Abstract
AbstractWomen’s health is important for society. Despite the known biological and sex-related factors influencing the risk of diseases among women, the network of the full spectrum of diseases in women is underexplored. This study aimed to systematically examine the women-specific temporal pattern (trajectory) of the disease network, including the role of baseline physical examination indexes, and blood and urine biomarkers. In the UK Biobank study, 502,650 participants entered the cohort from 2006 to 2010, and were followed up until 2019 to identify disease incidence via linkage to the patient registers. For those diseases with increased risk among women, conditional logistic regression models were used to estimate odds ratios (ORs), and the binomial test of direction was further used to build disease trajectories. Among 301 diseases, 82 diseases in women had ORs > 1.2 and p < 0.00017 when compared to men, involving mainly diseases in the endocrine, skeletal and digestive systems. Diseases with the highest ORs included breast diseases, osteoporosis, hyperthyroidism, and deformity of the toes. The biomarker and disease trajectories suggested estradiol as a risk predictor for breast cancer, while a high percentage of reticulocyte, body mass index and waist circumference were associated with an increased risk of upper-limb neuropathy. In addition, the risk of cholelithiasis was increased in women diagnosed with dyspepsia and diaphragmatic hernia. In conclusion, women are at an increased risk of endocrine, skeletal and digestive diseases. The biomarker and disease trajectories in women suggested key pathways to a range of adverse outcomes downstream, which may shed light on promising targets for early detection and prevention of these diseases.
Funder
Grant of Science and Technology of Fujian, China
Startup Fund for high-level talents of Fujian Medical University
Startup Fund for scientific research, Fujian Medical University
Laboratory Construction Program of Fujian Medical University
Natural Science Foundation of Fujian Province
Karolinska Institute
Publisher
Springer Science and Business Media LLC
Cited by
8 articles.
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