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Seasonal and Diurnal Variations in Cardiometabolic Traits in the GOLDN Study
Author(s) -
Dashti Hassan,
Aslibekyan Stella,
Smith Caren,
Arnett Donna,
Ordovas Jose
Publication year - 2015
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.29.1_supplement.736.26
Subject(s) - blood pressure , postprandial , anthropometry , circadian rhythm , population , medicine , cohort , endocrinology , biology , demography , diabetes mellitus , environmental health , sociology
Seasonal and diurnal variations in cardiometabolic traits are driven by changes in photoperiod and outdoor temperature and also the circadian clock. Because participant recruitment in the multi‐sited family‐based Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) cohort was evenly distributed over a 3‐year period and ranged between 7:00 AM and 11:00 AM, we had the opportunity to examine whether photoperiod and outdoor temperature on the day of participants' assessment and time of assessment associate with cardiometabolic traits. We used multiple linear regression models adjusted for age, sex, BMI and study site ( n =821). Outdoor temperature showed associations with blood pressure (BP) independent of photoperiod. Each additional 1 o C increase was associated with 0.19 mmHg lower systolic BP [ β ± SE = ‐0.19 ± 0.05 mmHg; P =0.0002] and 0.10 mmHg lower diastolic BP [ β ± SE = ‐0.10 ± 0.03 mmHg; P =0.001]. The association between outdoor temperature and BP was modified by age and hypertension status, but not geographical location. No seasonal differences were observed in self‐reported dietary intake, and anthropometric, lipid and glycemic traits. Furthermore, assessment time showed associations with fasting lipids [total cholesterol ( P =3.3E‐06), LDL‐C ( P =0.004), and TG ( P =0.004)] and postprandial response to a high‐fat meal ( P =1.1E‐07). The observed associations lend support to the oscillation of important cardiometabolic traits, and suggest that cross‐sectional analyses of population‐based cohorts may need to factor in seasonality and assessment time when investigating cardiometabolic traits, particularly BP.