title: Obesity and insurance risk: the insurance industry's viewpoint.
abstract: Obesity is regarded by insurance companies as a substantial risk for both life and disability policies.  This risk increases proportionally with the degree of obesity.  Mortality statistics for life insurance were the earliest indicator that the cost of obesity to the individual was a decreased life span and increased illness, particularly that affecting the cardiovascular and musculoskeletal systems.  The prevalence of coronary heart disease rises with increases in the body mass index in both men and women.  Cigarette smoking greatly augments these risks in both sexes.  Hypertension and diabetes are very common in obese persons and add further to the risks of vascular disease.  Abdominal obesity (when the abdominal girth measured round the umbilicus exceeds the maximum measurement round the hips) is correlated with the risk of cardiac disease and stroke, independently of bodyweight.  Insurance companies consider abdominal obesity as unfavourable and rate it accordingly. Obesity (even that of moderate degree) greatly increases the chances of disability due to cardiovascular disease or musculoskeletal illness.  In one study of 51 522 adult Finns, 25% of disability pensions in women were found to result directly from obesity.  Obesity causes increased health expenditure, decreased life span and productivity, and premature retirement.  Insurance companies are compelled to build these risks into their policies.  However, because the excess mortality occurs late in mild to moderate obesity, some companies may minimise this risk for life policies that mature early.
authors.affiliation: West Middlesex Hospital, Isleworth, England.
authors.forename: I M
authors.initials: IM
authors.lastname: Baird
mesh_terms: D002318:Cardiovascular Diseases / Q000453:epidemiology; D017281:Cost of Illness; D006233:Persons with Disabilities; D006801:Humans; D007348:Insurance, Health; D007352:Insurance, Life; D009765:Obesity / Q000453:epidemiology*; D012307:Risk Factors