Intergenerational Effects On Health




Fetal Origins Hypothesis – An Epidemiological Explanation For The Possible Connection Between In Utero Conditions And Later Outcomes

The biological foundation for linking in utero conditions to later life outcomes is the fetal origins hypothesis. This hypothesis, championed by British physician David Barker, asserts that nutrient deprivation at the beginning of life can raise adult chronic disease risk. Looking across areas in England, Barker noted that infant mortality rates were correlated with later mortality rates of the same cohorts. The biological underpinnings of the fetal origins hypothesis suggest that nutrition during pregnancy affects fetal development. If a fetus is deprived of nutrients in utero, available nutrients are diverted for neurological development while the development of nonneurological systems are sacrificed. This tradeoff manifests itself later in life in the form of higher hypertension risk and increased insulin sensitivity.

Although the hypothesis has gained some acceptance, it is still highly disputed – partially because solid empirical support is difficult to come by. For one, the data demands of testing such a hypothesis require data on both early life conditions and later outcomes. This is an arduous demand given that the collection of high quality data in many countries is only a recent phenomenon. Probably the most foreboding critique of this hypothesis is that it was originally based on observational data and thus, is susceptible to typical omitted variables bias issues. However, it should be noted that animal studies (excluding humans) where the fetal environment is more easily manipulable generally show strong support of the fetal origins hypothesis.




The toolkit of economists is well-suited to addressing these two shortcomings of the public health and medical literature on this topic. Economists have used clever quasi-experimental strategies (many of which will be discussed later in this article) to identify causal relationships between early life conditions and later outcomes. A subset of these natural experiments include the 1918 and 1957 flu epidemics, maternal fasting during Ramadan, variation in malaria prevalence either due to seasonal variation or eradication campaigns, and the implementation of the federal Food Stamps program.

The application of the fetal origins hypothesis in the economics literature is broad. For instance, it is the most common explanation for the association between birth weight, a measure of in utero nutrition, and educational attainment, adult economic outcomes, and adult health outcomes. Some might argue that this is an incorrect interpretation of the fetal origins hypothesis because the hypothesis is specifically about how in utero circumstances have a latent impact which is only expressed in late adulthood, not in early adulthood.

It should be noted that although the fetal origins hypothesis provides a biological basis for the relationship between the in utero environment and subsequent outcomes, estimates of the relationship between early life circumstances and later outcomes will combine both the biological effect and the effects of any ensuing investment decisions. Several studies have been interested in whether investment responses are compensatory or reinforcing, but due to the difficulty measuring intermediate inputs the literature has not reached a consensus regarding which type of investment behavior is more predominant.

Measuring In Utero Health And Later Health

Of critical importance in the in utero and early life health literature is the measurement of health. Measurement of in utero health without intervention is nearly impossible. However, via blood samples, measurements of the maternal environment can be made (e.g., cortisol levels indicating stress). But such data are not part of standard datasets commonly used by economists.

As an alternative measure of in utero health, researchers frequently use measures of health at the time of birth. These include birth weight, appearance, pulse, grimace, activity, respiration (APGAR) score, length of gestation, and infant mortality. Most of these measures are likely a reflection of the effects of the in utero environment rather than the circumstances after birth. Although shifts in many of these outcomes (e.g., birth weight) may not be so meaningful, economists frequently are interested in the tails of the distribution of these outcomes. Low birth weight (<2500 g), very low birth weight (<1500 g), and premature birth (<37 weeks of gestation) are focal outcomes.

In the past 10 years, health economists have debated whether birth weight is an adequate measure of in utero health. Although the measurement of birth weight is easy, by itself, birth weight is not necessarily reflective of any health issues. Historically, interest in this measure by researchers is mainly predicated on the strong birth weight and infant mortality correlation. But such correlation does not imply causation. As an innovative approach to control for possibly confounding factors, researchers have compared birth weight differences between twins and have related those differences to within twin-pair differences in infant mortality. A weaker birth weight and infant mortality relationship emerges from this approach. Nevertheless, the importance of birth weight as a leading health indicator has been reaffirmed with the many recent studies mapping a connection between birth weight and longer run outcomes such as educational attainment, wages, and rates of disability as adults.

Measuring early childhood health is equally difficult as measuring in utero health. Easily obtained health measures such as childhood mortality are rare, making it challenging to find effects of interventions on mortality. The most common chronic conditions in childhood are asthma, hay fever, and bronchitis, but they inflict less than 15% of children in a particular year. Aggregating these conditions to derive a single index measure of health is challenging because it is unclear how to combine these outcomes sensibly. For example, an outcome of the number of chronic conditions a child has would give equal weight to epilepsy as it does to bronchitis.

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