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Abstract
Objective Maternal obesity and gestational diabetes mellitus (GDM) are becoming major public health concerns in developing countries. Understanding their relationship can help in developing contextually appropriate and targeted prevention strategies and interventions to improve maternal and infant health outcomes. This study aimed to determine the association of maternal overweight and obesity with GDM among pregnant women in Ethiopia.
Design Case-control study.
Setting The study was conducted in selected public hospitals in Addis Ababa, Ethiopia, from 10 March to 30 July 2020.
Participants 159 pregnant women with GDM (cases) and 477 pregnant women without GDM (controls).
Outcome measures and data analysis Screening and diagnosis of GDM in pregnant women was done by a physician using the 2013 WHO criteria of 1-hour plasma glucose level of 10.0 mmol/L (180 mg/dL) or 2-hour plasma glucose level of 8.5–11.0 mmol/L (153–199 mg/dL) following a 75 g oral glucose load. Overweight and obesity were measured using mid-upper arm circumference (MUAC). Binary logistic regression with bivariate and multivariable models was done to measure the association of overweight and obesity with GDM. Adjusted ORs (AORs) with a 95% CI were computed, and statistical significance was determined at a value of p=0.05.
Results GDM was associated with obesity (MUAC≥31) (AOR 2.80; 95% CI 1.58 to 4.90), previous history of caesarean section (AOR 1.91; 95% CI 1.14 to 3.21) and inadequate Minimum Dietary Diversification Score <5 (AOR 3.55; 95% CI 2.15 to 5.86). The AOR for overweight (MUAC≥28 and MUAC<31) was 1.51 (95% CI 0.71 to 3.21). The odds of developing GDM were 72% lower in pregnant women who were engaging in high-level physical activity (AOR 0.28; 95% CI 0.12 to 0.67).
Conclusion Obesity, but not overweight, was significantly associated with the development of GDM. Screening for GDM is recommended for pregnant women with obesity (MUAC≥31) for targeted intervention. Antenatal care providers should provide information for women of childbearing age on maintaining a healthy body weight before and in-between pregnancies and the need for healthy, diversified food and high-level physical activity.
- Obesity
- Diabetes in pregnancy
- Maternal medicine
- Diabetes & endocrinology
Data availability statement
Data are available upon reasonable request. All data relevant to the study are included in the article or uploaded as supplementary information.
This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
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STRENGTHS AND LIMITATIONS OF THIS STUDY
This study was conducted across multiple centres and used a robust analytical observational study design with a reasonably large and representative sample.
Using standard measurements such as mid-upper arm circumference for assessing overweight/obesity and the oral glucose tolerance test for screening gestational diabetes mellitus improves the validity of the results.
The physical activity and dietary data were self-reported by women for the past 7 days prior to the interview, potentially affected by recall bias.
Introduction
Gestational diabetes mellitus (GDM) is defined as glucose intolerance first detected during pregnancy and usually diagnosed at 24–28 weeks of gestational age or at any time in pregnancy if one or more of the following criteria are met: fasting plasma glucose 5.1–6.9 mmol/L (92–125 mg/dL), 1-hour plasma glucose 10.0 mmol/L (180 mg/dL) following a 75 g oral glucose load, and 2-hour plasma glucose 8.5–11.0 mmol/L (153–199 mg/dL) following a 75 g oral glucose load.1
Despite the fact that GDM usually exists as a transient disorder during pregnancy and resolves once the pregnancy ends, it is associated with a higher incidence of maternal morbidity, including caesarean deliveries, birth trauma, hypertensive disorders of pregnancy (including pre-eclampsia), and a higher risk of developing GDM in subsequent pregnancies. About half of women with a history of GDM will develop type 2 diabetes mellitus (T2DM) within 5–10 years after delivery. Babies born to mothers with GDM also have a higher lifetime risk of obesity, cardiovascular disease and developing T2DM.2–8 Perinatal and neonatal morbidities like macrosomia, shoulder dystocia birth injury, hypoglycaemia, polycythaemia, and hyperbilirubiaemia, lifetime obesity, and low Apgar Score also increased.4 5 8–12
It is estimated that 21.1 million (16.7%) of live births to women in 2021 had some form of hyperglycaemia in pregnancy. Of these, 80.3% were due to GDM, while 10.6% were the result of diabetes detected prior to pregnancy, and 9.1% were due to diabetes (including type 1 and type 2) first detected in pregnancy.13
The vast majority (87.5%) of cases of hyperglycaemia in pregnancy were in low-income and middle-income countries, where access to maternal care is often limited.13 GDM prevalence in Africa is 13.61%. The prevalence is highest in central Africa (20.4%) and lowest in northern Africa (7.57% subregions).14 In Ethiopia, the prevalence is different in studies, ranging from 4.2% in Gondar, southern Ethiopia, to 12.8% in Wolaita, North-West Ethiopia.15 16
Studies showed that risk factors for GDM include maternal overweight and obesity.14 16–21 However, most of the studies use body mass index (BMI) as a measure of overweight/obesity, which could be biased due to the fact that BMI is not sensitive to determining overweight and obesity in pregnancy due to its additional weight gain from the fetus and placenta as well as an increase in the size of maternal organs, especially the breast and the uterus. Instead, several studies recommend using mid-upper arm circumference (MUAC) as a substitute for BMI in pregnant women.22–27
In Ethiopia, the 2016 EDHS report revealed that the proportion of women who are overweight or in the range of obesity in Ethiopia has increased from 3% in 2000 to 8% in 2016.28 Despite this increase in the incidence of overweight and obesity in Ethiopia, limited studies are showing the association of overweight and obesity with GDM in pregnant women. Even the limited available studies had either controversial findings on the association of overweight and obesity with GDM or used insensitive measurements to assess overweight and obesity. Due to late booking into ANC in our country and because self-report of prepregnancy BMI is not reliable, it is difficult to get prepregnancy or early pregnancy BMI of pregnant women to assess obesity.
Understanding the relationship between overweight or obesity and GDM can help in developing contextually appropriate and targeted prevention strategies and interventions to improve maternal and infant health outcomes. Hence, this study aimed to determine the association of maternal overweight and obesity with GDM among pregnant women in Ethiopia.
Understanding the relationship between overweight or obesity and GDM can help in developing contextually appropriate and targeted prevention strategies and interventions to improve maternal and infant health outcomes. Hence, this study aimed to determine the association of maternal overweight and obesity with GDM among pregnant women in Ethiopia.
Methods
Study design, setting and period
The study was conducted in eight selected hospitals and ANC clinics that provide maternal and child health services in Addis Ababa Administrative City, from 10 March to 30 July 2020. These hospitals primarily provide maternal and child healthcare.
The study was conducted using an unmatched case-control study design and reported according to the Strengthening the Reporting of Observational Studies in Epidemiology checklist of items for case-control studies (online supplemental file 1).
Supplemental material
Study population
Pregnant women with a gestational age >24 weeks who attended antenatal care services in the selected maternal and child health service provision hospitals during the study period were the study population. Cases were pregnant women with a gestational age >24 weeks with the diagnosis of GDM by oral glucose tolerance test, and controls were pregnant women with a gestational age >24 weeks without GDM.
Inclusion criteria
Pregnant women with a gestational age >24 weeks who attend ANC in selected maternal and child health service provision hospitals.
Exclusion criteria
Pregnant women with known type 1 diabetes mellitus (T1DM), pregnant women with known T2DM and pregnant women having multiple pregnancies confirmed by ultrasound screening were excluded.
Sample size determination and sampling approach
The sample size was determined using EPI Info software V.7, employing the double population proportion formula for a case-control study design.29 The calculation was based on several assumptions: a Z-score corresponding to a 95% confidence level, a power of 80%, a ratio of 3:1 between controls and cases, and an OR of 2.0., It also took into account a 14.4% exposure rate (overweight and/or obesity) among women without GDM from a study in Gondar, Ethiopia16 as well as a 10% non-response rate. Ultimately, the final sample consisted of 159 pregnant women with GDM (cases) and 477 without GDM (controls). Eight hospitals were selected based on the availability of the oral glucose tolerance test (OGTT) test for screening GDM and the number of pregnant women they serve. A proportional allocation to population size was used to allocate the number of participants in each hospital. The base for proportional allocation was the last 3-month record of GDM cases in each hospital. Eligible pregnant women who were diagnosed with GDM by the physician using a 75 g or 100 g OGTT test were considered cases. All cases attending ANC during the data collection period were included in the study until the required sample size was reached. Three consecutively found women who were negative for GDM were considered controls. This procedure was continued until the required sample size was attained.
Data collection
Data were collected through face-to-face interviews using a structured questionnaire, which was prepared after a review of different literature (online supplemental file 2). The dietary and physical activity sections of the questionnaire were adapted from the Food and Nutrition Technical Assistance (FANTA) 2016 version of women’s minimum dietary diversity measurement tool and the short form of the International Physical Activity Questionnaire (IPAQ), respectively.30 31 The outcome variable, GDM, was obtained from the pregnant women’s ANC chart. The questionnaire was prepared in English and then translated to Amharic (the national language) and back-translated to English to observe consistency. A pretest was done 2 weeks before the actual data collection period on 3% (n=19) of the sample size at Zewditu Memorial Hospital, TASH, SPHMMC, and Grace MCH.
Supplemental material
The MUAC was measured on the left arm using a non-stretchable measuring tape. Dietary diversity was assessed using a 24-hour food recall method using the FANTA 2016 version of a woman’s minimum dietary diversity measurement tool. The short-form IPAQ was used to assess the physical activities that women do as part of their everyday lives. Participants will be asked to recall their activities from the last 7 days preceding the interview. Data were reported as high, moderate and low using the IPAQ scoring protocol.32
Operational definitions
Overweight in pregnancy: Having a MUAC measurement of ≥28 and <31 was considered overweight.16 33
Obesity in pregnancy: Having a MUAC measurement of ≥31 was considered obesity.22
High-risk pregnant women for GDM: Having macrosomia (current or past pregnancy), GDM in the past, unexplained stillbirth, T2DM in a first-degree relative, and history of recurrent abortion.
Presence of GDM: The 2013 WHO criteria of 1-hour plasma glucose level of 10.0 mmol/L (180 mg/dL) or 2-hour plasma glucose level of 8.5–11.0 mmol/L (153–199 mg/dL) following a 75 g oral glucose load by a physician was used to diagnose GDM.34
Diabetes in pregnancy: Known T1DM, known T2DM and diabetes first detected in pregnancy before 24 weeks of gestational age from history and an ANC follow-up card.
High on the IPAQ: Engage in vigorous-intensity activity on at least 3 days or 7 or more days of any combination of walking, moderate-intensity or vigorous-intensity activities.
Moderate on the IPAQ: Engage in five or more days of moderate-intensity activity and/or walking of at least 30 min per day; or five or more days of any combination of walking, moderate-intensity or vigorous-intensity activities.
A low level of physical activity on the IPAQ: means that you are not meeting any of the criteria for either moderate or high levels of physical activity.
Adequate dietary diversity: If the pregnant woman has consumed the list of defined food groups on the previous day or night, she will get a score of 1 or, if not, 0. The MDDS of 5 or more was categorised as adequate dietary diversity.
Data processing and analysis
The data were cleaned, edited and entered into EpiData V4.1. Then the data were exported to SPSS window V.21 for analysis.
The collected data were coded, entered, cleaned and checked for missing values using EpiData Manager V.4.2 and analysed using SPSS V.21. Descriptive statistics were done by computing proportions and summary statistics. Binary logistic regression analysis was used to determine the association of overweight and obesity with GDM. Initially, bivariate logistic regression analysis was done, and a crude OR with a 95% CI was computed. In the bivariate analysis, variables with a value of p<0.25 were included in the multivariable logistic regression analysis.35 Adjusted ORs (AORs) with a 95% CI were calculated and factors with a value of p<0.05 were declared independent predictors.
Ethical approval and consent to participate
The chief executive officer of each hospital was informed about the aim of the study, and written permission was obtained before starting data collection. Furthermore, informed consent was obtained from each study participant. The names of the participants were not written on the questionnaire, and the confidentiality of the data was maintained at each step.
Patient and public involvement
None.
Results
Sociodemographic characteristics of the participants
The study included 636 pregnant women, 159 with GDM (cases) and 477 without GDM (controls), giving a response rate of 100%. The mean (SD) age of respondents was 31.9 (4.8) years for cases and 29.5 (4.8) years for controls. Additionally, 158 cases (99.4%) and 475 controls (99.6%) were married. Furthermore, 109 cases (68.6%) and 296 controls (62.1%) had a monthly income of Ethiopian birr 4000 or more (table 1).
Sociodemographic characteristics of participants
Dietary, lifestyle, obstetric and medical-related characteristics of participants
Among the study participants, 95 (59.7%) of cases and 82 (17.2%) of controls had inadequate dietary diversification scores (<5). Forty-four per cent of women with GDM and 14.7% of those without GDM had low levels of physical activity. Among women with GDM, 86.2% were overweight, compared with 68.1% of women without GDM. Obesity was observed in 66.7% of women with GDM and 21.4% of those without. Additionally, 30.2% of women with GDM and 17.7% of those without GDM had a history of delivering macrocosmic babies. A history of caesarean delivery was reported by 61.2% of cases and 28.7% of controls. A notable number of women experienced abortion or miscarriage, with 50 cases and 66 controls affected. Furthermore, 12.2% of cases and 8.3% of controls had a history of stillbirth, and 14.4% of cases and 8.8% of controls had previously experienced GDM (table 2).
Dietary, lifestyle, obstetric and medical-related characteristics
Of the total pregnant women with GDM, 90 (56.6%) had a family history of T2DM and 21 (13.2%) had first-degree relatives with GDM (figure 1).
Family history of type 2 diabetes mellitus (T2DM) and first-degree relatives with gestation diabetes mellitus (GDM) among cases and controls.
Determinants of GDM
In this study, the results of bivariate logistic regression analysis showed that age group, gravidity, history of delivering a macrosomic baby, history of caesarean delivery, history of abortion or miscarriage, history of stillbirth, history of previous GDM, family history of T2DM, first-degree relative having GDM, MDDS, physical activity, overweight, and obesity were found to be associated with GDM at a value of p<0.25 (full bivariate analysis table, online supplemental file 3). After adjusting for possible confounders, obesity, history of caesarean section in a previous delivery, engaging in high-level physical activity, and having an inadequate minimum dietary diversification score were found to be significantly associated with the development of GDM. The overall fit of the multivariable logistic regression model was verified by the Hosmer-Lemeshow test, yielding a value of p=0.12.
Supplemental material
Accordingly, pregnant women with obesity (MUAC ≥31) were three times more likely to have GDM than pregnant women without obesity (AOR=2.80; 95% CI 1.58 to 4.90). The odds of developing GDM were nearly two times higher (AOR: 1.91, 95% CI 1.14 to 3.21) for women with a history of caesarean section in a previous delivery than their counterparts. Those women who had inadequate minimum dietary diversification score were three times more likely (AOR: 3.55, 95% CI 2.15 to 5.86) to develop GDM than those who had an adequate minimum dietary diversification score. The odds of developing GDM were 72% lower in pregnant women who were engaging in high-level physical activity (AOR=0.28; 95% CI 0.12 to 0.67) (table 3).
Factors associated with GDM
Discussion
The study found that obesity, a history of caesarean section in a previous delivery, engaging in high (vigorous) physical activity, and having an inadequate Minimum Dietary Diversification Score were found to be the determinants of GDM.
This study revealed that pregnant women with obesity (MUAC≥31) were three times more likely to have GDM than pregnant women without obesity. This is in line with studies from Ethiopia and Tanzania that showed overweight and/or obesity (MUAC≥28) were significantly associated with the development of GDM, though they measured overweight and obesity together.16 33 Using prepregnancy BMI, different studies in Tanzania, Cameron and Malaysia also revealed that obesity has a significant association with the development of GDM.18–20 This finding is also in agreement with systematic review and meta-analysis studies that revealed there was a significant association between obesity and GDM.14 21 36 This can be explained by the fact that obesity leads to decreased insulin sensitivity and a higher degree of insulin resistance and contributes to GDM development.37 38
The study also revealed that GDM was two times higher in pregnant women with a history of caesarean section delivery. Gestational diabetes increases the risk of a large baby, which might make caesarean delivery more likely. This finding was supported by different studies conducted in Ethiopia.15 39 40
The other finding of this study was that the presence of GDM was three times higher among women with an inadequate minimum dietary score. Similarly, three studies in Ethiopia revealed that inadequate dietary diversity increases the risk of developing GDM.16 39 41 A systematic review and meta-analysis also showed that adherence to a diet with a high Alternate Healthy Eating Index 2010 Score was associated with a reduced risk of GDM by 83%,42 and a prospective observational study in Iceland showed that adhering to a prudent dietary pattern in pregnancy was associated with a lower risk of GDM.43 This observation is possible because inadequate dietary diversity will decrease the probability of getting a high-fibre diet that controls blood sugar levels.44
The odds of developing GDM were 72% lower in pregnant women who were engaging in high-level physical activity compared with women who were engaged in low and moderate physical activity. This finding is supported by three studies conducted in Ethiopia.16 39 41 Similarly, the result agrees with findings from Tanzania, Vietnam, a randomised trial from China and two systematic reviews.42 45–48 This result is explained by the fact that exercise increases insulin sensitivity, possibly by changing the adipokine profile and by upregulating antioxidant defence mechanisms.49
This study was conducted across multiple centres and used a more robust analytical observational study design with a larger and more representative sample size. Using standard measurements such as MUAC for assessing overweight/obesity and the OGTT for screening GDM provides more valid results. However, the study is not without limitations. First, the physical activity and dietary data were self-reported by women for the past 7 days prior to the interview, potentially affected by recall bias. Second, the data on dependent and independent variables were collected at the same time, which makes it difficult to assess the temporal relationships between exposure and outcome variables.
Conclusions
GDM was high in pregnant women with obesity (having MUAC≥31), but not in overweight women. Moreover, pregnant women with a previous history of caesarean section and having inadequate Dietary Diversification Scores have a higher risk of getting GDM, and engaging in high physical activity was found to be a protective factor for the development of GDM. This study suggests that the health authorities should develop obesity screening and prevention guidelines for women of childbearing age before conception time. Health education programmes should be planned in all health facilities, and awareness of maintaining a healthy body weight before and in-between pregnancies and the need for healthy, diversified food and physical activity should be emphasised.
Data availability statement
Data are available upon reasonable request. All data relevant to the study are included in the article or uploaded as supplementary information.
Ethics statements
Patient consent for publication
Ethics approval
This study involves human participants. This research was approved by the School of Public Health, College of Health Science, Addis Ababa University, Institutional Review Board and Addis Ababa Health Bureau ethical review committee (reference no. A/A/H/B/8265/227). The chief executive officer of each hospital was informed about the aim of the study, and written permission was obtained before starting data collection. Furthermore, informed consent was obtained from each study participant. The names of the participants were not written on the questionnaire, and the confidentiality of the data was kept at each step. Participants gave informed consent to participate in the study before taking part.
Acknowledgments
The authors thank Addis Ababa University and the Addis Ababa health office for their close support. The authors also thank the study participants, supervisors and data collectors for their willingness and cooperation during data collection and fieldwork.
Supplementary materials
Supplementary Data
This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.
Footnotes
Contributors YMS was involved in conceiving, designing, implementing the study, designing the questionnaire, data collection, statistical analysis, and manuscript writing. YS was involved in the designing, supervision, statistical analysis, and manuscript writing. ND was involved in the designing, supervision, statistical analysis. All authors reviewed and approved the final manuscript. YMS is acting as guarantor.
Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests None declared.
Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Provenance and peer review Not commissioned; externally peer reviewed.
Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.