Tibetan protection from intrauterine growth restriction (IUGR) and reproductive loss at high altitude

Am J Hum Biol. 2001 Sep-Oct;13(5):635-44. doi: 10.1002/ajhb.1102.


Chronic hypoxia at high altitude restricts fetal growth, reducing birth weight and increasing infant mortality. We asked whether Tibetans, a long-resident high-altitude population, exhibit less altitude-associated intrauterine growth restriction (IUGR) and prenatal or postnatal reproductive loss than Han (ethnic Chinese), a group that has lived there for a shorter period of time. A population sample was obtained, comprising 485 deliveries to Tibetan or Han women over an 18-month period at 8 general hospitals or clinics located at 2,700-4,700 m in the Tibet Autonomous Region, China. Birth weight, gestational age, and other information were recorded for each delivery. Prenatal and postnatal mortality were calculated using information obtained from all pregnancies or babies born to study participants. Tibetan babies weighed more than the Han, averaging 310 g heavier at altitudes 2,700-3,000 m (95% CI = 126, 494 g; P < 0.01) and 530 g heavier at 3,000-3,800 m (210, 750 g; P < 0.01). More Han than Tibetan babies were born prematurely. Prenatal and postnatal mortality rose with increasing elevation and were 3-fold higher across all altitudes in the Han than the Tibetans (P < 0.05). Tibetans experience less altitude-associated IUGR than Han and have lower levels of prenatal and postnatal mortality. When the relationships between birth weight and altitude are compared among these and other high-altitude populations, those living at high altitude the longest have the least altitude-associated IUGR. This may suggest the occurrence of an evolutionary adaptation.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adult
  • Altitude*
  • Birth Weight
  • Female
  • Fetal Death / ethnology*
  • Fetal Growth Retardation / ethnology*
  • Humans
  • Infant Mortality*
  • Infant, Newborn
  • Linear Models
  • Tibet / epidemiology