Skip to main content Accessibility help

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.

Close cookie message
×
Home
  • Home

Refine search

Refine search

Access:
Content type:
Publication date:
Apply
Subject: Show more
Journals Show more
Publishers: Show more
Societies Show more
Series: Show more
Collections: Show more

Actions for selected content:

Select all | Deselect all
  • View selected items
  • Export citations
  • Download PDF (zip)
  • Send to Kindle
  • Send to Dropbox
  • Send to Google Drive

Save Search

You can save your searches here and later view and run them again in "My saved searches".

Please provide a title, maximum of 40 characters.
Cancel
×

233 results

Page 1 of 12

  • Associations of sugar sweetened beverage intake at ages 18 months and 5 years with adiposity outcomes at age 6 years: The Singapore GUSTO mother-offspring cohort
  • Phaik Ling Quah, Josefien Kleijweg, Ya Yin Chang, Jia Ying Toh, Hui Xian Lim, Ray Sugianto, Izzuddin M Aris, Wen Lun Yuan, Mya Thway Tint, Jonathan Y. Bernard, Padmapriya Natarajan, Falk Müller-Riemenschneider, Keith M. Godfrey, Peter D. Gluckman, Yap-Seng Chong, Lynette P. Shek, Kok Hian Tan, Johan G Eriksson, Fabian Yap, Yung Seng Lee, Mary F.F. Chong
  • Journal: British Journal of Nutrition /
  • Published online by Cambridge University Press: 03 September 2019, pp. 1-25
    • Article
    • Access
    • PDF
    • Export citation
  • View abstract

    Consumption of sugar sweetened beverages (SSBs) in infants and young children are less explored in Asian populations. The Growing in Singapore Towards healthy Outcomes (GUSTO) cohort study examined associations between SSB intakes at ages 18 months and 5 years with adiposity measures at age 6 years. We studied Singaporean infants/children with SSB intake assessed by food frequency questionnaires (FFQ) at ages 18 months (n=555) and 5 years (n=767). The median (interquartile range) for SSB intakes is 28(5.5-98) ml at age 18 months and 111 (57-198) ml at age 5 years. Associations between SSB intakes (100 ml/day increments and tertile categories) and adiposity measures (BMI standard deviation scores (s.d. unit), sum of skinfolds (SSFs)) and overweight/obesity status were examined using multivariable linear and Poisson regression models, respectively. After adjusting for confounders and additionally for energy intake, SSB intakes at age 18 months were not significantly associated with later adiposity measures and overweight/obesity outcomes. In contrast, at age 5 years, SSB intakes when modelled as 100ml/day increments were associated with higher BMI by 0.09 (95% CI: 0.02, 0.16) s.d. unit, higher SSF thickness by 0.68 (0.06, 1.44) mm, and increased risk for overweight/obesity by 1.2 times (1.07, 1.23) at age 6 years. Trends were consistent with SSB intakes modelled as categorical tertiles. In summary, SSB intake in young childhood is associated with higher risks of adiposity and risk for overweight/obesity. Public health policies working to reduce SSB consumption need to focus on prevention programs targeted at young children.

Computational Bayesian Statistics
  • Computational Bayesian Statistics
  • An Introduction
  • M. Antónia Amaral Turkman, Carlos Daniel Paulino, Peter Müller
  • Published online: 18 February 2019
  • Print publication: 28 February 2019
  • View description
    Meaningful use of advanced Bayesian methods requires a good understanding of the fundamentals. This engaging book explains the ideas that underpin the construction and analysis of Bayesian models, with particular focus on computational methods and schemes. The unique features of the text are the extensive discussion of available software packages combined with a brief but complete and mathematically rigorous introduction to Bayesian inference. The text introduces Monte Carlo methods, Markov chain Monte Carlo methods, and Bayesian software, with additional material on model validation and comparison, transdimensional MCMC, and conditionally Gaussian models. The inclusion of problems makes the book suitable as a textbook for a first graduate-level course in Bayesian computation with a focus on Monte Carlo methods. The extensive discussion of Bayesian software - R/R-INLA, OpenBUGS, JAGS, STAN, and BayesX - makes it useful also for researchers and graduate students from beyond statistics.

Page 1 of 12