Fig. 5: Outdoor temperature and its diurnal variation as key meteorological factors influencing intergenerational BAT activity and adiposity.
From: Pre-fertilization-origin preservation of brown fat-mediated energy expenditure in humans
a, Schematic of the study design for the meteorological survey and the definition of pregnancy periods. The pregnancy period was divided into five periods: preconception (−12 to −9 months), the first trimester (−9 to −6 months), second trimester (−6 to −3 months), third trimester (−3 to 0 months) and postpartum (0 to 3 months). b, Schematic showing the extraction of meteorological data for pregnancy periods from Japan created by the JMA, the NARO and the NAOJ. Data were obtained for birth and fertilization regions. c, Multivariate logistic regression using the backward stepwise method to predict BAT activity in young male volunteers (n = 93, model 1). Model 1 was adjusted for age, BMI, medical history and lifestyle factors (smoking and shift work). Variables included BAT activity (binary: 1 or 0), age and BMI: (the tertile values: 1, 2 or 3), low birth weight (yes, 1 and no, 0), smoking status (never, former, current: 1, 2, 3) and shift work (never, former, current: 1, 2, 3). d, Independent effects of diurnal temperature variation on BAT activity in c (model 2). Diurnal variation, calculated as the difference between dairy maximum and minimum temperatures, was added alongside daily mean temperature and other meteorological parameters. Model 2 adjustments were identical to model 1. e, Participants were categorized by seasonal birth and fertilization conditions: (1) warm birth/warm fertilization (n = 77), (2) warm birth/cold fertilization (n = 111), (3) cold birth/warm fertilization (n = 82) and (4) cold birth and cold fertilization (n = 86). f,g, Combined effects of the seasons of birth and fertilization on BAT prevalence (f) and activity (g). Numbers of participants with active BAT/total participants are indicated on the bars. Biologically independent samples (c–g). Data are adjusted ORs with 95% CIs as error bars: two-tailed P values by multivariate logistic regression (c,d); percentage: one-tailed P values by Fisher’s exact test (f); mean ± s.e.m.; two-tailed P values by unpaired Student’s t-test (g).
