Maternal pregestational diabetes and risk of acute lymphoblastic leukemia in the offspring: A population-based study in Northern Italy

Residential exposure to magnetic fields from transformer stations and risk of childhood leukemia

BACKGROUND

Several studies have documented an increased risk of leukemia among children exposed to magnetic fields from high-voltage power lines, with some evidence of dose-response relation. However, findings in some studies have been inconsistent, and data on the effects of different sources of exposure are lacking. In this study, we evaluated the relation of childhood leukemia risk to exposure to magnetic fields from transformer stations.

METHODS

We conducted a population-based case-control study in a pediatric population of two Northern Italian provinces of Modena and Reggio Emilia. We included 182 registry-identified childhood leukemia cases diagnosed during 1998-2019 and 726 population controls matched on sex, year of birth, and province of residence. We assessed exposure by calculating distance from childhood residence to the nearest transformer station within a geographical information system, computing disease odds ratios (ORs) and 95% confidence intervals (CIs) using conditional logistic regression, adjusting for potential confounders. We evaluated exposure using two buffers (15 m and 25 m radius) and assessed two case groups: leukemia (all subtypes) and acute lymphoblastic leukemia (ALL).

RESULTS

Residing within 15 m of a transformer station (vs. ≥15 m) was not appreciably associated with risk of leukemia (all subtypes) or ALL. We found similar results using a less stringent exposure buffer (25 m). Among children aged ≥5 years, the adjusted ORs were 1.3 (95% CI 0.1-12.8) for leukemia and 1.3 (95% CI 0.1-12.4) for ALL using the 15 m buffer, while they were 1.7 (95% CI 0.4-7.0) for leukemia and 0.6 (95% CI 0.1-4.8) for ALL using the 25 m buffer.

CONCLUSIONS

While we found no overall association between residential proximity to transformer stations and childhood leukemia, there was some evidence for elevated risk of childhood leukemia among children aged ≥5 years. Precision was limited by the low numbers of exposed children.

Maternal BMI, Diabetes, and Gestational Weight Gain and Risk for Pediatric Cancer in Offspring: A Systematic Review and Meta-Analysis

Background

Pediatric cancer incidence has steadily increased concurrent with rising adult obesity, but associations between maternal obesity and associated comorbidities and pediatric cancer risk remain understudied. We aimed to quantitatively characterize associations of pediatric cancer risk with maternal prepregnancy body mass index (BMI), gestational weight gain, and maternal diabetes.

Methods

We performed a comprehensive and systematic literature search in Ovid and EMBASE from their inception to March 15, 2021. Eligible studies reported risk estimates and sample sizes and provided sufficient description of outcome and exposure ascertainment. Random effects models were used to estimate pooled effects.

Results

Thirty-four studies were included in the analysis. Prepregnancy BMI was positively associated with leukemia risk in offspring (odds ratio [OR] per 5-unit BMI increase =1.07, 95% confidence intervals [CI] = 1.04 to 1.11; I² = 0.0%). Any maternal diabetes was positively associated with acute lymphoblastic leukemia risk (OR = 1.46, 95% CI = 1.28 to 1.67; I² = 0.0%), even after restricting to birthweight-adjusted analyses (OR = 1.74, 95% CI = 1.29 to 2.34; I² = 0.0%), and inversely associated with risk of central nervous system tumors (OR = 0.73, 95% CI = 0.55 to 0.97; I² = 0.0%). Pregestational diabetes (OR = 1.57, 95% CI = 1.11 to 2.24; I² = 26.8%) and gestational diabetes (OR = 1.40, 95% CI = 1.12 to 1.75; I² = 0.0%) were also positively associated with acute lymphoblastic leukemia risk. No statistically significant associations were observed for gestational weight gain.

Conclusions

Maternal obesity and diabetes may be etiologically linked to pediatric cancer, particularly leukemia and central nervous system tumors. Our findings support weight management and glycemic control as important components of maternal and offspring health. Further validation is warranted.

Maternal diabetes and risk of childhood malignancies in the offspring: a systematic review and meta-analysis of observational studies

AIMS

Diabetes mellitus (DM) is widely recognized as a risk factor for diverse cancers in adults. However, the association between maternal diabetes and risk of childhood cancer in the offspring has so far not been well studied. We thus conducted a meta-analysis to evaluate the role of maternal diabetes on the risk of childhood cancer.

METHODS

We performed a comprehensive literature search to identify eligible studies published up to June 20, 2020, including the PubMed, Web of science and Embase databases. Summary odds ratios (OR) and 95% confidence intervals (CI) were computed using a random-effects model (I² ≥ 25%) or a fixed-effect model (I² < 25%).

RESULTS

Totally, sixteen case-control and six cohort studies on the risk of childhood cancer associated with maternal diabetes were included. Overall, children of diabetic women had a significantly increased risk in childhood malignancy (OR, 1.30; 95% CI, 1.10-1.53). Notably, a significantly elevated risk of childhood cancer in the offspring was found for women with pre-existing diabetes (OR, 1.41; 95% CI, 1.17-1.70), but not for women with gestational diabetes mellitus (GDM) (OR, 1.10; 95% CI, 0.94-1.28). For site-specific cancers, maternal diabetes was associated with a higher risk of leukemia in offspring (OR, 1.30; 95% CI, 1.15-1.48), especially for acute lymphoblastic leukemia (OR, 1.44; 95% CI, 1.27-1.64). However, no significant associations were observed between maternal diabetes and the risk of lymphomas and retinoblastoma.

CONCLUSIONS

Our meta-analysis indicates that maternal diabetes is associated with an increased risk of childhood cancer in the offspring, particularly for acute lymphoblastic leukemia. Future study should investigate the underlying biological mechanisms behind the association.