Purpose To examine the association between the presence and severity of migraine and development of primary open-angle glaucoma (POAG) using a nationwide population-based longitudinal cohort data. Methods Data were retrieved from the Korean National Health Insurance Service for 2,716,562 individuals aged ≥ 40 years and assessed for the development of POAG from 2009 through 2018. Subjects were classified into the following 3 groups: healthy control subjects, subjects with mild migraine, and those with severe migraine. Hazard ratios (HR) of glaucoma development were calculated for each group. Subgroup analyses of subjects stratified by age, sex, lifestyle factors (smoking, drinking, and body mass index (BMI)), and comorbidities (diabetes, hypertension, and dyslipidemia). Results During the 9-year follow-up period, the incidence rate of POAG per 1000 person-years was 2.41 and 3.25 in subjects without and with migraine, respectively. Among the migraine group, the incidence rate was 3.14 and 3.89 in mild and severe subgroups, respectively. The HR was 1.355 (95% CI, 1.300–1.412) and 1.188 (95% CI, 1.140–1.239) before and after adjusting for potential confounding factors in the migraine group per se. Regarding the severity of migraine, the adjusted HRs were 1.169 (95% CI, 1.117–1.224) in the mild migraine group, and 1.285 (95% CI, 1.166–1.415) in the severe migraine group compared to the control group. The results were consistent in subgroup analyses after stratifying by age, sex, lifestyle factors, and comorbidities. Conclusions Migraine is associated with increased risk of POAG development. Furthermore, chronic and severe migraine is associated with greater risk of POAG development.

Obesity has been associated with increased intraocular pressure (IOP), but the results are inconsistent. Recently, a subgroup of obese individuals with good metabolic profiles were suggested to have better clinical outcomes than normal-weight individuals with metabolic diseases. The relationships between IOP and different combinations of obesity and metabolic health status have not been investigated. Therefore, we investigated the IOP among groups with different combinations of obesity status and metabolic health status. We examined 20,385 adults aged 19 to 85 years at the Health Promotion Center of Seoul St. Mary’s Hospital between May 2015 and April 2016. Individuals were categorized into four groups according to obesity (body mass index (BMI) ≥ 25 kg/m2) and metabolic health status (defined based on prior medical history or abdominal obesity, dyslipidemia, low high-density lipoprotein cholesterol, high blood pressure, or high fasting blood glucose levels upon medical examination). ANOVA and ANCOVA were performed to compare the IOP among the subgroups. The IOP of the metabolically unhealthy obese group (14.38 ± 0.06 mmHg) was the highest, followed by that of the metabolically unhealthy normal-weight group (MUNW, 14.22 ± 0.08 mmHg), then, the metabolically healthy groups (p < 0.001; 13.50 ± 0.05 mmHg and 13.06 ± 0.03 mmHg in the metabolically healthy obese (MHO) and metabolically healthy normal-weight groups, respectively). Subjects who were metabolically unhealthy showed higher IOP compared to their counterparts who were metabolically healthy at all BMI levels, and there was a linear increase in IOP as the number of metabolic disease components increased, but no difference between normal-weight vs. obese individuals. While obesity, metabolic health status, and each component of metabolic disease were associated with higher IOP, those who were MUNW showed higher IOP than those who were MHO, which indicates that metabolic status has a greater impact than obesity on IOP.

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