Publication
Sugar-sweetened beverage consumption and genetic predisposition to obesity in 2 Swedish cohorts
Journal Paper/Review - Jul 27, 2016
Brunkwall Louise, Orho-Melander Marju, Franks Paul W, Johansson Ingegerd, Barroso Inês, Ericson Ulrika, Rukh Gull, Hindy George, Chen Yan, Renström Frida
Units
PubMed
Doi
Citation
Type
Journal
Publication Date
Issn Electronic
Pages
Brief description/objective
BACKGROUND
The consumption of sugar-sweetened beverages (SSBs), which has increased substantially during the last decades, has been associated with obesity and weight gain.
OBJECTIVE
Common genetic susceptibility to obesity has been shown to modify the association between SSB intake and obesity risk in 3 prospective cohorts from the United States. We aimed to replicate these findings in 2 large Swedish cohorts.
DESIGN
Data were available for 21,824 healthy participants from the Malmö Diet and Cancer study and 4902 healthy participants from the Gene-Lifestyle Interactions and Complex Traits Involved in Elevated Disease Risk Study. Self-reported SSB intake was categorized into 4 levels (seldom, low, medium, and high). Unweighted and weighted genetic risk scores (GRSs) were constructed based on 30 body mass index [(BMI) in kg/m(2)]-associated loci, and effect modification was assessed in linear regression equations by modeling the product and marginal effects of the GRS and SSB intake adjusted for age-, sex-, and cohort-specific covariates, with BMI as the outcome. In a secondary analysis, models were additionally adjusted for putative confounders (total energy intake, alcohol consumption, smoking status, and physical activity).
RESULTS
In an inverse variance-weighted fixed-effects meta-analysis, each SSB intake category increment was associated with a 0.18 higher BMI (SE = 0.02; P = 1.7 × 10(-20); n = 26,726). In the fully adjusted model, a nominal significant interaction between SSB intake category and the unweighted GRS was observed (P-interaction = 0.03). Comparing the participants within the top and bottom quartiles of the GRS to each increment in SSB intake was associated with 0.24 (SE = 0.04; P = 2.9 × 10(-8); n = 6766) and 0.15 (SE = 0.04; P = 1.3 × 10(-4); n = 6835) higher BMIs, respectively.
CONCLUSIONS
The interaction observed in the Swedish cohorts is similar in magnitude to the previous analysis in US cohorts and indicates that the relation of SSB intake and BMI is stronger in people genetically predisposed to obesity.