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3 Fetal and Infant Origins of Obesity
Emily Oken1,2 and Susan E. Ozanne3
1 Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
2 Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA
3 University of Cambridge Metabolic Research Laboratories and MRC Metabolic Diseases Unit, Wellcome‐MRC Institute of Metabolic Science, Cambridge, UK
Background
The global obesity epidemic has spared no segment of the population, even children. In the United States, prevalence of all categories of obesity among children has continued to increase over the past decade, including in the youngest children aged 2–5 years [1]. Globally, between 1980 and 2015 the prevalence of obesity increased from 3.9 to 7.2% in boys and from 3.7 to 6.4% in girls aged 2–4 years [2]. Multiple streams of evidence suggest that exposures occurring in early life, including prenatally and even preconceptionally, contribute to these obesity trends. In this chapter, we provide a brief overview of obesity assessment in children, review evidence from human and animal studies regarding early life exposures that likely influence body weight development, discuss potential mechanisms, and finally review implications for clinical and public health practice.
Assessing obesity in children
In both clinical practice and public health surveillance, children’s weight status is routinely assessed according to body mass index (BMI), calculated as weight in kilograms divided by height (or recumbent length in children under age 2 years) in meters squared, and categorized compared with a reference population of the same age and sex. The World Health Organization Child Growth Standard, which provides standards for weight, length, and BMI‐for‐age and sex for children from birth to age 18 years, is used as the reference in most settings [3,4]. With this tool, obesity is defined as BMI above the 97.7th percentile. In the United States, many continue to calculate BMI percentiles from growth charts developed by the Centers for Disease Control and Prevention (CDC), which provide reference data based on US‐specific, population‐based norms for children 2 years and older [5]. Within the CDC reference, obesity is defined as BMI at or above the 95th percentile for age and sex, and overweight as a BMI between the 85th and 95th percentiles. While the two different references yield slightly different thresholds and thus slightly different obesity prevalence values within a population, they are equally predictive of obesity and adverse cardiometabolic risk in later childhood and adolescence [6,7].
BMI is not a direct assessment of body composition, and thus some caution is appropriate as it is composed of both lean mass and fat mass. Nevertheless, BMI is strongly correlated with other more direct measures of adiposity such as skinfold thickness, dual‐x‐ray absorptiometry (DXA), and bioimpedance, especially at the higher end of the distribution [8]. Obesity, measured using BMI, often persists from childhood or adolescence into adulthood; therefore, children with obesity are more likely to become adults with obesity, further highlighting the importance of early interventions [9]. While multiple other techniques exist that more directly assess fat and lean mass, there is no evidence to suggest that any measure is better than BMI for diagnosing obesity in childhood or predicting adult obesity and morbidity [10]. Thus, evidence‐based guidelines recommend using BMI to clinically screen children and adolescents for obesity to allow for subsequent referral and multidisciplinary treatment [11]. In parallel, most researchers continue to use BMI as the primary measure of obesity in their studies.
Conceptual frameworks
Two paradigms offer useful conceptual frameworks for understanding the developmental origins of obesity. One is termed the “life course approach to chronic disease” [12]. Factors may act in the preconceptional phase through the prenatal period, into infancy, childhood, and beyond, to determine the risk of chronic disease. Orthogonal to the time axis, influencing factors can range from the social/built/natural environment (macro) through behavior, physiology, and genetics (micro). Factors interact with each other over the life course, with different determinants being more or less important at different life stages. Under this paradigm, some factors may be more deterministic than others.
“Programming” refers to insults at critical or sensitive periods of development that have lifelong, sometimes irreversible consequences. A commonly known example is that of the synthetic estrogen diethylstilbestrol (DES), for which intrauterine exposure is associated with risk for clear cell adenocarcinoma of the vagina and cervix in late life, but postnatal exposure is not [13]. Furthermore, exposure to hyperglycemia during fetal life predisposes subsequent increased risks for obesity and type 2 diabetes [14–16]. Other