Multilevel Twin Models: Geographical Region as a Third Level Variable

Does neighbourhood deprivation influence low back pain and arthritis: An empirical study using multilevel twin design

OBJECTIVE

Neighbourhood deprivation has been found to be associated with many health conditions, but its association with low back pain (LBP) and arthritis is unclear. This study aimed to examine the association between neighbourhood deprivation with LBP and arthritis, and its potential interaction with individual socioeconomic status (SES) on these outcomes.

METHODS

Monozygotic (MZ) twins from the Washington State Twin Registry were used to control for genetic and common environmental factors that could otherwise confound the purported relationship. Multilevel models were employed to examine the association between neighbourhood deprivation as well as individual-level SES with LBP/arthritis, adjusting for age, sex, body mass index (BMI) and residence rurality.

RESULTS

There were 6,380 individuals in the LBP sample and 2,030 individuals in the arthritis sample. Neighbourhood deprivation was not associated with LBP (P = 0.26) or arthritis (P = 0.61), and neither was its interaction with individual-level SES. People without a bachelor's degree were more likely to report LBP (OR 1.44, 95% CI 1.26-1.65) or both LBP and arthritis (OR 1.67, 95% CI 1.14-2.45) than those with a bachelor's degree, but not for arthritis alone (P = 0.17). Household income was not significantly associated with LBP (P = 0.16) or arthritis (p = 0.23) independent of age, sex, and BMI.

CONCLUSION

Our study did not find significant associations between neighbourhood deprivation and the presence of LBP or arthritis. More research using multilevel modelling to investigate neighbourhood effects on LBP and arthritis is recommended.

Worldwide Well-Being: Simulated Twins Reveal Genetic and (Hidden) Environmental Influences

What are the major sources of worldwide variability in subjective well-being (SWB)? Twin and family studies of SWB have found substantial heritability and strong effects from unique environments but virtually no effects from shared environments. However, extant findings are not necessarily valid at the global level. Prior studies have examined within-countries variability but did not take into account mean differences across nations. In this article, we aim to estimate the effects of genetic factors, individual environmental exposures, and shared environments for the global population. We combine a set of knowns from national well-being studies (means and standard deviations) and behavioral-genetic studies (heritability) to model a scenario of twin studies across 157 countries. For each country, we simulate data for a set of twin pairs and pool the data into a global sample. We find a worldwide heritability of 31% to 32% for SWB. Individual environmental factors explain 46% to 52% of the variance (including measurement error), and shared environments account for 16% to 23% of the global variance in SWB. Worldwide, well-being is somewhat less heritable than within nations. In contrast to previous within-countries studies, we find a notable effect of shared environments. This effect is not limited to within families but operates at a national level.

Maximizing the value of twin studies in health and behaviour

In the classical twin design, researchers compare trait resemblance in cohorts of identical and non-identical twins to understand how genetic and environmental factors correlate with resemblance in behaviour and other phenotypes. The twin design is also a valuable tool for studying causality, intergenerational transmission, and gene-environment correlation and interaction. Here we review recent developments in twin studies, recent results from twin studies of new phenotypes and recent insights into twinning. We ask whether the results of existing twin studies are representative of the general population and of global diversity, and we conclude that stronger efforts to increase representativeness are needed. We provide an updated overview of twin concordance and discordance for major diseases and mental disorders, which conveys a crucial message: genetic influences are not as deterministic as many believe. This has important implications for public understanding of genetic risk prediction tools, as the accuracy of genetic predictions can never exceed identical twin concordance rates.