Low Birth Weight

Background: This case-control study aimed to assess the prevalence of symptoms and risk of obstructive sleep apnea (OSA) among Saudi pregnant women.
Methods: The study included consecutive Saudi pregnant women attending the antenatal service between July 2015 and December 2016. Pregnant women were compared with an age-matched group of non-pregnant women. OSA symptoms and risk were assessed using a validated Arabic version of the Berlin questionnaire (BQ).
Results: The study included 742 pregnant women and 742 age-matched non-pregnant women. At the time of the survey, 8.2% were in the first trimester; 33.4% in the second trimester; and 58.4%in third trimester. Snoring was reported by 14% of pregnant women and 5% reported breathing pauses during sleep. Based on the BQ stratification for risk of OSA, 19.3% of pregnant women and 16.6% of the control group were at high risk for OSA. A comparison between the high OSA-risk and low OSA-risk pregnant women revealed that the pregnant women in high risk group were older (30.9±5.9 years vs. 29±5.4 years, p=0.001), had a higher body mass index (BMI) (34.3±5.2 kg/m2 vs. 28.7±5.8 kg/m2, p<0.001), and higher parity (1.9±2 vs. 1.5±1.7, p=0.020). A multivariate logistic regression analysis revealed the following independent variables, BMI (OR 1.173 [95% CI 1.129 - 1.219], p<0.001), PIH (OR 7.85 [95% CI 1.691 - 36.447], p=0.013) and presence of RLS (OR 2.209 [95% CI 1.332 - 3.279], p<0.001).
Conclusions: OSA symptoms and risk were relatively common among Saudi pregnant women. Increasing the awareness among physicians about this association is essential to improve early detection of the disorder.

Objective Measurement of plasma methadone concentration to investigate the rate of clearance of methadone prescribed for heroin dependence in the first, second and third trimesters of pregnancy. A secondary objective was to evaluate the outcome of pregnancy. Methods Longitudinal within subject study of nine pregnant opioid dependent subjects prescribed methadone at the Leeds Addiction Unit, an outpatient community based treatment centre. Plasma concentration versus time data for methadone was collected during each trimester and post-partum for our subjects. Data was available for the first and second trimesters for 4/9 cases. All but one of the subjects provided data during the third trimester and data post-partum was collected from three respondents. Measurements of methadone levels in plasma were carried out using high performance liquid chromatography (HPLC). Results Trough mean plasma methadone concentrations reduced as the pregnancies progressed from 0.12 mg/L (first trimester) to 0.07 mg/L (third trimester). The weight-adjusted clearance rates gradually increased from a mean of 0.17 to 0.21 L/hr/kg during pregnancy, although patterns differed substantially between the nine women. An assessment of relative clearance of methadone using two patients for whom we have had all three CL values (trimester 1–3) demonstrated notable change of CL (P=0.056) over time. Eight of our subjects delivered (3 males), within two weeks of their due date the ninth (male) was premature (21 days). The mean length of gestation was 39.7 weeks (SD=10 days) and none of the neonates met criterion for ‘low birth weight’ mean 3094, SD 368 g). Five neonates spent time (0.5–28 days) in a special care baby unit (SCUBU) and 4 of these displayed signs of methadone withdrawal. Conclusions General Practitioners and hospital doctors should recognise the significant benefits of prescribing methadone for heroin-dependent women during pregnancy. We recommend that if a pregnant opioid user complains of methadone withdrawal symptoms (i.e. that the methadone dose does not “hold” them) the prescribing clinician takes this observation seriously and considers a more detailed assessment. Further work on key factors undergoing changes during pregnancy accounting for differences in methadone metabolism in the mother, fetus and neonate are required.

Hunger, with its adverse consequences for children, continues to be an important national problem. Previous studies that document the deleterious effects of hunger among children cannot distinguish child from family hunger and do not take into account some critical environmental, maternal, and child variables that may influence child outcomes. This study examines the independent contribution of child hunger on children&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;s physical and mental health and academic functioning, when controlling for a range of environmental, maternal, and child factors that have also been associated with poor outcomes among children. With the use of standardized tools, comprehensive demographic, psychosocial, and health data were collected in Worcester, Massachusetts, from homeless and low-income housed mothers and their children (180 preschool-aged children and 228 school-aged children). Mothers and children were part of a larger unmatched case-control study of homelessness among female-headed households. Hunger was measured by a set of 7 dichotomous items, each asking the mother whether she has or her children have experienced a particular aspect of hunger during the past year--1 concerns food insecurity for the entire family, 2 concern adult hunger, and 4 involve child hunger. The items, taken from the Childhood Hunger Identification Project measure, are summed to classify the family and divided into 3 categories: no hunger, adult or moderate child hunger, or severe child hunger (indicating multiple signs of child hunger). Outcome measures included children&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;s chronic health condition count using questions adapted from the National Health Interview Survey, Child Health Supplement, and internalizing behavior problems and anxiety/depression, measured by the Child Behavior Checklist. Additional covariates included demographic variables (ie, age, gender, ethnicity, housing status, number of moves, family size, income), low birth weight, child life events (ie, care and protection order, out of home placement, abuse, severe life events count), developmental problems (ie, developmental delay, learning disability, emotional problems), and mother&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;s distress and psychiatric illness. Multivariate regression analyses examined the effect of child hunger on physical and mental health outcomes. The average family size for both preschoolers and school-aged children was 3; about one third of both groups were white and 40% Puerto Rican. The average income of families was approximately $11 000. Among the school-aged children, on average 10 years old, 50% experienced moderate child hunger and 16% severe child hunger. Compared with those with no hunger, school-aged children with severe hunger were more likely to be homeless (56% vs 29%), have low birth weights (23% vs 6%), and have more stressful life events (9 vs 6) when compared with those with no hunger. School-aged children with severe hunger scores had parent-reported anxiety scores that were more than double the scores for children with no hunger and significantly higher chronic illness counts (3.4 vs 1.8) and internalizing behavior problems when compared with children with no hunger. There was no relationship between hunger and academic achievement. Among preschool-aged children, who averaged 4 years of age, 51% experienced moderate child hunger and 8% severe child hunger. For preschoolers, compared with children with no hunger, severe hunger was associated with homelessness (75% vs 48%), more traumatic life events (8.5 vs 6), low birth weight (23% vs 6%), and higher levels of chronic illness and internalizing behavior problems. Mothers of both preschoolers and school-aged children who reported severe hunger were more likely to have a lifetime diagnosis of posttraumatic stress disorder. For school-aged children, severe hunger was a significant predictor of chronic illness after controlling for housing status, mother&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;s distress, low birth weight, and child live events. For preschoolers, moderate hunger was a significant predictor of health conditions while controlling for potenns while controlling for potential explanatory factors. For both preschoolers and school-aged children, severe child hunger was associated with higher levels of internalizing behavior problems. After controlling for housing status,…

Machine learning (ML) is a subject that focuses on the data analysis using various statistical tools and learning processes in order to gain more knowledge from the data. The objective of this research was to apply one of the ML techniques on the low birth weight (LBW) data in Indonesia. This research conducts two ML tasks, including prediction and classification. The binary logistic regression model was firstly employed on the train and the test data. Then, the random approach was also applied to the data set. The results showed that the binary logistic regression had a good performance for prediction , but it was a poor approach for classification. On the other hand, random forest approach has a very good performance for both prediction and classification of the LBW data set.