|Year : 2022 | Volume
| Issue : 4 | Page : 180-185
Association of sleep quality and duration with gestational diabetes mellitus: The Qazvin maternal and neonatal metabolic study
Sima Hashemipour, Fatemeh Lalooha, Fatemeh Sadat Etemad, Fatemeh Habibi Nozari
Metabolic Diseases Research Center, Research Institute for Prevention of Non-Communicable Disease, Qazvin University of Medical Sciences, Qazvin, Iran
|Date of Submission||19-Jul-2022|
|Date of Decision||12-Oct-2022|
|Date of Acceptance||19-Oct-2022|
|Date of Web Publication||22-Nov-2022|
Metabolic Diseases Research Center, Research Institute for Prevention of Non-Communicable Disease, Qazvin University of Medical Sciences, Qazvin
Source of Support: None, Conflict of Interest: None
Introduction: Association of a good sleep quality and adequate nocturnal sleep duration with metabolic health has been reported in several epidemiological studies. This study aimed to evaluate the impact of sleep quality and duration on gestational diabetes mellitus (GDM) occurrence. Methods: In this longitudinal study, 821 pregnant women with the gestational age of ≤14 weeks were included from 2018 to 2020 by convenience sampling. The participants were evaluated in terms of sleep quality using the Pittsburgh Sleep Quality Index and nocturnal sleep duration. They were also examined for GDM at gestational weeks 24–28. Two GDM and non-GDM groups were compared regarding sleep quality and duration. The multivariate logistic regression analysis was performed to assess the independent association of sleep-related variables with GDM occurrence. Results: The final analysis was performed on 658 participants. The means of age and gestational week of the participants were 29.8 ± 4.9 years and 8.8 ± 4.4 weeks, respectively, on inclusion in the study. During follow-up, GDM occurred in 104 (15.8%) participants. Poor sleep quality, sleep quality components, and nocturnal sleep duration showed no significant difference between groups. The frequency of night sleep duration <7 h was higher in the GDM group compared to the non-GDM group (14.4% vs. 7.8%, P = 0.028). However, in the multivariate analysis, there was no independent association between nocturnal sleep <7 h and GDM occurrence. Conclusion: Sleep quality, nocturnal sleep duration, and short nocturnal sleep duration had no independent association with GDM occurrence.
Keywords: Gestational diabetes mellitus, short sleep duration, sleep duration, sleep quality
|How to cite this article:|
Hashemipour S, Lalooha F, Etemad FS, Nozari FH. Association of sleep quality and duration with gestational diabetes mellitus: The Qazvin maternal and neonatal metabolic study. Asian J Soc Health Behav 2022;5:180-5
|How to cite this URL:|
Hashemipour S, Lalooha F, Etemad FS, Nozari FH. Association of sleep quality and duration with gestational diabetes mellitus: The Qazvin maternal and neonatal metabolic study. Asian J Soc Health Behav [serial online] 2022 [cited 2023 Mar 22];5:180-5. Available from: http://www.healthandbehavior.com/text.asp?2022/5/4/180/361708
| Introduction|| |
Sleep is a physiological process that is essential for psychological and physical health. The importance of sleep is beyond the simple rest needed for restarting daily activities. Free radicals are accumulated during wakefulness, and the non-REM phase of sleep provides an opportunity for restoring free radical-induced tissue damage., In addition, various changes in hormone secretion (especially cortisol and growth hormone) and in the sympathetic tone occur during sleep and are important for maintaining metabolic health.,
The relationship between a good sleep quality and metabolic health has been reported in several epidemiological studies. Higher visceral adiposity, insulin resistance, and higher incidence of diabetes have been reported in poor sleepers compared with good sleepers., Duration of sleep is another important factor for glucose homeostasis. Extremely short or long sleep durations have been reported as risk factors for metabolic syndrome and diabetes.,,
Pregnancy is a physiologic process accompanied by high levels of insulin resistance. Increased counter-regulatory hormone secretion by the placenta leads to substantial insulin resistance, which can lead to gestational diabetes mellitus (GDM) in susceptible pregnant women. On the other hand, the physiological, hormonal, and behavioral changes in pregnancy induce profound changes in sleep. The spectrum of pregnancy-induced sleep disturbances ranges from poor sleep quality, highly prevalent insomnia, and changed sleep duration (especially shortened sleep in the first trimester).
The impact of some risk factors, such as having a history of GDM or being overweight/obese, on GDM is well known; however, the role of nontraditional risk factors of GDM such as poor sleep quality and/or extremely short or long sleep duration is more controversial.,,,,
In addition to controversial results, there are some shortcomings in the literature. First, most studies are cross-sectional; thus, the evaluation of causality is impossible.,, More importantly, in some studies, nonstandard tools have been used to evaluate sleep quality, and assessment of sleep quality was limited to posing one to three questions to assess participants' feeling about sleep quality or only the frequency of insomnia.,, Even in the meta-analysis published by Zhu et al. on the association of sleep quality and gestational diabetes, more than 50% of the studies' weight belonged to three studies using nonstandard tools for sleep quality evaluation. The third important weakness in the literature is the lack of adjustment for the results for potential confounders. In the meta-analysis by Zhu et al., of the eight included studies, adjustments for multiple confounders were performed only in three studies.
Based on the above considerations, this prospective longitudinal study was designed to investigate the association of sleep quality and nocturnal sleep durations using a standard questionnaire and adjustment for potential confounders in the first trimester of pregnancy with the occurrence of GDM in gestational weeks 24–28.
Study design and setting
This prospective longitudinal study was conducted on women visiting obstetrics/gynecology clinics for antenatal care from September 2018 to May 2020 in Qazvin, the capital of Qazvin Province, Iran.
Participants and eligibility criteria
Women were recruited for this study from their first prenatal care visit. The eligibility criteria were pregnant women aged ≥20 years with a gestational age of ≤14 weeks according to the last menstrual period or ultrasound examination. The participants who had diabetes mellitus before pregnancy were excluded from the analysis.
Sample size estimation
The Qazvin maternal and neonatal metabolic study was designed to evaluate adverse pregnancy outcomes. To calculate the sample size with appropriate power, we considered the outcome of pre-eclampsia with the lowest prevalence. With the prevalence of preeclampsia of about 6%, a power of 80%, d = 0.02, α = 0.05, attrition of 20%, and early abortion rate of about 10%, the sample size was calculated to be at least 717 participants; however, due to having enough resources, we recruited 821 participants.
Sampling was performed by the convenience method. All eligible pregnant women from September 2018 to May 2020 entered the study.
Measures and outcomes
The data were collected during three antenatal visits: (1) The first antenatal visit at ≤14 gestational weeks, (2) during gestational weeks 22–28, and (3) during the first 6 weeks postpartum. On the first visit, information regarding demographic and social characteristics, a history of chronic diseases and use of medications, and previous gestational histories were recorded by two trained interviewers. The Pittsburgh Sleep Quality Index (PSQI) was used to evaluate sleep quality in the previous month. This questionnaire includes 19 items assessing seven components of sleep quality: sleep latency, sleep disturbances, habitual sleep efficiency, subjective sleep quality, sleep duration, using sleep medications, and daytime dysfunction. Each component is rated on a 0–3 scale, where 0 indicates no difficulty and 3 indicates the highest difficulty. Poor sleep quality has been defined as the PSQI total score >5. The reliability and validity of this questionnaire had previously been evaluated in the Iranian population. In our study, the value of Cronbach's alpha for testing the internal consistency of PSQI was 0.70. The Baecke questionnaire was used to assess physical activity in the past 12 months. This questionnaire includes 16 questions with three domains of physical activity (occupational, sport, and recreational activities) in the past 12 months. Physical activity is assessed by summing the scores of these three domains. The reliability and validity of this questionnaire had been examined in the Iranian population. In our study, the value of Cronbach's alpha of the Baecke physical activity questionnaire was 0.76
The oral glucose tolerance test (OGTT) was performed on the second visit (gestational weeks 24–28). Normal OGTT was defined as fasting blood glucose levels <92 mg/dL, 1-h glucose level <180 mg/dL, and 2-h glucose level <153 mg/dL. GDM was defined as having at least one measure above these values.
This study was approved by the Ethics Committee of Qazvin University of Medical Sciences (code: IR.QUMS.REC.1394.819). All the participants gave their written informed consent to participate in the study.
Statistical analysis was performed using SPSS-24. The blood glucose was measured via Cobas c 501: Hitachi automated Analyzer using Roche kit. The normality of quantitative data was examined by the Kolmogorov–Smirnov test. The t-test and Chi-square test were run to compare quantitative and categorical data, respectively. Logarithmic transformation was performed before comparing the data with a nonnormal distribution by t-test.
The multivariate logistic regression analysis was conducted to assess the independent association of poor sleep quality, mean night sleep duration, night sleep duration of < 7 h, and night sleep duration of >9 h (as independent variables) with the occurrence of GDM (as the dependent variable). Adjustments were made by entering variables with P < 0.2 into the univariate analysis in two separate models. In Model 1, the variables of age, gravidity, history of GDM in previous pregnancies, and body mass index (BMI) before pregnancy were entered into the model. In Model 2, an adjustment was made for the variables of Model 1 plus physical activity P < 0.05 was considered significant.
| Results|| |
In total, 821 pregnant women were recruited. Of these participants, 163 were excluded from the final analysis due to having a history of diabetes before pregnancy (n = 12), loss to follow-up (n = 124), overt undiagnosed diabetes (n = 6), and missing data (n = 21). Therefore, the final analysis was performed on 658 participants [Figure 1].
There was no significant difference between the excluded and analyzed groups regarding the demographic data, psychosocial parameters, and sleep-related variables.
During follow-up, GDM occurred in 104 (15.8%) participants. The demographic characteristics of the participants categorized by GDM status are shown in [Table 1]. The mean age, prepregnancy BMI, and frequency of GDM history were significantly higher in the GDM group compared to the non-GDM group. There was no difference in terms of other demographic characteristics between the two groups [Table 1].
|Table 1: The baseline characteristics of participants categorized by gestational diabetes mellitus status|
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The sleep quality component and sleep duration are compared between GDM and non-GDM groups in [Table 2]. The sleep quality components, the total sleep quality score, and good/poor sleep quality showed no significant difference between the groups. In terms of sleep duration, the GDM group had mild borderline significantly shorter sleep duration compared to the non-GDM group (8.4 h ± 1.5 h vs. 8.7 ± 1.4 h, P = 0.055). The frequency of night sleep duration <7 h was higher in the GDM compared to the non-GDM group (14.4% vs. 7.8%, P = 0.028). There was no difference regarding the variable night sleep duration >9 h between the two groups.
|Table 2: Association of sleep quality components and sleep duration with gestational diabetes mellitus|
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The crude and adjusted risks of poor sleep quality and sleep duration for GDM occurrence are listed in [Table 3]. Having a night sleep duration of <7 h was associated with a two times higher risk of GDM; however, after adjustment for other GDM risk factors, no significant association was observed. Other variables of poor sleep quality, mean night sleep duration, and night sleep duration of >9 h did not have any significant relationship with GDM, either in the adjusted or unadjusted models.
|Table 3: Adjusted risk for poor sleep quality and sleep duration for the occurrence of gestational diabetes mellitus|
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| Discussion|| |
In this prospective longitudinal study, we did not find any association of sleep quality components and their total score with the occurrence of GDM. Night sleep <7 h was associated with twice the risk of GDM in the later months; however, in adjusted models, there was no significant association between short sleep duration and GDM. Other measures of night sleep duration such as mean or long sleep duration also had no association with GDM. Regarding the nonsignificant results in the adjusted models, concealment of the relationship between sleep duration and quality by other variables is less probable in our study.
Evidence on the impact of sleep quality on GDM is highly inconsistent. In a cohort study by Cai et al. on Asian pregnant women, poor sleep quality was associated with a 1.75 times higher risk of GDM. The authors concluded that poor sleep quality predisposes Asian women to GDM. In a cross-sectional study by Bisson et al., pregnant women were compared with nonpregnant women regarding sleep quality using objective (polysomnography) and subjective (PSQI) methods. In this study, sleep quality had no association with GDM. In a study by Ahmed et al., sleep quality was assessed in two phases of the 22nd and 32nd gestational weeks. Sleep quality was worse in the later phase of pregnancy; nevertheless, the authors did not find any relationship between poor sleep quality and maternal serum glucose.
Sharma et al. and Reutrakul et al. found no association between sleep quality and GDM., In the meta-analysis by Zhu et al., poor sleep quality was a significant risk factor for GDM (pooled OR = 1.43, 95% CI: 1.16, 1.77, P = 0.001). However, in three studies with the highest weight in the analysis, the assessment of sleep quality was performed with nonstandard tools. In the study by Zhong et al., sleep quality was assessed by one question about the frequency of experiencing insomnia in the previous month. In the study by Wang et al., sleep quality was evaluated by one question on the participants' feelings about their sleep quality during the index pregnancy. Furthermore, in the study by Xu et al., the participants were asked only the following question: “How is your quality of sleep during pregnancy?” Due to the very large sample size of these three studies, their weight accounted for 58.6% of the studies' weight in the meta-analysis. Therefore, as the authors also stated, the results of this meta-analysis should be interpreted with caution.
Similar to the impact of sleep quality on the GDM risk, the reported data on the association of sleep duration and GDM risk are inconsistent. In the studies by Cai et al. and Reutrakul et al., short nocturnal sleep duration, defined as <6 h and <7 h, respectively, was a risk factor for GDM., In the study by Reutrakul et al., nocturnal sleep duration had an inverse correlation with blood glucose 1 h after a 50-g glucose tolerance test; for each hour decrease in nocturnal sleep duration, a 4% increase in blood glucose was detected. On the contrary, in the study by Wang et al., a j-shaped association between sleep duration and GDM was found, and sleep duration ≥9 h was associated with an about 20% higher risk of GDM. In the studies by Ahmed et al. and Bisson et al., no relationship was reported between sleep duration and GDM., In our study, unadjusted sleep duration <7 h was associated with a higher GDM risk; nevertheless, there was no significant association after adjusting for other GDM risk factors.
Considering previous studies on sleep quality and/or duration, it seems that some socioeconomic or psychological factors may influence this association. In our previous study on the impact of sleep quality on metabolic syndrome in workers versus employees, poor sleep quality was independently associated with a three times higher risk of metabolic syndrome in workers, but no association was found in the employee group. According to Jennings et al., sleep quality was associated with metabolic syndrome; however, after adjusting for depression, this relationship became nonsignificant. In the study by Nguyen-Rodriguez et al., high sleep latency was a risk factor for emotional eating; however, in multivariate models, the anxiety trait was an essential factor for emotional eating in participants with high sleep latency.
Given the above considerations, designing other studies to examine the roles of race, as well as socioeconomic and psychological factors, in the impact on sleep quality/duration is warranted.
Our study had some limitations and advantages. The main limitation of this research was evaluating sleep quality and duration by subjective methods. The advantages of our study were its longitudinal design and acceptable sample size.
| Conclusion|| |
We did not find any relationship between sleep quality in the first trimester and GDM occurrence in the later months. Despite the twice higher risk of GDM in women with nocturnal sleep duration <7 h, this association was not independent in the multivariate analysis.
The authors would like to thank the participants for their collaboration, and the Research Department of the Qazvin University of Medical Science for endorsement of this project.
Financial support and sponsorship
This study was supported by a grant from the Research Department of Qazvin University of Medical Sciences.
Conflicts of interest
There are no conflicts of interest.
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[Table 1], [Table 2], [Table 3]