Determinants of Suboptimal Gestational Weight Gain among Antenatal Women Residing in the Highest Gross Domestic Product (GDP) Region of Malaysia

Shahrir, Nurul Farehah; Rohana, A.J.; Hamid, Noor Aman; Daud, Zaiton; Asis, Siti Harirotul Hamrok

doi:10.3390/nu14071436

Cited by 3 publications

(1 citation statement)

References 26 publications

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“…Excessive GWG is associated with an increased risk of gestational diabetes, gestational hypertension, preeclampsia, preterm birth, cesarean delivery, macrosomia, infant mortality, postpartum weight retention, and childhood obesity ( 8 – 12 ). Recent reports indicate a high prevalence of inadequate gestational weight gain in South Asia, in particular in India ( 13 , 14 ). Appropriate GWG is usually evaluated in comparison to two international standards – those of the Institute of Medicine (IOM) and International Fetal and Newborn Growth-21st (Intergrowth-21st) ( 9 , 15 ).…”

Section: Introductionmentioning

confidence: 99%

Gestational weight gain in the REVAMP pregnancy cohort in Western India: Comparison with international and national references

Dangat

Gupte²,

Wagh

et al. 2022

Front. Med.

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ObjectiveTo determine the trimester specific gestational weight gain (GWG) in a population of pregnant women from Western India and compare it with the Intergrowth–21st international and an Indian reference (GARBH–Ini cohort—Group for Advanced Research on BirtH outcomes).Study designA prospective longitudinal observational study was undertaken in Pune, West India and data for gestational weight gain was collected [the REVAMP study (Research Exploring Various Aspects and Mechanisms in Preeclampsia)]. Generalized Additive Models for Location, Scale and Shape method (GAMLSS model) were used to create GWG centile curves according to gestational age, stratified by BMI at recruitment (n = 640) and compared with Intergrowth-21st reference and GARBH–Ini cohort. Multivariable regression analysis was used to evaluate the relationship between GWG and antenatal risk factors.ResultsThe median GWG was 1.68, 5.80, 7.06, and 11.56 kg at gestational ages 18, 26, 30, and 40 weeks, respectively. In our study, pregnant women gained less weight throughout pregnancy compared to Intergrowth-21st study, but more weight compared to the GARBH–Ini cohort centile curves in all the BMI categories. GWG in overweight/obese women (BMI ≥ 25) was significantly lower (<0.001) as compared to underweight (BMI < 18.5), or normal weight women (BMI ≥ 18.5 and <25). The median GWG at 40 weeks in underweight, normal and overweight/obese women was 13.18, 11.74, and 10.48 kg, respectively. Higher maternal BMI, older maternal age, higher parity and higher hemoglobin concentrations were associated with lower GWG, while taller maternal height was associated with greater GWG.ConclusionGWG of Indian women is lower than the prescriptive standards of the Intergrowth charts.

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Section: Introductionmentioning

confidence: 99%

Gestational weight gain in the REVAMP pregnancy cohort in Western India: Comparison with international and national references

Dangat

Gupte²,

Wagh

et al. 2022

Front. Med.

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Modeling labor costs using artificial intelligence tools

Momade

Durdyev

Dixit

et al. 2022

IJBPA

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PurposeConstruction projects in Malaysia are often delayed and over budget due to heavy reliance on labor. Linear regression (LR) models have been used in most labor cost (LC) studies, which are less accurate than machine learning (ML) tools. Construction management applications have increasingly used ML tools in recent years and have greatly impacted forecasting. The research aims to identify the most influential LC factors using statistical approaches, collect data and forecast LC models for improved forecasts of LC.Design/methodology/approachA thorough literature review was completed to identify LC factors. Experienced project managers were administered to rank the factors based on importance and relevance. Then, data were collected for the six highest ranked factors, and five ML models were created. Finally, five categorical indices were used to analyze and measure the effectiveness of models in determining the performance category.FindingsWorker age, construction skills, worker origin, worker training/education, type of work and worker experience were identified as the most influencing factors on LC. SVM provided the best in comparison to other models.Originality/valueThe findings support data-driven regulatory and practice improvements aimed at improving labor issues in Malaysia, with the possibility for replication in other countries facing comparable problems.

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Exploring the relationship between sunlight exposure, psychological health, and gestational weight gain: a prospective observational study

Kaur,

Kok,

Jamil

et al. 2024

BMC Public Health

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Introduction Gestational weight gain (GWG) is influenced by various factors during pregnancy. This study attempts to explore the relationship between environmental factors i.e., sunlight exposure and psychological health i.e. psychological well-being and sleep quality during pregnancy with total gestational weight gain. Methods This was a prospective observational study conducted in government maternity clinics in Kuala Lumpur. Pregnant women aged 19–39 years without comorbidities were recruited during second trimester and followed up until birth. The participants were required to wear a UVB dosimeter for a total of three consecutive days (2 weekdays and 1 weekend) to determine sunlight exposure (SED) during their second trimester. The PSQI and DASS-21 were used to determine sleep quality and psychological wellbeing, respectively. GWG data were collected from clinic health records. The association of sun exposure and psychological health with total GWG was determined using multiple linear regression. Results A total of 73 pregnant women aged 27.9 ± 3.3 years were included in the analysis. The prevalence of pregnant women exhibiting stress, anxiety, and depression symptoms was 11%, 40%, and 16% respectively. The global PSQI median score was 5 (IQR = 3), with 59% having poor sleep quality. Median sleep duration was 7 h (IQR = 2) while median sleep efficiency was 92% (IQR = 14). The median SED was 0.04 (IQR = 0.09), with 51% of them being under the 50th percentile. The majority had adequate GWG (58%). Sleep parameters were not found to be correlated with total GWG except for sleep latency (ρ = -0.356, p = 0.002). Sunlight exposure was found to have no significant relationship with sleep and total GWG. Adjusted multiple linear regression showed that greater depression is associated with higher total GWG (β = 0.239, p = 0.039) while controlling for sleep quality. Conclusion Depression was associated with total GWG when sleep quality was controlled for while sunlight exposure had no significant association with GWG. Future studies should study the complex relationship between factors of mental health, sleep, and weight gain during pregnancy. Healthcare providers may be better equipped to develop interventions aimed to prevent negative maternal and fetal health outcomes.

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Determinants of Suboptimal Gestational Weight Gain among Antenatal Women Residing in the Highest Gross Domestic Product (GDP) Region of Malaysia

Cited by 3 publications

References 26 publications

Gestational weight gain in the REVAMP pregnancy cohort in Western India: Comparison with international and national references

Gestational weight gain in the REVAMP pregnancy cohort in Western India: Comparison with international and national references

Modeling labor costs using artificial intelligence tools

Exploring the relationship between sunlight exposure, psychological health, and gestational weight gain: a prospective observational study

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