Perinatal photoperiod associations with diabetes and chronotype prevalence in a cross-sectional study of the UK Biobank

Abstract

Experimental studies indicate that perinatal light may imprint the circadian timing system, subsequently affect later life physiology, and possibly disease risk. We combined individual time-of-year of birth and corresponding latitude to determine perinatal photoperiod characteristics for UK Biobank participants (n = 460,761) and tested for associations with diabetes mellitus (DM, the pathophysiology of which is often linked with circadian disruption) and chronotype (a trait co-governed by the circadian timing system) prevalence in a cross-sectional investigation. The UK Biobank is a population-based cohort with a 5.5% participation rate (~9.2 million individuals were invited into the study between 2006 and 2010). We defined three groups based on photoperiods experienced in the 3 rd trimester of pregnancy and first 3 months post-birth time windows: (1) those who exclusively experienced non-extreme photoperiods (NEP, 8-16 hours), (2) those who experienced at least one extreme short photoperiod (ESP, <8 hours), and those who experienced at least one extreme long photoperiod (ELP, >16 hours). For individuals in each group and time window, mean daily photoperiod and relative photoperiod range (relative = relative to the mean) were calculated. Inclusion of relative photoperiod range adds dispersion information (relative change of photoperiods) to statistical models. Multivariable and multinomial logistic regression analyses were used to estimate odds ratios (ORs) and corresponding 95% confidence intervals (CIs). Increased 3 rd trimester relative range was associated with decreased odds of DM (OR 0.63 95%CI 0.49-0.81) in the NEP group, but increased odds of DM were detected for the ESP (OR 1.34, 95%CI 0.96-1.86) and ELP groups (OR 1.32, 95%CI 0.78-2.22). Increased 3 rd trimester relative range was associated with increased odds of being a "Morning" (OR 1.20, 95%CI 1.02-1.41) or "Evening" (OR 1.43, 95%CI 1.21-1.69) chronotype in the NEP group, but this was not observed in other groups. Additionally, different effect sizes and directions of association with DM were observed in different strata of ethnicity and chronotype and statistically significant odds ratio modifications were detected. In conclusion, perinatal photoperiod associations with DM and chronotype prevalence are detected in the UK Biobank. NEP, ESP, and ELP differences are speculated to be caused by a non-linear dose-response to photoperiods from 0-24 hours or by confounding due to artificial light playing a dominant role in ESP individuals and seeking darkness in ELP individuals. Ethnicity and chronotype may be important effect modifiers of perinatal photoperiod associations with DM. Potential for selection biases due to low UK Biobank participation rate disallows stating conclusions too strongly. Overall, further studies are needed to confirm different perinatal photoperiod associations with DM and chronotype. Further investigations into the hypothesized imprinting mechanism are also warranted.

Accuracy of retrospective birth location data – An analysis based on siblings

“…These location data have in turn been used in a wide range of empirical applications, such as those studying geographic mobility 1,2 , geographic stratification and spatial correlation of genetic variation [3][4][5][6][7][8] , assortative mating and social homogamy 9,10 , but they have also been used to capture regional differences in infrastructure, health or economic circumstances, such as the staggered roll-out of policy 11 . Similarly, they have allowed researchers to include area of birth fixed effects to account for systematic differences between geographical areas 12,13 , and to merge in external information on (area-level) weather, health or socio-economic information [14][15][16][17][18][19][20][21] . Despite much research in a wide range of applications relying on these retrospectively recorded (birth) locations, very little work has explored the accuracy of these data, especially considering they often rely on individuals' correct 30+ year recall.…”

Questions of Communicative Change and Continuity

“…So far, our knowledge about the impact of one's season of birth has originated almost exclusively from biology, medicine, psychiatry and neu roscience (overviews, e.g., in Zhang et al, 2019;Schoenbach, 2018;Mar tinez-Bakker et al, 2014, andAxt &Axt-Gadermann, 2004)-sometimes based on huge datasets (e.g., Lewis et al, 2021). As examples, just a few more recent results: People born in spring or early summer of the north of the northern hemisphere-compared to those born in the fall and early winter-have a significantly higher chance to die of a cardiovascular disea se (Uji et al, 2021;Zhang et al, 2019).…”