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- 2019
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Journal article (peer-reviewed)
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- Haghighi, Mona, et al.
(author)
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A Comparison of Rule-based Analysis with Regression Methods in Understanding the Risk Factors for Study Withdrawal in a Pediatric Study
- 2016
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In: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 6
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Journal article (peer-reviewed)abstract
- Regression models are extensively used in many epidemiological studies to understand the linkage between specific outcomes of interest and their risk factors. However, regression models in general examine the average effects of the risk factors and ignore subgroups with different risk profiles. As a result, interventions are often geared towards the average member of the population, without consideration of the special health needs of different subgroups within the population. This paper demonstrates the value of using rule-based analysis methods that can identify subgroups with heterogeneous risk profiles in a population without imposing assumptions on the subgroups or method. The rules define the risk pattern of subsets of individuals by not only considering the interactions between the risk factors but also their ranges. We compared the rule-based analysis results with the results from a logistic regression model in The Environmental Determinants of Diabetes in the Young (TEDDY) study. Both methods detected a similar suite of risk factors, but the rule-based analysis was superior at detecting multiple interactions between the risk factors that characterize the subgroups. A further investigation of the particular characteristics of each subgroup may detect the special health needs of the subgroup and lead to tailored interventions.
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- Schneider, Verena, et al.
(author)
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Loneliness Trajectories, Associated Factors and Subsequent Health in Children and Young People During the COVID-19 Pandemic: A National Matched Cohort Study
- 2023
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In: Psychology Research and Behavior Management. - : DOVE MEDICAL PRESS LTD. - 1179-1578. ; 16, s. 4461-4477
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Journal article (peer-reviewed)abstract
- Purpose: Loneliness is common amongst children and young people (CYP) and is an independent risk factor for poor health. This study aimed to i) determine whether subgroups of CYP with different loneliness trajectories (during the second year of the pandemic) exist; ii) examine associations with socio-demographic characteristics and subsequent health; and iii) understand whether associations between loneliness and subsequent health were modified by SARS-CoV-2 infection. Methods: A total of 5851 CYP (N=3260 SARS-CoV-2 positive and 2591 SARS-CoV-2 negative) provided data on loneliness (via the validated 3-item version of the UCLA Loneliness Scale for Children) at least twice in a 12-month period post PCR index-testing (conducted October 2020-March 2021). Latent class growth analyses were used to identify distinct classes of loneliness trajectories. Multinomial logistic regression was used to identify socio-demographic characteristics associated with class membership. Logistic regression models assessed the odds of reporting impairing symptoms 12-months post index-test. Results: Four distinct loneliness trajectories were identified: three mostly stable (low, medium, high) and one low-increasing trajectory. Being older, female, living in more deprived areas and testing negative were associated with greater odds of being in the highest vs lowest loneliness trajectory; eg OR for female vs male: 5.6 (95% CI:4.1,7.8); OR for 15-17 vs 11-14 years: 4.5 (95% CI:3.4,6.0). Following higher loneliness trajectories was associated with higher odds of experiencing impairing symptoms 12-months post index-test: ORadjusted (compared to lowest loneliness trajectory) were 15.9 (95% CI:11.9,21.3) (high loneliness), 6.5 (5.3,7.9) (medium loneliness) and 2.3 (1.9,2.8) (low-increasing loneliness). There was no evidence that this association was modified by PCR index-test result. Conclusion: About 5.3% of CYP were classified into a group experiencing (chronically) high loneliness. Being female, older and from more deprived areas were risk factors of belonging to this group. Results suggest that even small increases from low loneliness levels may be associated with worse health outcomes.
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- Williamson, Alice, et al.
(author)
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Genome-wide association study and functional characterization identifies candidate genes for insulin-stimulated glucose uptake
- 2023
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In: Nature Genetics. - : Springer Nature. - 1061-4036 .- 1546-1718. ; 55:6, s. 973-983
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Journal article (peer-reviewed)abstract
- Distinct tissue-specific mechanisms mediate insulin action in fasting and postprandial states. Previous genetic studies have largely focused on insulin resistance in the fasting state, where hepatic insulin action dominates. Here we studied genetic variants influencing insulin levels measured 2 h after a glucose challenge in >55,000 participants from three ancestry groups. We identified ten new loci (P < 5 × 10-8) not previously associated with postchallenge insulin resistance, eight of which were shown to share their genetic architecture with type 2 diabetes in colocalization analyses. We investigated candidate genes at a subset of associated loci in cultured cells and identified nine candidate genes newly implicated in the expression or trafficking of GLUT4, the key glucose transporter in postprandial glucose uptake in muscle and fat. By focusing on postprandial insulin resistance, we highlighted the mechanisms of action at type 2 diabetes loci that are not adequately captured by studies of fasting glycemic traits.
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