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Debbie A Lawlor

Researcher at University of Bristol

Publications -  1118
Citations -  118183

Debbie A Lawlor is an academic researcher from University of Bristol. The author has contributed to research in topics: Population & Body mass index. The author has an hindex of 147, co-authored 1114 publications receiving 101123 citations. Previous affiliations of Debbie A Lawlor include Southampton General Hospital & University of Vermont.

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Measuring socio-economic position for epidemiological studies in low- and middle-income countries: a methods of measurement in epidemiology paper

TL;DR: This article describes the measures of SEP used in low- and middle-income countries (LMIC) in terms of its theoretical basis, interpretation, measurement, strengths and limitations, and provides brief comparisons between LMIC and HIC.
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Association of maternal weight gain in pregnancy with offspring obesity and metabolic and vascular traits in childhood.

TL;DR: Greater maternal prepregnancy weight and gestational weight gain up to 36 weeks of gestation are associated with greater offspring adiposity and adverse cardiovascular risk factors.
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Novel Loci for Adiponectin Levels and Their Influence on Type 2 Diabetes and Metabolic Traits: A Multi-Ethnic Meta-Analysis of 45,891 Individuals

Zari Dastani, +618 more
- 29 Mar 2012 - 
TL;DR: A meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease identifies novel genetic determinants of adiponectin levels, which, taken together, influence risk of T2D and markers of insulin resistance.
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Physical activity attenuates the influence of FTO variants on obesity risk: A meta-analysis of 218,166 adults and 19,268 children

Tuomas O. Kilpeläinen, +115 more
- 01 Nov 2011 - 
TL;DR: In this paper, a meta-analysis of data from 45 studies of adults and nine studies of children and adolescents was conducted to confirm or refute unambiguously whether physical activity attenuates the association of FTO with obesity risk.
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Clustered environments and randomized genes: a fundamental distinction between conventional and genetic epidemiology.

TL;DR: The findings demonstrate the potential power of a methodology that utilizes genetic variants as indicators of exposure level when studying environmentally modifiable risk factors and illustrate why observational studies have produced misleading claims regarding potentially causal factors for disease.