scholarly journals SUBNORMAL BIRTHWEIGHT AND INDUSTRIAL AIR POLLUTANTS – A COMPARISON OF SPATIAL-TEMPORAL HOT SPOT PATTERNS

2018 ◽  
Vol 23 (suppl_1) ◽  
pp. e38-e38
Author(s):  
Charlene Nielsen ◽  
Carl Amrhein ◽  
Jesus Serrano Lomelin ◽  
Osmar Zaiane ◽  
Alvaro Osornio Vargas
Keyword(s):  
Birth Weight ◽  
Low Birth Weight ◽  
Hot Spots ◽  
Hot Spot ◽  
Temporal Patterns ◽  
Space Time ◽  
Postal Code ◽  
Birth Registry ◽  
Time Pattern ◽  
Increasing Trend

Abstract BACKGROUND Disorders related to short gestation and low birth weight are the 2nd cause of infant death in Canada and have been increasing, especially in Alberta. Individual maternal risks are important but environmental exposures during pregnancy may restrict fetal growth. This contributes to small for gestational age (SGA: < tenth percentile weight for pregnancy duration) and low birth weight at term (LBWT: <2500 grams at ≥37 weeks-gestation). OBJECTIVES We examined the spatial-temporal patterns of SGA and LBWT with patterns of pollutants around conception, middle trimester, and birth. DESIGN/METHODS We aggregated postal code locations of mothers’ residences from the 2006–2012 birth registry in to space-time bins to analyze emerging hot spots. We applied the space-time pattern analysis on 70 industrial chemical emissions from the National Pollutant Release Inventory (NPRI) in estimated three month intervals. Then we statistically associated the classified patterns of SGA/LBWT with the pollutant patterns using the kappa statistic to determine how much the hot spot categories agree. The difference between kappa values indicated which trimester would be more important for which chemical. RESULTS ​There was an increasing trend for SGA (consecutive hot spots) and for LBWT (sporadic hot spots) in major urban centers. There was an increasing trend for 15 chemicals (varying hot spots). 28 chemical patterns had a kappa index greater than 0.2 with SGA or LBWT patterns. Although there is poor agreement between the space-time patterns, the maximum kappa values occurred mostly with LBWT and around birth. CONCLUSION Spatial-temporal patterns of chemicals identified in published literature (e.g. particulate matter and gases) agreed more with timing around conception; however, there were additional pollutants identified during the birth trimester. Our research is moving us toward a better understanding of the spatial-temporal link between environment and early health.

scholarly journals Does Entrepreneurship Contribute to Innovation Performance When Considering Spatial Spillover Effects? Evidence From the Automobile Industrial Cluster in China

SAGE Open ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 215824402098299
Author(s):  
Haishi Li ◽  
Xiangyi Xu ◽  
Shuaishuai Li
Keyword(s):  
Automobile Industry ◽  
Hot Spots ◽  
Hot Spot ◽  
Empirical Support ◽  
Temporal Patterns ◽  
Spillover Effects ◽  
Industrial Clusters ◽  
Innovation Performance ◽  
Spatial Spillover ◽  
Spatio Temporal

Entrepreneurship, as one of the important factors to promote industrial innovation, is closely related to the development of the regional economy. Based on the methods of Kernel density and standard deviation ellipse, this article presents the spatio-temporal patterns of entrepreneurship and innovation performance. The article also examines the spatial spillover mechanism of entrepreneurship on innovation performance by establishing spatial Durbin models. The heterogeneous results of the spatial regression models in six clusters are also discussed. The final results show that the spatio-temporal patterns of entrepreneurship are gradually presenting three major hot spots and two secondary hot spots while the spatio-temporal patterns of innovation performance are presenting four major hot spots and a secondary hot spot; the spatial distribution of both entrepreneurship and innovation performance are changing regularly; the spillover effects of entrepreneurship and innovation performance are both significant; the spatial spillover mechanisms in six automobile industrial clusters are different. The results can provide empirical support for decision-making in the automobile industry in China in the future.

scholarly journals Neonatal heel prick screening TSH concentration in the Netherlands as indicator of iodine status

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Janneke Verkaik-Kloosterman
Keyword(s):  
Birth Weight ◽  
Low Birth Weight ◽  
The Netherlands ◽  
Thyroid Stimulating Hormone ◽  
Preterm Neonates ◽  
Iodine Status ◽  
Increasing Trend ◽  
Heel Prick ◽  
Potential Conditions ◽  
Iodine Sufficiency

Abstract Background Neonatal Thyroid Stimulating Hormone (nTSH) is proposed as indicator of iodine deficiency in a population. Population’s iodine sufficiency is indicated by a proportion of the newborns less than 3% having nTSH above 5 mIU/L. The aim of this study was to explore the Dutch neonatal heel prick screening TSH data to assess iodine status in the Netherlands and identify determinants and potential confounders of this assessment. Methods All newborns born in the Netherlands between 2007 and 2015 with a heel prick collection at day 3-7 were included (n = 1,435,600), except preterm neonates and baby’s with a low birth weight. Total T4 was measured for all children, nTSH was measured in the ~ 20% children with lowest total T4. Results The proportion with nTSH > 5mIU/L fluctuated between 0.6-1.3% in 2007-2015. nTSH was significantly associated with laboratory performing the nTSH assay and age of heel prick sampling. The overall increasing trend in proportion nTSH >1mIU/L was confounded by the laboratories with different and changed assays. Conclusions The low proportion neonates with high nTSH suggests a sufficient iodine status in the Netherlands. Whether the increased proportion nTSH>1mIU/L over the years is an early indicator of deterioration of the iodine status remains unclear, due to differences and changes in analytical assays. nTSH might be a valuable and inexpensive way to get crude insight in the (trend in) iodine status, but more research is needed on the validity and potential conditions.

scholarly journals KIR and HLA-C: Immunogenetic regulation of human birth weight

2014 ◽  
Vol 24 (1-2) ◽  
Author(s):  
Lydia E. Farrell ◽  
Susan E. Hiby ◽  
Richard Apps ◽  
Olympe Chazara ◽  
Lill Trogstad ◽  
...  
Keyword(s):  
Birth Weight ◽  
Low Birth Weight ◽  
Gene Interactions ◽  
Stabilizing Selection ◽  
Immune Gene ◽  
Birth Registry ◽  
Immune Genes ◽  
Medical Birth Registry ◽  
Using Data ◽  
Human Birth

Pregnancies resulting in very small or very large babies are at higher risk of obstetric complications with increased morbidity for both mother and baby. Using data from the Medical Birth Registry of Norway we have shown how human birth weight is still subject to stabilizing selection. Particular combinations of maternal/fetal immune genes have been implicated in pregnancies resulting in a low birth weight baby (&lt;5th birth weight centile). More specifically, an inhibitory maternal <em>KIRAA</em> genotype with a paternally derived fetal <em>HLA-C2</em> ligand. At the other end of the birth weight spectrum the presence of an activating maternal <em>KIR2DS1</em> gene is associated with increased birth weight in linear or logistic regression analyses of all pregnancies &gt;5th centile (p=0.005, OR=2.65). Thus, inhibitory maternal <em>KIR</em> combined with fetal <em>HLA-C2</em> is more frequently associated with low birth weight, whereas activating maternal <em>KIR</em> with fetal <em>HLA-C2</em> ligand is associated with increasing birth weight. Our findings using the MoBa cohort have replicated the association of <em>KIR </em>and <em>HLA-C </em>seen in poor placentation, and confirm the importance of maternal/fetal immune gene interactions in determining the outcome of pregnancy.

scholarly journals Lower birth weight indicates higher risk of autistic traits in discordant twin pairs

2011 ◽  
Vol 42 (5) ◽  
pp. 1091-1102 ◽  
Author(s):  
M. Losh ◽  
D. Esserman ◽  
H. Anckarsäter ◽  
P. F. Sullivan ◽  
P. Lichtenstein
Keyword(s):  
Risk Factor ◽  
Birth Weight ◽  
Low Birth Weight ◽  
Developmental Disorders ◽  
Neurodevelopmental Disorder ◽  
Autistic Traits ◽  
Population Based ◽  
Autism Spectrum ◽  
Birth Registry ◽  
Discordant Twin

BackgroundAutism spectrum disorder (ASD) is a neurodevelopmental disorder of complex etiology. Although strong evidence supports the causal role of genetic factors, environmental risk factors have also been implicated. This study used a co-twin–control design to investigate low birth weight as a risk factor for ASD.MethodWe studied a population-based sample of 3715 same-sex twin pairs participating in the Child and Adolescent Twin Study of Sweden (CATSS). ASD was assessed using a structured parent interview for screening of ASD and related developmental disorders, based on DSM-IV criteria. Birth weight was obtained from medical birth records maintained by the Swedish Medical Birth Registry.ResultsTwins lower in birth weight in ASD-discordant twin pairs (n=34) were more than three times more likely to meet criteria for ASD than heavier twins [odds ratio (OR) 3.25]. Analyses of birth weight as a continuous risk factor showed a 13% reduction in risk of ASD for every 100 g increase in birth weight (n=78). Analysis of the effect of birth weight on ASD symptoms in the entire population (most of whom did not have ASD) showed a modest association. That is, for every 100 g increase in birth weight, a 2% decrease in severity of ASD indexed by scores on the Autism – Tics, attention-deficit hyperactivity disorder (AD/HD), and other Comorbidities (A-TAC) inventory would be expected in the sample as a whole.ConclusionsThe data were consistent with the hypothesis that low birth weight confers risk to ASD. Thus, although genetic effects are of major importance, a non-genetic influence associated with birth weight may contribute to the development of ASD.

scholarly journals Changing trends of birth weight with maternal age: a cross-sectional study in Xi'an city of Northwestern China

2020 ◽  
Author(s):  
Shanshan Wang ◽  
Liren Yang ◽  
Li Shang ◽  
Wenfang Yang ◽  
Cuifang Qi ◽  
...  
Keyword(s):  
Birth Weight ◽  
Low Birth Weight ◽  
Maternal Age ◽  
Additive Model ◽  
Cross Sectional Study ◽  
Birth Date ◽  
Childbearing Age ◽  
Birth Registry ◽  
Cross Sectional ◽  
Live Births

Abstract Background: Most studies have shown that maternal age is associated with birth weight. However, the specific relationship between each additional year of maternal age and birth weight remains unclear. The study aimed to analyze the specific association between maternal age and birth weight. Methods: Raw data for all live births from 2015 to 2018 were obtained from the Medical Birth Registry of Xi’an, China. A total of 490143 mother-child pairs with full-term singleton live births and the maternal age ranging from 20 to 40 years old were included in our study. Birth weight, gestational age, birth date of the newborns, maternal birth date, residence and ethnicity were collected. Generalized additive model and two-piece wise linear regression model were used to analyze the specific relationships between maternal age and birth weight, risk of low birth weight, and risk of macrosomia. Results: The relationships between maternal age and birth weight, risk of low birth weight, and risk of macrosomia were nonlinear. Birth weight increased 16.204 g per year when maternal age is less than 24 years old (95%CI: 14.323, 18.086), and increased 12.051g per year when maternal age ranged from 24 to 34 years old (95%CI: 11.609, 12.493), then decreased 0.824g per year (95% CI: -3.112, 1.464). The risk of low birth weight decreased with the increase of maternal age until 36 years old (OR= 0.917, 95%CI: 0.903, 0.932 when maternal age younger than 27 years old; OR= 0.965, 95%CI: 0.955, 0.976 when maternal age ranging from 27 to 36 years old), then increased when maternal age older than 36 years old (OR=1.133, 95%CI: 1.026, 1.250). The risk of macrosomia increased with the increase of maternal age (OR=1.102, 95%CI: 1.075, 1.129 when maternal age younger than 24 years old; OR=1.065, 95%CI: 1.060, 1.071 when maternal age ranged from 24 to 33 years old; OR=1.029, 95%CI: 1.012, 1.046 when maternal age older than 33 years old). Conclusions: For women of childbearing age (20-40 years old), the threshold of maternal age on low birth weight was 36 years old, and the risk of macrosomia increased with the increase of maternal age.

scholarly journals Changing trends of birth weight with maternal age: a cross-sectional study in Xi’an city of Northwestern China

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Shanshan Wang ◽  
Liren Yang ◽  
Li Shang ◽  
Wenfang Yang ◽  
Cuifang Qi ◽  
...  
Keyword(s):  
Birth Weight ◽  
Low Birth Weight ◽  
Maternal Age ◽  
Additive Model ◽  
Cross Sectional Study ◽  
Birth Date ◽  
Childbearing Age ◽  
Birth Registry ◽  
Cross Sectional ◽  
Live Births

Abstract Background Most studies have shown that maternal age is associated with birth weight. However, the specific relationship between each additional year of maternal age and birth weight remains unclear. The study aimed to analyze the specific association between maternal age and birth weight. Methods Raw data for all live births from 2015 to 2018 were obtained from the Medical Birth Registry of Xi’an, China. A total of 490,143 mother-child pairs with full-term singleton live births and the maternal age ranging from 20 to 40 years old were included in our study. Birth weight, gestational age, neonatal birth date, maternal birth date, residence and ethnicity were collected. Generalized additive model and two-piece wise linear regression model were used to analyze the specific relationships between maternal age and birth weight, risk of low birth weight, and risk of macrosomia. Results The relationships between maternal age and birth weight, risk of low birth weight, and risk of macrosomia were nonlinear. Birth weight increased 16.204 g per year when maternal age was less than 24 years old (95%CI: 14.323, 18.086), and increased 12.051 g per year when maternal age ranged from 24 to 34 years old (95%CI: 11.609, 12.493), then decreased 0.824 g per year (95% CI: -3.112, 1.464). The risk of low birth weight decreased with the increase of maternal age until 36 years old (OR = 0.917, 95%CI: 0.903, 0.932 when maternal age was younger than 27 years old; OR = 0.965, 95%CI: 0.955, 0.976 when maternal age ranged from 27 to 36 years old), then increased when maternal age was older than 36 years old (OR = 1.133, 95%CI: 1.026, 1.250). The risk of macrosomia increased with the increase of maternal age (OR = 1.102, 95%CI: 1.075, 1.129 when maternal age was younger than 24 years old; OR = 1.065, 95%CI: 1.060, 1.071 when maternal age ranged from 24 to 33 years old; OR = 1.029, 95%CI: 1.012, 1.046 when maternal age was older than 33 years old). Conclusions For women of childbearing age (20–40 years old), the threshold of maternal age on low birth weight was 36 years old, and the risk of macrosomia increased with the increase of maternal age.

scholarly journals Changing trends of birth weight with maternal age: a cross-sectional study in Xi'an city of Northwestern China

2020 ◽  
Author(s):  
Shanshan Wang ◽  
Liren Yang ◽  
Li Shang ◽  
Wenfang Yang ◽  
Cuifang Qi ◽  
...  
Keyword(s):  
Birth Weight ◽  
Low Birth Weight ◽  
Maternal Age ◽  
Additive Model ◽  
Cross Sectional Study ◽  
Birth Date ◽  
Childbearing Age ◽  
Birth Registry ◽  
Cross Sectional ◽  
Specific Association

Abstract Background Most studies have shown that maternal age was associated with birth weight. However, specific relationships between each additional year of maternal age and birth weight remain unclear. The study aimed to analyze the specific association between maternal age at birth and birth weight. Methods Raw data for all live births from 2015 to 2018 was obtained from the Medical Birth Registry of Xi’an, China. 490143 mother-child pairs with full-term singleton live birth and the maternal age ranged from 20 to 40 years old were included in our study. Birth weight, gestational age, the birth date of the newborns, maternal birth date, residence, and ethnicity were collected. Generalized additive model and two-piece wise linear regression model were used to analyze the specific relationship between maternal age and birth weight, risk of low birth weight, and risk of macrosomia. Results The relationships between maternal age and birth weight, risk of low birth weight, and risk of macrosomia were nonlinear. Birth weight increased 16.204 g per year before age 24(95%CI: 14.323, 18.086), and increased 12.051g per year when maternal age ranged from 24 to 34(95%CI: 11.609, 12.493), then decreased 0.824g per year (95% CI: -3.112, 1.464). The risk of low birth weight decreased until age 36(OR= 0.917, 95%CI: 0.903, 0.932 for maternal age younger than 27; OR= 0.965, 95%CI: 0.955, 0.976 for maternal age ranged from 27 to 36), then increased (OR= 1.133, 95%CI: 1.026, 1.250). The risk of macrosomia increased with the increase of maternal age (OR=1.102, 95%CI: 1.075, 1.129 for maternal age younger than 24; OR=1.065, 95%CI: 1.060, 1.071 for maternal age ranged from 24 to 33; OR= 1.029, 95%CI: 1.012, 1.046 for maternal age older than 33). Conclusions For women of childbearing age (20-40 years old), the threshold maternal age for low birth weight was 36 years old, and the risk of macrosomia increased with the increase of maternal age.

scholarly journals Changing trends of birth weight with maternal age: a cross-sectional study in Xi'an city of Northwestern China

2020 ◽  
Author(s):  
Shanshan Wang ◽  
Liren Yang ◽  
Li Shang ◽  
Wenfang Yang ◽  
Cuifang Qi ◽  
...  
Keyword(s):  
Birth Weight ◽  
Low Birth Weight ◽  
Maternal Age ◽  
Additive Model ◽  
Cross Sectional Study ◽  
Birth Date ◽  
Childbearing Age ◽  
Birth Registry ◽  
Cross Sectional ◽  
Live Births

Abstract Background: Most studies have shown that maternal age is associated with birth weight. However, the specific relationship between each additional year of maternal age and birth weight remains unclear. The study aimed to analyze the specific association between maternal age and birth weight.Methods: Raw data for all live births from 2015 to 2018 were obtained from the Medical Birth Registry of Xi’an, China. A total of 490143 mother-child pairs with full-term singleton live births and the maternal age ranging from 20 to 40 years old were included in our study. Birth weight, gestational age, neonatal birth date, maternal birth date, residence and ethnicity were collected. Generalized additive model and two-piece wise linear regression model were used to analyze the specific relationships between maternal age and birth weight, risk of low birth weight, and risk of macrosomia.Results: The relationships between maternal age and birth weight, risk of low birth weight, and risk of macrosomia were nonlinear. Birth weight increased 16.204 g per year when maternal age was less than 24 years old (95%CI: 14.323, 18.086), and increased 12.051g per year when maternal age ranged from 24 to 34 years old (95%CI: 11.609, 12.493), then decreased 0.824g per year (95% CI: -3.112, 1.464). The risk of low birth weight decreased with the increase of maternal age until 36 years old (OR= 0.917, 95%CI: 0.903, 0.932 when maternal age was younger than 27 years old; OR= 0.965, 95%CI: 0.955, 0.976 when maternal age ranged from 27 to 36 years old), then increased when maternal age was older than 36 years old (OR=1.133, 95%CI: 1.026, 1.250). The risk of macrosomia increased with the increase of maternal age (OR=1.102, 95%CI: 1.075, 1.129 when maternal age was younger than 24 years old; OR=1.065, 95%CI: 1.060, 1.071 when maternal age ranged from 24 to 33 years old; OR=1.029, 95%CI: 1.012, 1.046 when maternal age was older than 33 years old).Conclusions: For women of childbearing age (20-40 years old), the threshold of maternal age on low birth weight was 36 years old, and the risk of macrosomia increased with the increase of maternal age.

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