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I recently saw a patient who imagined herself in the last month of pregnancy, and who, while talking to me, exclaimed at the violence of the movements, but on examination I found that her uterus was normal in size, and that her enlarged abdomen was due to a rapidly increasing deposit of fat.
—J. Whitridge Williams (1903)
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At the beginning of the last century, obesity was not terribly problematic, and with few exceptions, Williams did not refer to its adverse obstetrical effects. Fast forward to today when excessive weight is a major health problem in many affluent societies (GBD 2015 Obesity Collaborators, 2017). Indeed, by 2014, more than a third of all adults in the United States were obese (Ogden, 2015).
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The adverse health aspects of obesity are staggering and include risks for diabetes mellitus, heart disease, hypertension, stroke, and osteoarthritis. Obese gravidas and their fetuses are predisposed to various serious pregnancy-related complications and to higher long-term morbidity and mortality rates.
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GENERAL CONSIDERATIONS
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Definitions and Prevalence
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Of systems to classify obesity, the body mass index (BMI), also known as the Quetelet index, is most often used. The BMI is calculated as weight in kilograms divided by the square of the height in meters (kg/m2). Calculated BMI values are available in various chart and graphic forms (Fig. 48-1). The National Institutes of Health (2000) classifies adults according to BMI as follows: normal is 18.5 to 24.9 kg/m2, overweight is 25 to 29.9 kg/m2, and obese is ≥30 kg/m2. Obesity is further divided into: class 1 is 30 to 34.9 kg/m2, class 2 is 35 to 39.9 kg/m2, and class 3 is ≥40 kg/m2. Class 3 obesity is often referred to as morbid obesity, with super-morbid obesity describing a BMI ≥50 kg/m2.
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Using these definitions, from 2011 to 2014, slightly more women than men were designated obese—36 versus 34 percent (Ogden, 2015). Among girls and women, the prevalence of obesity rises with age and varies among ethnicities (Fig. 48-2). Although obesity is now common among all socioeconomic levels, the overall severity advances with increasing poverty (Bilger, 2017). Also, a genetic predisposition has been identified from several gene loci (Locke, 2015; Shungin, 2015).
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