Dataset Information

Maternal socioeconomic factors and the risk of premature birth and low birth weight in Cyprus: a case-control study.

ABSTRACT:

Background

Prematurity and low birth weight are significant predictors of perinatal morbidity and mortality and are influenced by the overall health and socioeconomic status of the pregnant mother. Although Cyprus is characterized by the highest prematurity rate in Europe (13.1% in 2014), the relationship between maternal health and socioeconomic characteristics with prematurity and low birth weight has never been investigated. We aimed to investigate the association of maternal demographic, clinical and socioeconomic characteristics with premature delivery and low neonatal birth weight in Cyprus.

Methods

In a case-control design, questionnaire data were collected from 348 women who gave birth prematurely (cases) and 349 women who gave birth at term (controls). Information was obtained on gestation duration and birth weight as well as maternal demographic, socioeconomic and clinical profiles, including parameters such as smoking, body mass index, alcohol consumption, presence of gestational diabetes and mental health factors.

Results

Premature delivery was associated with greater maternal age (OR: 1.12, 95% CI: 1.06-1.18), absence of gestational diabetes (OR: 0.53, 95% CI: 0.30-0.97), long working hours (OR: 3.77, 95% CI: 2.08-6.84) and emotional stress (OR: 8.5, 95% CI: 3.03-23.89). Within the cases group, emotional stress was also associated with lower birth-weight (?: -323.68 (95% CI: -570.36, -?77.00).

Conclusions

The findings of this study demonstrate the positive association of maternal psychological factors, working conditions as well as maternal age with prematurity and low birth weight in Cyprus. Additional, prospective, studies are needed in the country to further investigate these associations and inform public health intervention measures.

SUBMITTER: Stylianou-Riga P

PROVIDER: S-EPMC6146509 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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Publications

Maternal socioeconomic factors and the risk of premature birth and low birth weight in Cyprus: a case-control study.

Stylianou-Riga Paraskevi P Kouis Panayiotis P Kinni Paraskevi P Rigas Angelos A Papadouri Thalia T Yiallouros Panayiotis K PK Theodorou Mamas M

Reproductive health 20180919 1

<h4>Background</h4>Prematurity and low birth weight are significant predictors of perinatal morbidity and mortality and are influenced by the overall health and socioeconomic status of the pregnant mother. Although Cyprus is characterized by the highest prematurity rate in Europe (13.1% in 2014), the relationship between maternal health and socioeconomic characteristics with prematurity and low birth weight has never been investigated. We aimed to investigate the association of maternal demograp ...[more]

PMID: 30231873

Similar Datasets

Project description:BackgroundMothers in low socio-economic conditions frequently have low birth weight infants. Inaddition Physically demanding work during pregnancy also contributes to poor fetal growth. During gestation a woman needs balanced nutrition for a healthy outcome. Women with inadequate nutritional status at conception are at greater risk of aquiring disease; their health usually depends on the availability and consumption of balanced diet, and therefore they are unlikely to be able to resist with their high nutrient needs during pregnancy. Therefore, the main purpose of this study was to assess the maternal risk factors associated low birth weight in public hospitals of Mekelle city, Tigray North Ethiopia, 2017/2018.MethodsUn-matched case-control study design was conducted among women who delivered in public hospitals of Mekelle city. Data was collected using a structured questionnaire through interview, direct physical assessment and medical record review of mothers. Sample size was calculated by Epi-info version 7.0 to get a final sample size of 381(cases = 127 and controls = 254). SPSS version 20 was used for analysis. Bivariate and multivariate logistic regression analysis was used to determine the effect of the independent variables on birth weight. Presence of significant association was determined using OR with its 95%CI. A P value of less than 0.05 was considered to declare statistical significance. Table, graphs and texts were used to present the data.ResultMost of the mothers (70.1% cases and 43.7% controls) were housewives. This study showed that maternal age ≤ 20 years (AOR = 6.42(95% CI = (1.93-21.42)), ANC follow up (AOR = 3.73(95%CI (1.5-9.24)), History of medical illness (AOR = 14.56(95% CI (3.69-57.45), Iron folate intake (AOR = 21.56(95%CI (6.54-71.14)), Maternal height less than 150 cm (AOR = 9.27(95%CI 3.45-24.89)) and Pregnancy weight gain (AOR = 4.93(95%CI = 1.8-13.48) were significant predictors of low birth weight.ConclusionThe study suggests that inadequate ANC follow-up, preterm birth and history of chronic medical illness, maternal height, pregnancy weight gain, and Iron intake were. Were significant predictors of low birth weight. Health professionals should screen and consulate pregnant mothers who are at risk of having infants with LBW and ensure that women have access to essential health information on the causes of low birth weight.

Project description:Background: Despite of extensive research the genetic component of extremely low birth weight in newborns has remained obscure. Results: The aim of the case study was to identify candidate gene(s) causing extremely low birth weight (ELBW) in newborns and hypotrophy in infants. A four-member family was studied: mother, father and two ELBW-phenotype children. The studies were carried out due to the medical conditions of the second child at birth and post-partum: peculiar phenotype, micro-anomalies, recurrent infections, suspicion of autoimmune hepatitis, multifactorial encephalopathy, and suspicion of metabolic and chromosomal abnormalities. Whole genome single nucleotide polymorphism (SNP) genotyping array was used to investigate genomic rearrangements in both affected children using peripheral blood DNA samples. Whole blood transcriptome was assessed by using RNA sequencing (RNA-seq) in all four family members. RNA-seq identified a single gene – C14orf132 differentially expressed, with the level of the transcript significantly lower in blood samples of children. Copy number variant (CNV) analysis did not reveal any pathogenic CNVs in the region of C14orf132 gene of both affected children. Conclusion: We showed the importance of combining whole genome CNV and transcriptome analysis in identification of the candidate gene(s) in case studies. We propose the C14orf132 (chromosome 14 open reading frame 132) gene expression to be associated with the ELBW-phenotype. C14orf132 gene is a novel long non-coding RNA (lincRNA) with unknown function, which might be associated with the developmental delay through the altered gene expression Background: Despite of extensive research the genetic component of extremely low birth weight in newborns has remained obscure. Results: The aim of the case study was to identify candidate gene(s) causing extremely low birth weight (ELBW) in newborns and hypotrophy in infants. A four-member family was studied: mother, father and two ELBW-phenotype children. The studies were carried out due to the medical conditions of the second child at birth and post-partum: peculiar phenotype, micro-anomalies, recurrent infections, suspicion of autoimmune hepatitis, multifactorial encephalopathy, and suspicion of metabolic and chromosomal abnormalities. Whole genome single nucleotide polymorphism (SNP) genotyping array was used to investigate genomic rearrangements in both affected children using peripheral blood DNA samples. Whole blood transcriptome was assessed by using RNA sequencing (RNA-seq) in all four family members. RNA-seq identified a single gene – C14orf132 differentially expressed, with the level of the transcript significantly lower in blood samples of children. Copy number variant (CNV) analysis did not reveal any pathogenic CNVs in the region of C14orf132 gene of both affected children. Conclusion: We showed the importance of combining whole genome CNV and transcriptome analysis in identification of the candidate gene(s) in case studies. We propose the C14orf132 (chromosome 14 open reading frame 132) gene expression to be associated with the ELBW-phenotype. C14orf132 gene is a novel long non-coding RNA (lincRNA) with unknown function, which might be associated with the developmental delay through the altered gene expression Background: Despite of extensive research the genetic component of extremely low birth weight in newborns has remained obscure. Results: The aim of the case study was to identify candidate gene(s) causing extremely low birth weight (ELBW) in newborns and hypotrophy in infants. A four-member family was studied: mother, father and two ELBW-phenotype children. The studies were carried out due to the medical conditions of the second child at birth and post-partum: peculiar phenotype, micro-anomalies, recurrent infections, suspicion of autoimmune hepatitis, multifactorial encephalopathy, and suspicion of metabolic and chromosomal abnormalities. Whole genome single nucleotide polymorphism (SNP) genotyping array was used to investigate genomic rearrangements in both affected children using peripheral blood DNA samples. Whole blood transcriptome was assessed by using RNA sequencing (RNA-seq) in all four family members. RNA-seq identified a single gene – C14orf132 differentially expressed, with the level of the transcript significantly lower in blood samples of children. Copy number variant (CNV) analysis did not reveal any pathogenic CNVs in the region of C14orf132 gene of both affected children. Conclusion: We showed the importance of combining whole genome CNV and transcriptome analysis in identification of the candidate gene(s) in case studies. We propose the C14orf132 (chromosome 14 open reading frame 132) gene expression to be associated with the ELBW-phenotype. C14orf132 gene is a novel long non-coding RNA (lincRNA) with unknown function, which might be associated with the developmental delay through the altered gene expression. Background: Despite of extensive research the genetic component of extremely low birth weight in newborns has remained obscure. Results: The aim of the case study was to identify candidate gene(s) causing extremely low birth weight (ELBW) in newborns and hypotrophy in infants. A four-member family was studied: mother, father and two ELBW-phenotype children. The studies were carried out due to the medical conditions of the second child at birth and post-partum: peculiar phenotype, micro-anomalies, recurrent infections, suspicion of autoimmune hepatitis, multifactorial encephalopathy, and suspicion of metabolic and chromosomal abnormalities. Whole genome single nucleotide polymorphism (SNP) genotyping array was used to investigate genomic rearrangements in both affected children using peripheral blood DNA samples. Whole blood transcriptome was assessed by using RNA sequencing (RNA-seq) in all four family members. RNA-seq identified a single gene – C14orf132 differentially expressed, with the level of the transcript significantly lower in blood samples of children. Copy number variant (CNV) analysis did not reveal any pathogenic CNVs in the region of C14orf132 gene of both affected children. Conclusion: We showed the importance of combining whole genome CNV and transcriptome analysis in identification of the candidate gene(s) in case studies. We propose the C14orf132 (chromosome 14 open reading frame 132) gene expression to be associated with the ELBW-phenotype. C14orf132 gene is a novel long non-coding RNA (lincRNA) with unknown function, which might be associated with the developmental delay through the altered gene expression.

Dataset Information

Maternal socioeconomic factors and the risk of premature birth and low birth weight in Cyprus: a case-control study.

Background

Methods

Results

Conclusions

Publications

Maternal socioeconomic factors and the risk of premature birth and low birth weight in Cyprus: a case-control study.

Similar Datasets

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