The University of Southampton
University of Southampton Institutional Repository
Warning ePrints Soton is experiencing an issue with some file downloads not being available. We are working hard to fix this. Please bear with us.

Pre-pregnancy dietary patterns and risk of gestational diabetes mellitus: results from an Australian population-based prospective cohort study

Pre-pregnancy dietary patterns and risk of gestational diabetes mellitus: results from an Australian population-based prospective cohort study
Pre-pregnancy dietary patterns and risk of gestational diabetes mellitus: results from an Australian population-based prospective cohort study

AIMS/HYPOTHESIS: We examined the associations between pre-pregnancy dietary patterns and the incidence of gestational diabetes mellitus (GDM) in a population-based cohort study of women of reproductive age.

METHODS: The Australian Longitudinal Study on Women's Health included 3,853 women without pre-existing diabetes who were followed-up between 2003 and 2012. Pre-pregnancy dietary patterns were derived using factor analysis based on 101 food items from a validated food frequency questionnaire. GDM was self-reported and validated in a subsample. Multivariable regression models with generalised estimating equations were used to estimate RR and 95% CI.

RESULTS: During 9 years follow-up, 292 GDM cases (4.4%) were documented in 6,626 pregnancies. No associations were found for the 'Fruit and low-fat dairy' and 'Cooked vegetables' patterns. The 'Meats, snacks and sweets' pattern was associated with higher GDM risk after adjustment for socioeconomic, reproductive and lifestyle factors (RR [95% CI] per SD increase in score: 1.38 [1.02, 1.86]). Further adjustment for BMI attenuated the results (1.35 [0.98, 1.81]). In stratified analysis, the 'Meats, snacks and sweets' pattern was associated with significantly higher GDM risk in parous and obese women, and in women with lower educational qualifications. The 'Mediterranean-style' pattern was associated with lower GDM risk in the fully adjusted model (0.85 [0.76, 0.98]).

CONCLUSIONS/INTERPRETATION: These findings support general dietary recommendations for women of reproductive age to consume a diet rich in vegetables, whole grains, nuts and fish, and low in red and processed meats and snacks. Further prospective studies are needed to confirm these findings.

Adult, Australia/epidemiology, Body Mass Index, Cohort Studies, Diabetes, Gestational/epidemiology, Diet, Diet, Mediterranean, Feeding Behavior, Female, Follow-Up Studies, Humans, Longitudinal Studies, Population, Pregnancy, Prospective Studies, Risk Assessment, Socioeconomic Factors
0012-186X
2726-2735
Schoenaker, Danielle A.J.M.
84b96b87-4070-45a5-9777-5a1e4e45e818
Soedamah-Muthu, Sabita S.
a92e78f0-b28c-44f3-be86-e744fd004ff4
Callaway, Leonie K.
8c998763-afd8-4033-a364-84007b926f19
Mishra, Gita D.
02143b82-e536-4915-9b30-3c86cbe1a1fe
Schoenaker, Danielle A.J.M.
84b96b87-4070-45a5-9777-5a1e4e45e818
Soedamah-Muthu, Sabita S.
a92e78f0-b28c-44f3-be86-e744fd004ff4
Callaway, Leonie K.
8c998763-afd8-4033-a364-84007b926f19
Mishra, Gita D.
02143b82-e536-4915-9b30-3c86cbe1a1fe

Schoenaker, Danielle A.J.M., Soedamah-Muthu, Sabita S., Callaway, Leonie K. and Mishra, Gita D. (2015) Pre-pregnancy dietary patterns and risk of gestational diabetes mellitus: results from an Australian population-based prospective cohort study. Diabetologia, 58 (12), 2726-2735. (doi:10.1007/s00125-015-3742-1).

Record type: Article

Abstract

AIMS/HYPOTHESIS: We examined the associations between pre-pregnancy dietary patterns and the incidence of gestational diabetes mellitus (GDM) in a population-based cohort study of women of reproductive age.

METHODS: The Australian Longitudinal Study on Women's Health included 3,853 women without pre-existing diabetes who were followed-up between 2003 and 2012. Pre-pregnancy dietary patterns were derived using factor analysis based on 101 food items from a validated food frequency questionnaire. GDM was self-reported and validated in a subsample. Multivariable regression models with generalised estimating equations were used to estimate RR and 95% CI.

RESULTS: During 9 years follow-up, 292 GDM cases (4.4%) were documented in 6,626 pregnancies. No associations were found for the 'Fruit and low-fat dairy' and 'Cooked vegetables' patterns. The 'Meats, snacks and sweets' pattern was associated with higher GDM risk after adjustment for socioeconomic, reproductive and lifestyle factors (RR [95% CI] per SD increase in score: 1.38 [1.02, 1.86]). Further adjustment for BMI attenuated the results (1.35 [0.98, 1.81]). In stratified analysis, the 'Meats, snacks and sweets' pattern was associated with significantly higher GDM risk in parous and obese women, and in women with lower educational qualifications. The 'Mediterranean-style' pattern was associated with lower GDM risk in the fully adjusted model (0.85 [0.76, 0.98]).

CONCLUSIONS/INTERPRETATION: These findings support general dietary recommendations for women of reproductive age to consume a diet rich in vegetables, whole grains, nuts and fish, and low in red and processed meats and snacks. Further prospective studies are needed to confirm these findings.

This record has no associated files available for download.

More information

e-pub ahead of print date: 10 September 2015
Published date: December 2015
Keywords: Adult, Australia/epidemiology, Body Mass Index, Cohort Studies, Diabetes, Gestational/epidemiology, Diet, Diet, Mediterranean, Feeding Behavior, Female, Follow-Up Studies, Humans, Longitudinal Studies, Population, Pregnancy, Prospective Studies, Risk Assessment, Socioeconomic Factors

Identifiers

Local EPrints ID: 441368
URI: http://eprints.soton.ac.uk/id/eprint/441368
ISSN: 0012-186X
PURE UUID: 0575c623-eff2-45f0-a5cf-b264e490a097
ORCID for Danielle A.J.M. Schoenaker: ORCID iD orcid.org/0000-0002-7652-990X

Catalogue record

Date deposited: 10 Jun 2020 16:31
Last modified: 10 Jan 2022 03:21

Export record

Altmetrics

Contributors

Author: Sabita S. Soedamah-Muthu
Author: Leonie K. Callaway
Author: Gita D. Mishra

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×