Prevalence and predictors for postpartum sleep disorders: a nationwide analysis

Abstract

Objective

To describe the prevalence and predictors of postpartum sleep disorders.

Design

A retrospective cohort study.

Setting

Postpartum.

Population

Commercially insured women delivering in California (USA) between 2011 and 2014.

Methods

Using the Optum Clinformatics Datamart Database.

Main outcome measures

Prevalence of a postpartum sleep disorder diagnosis with and without a depression diagnosis up to 12 months following hospital discharge for inpatient delivery. We also identified predictors of a postpartum sleep disorder diagnosis using multivariable logistic regression.

Results

We identified 3535 (1.9%) women with a postpartum sleep disorder diagnosis. The prevalence of sleep disorder diagnoses was insomnia (1.3%), sleep apnea (0.25%), and other sleep disorder (0.25%). The odds of a postpartum sleep disorder were highest among women with a history of drug abuse (adjusted odds ratio (aOR): 2.70, 95% confidence interval (CI): 1.79–4.09); a stillbirth delivery (aOR: 2.15, 95% CI: 1.53–3.01); and chronic hypertension (aOR: 1.82; 95% CI: 1.57–2.11). A comorbid diagnosis of a postpartum sleep disorder and depression occurred in 1182 women (0.6%). These women accounted for 33.4% of all women with a postpartum sleep disorder. The strongest predictors of a comorbid diagnosis were a history of drug abuse (aOR: 4.13; 95% CI: 2.37–7.21) and a stillbirth delivery (aOR: 2.93; 95% CI: 1.74–4.92).

Conclusions

Postpartum sleep disorders are underdiagnosed conditions, with only 2% of postpartum women in this cohort receiving a sleep diagnosis using International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) codes. Insomnia was the most common disorder and one-third of women diagnosed with a postpartum sleep disorder had a co-morbid diagnosis of depression. Future studies are needed to improve the screening and diagnostic accuracy of postpartum sleep disorders.

Keywords:

• Depression
• insomnia
• sleep
• postpartum
• prevalence

Acknowledgements

Pervez Sultan is an Arline and Pete Harman Endowed Faculty Scholar of the Stanford Maternal and Child Health Research Institute. Data for this project were accessed using the Stanford Center for Population Health Sciences Data Core.

Ethical approval

The study was exempted from review by the institutional review board at Stanford University School of Medicine since it only used de-identified data.

Author contributions

PS and BC were involved in study conception, planning, study design, data interpretation, and manuscript writing. NG and MAK were involved in planning, data analysis, and interpretation. MK, FHB, SM, MAK, and CE were involved in data interpretation and manuscript writing. AJB was involved in study conception, planning, study design, data analysis, data interpretation, and manuscript writing.

Disclosure statement

None of the authors have any conflicts of interest to declare.

Data availability statement

Study data available upon reasonable request.

Additional information

Funding

The PHS Data Core is supported by a National Institutes of Health National Center for Advancing Translational Science Clinical and Translational Science Award (UL1 TR001085) and from Internal Stanford Funding.