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Constrained by limited energy and resources, organisms must compromise between offspring quantity and parental investment. This trade-off is represented by two primary reproductive strategies; K-strategists produce few offspring but provide substantial parental support, whereas r-strategists produce much progeny that receives little care. These strategies are related to an organism’s survival likelihood across its lifespan, which is represented by a survivorship curve. Three general types of...
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Intersecting birth weight-specific mortality curves: solving the riddle.

Olga Basso1, Allen J Wilcox

  • 1Epidemiology Branch, National Institute of Environmental Health Sciences/NIH, 111 T. W. Alexander Drive, Research Triangle Park, NC 27709, USA. bassoo2@niehs.nih.gov

American Journal of Epidemiology
|February 26, 2009
PubMed
Summary
This summary is machine-generated.

Unmeasured factors can explain why smaller babies in high-risk populations sometimes survive better. These confounders can reverse observed mortality gradients by birth weight, suggesting true gradients may be weaker than apparent.

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Area of Science:

  • Epidemiology
  • Biostatistics
  • Perinatal Health

Background:

  • Small babies from high infant mortality populations often show better survival than those from low-risk populations.
  • This counterintuitive survival pattern is frequently observed in perinatal and infant health studies.
  • Existing explanations often attribute this to unmeasured confounding factors.

Purpose of the Study:

  • To demonstrate how unmeasured confounding can explain the observed reversal of mortality risk among small infants.
  • To model the impact of unmeasured confounders on birth weight-specific mortality curves.
  • To re-evaluate the strength of the true mortality gradient by birth weight.

Main Methods:

  • Utilized a previously developed model for birth weight-specific mortality.
  • Introduced a simulated unmeasured confounder that decreases birth weight and increases mortality.
  • Analyzed the resulting changes in mortality curves stratified by known risk factors.

Main Results:

  • The model demonstrated that strong unmeasured confounders can cause mortality curves to intersect.
  • The addition of a confounder produced a reversal of risk among small babies.
  • Unmeasured confounders explain how high-risk babies within a birth weight stratum can have lower mortality.

Conclusions:

  • Unmeasured confounding factors can fully explain the phenomenon of better survival in small babies from high-risk populations.
  • These confounders can create the appearance of a reversed mortality gradient by birth weight.
  • The true gradient of infant mortality with respect to birth weight may be weaker than currently observed.