2000 ◽  
Vol 11 (6) ◽  
pp. 487-491 ◽  
Author(s):  
Shirley McGuire ◽  
Jeanie Clifford

This report presents the results of the first behavioral genetic studies of children's loneliness. Data were collected using both an adoption design and a twin-sibling design. As part of the Colorado Adoption Project, 133 sibling pairs (69 biologically related pairs and 64 unrelated pairs in adoptive families) completed a general loneliness scale when they were 9, 10, 11, and 12 years old. As part of the San Diego Sibling Study, 142 sibling pairs (22 monozygotic twin, 40 dizygotic twin, and 80 full-sibling pairs) between the ages of 8 and 14 years old completed a scale assessing loneliness at school. Both studies showed significant heritability and nonshared environmental influences for children's loneliness.


Author(s):  
Cecilia Lundholm ◽  
Henrik Larsson ◽  
Brian D’Onofrio ◽  
Catarina Almqvist

PEDIATRICS ◽  
2014 ◽  
Vol 134 (3) ◽  
pp. e806-e813 ◽  
Author(s):  
A. S. Khashan ◽  
L. C. Kenny ◽  
C. Lundholm ◽  
P. M. Kearney ◽  
T. Gong ◽  
...  

Appetite ◽  
2011 ◽  
Vol 57 (2) ◽  
pp. 510-516 ◽  
Author(s):  
M. Greg Horn ◽  
Amy. T. Galloway ◽  
Rose Mary Webb ◽  
Sandra G. Gagnon

2010 ◽  
Vol 40 (2) ◽  
pp. 338-345 ◽  
Author(s):  
C. Obel ◽  
J. Olsen ◽  
T. B. Henriksen ◽  
A. Rodriguez ◽  
M.-R. Jarvelin ◽  
...  

PLoS Medicine ◽  
2020 ◽  
Vol 17 (12) ◽  
pp. e1003452
Author(s):  
Maria Brandkvist ◽  
Johan Håkon Bjørngaard ◽  
Rønnaug Astri Ødegård ◽  
Ben Brumpton ◽  
George Davey Smith ◽  
...  

Background Obesity has tripled worldwide since 1975 as environments are becoming more obesogenic. Our study investigates how changes in population weight and obesity over time are associated with genetic predisposition in the context of an obesogenic environment over 6 decades and examines the robustness of the findings using sibling design. Methods and findings A total of 67,110 individuals aged 13–80 years in the Nord-Trøndelag region of Norway participated with repeated standardized body mass index (BMI) measurements from 1966 to 2019 and were genotyped in a longitudinal population-based health study, the Trøndelag Health Study (the HUNT Study). Genotyping required survival to and participation in the HUNT Study in the 1990s or 2000s. Linear mixed models with observations nested within individuals were used to model the association between a genome-wide polygenic score (GPS) for BMI and BMI, while generalized estimating equations were used for obesity (BMI ≥ 30 kg/m2) and severe obesity (BMI ≥ 35 kg/m2). The increase in the average BMI and prevalence of obesity was steeper among the genetically predisposed. Among 35-year-old men, the prevalence of obesity for the least predisposed tenth increased from 0.9% (95% confidence interval [CI] 0.6% to 1.2%) to 6.5% (95% CI 5.0% to 8.0%), while the most predisposed tenth increased from 14.2% (95% CI 12.6% to 15.7%) to 39.6% (95% CI 36.1% to 43.0%). Equivalently for women of the same age, the prevalence of obesity for the least predisposed tenth increased from 1.1% (95% CI 0.7% to1.5%) to 7.6% (95% CI 6.0% to 9.2%), while the most predisposed tenth increased from 15.4% (95% CI 13.7% to 17.2%) to 42.0% (95% CI 38.7% to 45.4%). Thus, for 35-year-old men and women, respectively, the absolute change in the prevalence of obesity from 1966 to 2019 was 19.8 percentage points (95% CI 16.2 to 23.5, p < 0.0001) and 20.0 percentage points (95% CI 16.4 to 23.7, p < 0.0001) greater for the most predisposed tenth compared with the least predisposed tenth, defined using the GPS for BMI. The corresponding absolute changes in the prevalence of severe obesity for men and women, respectively, were 8.5 percentage points (95% CI 6.3 to 10.7, p < 0.0001) and 12.6 percentage points (95% CI 9.6 to 15.6, p < 0.0001) greater for the most predisposed tenth. The greater increase in BMI in genetically predisposed individuals over time was apparent after adjustment for family-level confounding using a sibling design. Key limitations include a slightly lower survival to date of genetic testing for the older cohorts and that we apply a contemporary genetic score to past time periods. Future research should validate our findings using a polygenic risk score constructed from historical data. Conclusions In the context of increasingly obesogenic changes in our environment over 6 decades, our findings reveal a growing inequality in the risk for obesity and severe obesity across GPS tenths. Our results suggest that while obesity is a partially heritable trait, it is still modifiable by environmental factors. While it may be possible to identify those most susceptible to environmental change, who thus have the most to gain from preventive measures, efforts to reverse the obesogenic environment will benefit the whole population and help resolve the obesity epidemic.


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