Outdoor artificial light-at-night and cardiometabolic disease risk: an urban perspective from the Catalan GCAT cohort study.
Anna Palomar-CrosAna EspinosaSalva BaráAlejandro SánchezAntonia ValentínMarta CirachGemma Castaño-VinyalsKyriaki PapantoniouNatalia BlayRafael de CidDora RomagueraManolis KogevinasBarbara N HardingPublished in: American journal of epidemiology (2024)
We investigated the association between outdoor artificial light-at-night (ALAN) exposure and cardiometabolic risk in the GCAT study. We included 9,752 participants from Barcelona (59% women). We used satellite images (30m resolution) and estimated photopic illuminance and the circadian-regulation relevant melanopic illuminance (melanopic EDI). We explored the association between ALAN exposure and prevalent obesity, hypertension, and diabetes with logistic regressions. We assessed the relationship with incident cardiometabolic diseases ascertained through electronic health records (mean follow-up 6.5 years) with Cox proportional hazards regressions. We observed an association between photopic illuminance and melanopic EDI and prevalent hypertension, Odds ratio (OR) = 1.09 (95% CI, 1.01-1.16) and 1.08 (1.01-1.14) per interquartile range increase (0.59 and 0.16 lux, respectively). Both ALAN indicators were linked to incident obesity (hazard ratio [HR] = 1.29, 1.11-1.48 and 1.19, 1.05-1.34) and haemorrhagic stroke (HR = 1.73, 1.00-3.02 and 1.51, 0.99-2.29). Photopic illuminance was associated with incident hypercholesterolemia in all participants (HR = 1.17, 1.05-1.31) and with angina pectoris only in women (HR = 1.55, 1.03-2.33). Further research in this area and increased awareness on the health impacts of light pollution are needed. Results should be interpreted carefully since satellite-based ALAN data do not estimate total individual exposure.
Keyphrases
- electronic health record
- cardiovascular disease
- type diabetes
- blood pressure
- insulin resistance
- polycystic ovary syndrome
- metabolic syndrome
- air pollution
- particulate matter
- weight loss
- healthcare
- coronary artery disease
- heavy metals
- atrial fibrillation
- clinical decision support
- breast cancer risk
- weight gain
- risk assessment
- deep learning
- mental health
- pregnancy outcomes
- coronary artery
- single molecule
- human health
- adipose tissue
- percutaneous coronary intervention
- convolutional neural network
- brain injury
- body mass index
- mass spectrometry
- cervical cancer screening
- optical coherence tomography
- drinking water
- water quality
- health promotion