Early pregnancy hyperglycaemia as a significant predictor of large for gestational age neonates

Jayasinghe, Imasha Upulini; Koralegedara, Iresha Sandamali; Agampodi, Suneth

doi:10.1007/s00592-021-01828-1

Cited by 10 publications

(8 citation statements)

References 38 publications

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“…Several studies conducted worldwide have shown that a high blood glucose level is strongly associated with NAFLD 19 46 47. This may be due to alterations in lipid metabolism and inflammation within the adipose tissue and fat deposition in the liver, leading to insulin resistance 46.…”

Section: Discussion and Interpretationmentioning

confidence: 99%

Fatty Liver Index is a valid predictor of non-alcoholic fatty liver disease (NAFLD) in pregnancy

Koralegedara

Warnasekara

Rathnayake

et al. 2022

BMJ Open Gastroenterol

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BackgroundDespite the evidence for adverse pregnancy outcomes, non-alcoholic fatty liver disease (NAFLD) is not routinely addressed in early pregnancy. The Fatty Liver Index (FLI) has been proposed as a screening tool for NAFLD in the general population. We aim to develop mathematical models for predicting NAFLD in pregnancy and validate the FLI for first-trimester pregnant women.MethodsBiochemical and biophysical parameters were analysed in pregnant women with period of gestation <12 weeks was done among Rajarata Pregnancy Cohort, Sri Lanka. Fatty liver was graded as (FLG) 0, I or II by ultrasound scan. Binary logistic regression models were employed to identify the factors predicting FLG-II. Six FLIs were developed to predict FLG-II. Validity of the FLIs was compared using the receiver operating characteristic curves.ResultsThe study sample consisted of 632 pregnant women with a mean age of 28.8 years (SD: 5.8 years). Age (OR: 1.6, 95% CI 1.1 to 2.3), body mass index (OR: 1.7, 95% CI 1.1 to 2.5) and gamma-glutamyl transferase levels (OR: 2.1, 95% CI 1.5 to 3.0) were the independent predictors of FLG-II. While the model with liver enzymes provided the best prediction of NAFLD (both FLG I and II) (area under the curve [(AUC]): −0.734), the highest AUC (0.84) for predicting FLG-II was observed with the full model (model with all parameters). The proposed budget model (AUC >0.81) is the best model for screening fatty liver in community health setup.ConclusionFLIs could be used as screening tools for NAFLD based on resource availability in different settings. External validation of the FLI and further investigation of the proposed FLI as a predictor of adverse pregnancy outcomes are recommended.

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Section: Discussion and Interpretationmentioning

confidence: 99%

Fatty Liver Index is a valid predictor of non-alcoholic fatty liver disease (NAFLD) in pregnancy

Koralegedara

Warnasekara

Rathnayake

et al. 2022

BMJ Open Gastroenterol

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“…GDM and DM were collectively labelled as HIP. The detailed protocol on baseline evaluation and glycemic status evaluation of the cohort is published elsewhere [ 33 ]. BMI of the participants were categorized according to the Asia Pacific Guidelines for BMI classification [ 34 ].…”

Section: Methodsmentioning

confidence: 99%

Early pregnancy metabolic syndrome and risk for adverse pregnancy outcomes: findings from Rajarata Pregnancy Cohort (RaPCo) in Sri Lanka

Jayasinghe

Agampodi

Dissanayake

et al. 2023

BMC Pregnancy Childbirth

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Background Despite the intergenerational effects of metabolic disorders, evidence is greatly lacking on early pregnancy metabolic syndrome (MetS) and its effects on pregnancy outcomes from low- and middle-income countries. Thus, this prospective cohort of South Asian pregnant women aimed to evaluate how early pregnancy MetS would affect pregnancy outcomes. Methods A prospective cohort study was conducted among first-trimester (T1) pregnant women of Anuradhapura district, Sri Lanka recruited to the Rajarata Pregnancy Cohort in 2019. MetS was diagnosed by the Joint Interim Statement criteria before 13 weeks of gestational age (GA). Participants were followed up until their delivery, and the major outcomes measured were large for gestational age (LGA), small for gestational age (SGA), preterm birth (PTB) and miscarriage (MC). Gestational weight gain, gestational age at delivery and neonatal birth weight were used as measurements to define the outcomes. Additionally, outcome measures were re-assessed with adjusting fasting plasma glucose (FPG) thresholds of MetS to be compatible with hyperglycemia in pregnancy (Revised MetS). Results 2326 T1 pregnant women with a mean age of 28.1 years (SD-5.4), and a median GA of 8.0 weeks (IQR-2) were included. Baseline MetS prevalence was 5.9% (n = 137, 95%CI-5.0–6.9). Only 2027 (87.1%) women from baseline, had a live singleton birth, while 221(9.5%) had MC and 14(0.6%) had other pregnancy losses. Additionally, 64(2.8%) were lost to follow-up. A higher cumulative incidence of LGA, PTB, and MC was noted among the T1-MetS women. T1-MetS carried significant risk (RR-2.59, 95%CI-1.65–3.93) for LGA, but reduced the risk for SGA (RR-0.41, 95%CI-0.29–0.78). Revised MetS moderately increased the risk for PTB (RR-1.54, 95%CI-1.04–2.21). T1-MetS was not associated (p = 0.48) with MC. Lowered FPG thresholds were significantly associated with risk for all major pregnancy outcomes. After adjusting for sociodemographic and anthropometric confounders, revised MetS remained the only significant risk predictor for LGA. Conclusion Pregnant women with T1 MetS in this population are at an increased risk for LGA and PTB and a reduced risk for SGA. We observed that a revised MetS definition with lower threshold for FPG compatible with GDM would provide a better estimation of MetS in pregnancy in relation to predicting LGA.

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“…In 2014, over 90% of the pregnancy-related hyperglycemia occurred in low-income countries, and a quarter of all global cases are concentrated in South Asia [38]. A more recent study in Sri Lanka showed early detection of hyperglycemia in the first trimester, using the WHO diagnostic criteria, was associated with higher risk of LGA [39].…”

Section: Index Pregnancy Characteristics and Care Seekingmentioning

confidence: 99%

Demographic, socio-economic, obstetric, and behavioral factors associated with small-and large-for-gestational-age from a prospective, population-based pregnancy cohort in rural Nepal: a secondary data analysis

Hazel

Mohan

Zeger

et al. 2022

BMC Pregnancy Childbirth

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Background In South Asia, a third of babies are born small-for-gestational age (SGA). The risk factors are well described in the literature, but many studies are in high-and-middle income countries or measure SGA on facility births only. There are fewer studies that describe the prevalence of risk factors for large-for-gestational age (LGA) in low-income countries. We aim to describe the factors associated with SGA and LGA in a population-based cohort of pregnant women in rural Nepal. Methods This is a secondary data analysis of community-based trial on neonatal oil massage (22,545 women contributing 39,479 pregnancies). Demographic, socio-economic status (SES), medical/obstetric history, and timing of last menstruation were collected at enrollment. Vital signs, illness symptoms, and antenatal care (ANC) attendance were collected throughout the pregnancy and neonatal weight was measured for live births. We conducted multivariate analysis using multinomial, multilevel logistic regression, reporting the odds ratio (OR) with 95% confidence intervals (CIs). Outcomes were SGA, LGA compared to appropriate-for-gestational age (AGA) and were multiply imputed using birthweight recalibrated to time at delivery. Results SGA was associated with nulligravida (OR: 2.12 95% CI: 1.93–2.34), gravida/nulliparous (OR: 1.86, 95% CI: 1.26–2.74), interpregnancy intervals less than 18 months (OR: 1.16, 95% CI: 1.07–1.27), and poor appetite/vomiting in the second trimester, (OR: 1.27, 95% CI: 1.19–1.35). Greater wealth (OR: 0.78, 95% CI: 0.69–0.88), swelling of hands/face in the third trimester (OR: 0.81, 95% CI: 0.69–0.94) parity greater than five (OR: 0.77, 95% CI: 0.65–0.92), male fetal sex (OR: 0.91, 95% CI: 0.86–0.98), and increased weight gain (OR: 0.93 per weight kilogram difference between 2nd and 3rd trimester, 95% CI: 0.92–0.95) were protective for SGA. Four or more ANC visits (OR: 0.53, 95% CI: 0.41–0.68) and respiratory symptoms in the third trimester (OR: 0.67, 95% CI: 0.54–0.84) were negatively associated with LGA, and maternal age < 18 years (OR: 1.39, 95% CI: 1.03–1.87) and respiratory symptoms in the second trimester (OR: 1.27, 95% CI: 1.07–1.51) were positively associated with LGA. Conclusions Our findings are in line with known risk factors for SGA. Because the prevalence and mortality risk of LGA babies is low in this population, it is likely LGA status does not indicate underlaying illness. Improved and equitable access to high quality antenatal care, monitoring for appropriate gestational weight gain and increased monitoring of women with high-risk pregnancies may reduce prevalence and improve outcomes of SGA babies. Trial Registration The study used in this secondary data analysis was registered at Clinicaltrials.gov NCT01177111.

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Early pregnancy hyperglycaemia as a significant predictor of large for gestational age neonates

Cited by 10 publications

References 38 publications

Fatty Liver Index is a valid predictor of non-alcoholic fatty liver disease (NAFLD) in pregnancy

Fatty Liver Index is a valid predictor of non-alcoholic fatty liver disease (NAFLD) in pregnancy

Early pregnancy metabolic syndrome and risk for adverse pregnancy outcomes: findings from Rajarata Pregnancy Cohort (RaPCo) in Sri Lanka

Demographic, socio-economic, obstetric, and behavioral factors associated with small-and large-for-gestational-age from a prospective, population-based pregnancy cohort in rural Nepal: a secondary data analysis

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