Genetic and environmental effects on blood pressure in a Norwegian sample

Genet Epidemiol. 1992;9(1):11-26. doi: 10.1002/gepi.1370090104.

Abstract

Systolic (SBP) and diastolic (DBP) blood pressures were measured in a health screening of the adult population in Nord-Trøndelag, Norway. Correlations were computed for 23,936 pairs of spouses, 43,586 pairs of parent and offspring, 19,151 pairs of siblings, 1,251 pairs of grandparents-grandchildren, 1,146 pairs of biological uncles/aunts-nephews/nieces (avuncular), 801 non-biological avuncular pairs, 169 pairs of same-sex twins, and smaller groups of other types of relationships. Spouse correlations of 0.08 and 0.09 were approximately constant or slightly decreasing with marital duration. The correlation values for SBP and DBP were approximately 0.16 for parents-offspring, 0.19 to 0.23 for same-sex siblings with similar values for DZ twins, 0.19 and 0.16 for opposite-sex siblings, 0.52 and 0.43 for MZ twins, and close to zero for most of the second-order relationships. Genetic additive variance was estimated at 0.29 and genetic dominance variance at 0.18 with the best model for SBP. The corresponding estimates from the best models for DBP were 0.29 or lower and 0.22 or lower, the sum not exceeding 0.35. There was evidence of a moderate effect of environmental factors shared by same-sex siblings and twins (for DBP), but no cultural transmission, and whether or not adult relatives live together does not affect familial resemblance for BP. The data did not permit a very precise resolution of the relative magnitude of genetic dominance and sibling effects. The correlation structure did not show sex-specific genetic effects.

Publication types

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

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Blood Pressure / genetics
  • Blood Pressure / physiology*
  • Environmental Health / statistics & numerical data*
  • Female
  • Genetic Testing / methods*
  • Humans
  • Male
  • Middle Aged
  • Models, Statistical
  • Norway / epidemiology