📄 obstetrics and gynecology

COVID-19 containment policies and hyperglycemia in pregnancy: correlation with the Stringency Index in a nationwide Belgian cohort

In a nationwide Belgian cohort, the prevalence of hyperglycemia in pregnancy significantly increased during the latter half of 2020 compared to 2019, showing a strong positive correlation with the pandemic's Stringency Index, while neonatal weight percentiles remained unchanged.

Original authors: Costa, E., Vercoutere, A., Alexander, S., Boulvain, M., Derisbourg, S., Lamy, C., Delbaere, A., Racape, J.

Published 2026-06-22

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CC BY 4.0

Original authors: Costa, E., Vercoutere, A., Alexander, S., Boulvain, M., Derisbourg, S., Lamy, C., Delbaere, A., Racape, J.

Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). ⚕️ This is an AI-generated explanation of a preprint that has not been peer-reviewed. It is not medical advice. Do not make health decisions based on this content. Read full disclaimer

The Big Picture: A "Lockdown" Experiment

Imagine pregnancy as a long road trip. Usually, the car (the mother's body) runs smoothly, but sometimes the engine starts to sputter with high sugar levels, a condition called Hyperglycemia in Pregnancy (HIP). This is like the car overheating or running on bad fuel.

During 2020, the world hit the "pause button" due to the COVID-19 pandemic. Governments put up roadblocks, closed schools, and told people to stay home. This paper asks a simple question: Did these roadblocks change how often the "engine overheated" in pregnant women?

The researchers looked at data from over 229,000 babies born in Belgium in 2019 (before the lockdowns) and 2020 (during the lockdowns). They wanted to see if the strictness of the rules correlated with the number of mothers developing high blood sugar.

The "Stringency Index": A Thermometer for Rules

To measure how strict the rules were, the scientists used something called the Stringency Index (SI). Think of this as a thermometer for government rules.

0 degrees: No restrictions (everyone is free to go).
100 degrees: Maximum lockdown (schools closed, no gatherings, stay-at-home orders).

The study checked if the "temperature" of these rules matched the "fever" of high blood sugar in pregnant women.

What They Found: The Heat and the Fever

The researchers discovered a very strong connection, like a shadow following a person.

The First Half of the Year (Jan–June): When the babies were born in the first half of 2020, their mothers had been pregnant during the early days of the pandemic. The rules were just starting, and the number of high blood sugar cases was about the same as the previous year.
The Second Half of the Year (July–Dec): When babies were born later in 2020, their mothers had been pregnant during the peak of the lockdowns. Here, the number of high blood sugar cases spiked significantly.
- The highest peaks happened in July and November.
- The study found that the stricter the rules were (the higher the "thermometer" went), the more likely a mother was to develop high blood sugar. The correlation was so strong it was almost like a perfect match (0.82 out of 1.0).

Why did this happen?
The paper suggests that when the "thermometer" was high, people were stuck inside. This likely led to:

Less walking and exercise (the car isn't moving enough).
Changes in what people ate (maybe more snacking or comfort food).
More stress and anxiety (the engine is stressed out).
All these factors can make it harder for the body to manage sugar.

The Twist: The "Big Baby" Myth Didn't Happen

Usually, when a mother has high blood sugar, the baby tends to grow very large (like a balloon inflating too much). This is called a Large for Gestational Age (LGA) baby.

The researchers expected that because so many more mothers had high sugar in 2020, there would be a huge increase in "big babies."
But that didn't happen.

The number of big babies and small babies remained exactly the same in 2020 as it was in 2019.

The Analogy: It's as if the engine overheated (high sugar), but the car's cooling system worked perfectly to keep the size of the vehicle normal.
The Paper's Guess: The authors suggest this might be because doctors got really good at managing the sugar levels quickly (perhaps using video calls/telemedicine) or because the extra sugar wasn't "strong" enough to make the babies grow bigger, even though it was enough to trigger a diagnosis.

The Bottom Line

This study is like a weather report for public health. It tells us that when society puts up "storm barriers" (strict lockdowns), it can indirectly cause "floods" in maternal health (more high blood sugar).

However, even though the "flood" of high sugar happened, it didn't wash away the "houses" (the babies' sizes). The babies were born at normal sizes, suggesting that while the pandemic changed the mothers' health, the medical care or the nature of the sugar increase prevented it from changing the babies' growth.

In short: The stricter the lockdown, the more pregnant women developed high blood sugar. But surprisingly, the babies themselves didn't get bigger or smaller because of it.

Technical Summary: COVID-19 Containment Policies and Hyperglycemia in Pregnancy

Problem Statement
During the COVID-19 pandemic, the prevalence of gestational diabetes mellitus (GDM) and hyperglycemia in pregnancy (HIP) exhibited variable trends globally, with some regions reporting increases and others decreases. While anxiety and lifestyle modifications linked to pandemic restrictions have been hypothesized as contributors to increased prevalence, and changes in screening strategies as causes for decreases, the specific correlation between the intensity of containment measures and HIP prevalence has not been previously described. Furthermore, given that HIP is a known risk factor for large-for-gestational-age (LGA) newborns, it remains unclear whether pandemic-related restrictions led to measurable shifts in neonatal weight percentiles at the population level.

Methodology
This nationwide, population-based study utilized Belgian civil registration data to analyze all singleton live births in Belgium from January 1, 2019, to December 31, 2020 ( $n=229,170$ ).

Data Sources: Medical data were recorded by midwives and gynecologists at delivery, while sociodemographic data were collected by the civil registration service.
Variables:
- Outcome: HIP (including gestational and preexisting diabetes) and birthweight percentiles categorized as Small for Gestational Age (SGA <10th), Adequate for Gestational Age (AGA 10th–90th), and Large for Gestational Age (LGA >90th) using AUDIPOG curves.
- Exposure: The Stringency Index (SI), a composite measure (0–100) of governmental containment policies (e.g., school/workplace closures, stay-at-home requirements), was used to quantify restriction intensity.
- Covariates: Maternal age, parity, BMI, education level, household income, marital status, and nationality.
Statistical Analysis:
- Monthly proportions of HIP and birthweight categories were compared between 2019 and 2020.
- Crude and adjusted odds ratios (aORs) were calculated using logistic and multinomial regression, adjusting for baseline characteristics.
- To assess the temporal relationship between restrictions and HIP, the SI was correlated with monthly HIP aORs. The timing of HIP diagnosis was approximated to the month of screening (estimated at 26 weeks gestation) to align with the SI of that specific period.
- Spearman correlation coefficients were used to evaluate the relationship between the average SI and HIP aORs.

Key Results

HIP Prevalence: There was no significant difference in HIP prevalence between 2019 and 2020 for deliveries occurring from January to June. However, for deliveries from July to December 2020, a significant increase in HIP was observed compared to the same period in 2019.
- Peaks occurred in July (screening in April) with an aOR of 1.41 (95% CI 1.26–1.58) and November (screening in August) with an aOR of 1.33 (95% CI 1.18–1.49).
Correlation with Stringency Index: A strong positive correlation was found between the monthly average SI and the monthly aORs of HIP ( $r = 0.82$ , $p = 0.01$ ). The temporal pattern of HIP prevalence mirrored the evolution of pandemic restrictions, with the highest prevalence observed in women screened during periods of maximum stringency (first national lockdown).
Neonatal Outcomes: Despite the increase in HIP, there was no significant change in the distribution of neonatal weight percentiles (SGA, AGA, LGA) between 2019 and 2020. The only statistically significant finding was a minor reduction in LGA prevalence in September 2020, which the authors suggest may be a chance finding.
Demographics: While statistically significant differences existed in baseline characteristics (nationality, education, income, parity, BMI) between the two years, the absolute differences were small. The proportion of obese women and those with higher education increased slightly in 2020, but adjustment for these factors did not eliminate the association between SI and HIP.

Key Contributions

Novel Correlation: This is the first study to directly investigate and demonstrate a strong temporal correlation between the intensity of governmental containment measures (quantified by the SI) and the prevalence of HIP during the pandemic.
Temporal Granularity: By analyzing data month-by-month and aligning screening dates with restriction periods, the study moves beyond simple pre-pandemic vs. pandemic comparisons to identify specific windows of risk.
Discrepancy in Outcomes: The study highlights a dissociation between increased maternal hyperglycemia and neonatal growth outcomes, noting that the expected rise in LGA newborns did not materialize despite higher HIP rates.

Significance and Claims
The authors claim that their findings suggest societal restrictions during public health emergencies may have measurable indirect effects on maternal metabolic health, specifically increasing the risk of hyperglycemia in pregnancy. The strong correlation with the SI implies that the mechanisms driving this increase—likely reduced physical activity, altered dietary habits, and increased psychological stress—are directly linked to the severity of containment measures.

Regarding the lack of impact on birthweight, the authors propose two potential explanations consistent with existing literature:

Improved Management: The rapid adoption of telemedicine and intensive management may have mitigated the impact of GDM on fetal growth.
Mild Cases: The increase in HIP prevalence may have been driven primarily by mild forms of gestational diabetes, which raise prevalence statistics without significantly altering fetal growth distribution at the population level.

The paper concludes that these results may be useful for anticipating unintended consequences of future public health emergencies requiring similar containment measures, emphasizing the need to monitor maternal metabolic health during periods of restricted mobility and social disruption. The authors maintain a modest tone, acknowledging that the observational nature of the study precludes causal inference and that residual confounding cannot be excluded.