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Estimating heritability of height without zygosity information for twins under five years in low- and middle-income countries : An application of normal finite mixture distribution models

Karlsson, Omar LU ; Domingue, Benjamin W. ; Kim, Rockli and Subramanian, S. V. (2022) In SSM - Population Health 17.
Abstract

Twin studies are widely used to estimate heritability of traits and typically rely on knowing the zygosity of twin pairs in order to determine variation attributable to genetics. Most twin studies are conducted in high resource settings. Large scale household survey data, such as the Demographic and Health Surveys, collect various biomarkers for children under five years old in low- and middle-income countries. These data include twins but no information on zygosity. We applied mixture models to obtain heritability estimates without knowing zygosity of twins, using 249 Demographic and Health Surveys from 79 low- and middle-income countries (14,524 twin pairs). We focused on height of children, adjusted for age and sex, but also provided... (More)

Twin studies are widely used to estimate heritability of traits and typically rely on knowing the zygosity of twin pairs in order to determine variation attributable to genetics. Most twin studies are conducted in high resource settings. Large scale household survey data, such as the Demographic and Health Surveys, collect various biomarkers for children under five years old in low- and middle-income countries. These data include twins but no information on zygosity. We applied mixture models to obtain heritability estimates without knowing zygosity of twins, using 249 Demographic and Health Surveys from 79 low- and middle-income countries (14,524 twin pairs). We focused on height of children, adjusted for age and sex, but also provided estimates for other biomarkers available in the data. We estimated that the heritability of height in our sample was 46%.

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author
; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Height, Heritability, Low- and middle-income countries, Twin studies, Unknown zygosity
in
SSM - Population Health
volume
17
article number
101043
publisher
Elsevier
external identifiers
  • pmid:35242993
  • scopus:85124730171
ISSN
2352-8273
DOI
10.1016/j.ssmph.2022.101043
language
English
LU publication?
yes
additional info
Funding Information: OK was funded by a Wallander stipendium ( W19-0015 ) from the Jan Wallander and Tom Hedelius foundation .
id
624fa7ec-0d7b-433b-83b7-6eb5f08188ac
date added to LUP
2022-02-28 19:53:49
date last changed
2024-04-13 16:17:38
@article{624fa7ec-0d7b-433b-83b7-6eb5f08188ac,
  abstract     = {{<p>Twin studies are widely used to estimate heritability of traits and typically rely on knowing the zygosity of twin pairs in order to determine variation attributable to genetics. Most twin studies are conducted in high resource settings. Large scale household survey data, such as the Demographic and Health Surveys, collect various biomarkers for children under five years old in low- and middle-income countries. These data include twins but no information on zygosity. We applied mixture models to obtain heritability estimates without knowing zygosity of twins, using 249 Demographic and Health Surveys from 79 low- and middle-income countries (14,524 twin pairs). We focused on height of children, adjusted for age and sex, but also provided estimates for other biomarkers available in the data. We estimated that the heritability of height in our sample was 46%.</p>}},
  author       = {{Karlsson, Omar and Domingue, Benjamin W. and Kim, Rockli and Subramanian, S. V.}},
  issn         = {{2352-8273}},
  keywords     = {{Height; Heritability; Low- and middle-income countries; Twin studies; Unknown zygosity}},
  language     = {{eng}},
  publisher    = {{Elsevier}},
  series       = {{SSM - Population Health}},
  title        = {{Estimating heritability of height without zygosity information for twins under five years in low- and middle-income countries : An application of normal finite mixture distribution models}},
  url          = {{http://dx.doi.org/10.1016/j.ssmph.2022.101043}},
  doi          = {{10.1016/j.ssmph.2022.101043}},
  volume       = {{17}},
  year         = {{2022}},
}