.32], language β = 0.26 [0.19;0.34], and executive function β = 0.20 [0.15;0.26]. Adults with disturbed sleep, OR = 1.44 [1.08;1.93], and daytime sleepiness OR = 1.67 [1.16;2.40] had higher odds of MCI.Conclusion: Empirically derived sleep phenotypes capturing disturbed sleep and sleepiness had associations with self‐reported cognitive function and MCI in this sample of U.S. Hispanic/Latino adults.