Prevalence and Trends of Gestational Diabetes in a Large University Hospital in Lebanon Before and During the COVID-19 Pandemic

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The objective of our study was to determine the prevalence of GDM in Lebanon and to evaluate its risk factors before and during the COVID-19 pandemic. Methods Records of 2595 pregnant women who gave birth at the Hôtel-Dieu de France Hospital in Beirut, were collected retrospectively from 2018–2022. GDM was determined by documentation in the maternity fileward. A univariate analysis was performed to assess the factors affecting GDM. The χ² test, Fisher’s exact test, independent samples T-test, and ANOVA were used for this purpose. Results The mean age was 32.03 years (± 4.75). The mean BMI at the beginning of pregnancy was 24.86 kg/m² (± 8.99), and the mean gestational weight gain (GWG) was 12.17 kg (± 5.06). The overall prevalence of GDM was 4.1%, increasing significantly from 2.9% to 6.4% between 2018 and 2022 (p value = 0.007). The peak in 2020 coincided with the COVID-19 pandemic and the significant drop in income due to the concomitant economic and political crisis in the country. The risk factors associated with GDM included older age (p = 0.003) and obesity (p = 0.004). Conclusion The increasing trend of GDM incidence emphasizes the importance of implementing evidence-based prevention, diagnostic, and treatment strategies. Prevalence Gestational Diabetes Lebanon COVID-19 Pregnancy Figures Figure 1 Figure 2 Background Gestational diabetes mellitus (GDM) is a type of hyperglycemia that manifests for the first time during pregnancy and resolves after delivery ( 1 ). It is the most common metabolic-associated complication of pregnancy; it increases the risk of neonatal and maternal morbidity and is highly predictive of the subsequent development of type 2 diabetes in affected women( 2 , 3 ). Moreover, numerous studies indicate that hyperglycemia during pregnancy influences the long-term metabolic health of offspring ( 4 ). The global epidemiology of GDM and secular trends over recent decades remain unclear due to the lack of consensus on diagnostic criteria ( 5 ). In fact, the rates of GDM vary widely from approximately 1% to > 20% ( 6 , 7 ). Interestingly, a systematic review of 31 cohorts and cross-sectional studies with 136 705 women revealed that adopting the International Association of Diabetes in Pregnancy Study Group (IADPSG) criteria resulted in an overall 75% increase in GDM incidence compared with previous local criteria (relative risk, 1.75; 95% CI, 1.53–2.01) ( 8 ). The major risk factors that contribute to the increasing prevalence of GDM include increased maternal obesity and advanced maternal age ( 6 , 7 ). Although there is still no consensus on the best way to screen for GDM, there is broad agreement on the importance of early diagnosis and identification of women at risk to optimize glycemic control and reduce pregnancy-related complications and associated healthcare costs ( 9 ). Understanding population-specific healthcare needs over time is essential, and prevalence estimates are useful for this purpose ( 10 ). The prevalence of GDM in Lebanon remains largely unknown, and the few available studies date back to 2016 ( 10 ). In 2019, the country was plagued by one of the worst economic crises since the mid-20th century, followed by the COVID-19 pandemic, and culminated with the Beirut port explosion on August 4th, 2020 ( 11 ). Several prospective studies have demonstrated that exposure to stressful events predisposes individuals to hyperglycemia, metabolic syndrome, and type 2 diabetes (T2D) ( 12 , 13 ). Nevertheless, the literature examining the relationship between life stressors and GDM remains limited ( 14 ). To our knowledge, no such study has been conducted in Lebanon. Therefore, we aimed to determine the annual prevalence of GDM in a single tertiary care referral center in Lebanon from 2018–2022. We also examined the associated risk factors for GDM, such as maternal age, obesity, and gestational weight gain (GWG). Finally, we evaluated the impact of the COVID-19 pandemic and the economic crisis period on the incidence of GDM. Methods Study Design A retrospective observational study was conducted at Hôtel-Dieu de France (HDF) Hospital in Beirut, Lebanon. All pregnant Lebanese women admitted to the gynecology and obstetrics department for delivery between September 10, 2018, and December 31, 2022, were included. Data were extracted from the hospital's electronic medical record system (DX Care). Prior to September 2018, the files were not yet electronic. Women of non-Lebanese nationality were excluded, as were those with pregestational type 1 or type 2 diabetes. The following variables were retrieved from the records: location of residence, average monthly income, education level, and lifestyle habits such as smoking and a sedentary lifestyle. March 14, 2020, marked the beginning of the first total lockdown in Lebanon. Maternal age was stratified into the following categories: 40 years. Height (m), prepregnancy weight (kg), and prepregnancy body mass index (BMI) (kg/m 2 ) were noted. Underweight women had a BMI 30. Moreover, we divided our population into 2 groups according to BMI: 25 kg/m². GWG in kg was also recorded and then stratified according to Institute of Medicine (IOM) recommendations for each BMI category, with a total weight gain of 12.5–18 kg for underweight individuals (< 18.5 kg/m 2 ), 11.5–16 kg (0.35–0.50 kg/m2) for normal weight individuals (18.5–24.9 kg/m 2 ), 7–11.5 kg for overweight individuals (25–29.9 kg/m 2 ) and 5–9 kg for obese individuals (≥ 30 kg/m 2 ) ( 15 ). Other variables were also extracted, such as GDM treatment (diet, metformin, or insulin), smoking during pregnancy, COVID-19 pneumonia during pregnancy, gestational hypertension (GH), preeclampsia, eclampsia, preterm premature rupture of membranes (PPROM), mode of delivery (vaginal delivery, instrumental vaginal delivery or cesarean section) and neonatal complications such as macrosomia (with infant birth weight > 4000 g), intrauterine growth restriction and prematurity. Screening and diagnostic methods for GDM at Hôtel-Dieu de France: At HDF Hospital, all obstetricians used the same method of screening for GDM at 24–26 weeks of gestation for all pregnant women. The test consisted of a modified version of the oral glucose tolerance test (OGTT), which measures fasting blood glucose and only 2 hours after a 75 g oral glucose load. If the blood glucose level exceeded the established threshold (≥ 92 mg/dL at fasting or ≥ 153 mg/dL 2 hours after the glucose load), the woman was considered to have GDM and was referred to an endocrinologist for further management. For high-risk patients, a fasting blood glucose test was performed early in pregnancy, coupled with an HbA1c. Notably, there was no change in the screening policy between 2018 and 2022. Ethical considerations: The study received approval from the Ethics Committee of Hôtel-Dieu de France (Reference: Tfem/2023/72). Informed consent was not needed, as the data collection was anonymous and retrospective. Statistical analysis: The data were then analyzed via SPSS version 26. Continuous variables are expressed as the means and percentages, whereas categorical variables are expressed as frequencies and percentages. Next, a univariate analysis was conducted to evaluate differences in the variables of interest across years and then between the prepandemic period and the COVID-19 pandemic period. A univariate analysis was also performed to assess the factors affecting GDM. The χ² test, Fisher’s exact test, independent samples t test, and ANOVA were used for univariate analyses. The statistical significance threshold was set at p ≤ 0.05. Results Social and demographic characteristics of the population: A total of 2595 pregnant women who gave birth at HDF between 2018 and 2022 were included in the cohort (Figure 1). The number of deliveries in 2018 was much lower than that in other years because only records from the last 3 months of 2018 were included. Most women resided near the capital (Mount Lebanon 75.5% and Beirut 9.7%) (Table 1). Since 2020, income has significantly declined (p <0.001) over the subsequent years. Indeed, there was a shift from a majority with an income above $3000 (58.8% in 2018 and 56.1% in 2019) to a majority with an income lower than $1000 (46.8% in 2021 and 49.9% in 2022). Most of the women in our cohort (88.4%) had a university diploma (Table 1). The overall population was physically active (86.6%), but a significant increase in sedentary lifestyles was observed across the years (5% in 2018, 9.4% in 2019, 6.9% in 2020, 12.7% in 2021, and 14.1% in 2022). Moreover, 99% of women did not smoke during pregnancy, with no significant change from 2018 to 2022 (Table 1). Most pregnancies were carried at term (78.7%) and were singletons (95.6%) (Table 2). The mean age of the population was 32.03 years (± 4.75), with no significant difference across the study period. Most women became pregnant between 30 and 34 years of age (40%). Moreover, women 35 years and older represented a considerable proportion of our cohort (31.3%) (Table 2). The mean BMI at the beginning of pregnancy was 24.86 kg/m² (±8.99), and the mean GWG was 12.17 kg (±5.06), with no notable difference across the study period (Table 2). In fact, most women had a GWG in accordance with the IOM recommendations (38%) or even below these recommendations (32.7%) (Table 2). Prevalence of GDM at HDF: The overall GDM prevalence was 4.1%. This rate varied significantly over the years (3.1% in 2019, 2.9% in 2021, 3.6% in 2022, p value of 0.007) and peaked in 2020 (6.4%). The majority of GDM cases (79.4%) were mild and managed with lifestyle and dietary measures (Table 3). When stratified according to BMI, GDM prevalence was 4.46% and 10.54% in women with a BMI < 25 kg/m² and those with a BMI ≥ 25 kg/m², respectively. The GDM incidence according to each BMI category followed the same trends over the years, as shown in Figure 2 (p = 0.498). On the other hand, the mean maternal age remained the same across the years (p=0.36), with most individuals aged between 30 and 34 years (40.1%) (Table 2). Similarly, no significant fluctuations in GWG were observed from 2018 to 2022 (p=0.15). (Table 2) Other maternal complications during pregnancy: A significant increase in the rate of gestational hypertension was noted in 2020 and 2022 (1.4% in 2018, 1.5% in 2019, 2.56% in 2020, 1.43% in 2021, and 4.04% in 2022) (p value 0.013) (Table 4). However, no concomitant increase in the rates of preeclampsia, eclampsia, or premature rupture of membranes was observed (Table 4). A total of 177 COVID-19 cases were reported in our cohort. Additionally, a marked increase in the rate of cesarean sections was observed (34.37% in 2018, 55.73% in 2019, 55.56% in 2020, 53.67% in 2021, and 57.29% in 2022, with a p value <0.001) (Table 4). Neonatal complications: The mean birth weight of newborns was 3181.47 g ± 609.145, with no significant variation over the years. The highest rate of macrosomia was recorded in 2020 (4.17%), although this difference was not statistically significant (p =0.07) (Table 5). In parallel, excluding 2018, the incidence of intrauterine growth restriction (IUGR) was comparable between 2019 and 2022, with an overall incidence of 20 cases recorded (0.8%) (p=0.3) (Table 5). Risk factors for GDM and associated complications There was a significant association (p = 0.007) between the year of delivery and the presence of GDM, with 36.5% of women with GDM having delivered in 2020. A significant correlation between maternal age and GDM (p = 0.041) was observed, with higher rates of GDM among women aged 35--39 years and ≥ 40 years than among non-GDM individuals (35.4% vs 23.8% and 9.0% vs 5.4%, respectively) (Table 5). Similarly, patients with GDM were more overweight (35.4% vs 22.8%) and obese (18.8% vs 13.1%) than non-GDM individuals were (p = 0.004). Conversely, there was no significant association between GWG and GDM in the overall population (Table 5). Finally, women with GDM tended to have more gestational hypertension (p = 0.012) and an increased risk of fetal macrosomia (p < 0.001, Table 5). Discussion Our study revealed that the overall prevalence of GDM among pregnant women followed at HDF was 4.1%. This rate is slightly lower than the global prevalence of GDM, estimated at 6.6% by the latest edition of the International Diabetes Federation. It is also lower than the prevalence in Europe (7.0%) and North America (6.0%). Although our center is located in the Middle East and North Africa (MENA) region, its prevalence is notably lower than the estimated prevalence in this region, which is 30.2% ( 16 ). This difference is even more evident when comparing our population's GDM rate to the prevalence of GDM according to the IADPSG criteria, which is 14.2% globally, 12.3% in Europe, 11.7% in North America, 14.2% in South America and Africa, 23.3% in Southeast Asia, and 30% in the MENA region ( 16 ). According to the same study, our population's GDM rate is closer to the prevalence reported in high-income countries (6.6%) than in middle- or low-income countries (9.9% and 11.7%, respectively) ( 16 ). A meta-analysis of the prevalence of GDM in the MENA region between 2000 and 2019 revealed that it is the most affected region in the world, with a weighted overall GDM prevalence of 13%: Qatar (20.7%, 95% CI, 15.2–26.7%; 19 studies), Saudi Arabia (15%, 95% CI, 12.6–18.8%; 48 studies), and the UAE (13.4%, 95% CI, 9.4–18.0%; 14 studies) have the highest GDM prevalence, whereas Jordan has the lowest prevalence, with 4.7% (95% CI, 3.0–6.7%; six studies) ( 10 ). The same study places Lebanon in the middle, with a prevalence of 10.1% (6.7–15.1), but with an unpredictable distribution, as this estimate was based on only two small studies ( 17 , 18 ) involving approximately one hundred patients, without clear diagnostic criteria for GDM ( 10 ). Thus, our reported prevalence is closest to that reported in Jordan and seems to be lower than that reported in all other regional countries. This result is consistent with Lebanon having one of the lowest rates of T2DM among women of childbearing age in MENA (7%, 95% CI 5.9, 9.3) from 2000–2018 ( 19 ). This low GDM prevalence reported in our study, despite the rather advanced average maternal age (mean age 32 years), may be related to the socioeconomic profile of our population, as the majority of women belong to middle- and high-income groups. In addition, 88.5% of the women in our study had a university degree and lived in Beirut and its suburbs. A higher educational level may be associated with greater awareness of healthy dietary practices and better access to nutritious foods. Several studies have reported an inverse association between higher educational levels and the risk of GDM ( 20 ), as well as between higher socioeconomic status and GDM ( 21 , 22 ). Individuals with a higher educational level and better socioeconomic status may have a better understanding of health risk factors and better access to food and quality healthcare, which could reduce the risk of GDM ( 22 ). Our Lebanese cuisine, which is part of the Mediterranean diet, is protective against GDM, with an RR of 0.67; 95% CI 0.58–0.78 ( 23 ). Our population also appears to be mostly physically active, with a sedentary rate not exceeding 11%, while it reached 62.6% in Kuwait in 2014, 32.1% in Egypt in 2011, and 47% in Iraq in 2015 ( 24 ). Physical activity has also been shown to reduce the incidence of GDM ( 25 ). The obesity prevalence in our center was low (13.3%), markedly below the prevalence reported among women in the Middle East, which ranges between 40% and 50% ( 26 ). Finally, the adoption of a modified version of the OGTT by our gynecologists (which consists of only two blood glucose measurements at fasting and 2 hours after a 75 g oral glucose load) might have led to a lower estimation of GDM prevalence. Thus, it is difficult to compare prevalence rates on the basis of different criteria, especially since the IADPSG criteria are known to increase prevalence rates by 1.75 times ( 16 ). Our study also demonstrated an evident peak in the prevalence of GDM in 2020, at 6.4%, compared with less than 4% in the other studied years. The year 2020 marked the beginning of the COVID-19 pandemic, with two total lockdown periods (from March 14, 2020, to June 21, 2020, and then from November 14–30, 2020) ( 27 ). This same period coincided with a dramatic decrease in income due to the worst economic crisis in the country's history. Indeed, the Lebanese currency lost 90% of its value by the end of 2019, severely limiting the purchasing power of the Lebanese people and their access to necessities. The country then suffered from shortages of medication, fuel, and electricity ( 28 ). Finally, the explosion at Beirut port on August 4, 2020, described as the most powerful nonnuclear explosion of the 21st century, plunged the country into total disarray ( 29 ). Several studies have investigated the effect of the pandemic period on the prevalence of GDM and confirmed our findings. Zanardo et al. reported a significant increase in the prevalence of GDM in pregnant women during the COVID-19 pandemic in Italy, which was related mainly to the lockdown during the first trimester of pregnancy ( 30 ). Zheng et al. reported similar findings in China, indicating an association between exposure to lockdown and the risk of GDM when it occurs during the first four months of pregnancy, especially during the Level I lockdown, with cumulative exposures further increasing this risk ( 31 ). Ruiz-Roso et al. highlighted an increase in the consumption of sweet foods and snacks associated with a high rate of physical inactivity during the lockdown ( 32 ). However, our study does not show a decrease in the rate of physical activity in 2020. Indeed, during the early stages of the pandemic, some adaptive behaviors, such as engaging in self-care practices, exercising, and preparing healthy meals, were noted during the first lockdowns ( 33 ). La Verde et al. linked the increase in GDM diagnoses in Italy during the lockdown period and the months following it to increased weight gain during pregnancy, resulting in a higher BMI at delivery ( 34 ). In fact, Italy's national policy to restrict COVID-19 infection was rigorous, and outdoor physical activity was strictly limited ( 34 ). However, Zanardo et al. reported that the increase in GDM incidence was independent of maternal age, parity, socioeconomic status, maternal BMI before and after pregnancy, and GWG ( 30 ). These findings are consistent with our study, which did not show a significant increase in BMI before pregnancy or in GWG in 2020. The less stringent lockdown regulations in Lebanon than in China or Italy could be a contributing factor. Another interesting study evaluated the overall prevalence of GDM in Romania (5.78%), which increased from 4.06% to 8.2% before and during the COVID-19 pandemic, respectively ( 35 ). Thus, this increase in the GDM rate during the pandemic, without changes in BMI or physical activity, could result from exposure to stress factors, such as anxiety generated by the severity of the COVID-19 virus, uncertainty surrounding vaccines, or the search for effective therapeutic agents ( 36 ). Prospective studies have shown that elevated levels of inflammatory markers predict the risk of developing T2DM ( 37 ). Since GDM and T2DM share similar etiologies ( 38 ), it is therefore possible that exposure to stressful events during pregnancy triggers chronic inflammation and thus increases the risk of GDM. This hypothesis is supported by the fact that pregnancy itself is a very stressful period in a woman's life and is considered one of the most stressful conditions under normal circumstances ( 39 ). However, the causal relationship between early gestational stress and GDM remains unclear and requires more studies based on biochemical markers from the first trimester related to glucose, inflammation, insulin resistance, adipocytes, and the placenta ( 40 ). Lebanon experienced several political, economic, and security crises in 2020, layered on top of the health crisis. The phenomenon of causality between catastrophes and T2DM or pregnancy complications was well studied before the COVID-19 pandemic. For example, a study conducted in New York reported an increased risk of GDM following widespread power outages during Hurricane Sandy ( 41 ). A study following the 2011 earthquake in eastern Japan revealed a 5% increase in the prevalence of GDM among residents most affected by the disaster compared with those who were not affected ( 42 ). Importantly, following the year 2020, the rate of GDM decreased to 2.9% in 2021. The univariate analysis considering the entire pandemic period (2020–2022) does not reveal a statistically significant relationship between giving birth during this period and the development of GDM. It is plausible that this is due to the resilience of the Lebanese population and the numerous adaptive mechanisms in response to the obstacles hindering their daily lives. Furthermore, this peak in GDM in 2020 was not accompanied by a significant increase in insulin or oral hypoglycemic medication requirements in women with GDM in our cohort. These results contradict those of a Swiss study, which revealed increased needs for antidiabetic medications in women with GDM exposed to the pandemic compared with those not exposed to the pandemic ( 43 ). There was also a significant increase in the rate of gestational hypertension in 2020, without a significant increase in other maternal complications of GDM, such as preeclampsia, eclampsia, or premature rupture of membranes (PROM). Furthermore, no rise in macrosomia rates was observed despite the higher prevalence of GDM in 2020. The same Swiss study noted no differences regarding other cardiovascular-metabolic, psychological, obstetrical, or neonatal complications ( 43 ). This is likely a reflection of the continuity of proper medical follow-up for these women during this crisis period. Our study has several strengths. This is the first study that provides the prevalence of GDM in Lebanon after 2016 and examines its trends from 2018–2022, a period marked by several crises and incidents. However, this study has several limitations. First, this was a case‒control study, and no direct causal relationships between GDM and risk factors could be established. Additionally, data were extracted retrospectively from electronic medical records; therefore, several individual covariates, such as alcohol consumption, dietary habits, the presence of PCOS, and previous history of GDM, were missing. Moreover, the main criterion for determining the presence of GDM was the inclusion of information in the medical records, decreasing the sensitivity of detection ( 44 ). Therefore, our study may underestimate the prevalence of GDM. Furthermore, this study was conducted in a single academic center, which limits the generalizability of the results to the entire Lebanese population. Importantly, several stressful events affected the country simultaneously, whereby the increase in GDM rates in 2020 could not be attributed to a single factor. Finally, our study did not analyze the relationship between the duration of exposure to the lockdown or its timing relative to the pregnancy term and the risk of developing GDM. Conclusion In conclusion, the prevalence of GDM among pregnant women followed at Hôtel Dieu de France from 2018 to 2022 was 4.1% (ranging from 2.9% to 6.4%). This rate, which is lower than that of other countries in the MENA region, reflects a high standard of the medical health system. Furthermore, we highlighted a significant increase in this rate in 2020, peaking at 6.4%. In the absence of variations in BMI, GWG, and physical activity, the prevailing stress in Lebanon during this year could be the main culprit. Finally, it would be interesting to conduct a nationwide prospective study comparing the prevalence of GDM according to different screening methods and cutoffs. Abbreviations GDM Gestational diabetes mellitus IADPSG International Association of Diabetes in Pregnancy Study Group T2D Type 2 Diabetes GWG Gestational weight gain HDF Hôtel Dieu de France BMI Body Mass Index IOM Institute of Medicine GH Gestational hypertension PPROM preterm premature rupture of membranes OGTT Oral glucose tolerance test IUGR Intrauterine Growth Restriction WA Weeks of Amenorrhea MENA Middle East and North Africa COVID-19 Coronavirus SARS-CoV-2 Declarations Ethics approval and consent to participate The study received approval from the Ethics Committee of Hôtel-Dieu de France in accordance with the “Good Clinical Practice” guidelines described in the “Declaration of Helsinki” (October 2013 version) and the “International Ethical Guidelines for Biomedical Research Involving Human Subjects” of the Council for International Organizations of Medical Sciences (CIOMS), in collaboration with the World Health Organization (WHO). Informed consent was waived, as the data collection was anonymous and retrospective. Consent for publication Not applicable Competing interests The authors declare that they have no competing interests. Funding Not applicable Author Contribution NY and NG contributed to the conception and design of the study, acquisition of the data and writing of the manuscript.GAT contributed to data acquisition.MBA and MHG contributed to the revision and writing of the manuscript Acknowledgments Not applicable Data Availability The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request. References 14. Management of Diabetes in Pregnancy: Standards of Medical Care in Diabetes-2019. Diabetes care [Internet]. 2019 Jan [cited 2022 Oct 5];42(Suppl 1). Available from: https://pubmed.ncbi.nlm.nih.gov/30559240/ Modzelewski R, Stefanowicz-Rutkowska MM, Matuszewski W, Bandurska-Stankiewicz EM. 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Maternal and infant outcomes in women with and without gestational diabetes mellitus in the COVID-19 era in China: Lessons learned. Front Endocrinol. 2022;13:982493. Ruiz-Roso MB, Knott-Torcal C, Matilla-Escalante DC, Garcimartín A, Sampedro-Nuñez MA, Dávalos A, et al. COVID-19 Lockdown and Changes of the Dietary Pattern and Physical Activity Habits in a Cohort of Patients with Type 2 Diabetes Mellitus. Nutrients. 2020;12(8):2327. Farewell CV, Jewell J, Walls J, Leiferman JA. A Mixed-Methods Pilot Study of Perinatal Risk and Resilience During COVID-19. J Prim Care Community Health. 2020;11:2150132720944074. La Verde M, Torella M, Riemma G, Narciso G, Iavarone I, Gliubizzi L, et al. Incidence of gestational diabetes mellitus before and after the Covid-19 lockdown: A retrospective cohort study. J Obstet Gynaecol. 2022;48(5):1126–31. Chelu S, Bernad E, Craina M, Neamtu R, Mocanu AG, Vernic C, et al. Prevalence of Gestational Diabetes in preCOVID-19 and COVID-19 Years and Its Impact on Pregnancy: A 5-Year Retrospective Study. Diagnostics. 2022;12(5):1241. Hawryluck L, Gold WL, Robinson S, Pogorski S, Galea S, Styra R. SARS Control and Psychological Effects of Quarantine, Toronto, Canada. Emerg Infect Dis. 2004;10(7):1206–12. Duncan BB, Schmidt MI, Pankow JS, Ballantyne CM, Couper D, Vigo A, et al. Low-Grade Systemic Inflammation and the Development of Type 2 Diabetes. Diabetes. 2003;52(7):1799–805. Baz B, Riveline JP, Gautier JF. ENDOCRINOLOGY OF PREGNANCY: Gestational diabetes mellitus: definition, etiological and clinical aspects. Eur J Endocrinol. 2016;174(2):R43–51. Dunkel Schetter C, Tanner L. Anxiety, depression and stress in pregnancy: implications for mothers, children, research, and practice. Curr Opin Psychiatry. 2012;25(2):141–8. Syngelaki A, Visser GHA, Krithinakis K, Wright A, Nicolaides KH. First trimester screening for gestational diabetes mellitus by maternal factors and markers of inflammation. Metabolism. 2016;65(3):131–7. Xiao J, Zhang W, Huang M, Lu Y, Lawrence WR, Lin Z, et al. Increased risk of multiple pregnancy complications following large-scale power outages during Hurricane Sandy in New York State. Sci Total Environ. 2021;770:145359. Ishikuro M, Obara T, Murakami K, Ueno F, Noda A, Kikuya M, et al. Relation of Disaster Exposure With Maternal Characteristics and Obstetric Outcomes: the Tohoku Medical Megabank Project Birth and Three-Generation Cohort Study. J Epidemiol. 2023;33(3):127–35. Quansah DY, Gilbert L, Kosinski C, Le Dizès O, Horsch A, Benhalima K, et al. Cardio-Metabolic and Mental Health Outcomes Before and During the COVID-19 Pandemic in a Cohort of Women With Gestational Diabetes Mellitus in Switzerland. Front Endocrinol. 2022;13:948716. Hsu S, Selen DJ, James K, Li S, Camargo CA, Kaimal A, et al. Assessment of the Validity of Administrative Data for Gestational Diabetes Ascertainment. Am J Obstet Gynecol MFM. 2023;5(2):100814. Tables Table 1 to 5 are available in the Supplementary Files section. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8947137","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":603559080,"identity":"f526e670-65ac-46dc-a511-a9357410772a","order_by":0,"name":"Nour Yazbek","email":"","orcid":"","institution":"Hôtel-Dieu de France","correspondingAuthor":false,"prefix":"","firstName":"Nour","middleName":"","lastName":"Yazbek","suffix":""},{"id":603559081,"identity":"70326e2b-eb64-4958-992f-058099c9a7d3","order_by":1,"name":"Michel Bou Absi","email":"","orcid":"","institution":"Hôtel-Dieu de France","correspondingAuthor":false,"prefix":"","firstName":"Michel","middleName":"Bou","lastName":"Absi","suffix":""},{"id":603559082,"identity":"fa1d26f7-2dcb-4e28-b2ad-5004d3420af4","order_by":2,"name":"George Abi Tayeh","email":"","orcid":"","institution":"Hôtel-Dieu de France","correspondingAuthor":false,"prefix":"","firstName":"George","middleName":"Abi","lastName":"Tayeh","suffix":""},{"id":603559083,"identity":"89557a23-801f-4901-b141-73f26bd7678c","order_by":3,"name":"Marie-Hélène Gannagé-Yared","email":"","orcid":"","institution":"Hôtel-Dieu de France","correspondingAuthor":false,"prefix":"","firstName":"Marie-Hélène","middleName":"","lastName":"Gannagé-Yared","suffix":""},{"id":603559084,"identity":"a8ce6297-b659-43f0-9f48-058bb7f01023","order_by":4,"name":"Nada El Ghorayeb","email":"data:image/png;base64,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","orcid":"","institution":"Hôtel-Dieu de France","correspondingAuthor":true,"prefix":"","firstName":"Nada","middleName":"El","lastName":"Ghorayeb","suffix":""}],"badges":[],"createdAt":"2026-02-23 12:38:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8947137/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8947137/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104428816,"identity":"517c4029-c234-49ad-ad01-10bfccc7a160","added_by":"auto","created_at":"2026-03-11 15:13:37","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":102778,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eFlowchart describing the selection of pregnant women. GDM: Gestational \u003c/em\u003ediabetes mellitus\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8947137/v1/7692943c37bf651290cb52dc.png"},{"id":104428818,"identity":"05175a29-4321-4263-a2f0-b3fe0f70e0c9","added_by":"auto","created_at":"2026-03-11 15:13:37","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":123520,"visible":true,"origin":"","legend":"\u003cp\u003ePrevalence of gestational diabetes mellitus stratified by body mass index from 2019--2022; p value 0.498. BMI: Body mass index in kg/m². GDM: gestational diabetes.\u003c/p\u003e","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8947137/v1/c8023925c7c8cc26e50dd9a2.png"},{"id":104780153,"identity":"cd9554d7-049c-4155-bdf2-d0db2f0edfdf","added_by":"auto","created_at":"2026-03-17 07:51:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":934193,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8947137/v1/2a04f6c0-daf2-4b5a-b095-c6d13749218c.pdf"},{"id":104428819,"identity":"25d83a4f-8823-4fca-bd05-2b098beeafc6","added_by":"auto","created_at":"2026-03-11 15:13:37","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":54440,"visible":true,"origin":"","legend":"","description":"","filename":"Table15.docx","url":"https://assets-eu.researchsquare.com/files/rs-8947137/v1/5891d5219aa1ab79656723c1.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Prevalence and Trends of Gestational Diabetes in a Large University Hospital in Lebanon Before and During the COVID-19 Pandemic","fulltext":[{"header":"Background","content":"\u003cp\u003eGestational diabetes mellitus (GDM) is a type of hyperglycemia that manifests for the first time during pregnancy and resolves after delivery (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). It is the most common metabolic-associated complication of pregnancy; it increases the risk of neonatal and maternal morbidity and is highly predictive of the subsequent development of type 2 diabetes in affected women(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Moreover, numerous studies indicate that hyperglycemia during pregnancy influences the long-term metabolic health of offspring (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). The global epidemiology of GDM and secular trends over recent decades remain unclear due to the lack of consensus on diagnostic criteria (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). In fact, the rates of GDM vary widely from approximately 1% to \u0026gt;\u0026thinsp;20% (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Interestingly, a systematic review of 31 cohorts and cross-sectional studies with 136 705 women revealed that adopting the International Association of Diabetes in Pregnancy Study Group (IADPSG) criteria resulted in an overall 75% increase in GDM incidence compared with previous local criteria (relative risk, 1.75; 95% CI, 1.53\u0026ndash;2.01) (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). The major risk factors that contribute to the increasing prevalence of GDM include increased maternal obesity and advanced maternal age (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Although there is still no consensus on the best way to screen for GDM, there is broad agreement on the importance of early diagnosis and identification of women at risk to optimize glycemic control and reduce pregnancy-related complications and associated healthcare costs (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Understanding population-specific healthcare needs over time is essential, and prevalence estimates are useful for this purpose (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe prevalence of GDM in Lebanon remains largely unknown, and the few available studies date back to 2016 (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). In 2019, the country was plagued by one of the worst economic crises since the mid-20th century, followed by the COVID-19 pandemic, and culminated with the Beirut port explosion on August 4th, 2020 (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Several prospective studies have demonstrated that exposure to stressful events predisposes individuals to hyperglycemia, metabolic syndrome, and type 2 diabetes (T2D) (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Nevertheless, the literature examining the relationship between life stressors and GDM remains limited (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). To our knowledge, no such study has been conducted in Lebanon. Therefore, we aimed to determine the annual prevalence of GDM in a single tertiary care referral center in Lebanon from 2018\u0026ndash;2022. We also examined the associated risk factors for GDM, such as maternal age, obesity, and gestational weight gain (GWG). Finally, we evaluated the impact of the COVID-19 pandemic and the economic crisis period on the incidence of GDM.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design\u003c/h2\u003e \u003cp\u003eA retrospective observational study was conducted at H\u0026ocirc;tel-Dieu de France (HDF) Hospital in Beirut, Lebanon. All pregnant Lebanese women admitted to the gynecology and obstetrics department for delivery between September 10, 2018, and December 31, 2022, were included. Data were extracted from the hospital's electronic medical record system (DX Care). Prior to September 2018, the files were not yet electronic. Women of non-Lebanese nationality were excluded, as were those with pregestational type 1 or type 2 diabetes. The following variables were retrieved from the records: location of residence, average monthly income, education level, and lifestyle habits such as smoking and a sedentary lifestyle. March 14, 2020, marked the beginning of the first total lockdown in Lebanon. Maternal age was stratified into the following categories: \u0026lt;20, 20\u0026ndash;25, 25\u0026ndash;29, 30\u0026ndash;34, 35\u0026ndash;39, and \u0026gt;\u0026thinsp;40 years. Height (m), prepregnancy weight (kg), and prepregnancy body mass index (BMI) (kg/m\u003csup\u003e2\u003c/sup\u003e) were noted. Underweight women had a BMI\u0026thinsp;\u0026lt;\u0026thinsp;18.5, normal weight women had a BMI between 18.5\u0026ndash;24.9, overweight women had a BMI between 25\u0026ndash;29.9, and obese women had a BMI\u0026thinsp;\u0026gt;\u0026thinsp;30. Moreover, we divided our population into 2 groups according to BMI: \u0026lt;25 kg/m\u0026sup2; and \u0026gt;\u0026thinsp;25 kg/m\u0026sup2;. GWG in kg was also recorded and then stratified according to Institute of Medicine (IOM) recommendations for each BMI category, with a total weight gain of 12.5\u0026ndash;18 kg for underweight individuals (\u0026lt;\u0026thinsp;18.5 kg/m\u003csup\u003e2\u003c/sup\u003e), 11.5\u0026ndash;16 kg (0.35\u0026ndash;0.50 kg/m2) for normal weight individuals (18.5\u0026ndash;24.9 kg/m\u003csup\u003e2\u003c/sup\u003e), 7\u0026ndash;11.5 kg for overweight individuals (25\u0026ndash;29.9 kg/m\u003csup\u003e2\u003c/sup\u003e) and 5\u0026ndash;9 kg for obese individuals (\u0026ge;\u0026thinsp;30 kg/m\u003csup\u003e2\u003c/sup\u003e) (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Other variables were also extracted, such as GDM treatment (diet, metformin, or insulin), smoking during pregnancy, COVID-19 pneumonia during pregnancy, gestational hypertension (GH), preeclampsia, eclampsia, preterm premature rupture of membranes (PPROM), mode of delivery (vaginal delivery, instrumental vaginal delivery or cesarean section) and neonatal complications such as macrosomia (with infant birth weight\u0026thinsp;\u0026gt;\u0026thinsp;4000 g), intrauterine growth restriction and prematurity.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eScreening and diagnostic methods for GDM at Hôtel-Dieu de France:\u003c/h3\u003e\n\u003cp\u003eAt HDF Hospital, all obstetricians used the same method of screening for GDM at 24\u0026ndash;26 weeks of gestation for all pregnant women. The test consisted of a modified version of the oral glucose tolerance test (OGTT), which measures fasting blood glucose and only 2 hours after a 75 g oral glucose load. If the blood glucose level exceeded the established threshold (\u0026ge;\u0026thinsp;92 mg/dL at fasting or \u0026ge;\u0026thinsp;153 mg/dL 2 hours after the glucose load), the woman was considered to have GDM and was referred to an endocrinologist for further management. For high-risk patients, a fasting blood glucose test was performed early in pregnancy, coupled with an HbA1c. Notably, there was no change in the screening policy between 2018 and 2022.\u003c/p\u003e\n\u003ch3\u003eEthical considerations:\u003c/h3\u003e\n\u003cp\u003e The study received approval from the Ethics Committee of H\u0026ocirc;tel-Dieu de France (Reference: Tfem/2023/72). Informed consent was not needed, as the data collection was anonymous and retrospective.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis:\u003c/h2\u003e \u003cp\u003eThe data were then analyzed via SPSS version 26. Continuous variables are expressed as the means and percentages, whereas categorical variables are expressed as frequencies and percentages. Next, a univariate analysis was conducted to evaluate differences in the variables of interest across years and then between the prepandemic period and the COVID-19 pandemic period. A univariate analysis was also performed to assess the factors affecting GDM. The χ\u0026sup2; test, Fisher\u0026rsquo;s exact test, independent samples t test, and ANOVA were used for univariate analyses. The statistical significance threshold was set at p\u0026thinsp;\u0026le;\u0026thinsp;0.05.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eSocial and demographic characteristics of the population:\u003c/strong\u003e\u003c/p\u003e\n\u003cp id=\"_Toc157777433\"\u003eA total of 2595 pregnant women who gave birth at HDF between 2018 and 2022 were included in the cohort (Figure 1). The number of deliveries in 2018 was much lower than that in other years because only records from the last 3 months of 2018 were included. Most women resided near the capital (Mount Lebanon 75.5% and Beirut 9.7%) (Table 1). Since 2020, income has significantly declined (p \u0026lt;0.001) over the subsequent years. Indeed, there was a shift from a majority with an income above $3000 (58.8% in 2018 and 56.1% in 2019) to a majority with an income lower than $1000 (46.8% in 2021 and 49.9% in 2022). Most of the women in our cohort (88.4%) had a university diploma (Table 1). The overall population was physically active (86.6%), but a significant increase in sedentary lifestyles was observed across the years (5% in 2018, 9.4% in 2019, 6.9% in 2020, 12.7% in 2021, and 14.1% in 2022). Moreover, 99% of women did not smoke during pregnancy, with no significant change from 2018 to 2022 (Table 1). Most pregnancies were carried at term (78.7%) and were singletons (95.6%) (Table 2). The mean age of the population was 32.03 years (\u0026plusmn; 4.75), with no significant difference across the study period. Most women became pregnant between 30 and 34 years of age (40%). Moreover, women 35 years and older represented a considerable proportion of our cohort (31.3%) (Table 2). The mean BMI at the beginning of pregnancy was 24.86 kg/m\u0026sup2; (\u0026plusmn;8.99), and the mean GWG was 12.17 kg (\u0026plusmn;5.06), with no notable difference across the study period (Table 2). In fact, most women had a GWG in accordance with the IOM recommendations (38%) or even below these recommendations (32.7%) (Table 2).\u003c/p\u003e\n\u003cp\u003e\u003cspan id=\"_Toc157777428\"\u003e\u003cstrong\u003ePrevalence of GDM at HDF:\u003c/strong\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003eThe overall GDM prevalence was 4.1%. This rate varied significantly over the years (3.1% in 2019, 2.9% in 2021, 3.6% in 2022, p value of 0.007) and peaked in 2020 (6.4%). The majority of GDM cases (79.4%) were mild and managed with lifestyle and dietary measures (Table 3). When stratified according to BMI, GDM prevalence was 4.46% and 10.54% in women with a BMI \u0026lt; 25 kg/m\u0026sup2; and those with a BMI \u0026ge; 25 kg/m\u0026sup2;, respectively. The GDM incidence according to each BMI category followed the same trends over the years, as shown in Figure 2 (p = 0.498). On the other hand, the mean maternal age remained the same across the years (p=0.36), with most individuals aged between 30 and 34 years (40.1%) (Table 2). Similarly, no significant fluctuations in GWG were observed from 2018 to 2022 (p=0.15). (Table 2)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOther maternal complications during pregnancy:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA significant increase in the rate of gestational hypertension was noted in 2020 and 2022 (1.4% in 2018, 1.5% in 2019, 2.56% in 2020, 1.43% in 2021, and 4.04% in 2022) (p value 0.013) (Table 4). However, no concomitant increase in the rates of preeclampsia, eclampsia, or premature rupture of membranes was observed (Table 4). A total of 177 COVID-19 cases were reported in our cohort. Additionally, a marked increase in the rate of cesarean sections was observed (34.37% in 2018, 55.73% in 2019, 55.56% in 2020, 53.67% in 2021, and 57.29% in 2022, with a p value \u0026lt;0.001) (Table 4).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNeonatal complications:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe mean birth weight of newborns was 3181.47 g \u0026plusmn; 609.145, with no significant variation over the years. The highest rate of macrosomia was recorded in 2020 (4.17%), although this difference was not statistically significant (p =0.07) (Table 5). In parallel, excluding 2018, the incidence of intrauterine growth restriction (IUGR) was comparable between 2019 and 2022, with an overall incidence of 20 cases recorded (0.8%) (p=0.3) (Table 5).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRisk factors for GDM and associated complications\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere was a significant association (p = 0.007) between the year of delivery and the presence of GDM, with 36.5% of women with GDM having delivered in 2020. A significant correlation between maternal age and GDM (p = 0.041) was observed, with higher rates of GDM among women aged 35--39 years and \u0026ge; 40 years than among non-GDM individuals (35.4% vs 23.8% and 9.0% vs 5.4%, respectively) (Table 5). Similarly, patients with GDM were more overweight (35.4% vs 22.8%) and obese (18.8% vs 13.1%) than non-GDM individuals were (p = 0.004). Conversely, there was no significant association between GWG and GDM in the overall population (Table 5). Finally, women with GDM tended to have more gestational hypertension (p = 0.012) and an increased risk of fetal macrosomia (p \u0026lt; 0.001, Table 5).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur study revealed that the overall prevalence of GDM among pregnant women followed at HDF was 4.1%. This rate is slightly lower than the global prevalence of GDM, estimated at 6.6% by the latest edition of the International Diabetes Federation. It is also lower than the prevalence in Europe (7.0%) and North America (6.0%). Although our center is located in the Middle East and North Africa (MENA) region, its prevalence is notably lower than the estimated prevalence in this region, which is 30.2% (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). This difference is even more evident when comparing our population's GDM rate to the prevalence of GDM according to the IADPSG criteria, which is 14.2% globally, 12.3% in Europe, 11.7% in North America, 14.2% in South America and Africa, 23.3% in Southeast Asia, and 30% in the MENA region (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). According to the same study, our population's GDM rate is closer to the prevalence reported in high-income countries (6.6%) than in middle- or low-income countries (9.9% and 11.7%, respectively) (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). A meta-analysis of the prevalence of GDM in the MENA region between 2000 and 2019 revealed that it is the most affected region in the world, with a weighted overall GDM prevalence of 13%: Qatar (20.7%, 95% CI, 15.2\u0026ndash;26.7%; 19 studies), Saudi Arabia (15%, 95% CI, 12.6\u0026ndash;18.8%; 48 studies), and the UAE (13.4%, 95% CI, 9.4\u0026ndash;18.0%; 14 studies) have the highest GDM prevalence, whereas Jordan has the lowest prevalence, with 4.7% (95% CI, 3.0\u0026ndash;6.7%; six studies) (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). The same study places Lebanon in the middle, with a prevalence of 10.1% (6.7\u0026ndash;15.1), but with an unpredictable distribution, as this estimate was based on only two small studies (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e) involving approximately one hundred patients, without clear diagnostic criteria for GDM (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Thus, our reported prevalence is closest to that reported in Jordan and seems to be lower than that reported in all other regional countries. This result is consistent with Lebanon having one of the lowest rates of T2DM among women of childbearing age in MENA (7%, 95% CI 5.9, 9.3) from 2000\u0026ndash;2018 (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis low GDM prevalence reported in our study, despite the rather advanced average maternal age (mean age 32 years), may be related to the socioeconomic profile of our population, as the majority of women belong to middle- and high-income groups. In addition, 88.5% of the women in our study had a university degree and lived in Beirut and its suburbs. A higher educational level may be associated with greater awareness of healthy dietary practices and better access to nutritious foods. Several studies have reported an inverse association between higher educational levels and the risk of GDM (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e), as well as between higher socioeconomic status and GDM (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Individuals with a higher educational level and better socioeconomic status may have a better understanding of health risk factors and better access to food and quality healthcare, which could reduce the risk of GDM (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Our Lebanese cuisine, which is part of the Mediterranean diet, is protective against GDM, with an RR of 0.67; 95% CI 0.58\u0026ndash;0.78 (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Our population also appears to be mostly physically active, with a sedentary rate not exceeding 11%, while it reached 62.6% in Kuwait in 2014, 32.1% in Egypt in 2011, and 47% in Iraq in 2015 (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Physical activity has also been shown to reduce the incidence of GDM (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). The obesity prevalence in our center was low (13.3%), markedly below the prevalence reported among women in the Middle East, which ranges between 40% and 50% (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Finally, the adoption of a modified version of the OGTT by our gynecologists (which consists of only two blood glucose measurements at fasting and 2 hours after a 75 g oral glucose load) might have led to a lower estimation of GDM prevalence. Thus, it is difficult to compare prevalence rates on the basis of different criteria, especially since the IADPSG criteria are known to increase prevalence rates by 1.75 times (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOur study also demonstrated an evident peak in the prevalence of GDM in 2020, at 6.4%, compared with less than 4% in the other studied years. The year 2020 marked the beginning of the COVID-19 pandemic, with two total lockdown periods (from March 14, 2020, to June 21, 2020, and then from November 14\u0026ndash;30, 2020) (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). This same period coincided with a dramatic decrease in income due to the worst economic crisis in the country's history. Indeed, the Lebanese currency lost 90% of its value by the end of 2019, severely limiting the purchasing power of the Lebanese people and their access to necessities. The country then suffered from shortages of medication, fuel, and electricity (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). Finally, the explosion at Beirut port on August 4, 2020, described as the most powerful nonnuclear explosion of the 21st century, plunged the country into total disarray (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). Several studies have investigated the effect of the pandemic period on the prevalence of GDM and confirmed our findings. Zanardo et al. reported a significant increase in the prevalence of GDM in pregnant women during the COVID-19 pandemic in Italy, which was related mainly to the lockdown during the first trimester of pregnancy (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Zheng et al. reported similar findings in China, indicating an association between exposure to lockdown and the risk of GDM when it occurs during the first four months of pregnancy, especially during the Level I lockdown, with cumulative exposures further increasing this risk (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). Ruiz-Roso et al. highlighted an increase in the consumption of sweet foods and snacks associated with a high rate of physical inactivity during the lockdown (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). However, our study does not show a decrease in the rate of physical activity in 2020. Indeed, during the early stages of the pandemic, some adaptive behaviors, such as engaging in self-care practices, exercising, and preparing healthy meals, were noted during the first lockdowns (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). La Verde et al. linked the increase in GDM diagnoses in Italy during the lockdown period and the months following it to increased weight gain during pregnancy, resulting in a higher BMI at delivery (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). In fact, Italy's national policy to restrict COVID-19 infection was rigorous, and outdoor physical activity was strictly limited (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). However, Zanardo et al. reported that the increase in GDM incidence was independent of maternal age, parity, socioeconomic status, maternal BMI before and after pregnancy, and GWG (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). These findings are consistent with our study, which did not show a significant increase in BMI before pregnancy or in GWG in 2020. The less stringent lockdown regulations in Lebanon than in China or Italy could be a contributing factor. Another interesting study evaluated the overall prevalence of GDM in Romania (5.78%), which increased from 4.06% to 8.2% before and during the COVID-19 pandemic, respectively (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). Thus, this increase in the GDM rate during the pandemic, without changes in BMI or physical activity, could result from exposure to stress factors, such as anxiety generated by the severity of the COVID-19 virus, uncertainty surrounding vaccines, or the search for effective therapeutic agents (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). Prospective studies have shown that elevated levels of inflammatory markers predict the risk of developing T2DM (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). Since GDM and T2DM share similar etiologies (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e), it is therefore possible that exposure to stressful events during pregnancy triggers chronic inflammation and thus increases the risk of GDM. This hypothesis is supported by the fact that pregnancy itself is a very stressful period in a woman's life and is considered one of the most stressful conditions under normal circumstances (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). However, the causal relationship between early gestational stress and GDM remains unclear and requires more studies based on biochemical markers from the first trimester related to glucose, inflammation, insulin resistance, adipocytes, and the placenta (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). Lebanon experienced several political, economic, and security crises in 2020, layered on top of the health crisis. The phenomenon of causality between catastrophes and T2DM or pregnancy complications was well studied before the COVID-19 pandemic. For example, a study conducted in New York reported an increased risk of GDM following widespread power outages during Hurricane Sandy (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). A study following the 2011 earthquake in eastern Japan revealed a 5% increase in the prevalence of GDM among residents most affected by the disaster compared with those who were not affected (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). Importantly, following the year 2020, the rate of GDM decreased to 2.9% in 2021. The univariate analysis considering the entire pandemic period (2020\u0026ndash;2022) does not reveal a statistically significant relationship between giving birth during this period and the development of GDM. It is plausible that this is due to the resilience of the Lebanese population and the numerous adaptive mechanisms in response to the obstacles hindering their daily lives. Furthermore, this peak in GDM in 2020 was not accompanied by a significant increase in insulin or oral hypoglycemic medication requirements in women with GDM in our cohort. These results contradict those of a Swiss study, which revealed increased needs for antidiabetic medications in women with GDM exposed to the pandemic compared with those not exposed to the pandemic (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e). There was also a significant increase in the rate of gestational hypertension in 2020, without a significant increase in other maternal complications of GDM, such as preeclampsia, eclampsia, or premature rupture of membranes (PROM). Furthermore, no rise in macrosomia rates was observed despite the higher prevalence of GDM in 2020. The same Swiss study noted no differences regarding other cardiovascular-metabolic, psychological, obstetrical, or neonatal complications (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e). This is likely a reflection of the continuity of proper medical follow-up for these women during this crisis period.\u003c/p\u003e \u003cp\u003eOur study has several strengths. This is the first study that provides the prevalence of GDM in Lebanon after 2016 and examines its trends from 2018\u0026ndash;2022, a period marked by several crises and incidents. However, this study has several limitations. First, this was a case‒control study, and no direct causal relationships between GDM and risk factors could be established. Additionally, data were extracted retrospectively from electronic medical records; therefore, several individual covariates, such as alcohol consumption, dietary habits, the presence of PCOS, and previous history of GDM, were missing. Moreover, the main criterion for determining the presence of GDM was the inclusion of information in the medical records, decreasing the sensitivity of detection (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e). Therefore, our study may underestimate the prevalence of GDM. Furthermore, this study was conducted in a single academic center, which limits the generalizability of the results to the entire Lebanese population. Importantly, several stressful events affected the country simultaneously, whereby the increase in GDM rates in 2020 could not be attributed to a single factor. Finally, our study did not analyze the relationship between the duration of exposure to the lockdown or its timing relative to the pregnancy term and the risk of developing GDM.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, the prevalence of GDM among pregnant women followed at H\u0026ocirc;tel Dieu de France from 2018 to 2022 was 4.1% (ranging from 2.9% to 6.4%). This rate, which is lower than that of other countries in the MENA region, reflects a high standard of the medical health system. Furthermore, we highlighted a significant increase in this rate in 2020, peaking at 6.4%. In the absence of variations in BMI, GWG, and physical activity, the prevailing stress in Lebanon during this year could be the main culprit. Finally, it would be interesting to conduct a nationwide prospective study comparing the prevalence of GDM according to different screening methods and cutoffs.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eGDM\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGestational diabetes mellitus\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eIADPSG\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInternational Association of Diabetes in Pregnancy Study Group\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eT2D\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eType 2 Diabetes\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eGWG\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGestational weight gain\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eHDF\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eH\u0026ocirc;tel Dieu de France\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eBMI\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBody Mass Index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eIOM\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInstitute of Medicine\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eGH\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGestational hypertension\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003ePPROM\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003epreterm premature rupture of membranes\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eOGTT\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOral glucose tolerance test\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eIUGR\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eIntrauterine Growth Restriction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eWA\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eWeeks of Amenorrhea\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eMENA\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMiddle East and North Africa\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eCOVID-19\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCoronavirus SARS-CoV-2\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003e The study received approval from the Ethics Committee of H\u0026ocirc;tel-Dieu de France in accordance with the \u0026ldquo;Good Clinical Practice\u0026rdquo; guidelines described in the \u0026ldquo;Declaration of Helsinki\u0026rdquo; (October 2013 version) and the \u0026ldquo;International Ethical Guidelines for Biomedical Research Involving Human Subjects\u0026rdquo; of the Council for International Organizations of Medical Sciences (CIOMS), in collaboration with the World Health Organization (WHO). Informed consent was waived, as the data collection was anonymous and retrospective.\u003c/p\u003e \u003ch2\u003eConsent for publication\u003c/h2\u003e \u003cp\u003eNot applicable\u003c/p\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eNot applicable\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eNY and NG contributed to the conception and design of the study, acquisition of the data and writing of the manuscript.GAT contributed to data acquisition.MBA and MHG contributed to the revision and writing of the manuscript\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e \u003cp\u003eNot applicable\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e14. Management of Diabetes in Pregnancy: Standards of Medical Care in Diabetes-2019. Diabetes care [Internet]. 2019 Jan [cited 2022 Oct 5];42(Suppl 1). Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pubmed.ncbi.nlm.nih.gov/30559240/\u003c/span\u003e\u003cspan address=\"https://pubmed.ncbi.nlm.nih.gov/30559240/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eModzelewski R, Stefanowicz-Rutkowska MM, Matuszewski W, Bandurska-Stankiewicz EM. Gestational Diabetes Mellitus-Recent Literature Review. J Clin Med. 2022;11(19):5736.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBuchanan TA, Xiang AH, Page KA. Gestational diabetes mellitus: risks and management during and after pregnancy. Nat Rev Endocrinol. 2012;8(11):639\u0026ndash;49.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNijs H, Benhalima K. 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Infect Dis Obstet Gynecol. 2019;2019:1\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZein S, Rachidi S, Awada S, Osman M, Al-Hajje A, Shami N, et al. High iron level in early pregnancy increased glucose intolerance. J Trace Elem Med Biol. 2015;30:220\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAl-Rifai RH, Majeed M, Qambar MA, Ibrahim A, AlYammahi KM, Aziz F. Type 2 diabetes and pre-diabetes mellitus: a systematic review and meta-analysis of prevalence studies in women of childbearing age in the Middle East and North Africa, 2000\u0026ndash;2018. Syst Rev. 2019;8(1):268.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBouthoorn SH, Silva LM, Murray SE, Steegers EAP, Jaddoe VWV, Moll H, et al. Low-educated women have an increased risk of gestational diabetes mellitus: the Generation R Study. 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Lancet. 2016;387(10026):1377\u0026ndash;96.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBizri AR, Khachfe HH, Fares MY, Musharrafieh U. COVID-19 Pandemic: An Insult Over Injury for Lebanon. J Community Health. 2021;46(3):487\u0026ndash;93.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Bank. Lebanon Economic Monitor, Fall 2020 [Internet]. World Bank, Washington, DC. 2020 [cited 2026 Jan 30]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://hdl.handle.net/10986/34842\u003c/span\u003e\u003cspan address=\"https://hdl.handle.net/10986/34842\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbboud Mzawak M, Younes RS, Moukarzel C. Echoes of the blast: A qualitative study of loss and adaptation among bereaved families of the 2020 Beirut explosion. 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Nutrients. 2020;12(8):2327.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFarewell CV, Jewell J, Walls J, Leiferman JA. A Mixed-Methods Pilot Study of Perinatal Risk and Resilience During COVID-19. J Prim Care Community Health. 2020;11:2150132720944074.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLa Verde M, Torella M, Riemma G, Narciso G, Iavarone I, Gliubizzi L, et al. Incidence of gestational diabetes mellitus before and after the Covid-19 lockdown: A retrospective cohort study. J Obstet Gynaecol. 2022;48(5):1126\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChelu S, Bernad E, Craina M, Neamtu R, Mocanu AG, Vernic C, et al. Prevalence of Gestational Diabetes in preCOVID-19 and COVID-19 Years and Its Impact on Pregnancy: A 5-Year Retrospective Study. Diagnostics. 2022;12(5):1241.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHawryluck L, Gold WL, Robinson S, Pogorski S, Galea S, Styra R. SARS Control and Psychological Effects of Quarantine, Toronto, Canada. Emerg Infect Dis. 2004;10(7):1206\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDuncan BB, Schmidt MI, Pankow JS, Ballantyne CM, Couper D, Vigo A, et al. Low-Grade Systemic Inflammation and the Development of Type 2 Diabetes. Diabetes. 2003;52(7):1799\u0026ndash;805.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBaz B, Riveline JP, Gautier JF. ENDOCRINOLOGY OF PREGNANCY: Gestational diabetes mellitus: definition, etiological and clinical aspects. Eur J Endocrinol. 2016;174(2):R43\u0026ndash;51.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDunkel Schetter C, Tanner L. Anxiety, depression and stress in pregnancy: implications for mothers, children, research, and practice. Curr Opin Psychiatry. 2012;25(2):141\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSyngelaki A, Visser GHA, Krithinakis K, Wright A, Nicolaides KH. First trimester screening for gestational diabetes mellitus by maternal factors and markers of inflammation. Metabolism. 2016;65(3):131\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXiao J, Zhang W, Huang M, Lu Y, Lawrence WR, Lin Z, et al. Increased risk of multiple pregnancy complications following large-scale power outages during Hurricane Sandy in New York State. Sci Total Environ. 2021;770:145359.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIshikuro M, Obara T, Murakami K, Ueno F, Noda A, Kikuya M, et al. Relation of Disaster Exposure With Maternal Characteristics and Obstetric Outcomes: the Tohoku Medical Megabank Project Birth and Three-Generation Cohort Study. J Epidemiol. 2023;33(3):127\u0026ndash;35.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQuansah DY, Gilbert L, Kosinski C, Le Diz\u0026egrave;s O, Horsch A, Benhalima K, et al. Cardio-Metabolic and Mental Health Outcomes Before and During the COVID-19 Pandemic in a Cohort of Women With Gestational Diabetes Mellitus in Switzerland. Front Endocrinol. 2022;13:948716.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHsu S, Selen DJ, James K, Li S, Camargo CA, Kaimal A, et al. Assessment of the Validity of Administrative Data for Gestational Diabetes Ascertainment. Am J Obstet Gynecol MFM. 2023;5(2):100814.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 to 5 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Prevalence, Gestational Diabetes, Lebanon, COVID-19, Pregnancy","lastPublishedDoi":"10.21203/rs.3.rs-8947137/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8947137/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe prevalence of gestational diabetes mellitus (GDM) is increasing worldwide in parallel with obesity, maternal age, improved screening methods and wider screening coverage. The objective of our study was to determine the prevalence of GDM in Lebanon and to evaluate its risk factors before and during the COVID-19 pandemic.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eRecords of 2595 pregnant women who gave birth at the H\u0026ocirc;tel-Dieu de France Hospital in Beirut, were collected retrospectively from 2018\u0026ndash;2022. GDM was determined by documentation in the maternity fileward. A univariate analysis was performed to assess the factors affecting GDM. The χ\u0026sup2; test, Fisher\u0026rsquo;s exact test, independent samples T-test, and ANOVA were used for this purpose.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe mean age was 32.03 years (\u0026plusmn;\u0026thinsp;4.75). The mean BMI at the beginning of pregnancy was 24.86 kg/m\u0026sup2; (\u0026plusmn;\u0026thinsp;8.99), and the mean gestational weight gain (GWG) was 12.17 kg (\u0026plusmn;\u0026thinsp;5.06). The overall prevalence of GDM was 4.1%, increasing significantly from 2.9% to 6.4% between 2018 and 2022 (p value\u0026thinsp;=\u0026thinsp;0.007). The peak in 2020 coincided with the COVID-19 pandemic and the significant drop in income due to the concomitant economic and political crisis in the country. The risk factors associated with GDM included older age (p\u0026thinsp;=\u0026thinsp;0.003) and obesity (p\u0026thinsp;=\u0026thinsp;0.004).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe increasing trend of GDM incidence emphasizes the importance of implementing evidence-based prevention, diagnostic, and treatment strategies.\u003c/p\u003e","manuscriptTitle":"Prevalence and Trends of Gestational Diabetes in a Large University Hospital in Lebanon Before and During the COVID-19 Pandemic","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-11 15:13:32","doi":"10.21203/rs.3.rs-8947137/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-05-07T07:01:59+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-06T14:31:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"125920157980106644288002609155716642162","date":"2026-05-06T13:54:15+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-03T22:54:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"217759945385037780024403459590903330234","date":"2026-04-26T14:45:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"107936757225735415288162321420991420175","date":"2026-04-25T17:52:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"165524410539972340978009667373412467039","date":"2026-03-25T16:28:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"149403843229632113591090734050170919126","date":"2026-03-09T11:35:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"209201838180963617059544857264879239373","date":"2026-03-08T13:50:40+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-06T13:01:27+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-02-26T10:48:51+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-26T05:04:44+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-26T05:01:58+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2026-02-23T12:21:12+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"299820b8-8e24-47f6-b5bc-089e37209d1d","owner":[],"postedDate":"March 11th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-07T07:01:59+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-06T14:31:17+00:00","index":93,"fulltext":""},{"type":"reviewerAgreed","content":"125920157980106644288002609155716642162","date":"2026-05-06T13:54:15+00:00","index":92,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-03T22:54:48+00:00","index":76,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-05-07T07:10:12+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-11 15:13:32","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8947137","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8947137","identity":"rs-8947137","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}