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Preconception risk of gestational diabetes: development of a prediction model in nulliparous Australian women

Preconception risk of gestational diabetes: development of a prediction model in nulliparous Australian women
Preconception risk of gestational diabetes: development of a prediction model in nulliparous Australian women

AIM: To develop a prediction model for preconception identification of women at risk of gestational diabetes mellitus (GDM).

METHODS: Data from a prospective cohort, the Australian Longitudinal Study on Women's Health, were used. Nulliparous women aged 18-23 who reported a pregnancy up to age 37-42 were included. Preconception predictors of GDM during a first pregnancy were selected using logistic regression. Regression coefficients were multiplied by a shrinkage factor estimated with bootstrapping to improve prediction in external populations.

RESULTS: Among 6504 women, 314 (4.8%) developed GDM during their first pregnancy. The final prediction model included age at menarche, proposed age at future first pregnancy, ethnicity, body mass index, diet, physical activity, polycystic ovary syndrome, and family histories of type 1 or 2 diabetes and GDM. The model showed good discriminative ability with a C-statistic of 0.79 (95% CI 0.76, 0.83) after internal validation. More than half of the women (58%) were classified to be at risk of GDM (>2% predicted risk), with corresponding sensitivity and specificity values of 91% and 43%.

CONCLUSIONS: Nulliparous women at risk of GDM in a future first pregnancy can be accurately identified based on preconception lifestyle and health-related characteristics. Further studies are needed to test our model in other populations.

Adult, Australia, Cohort Studies, Diabetes, Gestational/ethnology, Female, Humans, Longitudinal Studies, Parity, Pregnancy, Prospective Studies, Risk Factors
0168-8227
48-57
Schoenaker, Danielle A.J.M.
84b96b87-4070-45a5-9777-5a1e4e45e818
Vergouwe, Yvonne
574ebf91-156f-424f-90d7-d8da62e559a5
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
Vergouwe, Yvonne
574ebf91-156f-424f-90d7-d8da62e559a5
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., Vergouwe, Yvonne, Soedamah-Muthu, Sabita S., Callaway, Leonie K. and Mishra, Gita D. (2018) Preconception risk of gestational diabetes: development of a prediction model in nulliparous Australian women. Diabetes Research and Clinical Practice, 146, 48-57. (doi:10.1016/j.diabres.2018.09.021).

Record type: Article

Abstract

AIM: To develop a prediction model for preconception identification of women at risk of gestational diabetes mellitus (GDM).

METHODS: Data from a prospective cohort, the Australian Longitudinal Study on Women's Health, were used. Nulliparous women aged 18-23 who reported a pregnancy up to age 37-42 were included. Preconception predictors of GDM during a first pregnancy were selected using logistic regression. Regression coefficients were multiplied by a shrinkage factor estimated with bootstrapping to improve prediction in external populations.

RESULTS: Among 6504 women, 314 (4.8%) developed GDM during their first pregnancy. The final prediction model included age at menarche, proposed age at future first pregnancy, ethnicity, body mass index, diet, physical activity, polycystic ovary syndrome, and family histories of type 1 or 2 diabetes and GDM. The model showed good discriminative ability with a C-statistic of 0.79 (95% CI 0.76, 0.83) after internal validation. More than half of the women (58%) were classified to be at risk of GDM (>2% predicted risk), with corresponding sensitivity and specificity values of 91% and 43%.

CONCLUSIONS: Nulliparous women at risk of GDM in a future first pregnancy can be accurately identified based on preconception lifestyle and health-related characteristics. Further studies are needed to test our model in other populations.

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More information

Accepted/In Press date: 28 September 2018
e-pub ahead of print date: 5 October 2018
Published date: December 2018
Keywords: Adult, Australia, Cohort Studies, Diabetes, Gestational/ethnology, Female, Humans, Longitudinal Studies, Parity, Pregnancy, Prospective Studies, Risk Factors

Identifiers

Local EPrints ID: 441330
URI: http://eprints.soton.ac.uk/id/eprint/441330
ISSN: 0168-8227
PURE UUID: c03d98dc-cbbb-44b7-a05b-1be3bf6b53e4
ORCID for Danielle A.J.M. Schoenaker: ORCID iD orcid.org/0000-0002-7652-990X

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Date deposited: 10 Jun 2020 16:30
Last modified: 17 Mar 2024 04:01

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Contributors

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

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