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Diabetes in Pregnancy and Risk of Antepartum Depression: A Systematic Review and Meta-Analysis of Cohort Studies

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  • Kai Wei Lee

    (Department of Family Medicine, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang, Selangor 43400, Malaysia)

  • Siew Mooi Ching

    (Department of Family Medicine, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang, Selangor 43400, Malaysia
    Malaysian Research Institute on Ageing, Universiti Putra Malaysia, Serdang, Selangor 43400, Malaysia)

  • Navin Kumar Devaraj

    (Department of Family Medicine, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang, Selangor 43400, Malaysia
    Malaysian Research Institute on Ageing, Universiti Putra Malaysia, Serdang, Selangor 43400, Malaysia)

  • Seng Choi Chong

    (Department of Psychiatry, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang, Selangor 43400, Malaysia)

  • Sook Yee Lim

    (Department of Nutrition and Dietetics, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang, Selangor 43400, Malaysia)

  • Hong Chuan Loh

    (Clinical Research Centre, Hospital Seberang Jaya, Ministry of Health Malaysia, Perai 13700, Pulau Pinang, Malaysia)

  • Habibah Abdul Hamid

    (Department of Obstetrics and Gynaecology, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang, Selangor 43400, Malaysia)

Abstract

Previous literature has reported that patients with diabetes in pregnancy (DIP) are at risk of developing antepartum depression but the results have been inconsistent in cohort studies. We conducted a systematic review and performed a meta-analysis to quantify the association between DIP and risk of antepartum depression in cohort studies. Medline, Cinahl, and PubMed databases were searched for studies investigating DIP involving pregnant women with pre-existing diabetes and gestational diabetes mellitus and their risk of antepartum depression that were published in journals from inception to 27 December 2019. We derived the summary estimates using a random-effects model and reported the findings as pooled relative risks (RR) and confidence interval (CI). Publication bias was assessed using a funnel plot and was quantified by Egger and Begg’s tests. Ten studies, involving 71,036 pregnant women were included in this meta-analysis. The pooled RR to develop antepartum depression was (RR = 1.430, 95% CI: 1.251–1.636) among women with gestational diabetes mellitus. Combining pregnant women with pre-existing diabetes mellitus and gestational diabetes mellitus, they had a significant increased risk of developing antepartum depression (RR = 1.431, 95% CI: 1.205–1.699) compared with those without it. In comparison, we found no association between pre-existing diabetes mellitus in pregnancy (RR = 1.300, 95% CI: 0.736–2.297) and the risk of developing antepartum depression. This study has a few limitations: first, different questionnaire and cut-off points were used in evaluation of depression across the studies. Second, there was a lack of data on history of depression prior to pregnancy, which lead to confounding bias that could not be solved by this meta-analysis. Third, data were dominated by studies in Western countries; this is due to the studies from Eastern countries failing to meet our inclusion criteria for statistical analysis. Women with gestational diabetes mellitus have an increased risk of developing antepartum depression compared to those without the disease. Therefore, more attention on the mental health status should be given on pregnant women diagnosed with pre-existing diabetes mellitus and gestational diabetes mellitus.

Suggested Citation

  • Kai Wei Lee & Siew Mooi Ching & Navin Kumar Devaraj & Seng Choi Chong & Sook Yee Lim & Hong Chuan Loh & Habibah Abdul Hamid, 2020. "Diabetes in Pregnancy and Risk of Antepartum Depression: A Systematic Review and Meta-Analysis of Cohort Studies," IJERPH, MDPI, vol. 17(11), pages 1-15, May.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:11:p:3767-:d:363130
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    1. Wallace, Byron C. & Dahabreh, Issa J. & Trikalinos, Thomas A. & Lau, Joseph & Trow, Paul & Schmid, Christopher H., 2012. "Closing the Gap between Methodologists and End-Users: R as a Computational Back-End," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 49(i05).
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