Data from the “Malmö Diet and Cancer (MDC)”  cohort was used. In this cohort, all men born between 1923 and 1945 and all women born between 1923 and 1950, living in the city of Malmö were invited to participate in a screening examination between 1991 and 1996. A total of 30,446 subjects participated; participation rate was approximately 41%. After exclusion of individuals with history of AF at baseline (n = 312), missing anthropometric measures, missing biological or life-style co-variables or missing follow-up (n = 4173), a total of 25,961 individuals (9883 men; 16,078 women) were included in the study population. Mean BMI in the excluded group was 26.6 kg/m2 and mean age was 59.6 years. The cumulative incidence rate of AF among the individuals excluded from the present study was 17% (761 out of 4485).
The overall mortality in participants was significantly lower compared to the non-participants; however, socioeconomic structure and prevalence of smoking and obesity has been shown to be comparable with the overall population .
The examinations were performed by trained nurses at the screening center. The subjects underwent measurement of blood pressure and anthropometric measures, completed a self-administered questionnaire and sampling of peripheral venous blood. Height was measured in a standing position with a fixed stadiometer, calibrated in centimeters (cm). Weight was rounded off to the nearest 0.1 kg using a balance-beam scale, with the subjects wearing light clothing and no shoes. BMI was calculated as weight (kg) divided by the square of the height (m2). Waist was measured as the circumference (cm) between the lowest rib and the iliac crest. Hip circumference (cm) was measured as the largest circumference between waist and thighs. WHR was defined as the waist circumference divided by the hip circumference. WHtR was defined as the waist circumference divided by the height.
Bioelectric Impedance Analyzers were used (BIA) for estimating body composition, and BF % was calculated using a mathematical algorithm, according to the procedure provided by the manufacturer (BIA 103, RJL systems, single-frequency analyzer, Detroit, USA).
Data on use of lipid-lowering, antihypertensive and anti-diabetic medications, smoking habits, alcohol consumption, leisure-time physical activity, education level, civil status and immigrant status was obtained through a self-admitted questionnaire.
Blood pressure was measured using a mercury-column sphygmomanometer after 10 min of rest in a supine position. Leukocyte concentration was analyzed consecutively in fresh heparinized blood. Diabetes mellitus was defined as self-reported physician’s diagnosis of diabetes or use of anti-diabetic medications or a diagnosis of diabetes in local or national patient registers. Low leisure-time physical activity was defined as the lowest third of a score calculated from 18 questions on physical activity in four seasons.
Subjects were categorized into smokers (occasional or habitual) and non-smokers (ex-smokers and never-smokers). High alcohol consumption was defined as > 40 g per day for men and > 30 g per day for women. Educational level was divided into three categories: < 9 years (primary education), 9–12 years (some/completed secondary education) and > 12 years (education at college or university level). Civil status was categorized into married and not married. Immigration was classified as Swedish-born and foreign born.
Ascertainment of AF
All subjects were followed from the baseline examination until first diagnosis of AF, death, emigration or 31st December 2016, whichever came first. Patients were followed by data linkage with the Swedish Hospital Discharge Register (HDR), the Swedish hospital-based out-patient register and the Swedish Cause of Death Register (CDR), which are administered by the Swedish National Board of Health and Welfare. These registers include all residents of Sweden, and there was no missing data at the stage of data linkage. Malmö University Hospital has reported to the HDR since 1969 and outpatient diagnoses have been reported since 2001. The CDR contains diagnoses from death certificates since 1952.
AF was defined as diagnosis code 427.92 (ICD-8, used up to 1986), 427D (ICD-9, used between 1987 and 1996) and I48 (ICD-10, used 1997–2016) . AF was defined as atrial fibrillation or atrial flutter, since these conditions have a close relationship .
Cox proportional hazards regression was used to examine the association between anthropometric measurements and incidence of AF. The anthropometric measurements used were BMI, WC, WHR, WHtR, BF %, weight and height, which were divided into quartiles with sex-specific quartile limits.
In a second analysis, BMI and WC were divided into commonly used risk-groups. For BMI, “underweight” was defined as BMI < 18.5 kg/m2, “normal weight” as 18.5 ≤ BMI < 25, “overweight” as 25 ≤ BMI < 30, “obese “ as 30 ≤ BMI < 35 and “severe obesity “ as BMI ≥ 35 in both sexes. For WC “Normal” was defined as WC < 94 cm in men and WC < 80 cm in women, “overweight” as 94 ≤ WC < 102 in men and 80 ≤ WC < 88 in women and “obese” as WC ≥ 102 cm in men and WC ≥ 88 cm in women.
The time axis was follow-up time until death, incident AF, emigration from Sweden, or end of follow-up (December 31st, 2016). Hazard ratios (HR) were calculated with 95% confidence intervals (CI). Analyses were performed using three models. The first model adjusted for age. The second model additionally adjusted for and biological risk factors (systolic blood pressure, leukocyte counts, use of antihypertensive and/or lipid-lowering drugs, diabetes mellitus, Apo A1, Apo B, smoking and physical activity). Finally, a third model also included socioeconomic factors (marital status, immigration status, high alcohol consumption and education). Since AF could be secondary to heart failure (HF) or acute myocardial infarction (AMI), we also performed a sensitivity analysis of incident AF in cases without preceding AMI or HF. In this analysis, all individuals were followed until death, incident AF, first diagnosis of heart failure (HF, ICD-10 code I50) or myocardial infarction (AMI ICD-10 code I21-22), date of emigration or December 31st, 2016, whichever came first. In this analysis, those with HF or AMI before baseline examination were excluded.
The proportional hazards assumption was assessed visually using Kaplan–Meier graphs, and found to be valid. Interaction between anthropometric measures and age were examined using multiplicative interaction terms.
To evaluate model discrimination for different anthropometric measures, we calculated Harrell’s c-statistics for the anthropometric measures, with risk factor adjustments in the third model . Since BMI is the most widely used measure of overall obesity, we used BMI as reference and present change of C-statistics (ΔC-statistics) when other anthropometric measures are applied. SPSS version 25 (SPSS Inc., Chicago, IL, USA) and STATA (version 12. StataCorp LLC, TX, USA) were used for statistical analyses.