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1. Design and participants

The data used was obtained from the Korean National Health and Nutrition Examination Survey (KNHANES 2017-2018), which addressed the prevalence of AMD, as determined by ophthalmologic examinations, using a newly generated variable (E-AMD). KNHANES is a nationwide population-based survey conducted annually by the Korean Ministry of Health and Welfare on subjects randomly selected using a stratified, multistage, probability sampling design. Interview and examinations were conducted in specially designed and equipped mobile centers. All subjects that participated in KNHANES provided written informed consent. More detailed information on KNHANES has already been published [12]. In this study, a final dataset of 6,993 participants aged ≥40 years that provided information on AMD, were included in the analysis (Figure 1). The study received approval form the Institutional Review Board of Gachon University Gil Medical Center, in accordance with established ethical standards (IRB no. GFIRB2021-481).

Figure 1. Flow diagram illustrating participant selection

2. Ophthalmic variables

AMD was identified through screening tests. AMD was defined based on the ophthalmologic examinations performed by certificated ophthalmologists, and the Epidemiologic Survey Committee of the Korean Ophthalmologic Society verified the quality of the ophthalmic surveys [13]. Ophthalmologic examinations included measurements of visual acuity and intraocular pressure, autorefraction, slit-lamp biomicroscopy, and fundus photography. Digital fundus photographs centered on the fovea (Diabetic Retinopathy Study standard field 2) were taken with a non-mydriatic fundus camera (TRC-NW6S, Topcon, Tokyo, Japan; Nikon D-80, Nikon, Tokyo, Japan) under physiological mydriasis. The examinations results classified AMD into Yes/No categories. Hyperopia, a common refractive error in which distant objects are seen more clearly than near objects due to the light rays entering the eye being focused behind the retina, was defined as a refractory error >＋0.5 D [14]. A history of cataract surgery was determined using self-reported questionnaires. Conditions were considered present when one or both eyes were affected.

3. Other variables

Health interviews and health examinations were performed during a single day by trained medical staff and interviewers. Information on age, sex, health behaviors (smoking history, alcohol drinking, and physical activity), histories of physician-diagnosed diseases (any cancer, myocardial infarction, stroke, hypertension, and type 2 diabetes) were collected during interviews. Current smokers were defined as individuals who smoked cigarettes at the time of interview. Frequent drinking was defined as drinking twice per week. Regular exercise was defined ≥2.5 hours/week of moderate-intensity activity, ≥1.25 hours/week of high-intensity activity, or a considered combination of activities. After each interview, body height and weight were measured using a standard scale with participants wearing light clothing and no shoes, and body mass index (BMI) was calculated by dividing weight by height squared (kg/m2). Obesity was defined as BMI ≥25.0 kg/m2 according to WHO criteria for the Asia-Pacific region [15].

4. Statistical analysis

Demographics and clinical characteristics of participants were assessed using Chi-square test. A multiple logistic regression model adjusted for potential confounding factors, extracted by stepwise multivariate logistic regression analysis, was used to evaluate associations between cancer history and AMD prevalence. We determined the prevalence of AMD with 95% confidence intervals (CIs) by cancer history in the whole cohort and in age subgroups (40-54, 55-64, and ≥65 years old). All statistical analyses were performed using Stata/MP software (version 17.0; Stata Corp., College Station, TX, USA). All statistical tests were two-tailed, and statistical significance was accepted for P-value <0.05.