Sentences with phrase «by maternal weight»

And the effects were not explained by maternal weight, diet, total calories consumed or other obesity risk factors, she added.

Not exact matches

The researchers note that avocados are unique among fruits and vegetables in that, by weight, they contain much higher amounts of the key nutrients folate and potassium, which are normally under - consumed in maternal diets.

Let's aim to have your maternal stores consumed by your body if you want to get back to your pre-pregnancy weight.

Maternal deprivation is a term used to describe a situation in which a child does not receive an adequate amount of consistent care as an infant and is believed to be one of the causes of failure to thrive, which is characterized by failure to gain weight and to achieve developmental milestones.

Mean and standard errors of monthly weight gain after adjusting for maternal age; race / ethnicity; education; household income; marital status; parity; postpartum Special Supplemental Nutrition Program for Women, Infants, and Children program participation; prepregnancy body mass index (calculated as weight in kilograms divided by height in meters squared); infant sex; gestational age; birth weight; age at solid food introduction; and sweet drinks consumption.

Descriptive data (eg, maternal age, ethnicity, parity, and infant birth weight) and information on SIDS risk factors (eg, history of maternal smoking during pregnancy) were collected by interview at the time of enrollment.

Descriptive statistics were reported for maternal demographic, social, and obstetric characteristics by maternity unit Baby Friendly status with a comparison of percentages, weighted for design effect (F statistic27 significance P ≤ 0.05).

Postnatal weight gain was taken from pediatric records, and the frequency of side effects was measured by maternal response to the interview questionnaire.

Data set forth by Taddio et al, 7 estimating that < 10 % of the maternal dose of fluoxetine is transferred to the nursing infant on a weight - adjusted basis, argue against that explanation.

Most studies addressed the issue of confounding by restricting the sample to low risk pregnancies and demonstrating that the two groups had similar maternal and gestational age, some demonstrated similar birth weights.

Although we could not find estimates of fan use in the US population, we examined the potential selection bias by evaluating characteristics associated with SIDS risks in study participants and nonparticipants in a previously published article.16 Using California birth certificate data, we compared the ORs for maternal age, maternal education, parity, birth weight, infant sex, and late initiation of prenatal care (> 5 months» gestation).

Other factors that negatively influence the likelihood of VBAC include increasing maternal age, high body mass index (BMI, calculated as weight in kilograms divided by height in meters squared), high birth weight, and advanced gestational age at delivery (more than 40 weeks)(45, 49 — 55).

This visit should include infant weight; physical examination, especially for jaundice and hydration; maternal history of breast problems (painful feedings, engorgement); infant elimination patterns (expect 3 — 5 urines and 3 — 4 stools per day by 3 — 5 days of age; 4 — 6 urines and 3 — 6 stools per day by 5 — 7 days of age); and a formal, observed evaluation of breastfeeding, including position, latch, and milk transfer.

Maternal and infant scales were checked for accuracy before each home visit by using standard weights.

Prevalence (± SE) of excess neonatal weight loss (weight loss > 10 % of birth weight; restricted to infants consuming < 60 mL of formula over the first 72 h; n = 218 with BMI data) by timing of onset of lactogenesis (OL), stratified by maternal BMI group.

We found little evidence that between - study heterogeneity in estimates was explained by age at measurement of blood pressure (p = 0.5), decade of birth (p = 0.2), stipulation of a minimum duration of breastfeeding (p = 0.5), proportion of the target population in the main analysis (p = 0.2), whether breastfeeding was exclusive for at least 2 months (p = 0.2), method of blood pressure measurement (p = 0.4), or whether effect estimates controlled for socioeconomic factors (p = 0.9), maternal factors in pregnancy (p = 0.9), or current weight (p = 0.9).

The low birth - weight advantage held up across the board for all children — regardless of race, socioeconomic status, enrichment experiences provided by parents, maternal education and a host of other factors.

«It will be valuable to learn whether improvements in earnings by families with pregnant women, improved maternal nutrition or reduced maternal stress — all factors associated with higher birth weight — also translate to better cognitive outcomes in childhood,» said Figlio, IPR faculty fellow and Orrington Lunt Professor of Education and Social Policy and of Economics at Northwestern's School of Education and Social Policy.

While the biological mechanism by which exposure to pollution causes lower birth weights are not fully understood, the scientists speculate that several factors could play a role, including maternal inflammation, altered placental function, and reduced nutrient delivery to the fetus, which may impede fetal growth.

But we show that the babies are not affected by physical activity or dieting, and that there are additional benefits including a reduction in maternal weight gain, diabetes in pregnancy, and the risk of requiring a caesarean section.

Iron supplementation resulted in an increased birth weight [5.3 ounces], gestational duration, and neonatal length; enhanced maternal and infant iron stores at 1 month after birth; and a decreased risk of low birth weight (by 58 percent) and prematurity.

Further analysis indicated that for every 10 mg increase in iron dose per day (up to 66 mg per day), risk of maternal anemia was 12 % lower, birth weight increased by 15 g and risk of low birth weight decreased by 3 %.

A new study of 513,501 mothers and 1,164,750 of their children born across 15 years aimed to take genetics out of the equation by assessing maternal and infant weight only for those women who had more than one child.

The association between maternal obesity and offspring chronic conditions may be driven by the association between maternal weight and child weight.

Covariates included the child's sex, calendar conception year (categorical variable), gestational age, maternal prepregnancy body mass index (BMI, calculated as weight in kilograms divided by height in meters squared)(BMI < 18.5 = underweight; 18.5 ≤ BMI < 25 = normal weight; 25 ≤ BMI < 30 = overweight; BMI ≥ 30 = obese), maternal age at delivery (younger than 20, 20 to 24, 25 to 29, 30 to 34, and ≥ 35 years), maternal education at delivery (≤ high school graduate, some college education, college graduate, postgraduate, or unknown), maternal race / ethnicity (Asian, black, white, or other), and gestational diabetes (yes / no).

Even maternal use of antibiotics during pregnancy leads to childhood weight gain, perhaps by permanently altering a baby's metabolism and microbiome.

You'd think a proven, previously - awarded commodity bearing the full weight of a ginormous one - woman show, weaving in and out of hangovers and maternal instincts for well over two hours, would delight both the Oscar voters who slipped Gena Rowlands into the 1980 lineup for Gloria (to which director Erick Zonca's gutsy melodrama is obviously indebted) as well as the voters who have actually seen a film by Derek Jarman.

The association between maternal obesity and offspring chronic conditions may be driven by the association between maternal weight and child weight.

This association was partially explained by maternal factors such as maternal BMI, smoking during pregnancy, and marital status and by child factors including television viewing, birth weight, and bottle feeding (data not shown but available on request).

Maternal body mass index (BMI) was calculated from self - reported height and weight measurements (weight in kilograms divided by height in meters squared).

These included characteristics on multiple levels of the child's biopsychosocial context: (1) child factors: race / ethnicity (white, black, Hispanic, and Asian / Pacific Islander / Alaska Native), age, gender, 9 - month Bayley Mental and Motor scores, birth weight (normal, moderately low, or very low), parent - rated child health (fair / poor vs good / very good / excellent), and hours per week in child care; (2) parent factors: maternal age, paternal age, SES (an ECLS - B — derived variable that includes maternal and paternal education, employment status, and income), maternal marital status (married, never married, separated / divorced / widowed), maternal general health (fair / poor versus good / very good / excellent), maternal depression (assessed by the Center for Epidemiologic Studies Depression Scale at 9 months and the World Mental Health Composite International Diagnostic Interview at 2 years), prenatal use of tobacco and alcohol (any vs none), and violence against the mother; (3) household factors: single - parent household, number of siblings (0, 1, 2, or 3 +), language spoken at home (English vs non-English), neighborhood good for raising kids (excellent / very good, good, or fair / poor), household urbanicity (urban city, urban county, or rural), and modified Home Observation for Measurement of the Environment — Short Form (HOME - SF) score.

Maternal obesity was assessed by self - report rather than measured height and weight.

This result confirms the role of familial obesity10, — , 12 and corresponds with the finding by Favaro and Santonastaso, 19 who showed that maternal neuroticism was associated with weight loss in children on a prescribed diet.

A covariate was included in the multivariate analyses if theoretical or empirical evidence supported its role as a risk factor for obesity, if it was a significant predictor of obesity in univariate regression models, or if including it in the full multivariate model led to a 5 % or greater change in the OR.48 Model 1 includes maternal IPV exposure, race / ethnicity (black, white, Hispanic, other / unknown), child sex (male, female), maternal age (20 - 25, 26 - 28, 29 - 33, 34 - 50 years), maternal education (less than high school, high school graduation, beyond high school), maternal nativity (US born, yes or no), child age in months, relationship with father (yes or no), maternal smoking during pregnancy (yes or no), maternal depression (as measured by a CIDI - SF cutoff score ≥ 0.5), maternal BMI (normal / underweight, overweight, obese), low birth weight (< 2500 g, ≥ 2500 g), whether the child takes a bottle to bed at age 3 years (yes or no), and average hours of child television viewing per day at age 3 years (< 2 h / d, ≥ 2 h / d).

However, it is important to be aware that these correlations could also be explained by third factor common to both variables, such as maternal concern about child weight status.

Maternal body mass index was calculated from self - reported height and weight measurements (weight in kilograms divided by height in meters squared).

Logistic regression analyses were conducted to estimate the effect of maternal IPV on asthma diagnosed by age 36 months while adjusting for potential confounders (child's sex, age, race / ethnicity, low birth weight, maternal education, economic hardship, and tobacco exposure).

Some mothers responses may have been influenced by their perceptions of the «right» behaviour with regards to feeding their children, and social desirability with regards to maternal and child weight status.

RESULTS: Hierarchical regression analyses revealed that long - term success (at least 5 % weight reduction by the 1 - year follow - up) versus failure (dropping out or less weight reduction) was significantly predicted by the set of psychosocial variables (family adversity, maternal depression, and attachment insecurity) when we controlled for familial obesity, preintervention overweight, age, and gender of the index child and parental educational level.

Regarding the child, the importance of the intrauterine and early postnatal environments for metabolic programming and modifications of the epigenome is increasingly recognised, 12 — 14 particularly for metabolic diseases such as obesity and diabetes.15 Thus, GDM is related to macrosomia at birth (> 4 kg), to excess body fat and (central) obesity and to insulin secretion in infants and children, the obesity being in part mediated by maternal body mass index (BMI) or birth weight.16 — 23 Intrauterine exposure to GDM also doubles the risk for subsequent type 2 diabetes in offspring compared with offspring of mothers with a high genetic predisposition for type 2 diabetes, but with normal glucose tolerance during the index pregnancy.24 Maternal prepregnancy overweight and excessive gestational weight gain also predict high birth weight and adiposity during infancy.12 25 This is highly relevant, as up to 60 % — 70 % of women with GDM are overweight or obese before pregnancy.26 Finally, maternal lifestyle behaviour such as a high fat diet or lack of physical activity during pregnancy can influence offspring adiposity independent of maternal obesimaternal body mass index (BMI) or birth weight.16 — 23 Intrauterine exposure to GDM also doubles the risk for subsequent type 2 diabetes in offspring compared with offspring of mothers with a high genetic predisposition for type 2 diabetes, but with normal glucose tolerance during the index pregnancy.24 Maternal prepregnancy overweight and excessive gestational weight gain also predict high birth weight and adiposity during infancy.12 25 This is highly relevant, as up to 60 % — 70 % of women with GDM are overweight or obese before pregnancy.26 Finally, maternal lifestyle behaviour such as a high fat diet or lack of physical activity during pregnancy can influence offspring adiposity independent of maternal obesiMaternal prepregnancy overweight and excessive gestational weight gain also predict high birth weight and adiposity during infancy.12 25 This is highly relevant, as up to 60 % — 70 % of women with GDM are overweight or obese before pregnancy.26 Finally, maternal lifestyle behaviour such as a high fat diet or lack of physical activity during pregnancy can influence offspring adiposity independent of maternal obesimaternal lifestyle behaviour such as a high fat diet or lack of physical activity during pregnancy can influence offspring adiposity independent of maternal obesimaternal obesity.12 27

Since 1981, the few studies that have evaluated maternal feeding style by direct observation in association with child weight status have included a total of only ∼ 200 child participants, and > 80 % of these participants have been white (3, 4, 10, 18, 28, 29).

We used an imputed variable for household income provided by the FFCWS given the degree of missing data (∼ 10 %).12 Supplementary models included birth weight, maternal report of the child's health status, and the number of siblings as covariates.

In a recent study of fetal scans, researchers found that when mothers are stressed out, their fetuses also show signs of distress.1 And in a separate study of nearly 8,000 pregnant women, researchers noted that moms with high anxiety and depression are at greater risk of adverse birth outcomes, such as low birth weight.2 These studies highlight the importance of identifying and alleviating prenatal maternal stress, a conclusion supported by CFRP data.

Other variables (maternal parity, housing stability, hospitalization, perceived health status, employment, use of the Women, Infants, and Children Supplemental Nutrition Program, and cigarette smoking; whether the mother was living with a partner; and infant gestational age, birth weight, need for transfer to an intensive care nursery, health insurance, special needs, health status as perceived by the mother, and age at the time of the survey) were included if the adjusted odds ratio differed from the crude odds ratio by at least 10 %, which is a well - accepted method of confounder selection when the decision of whether to adjust is unclear.42, 43 Any variable associated with both the predictor (depression) and the outcome (infant health services use, parenting practices, or injury - prevention measures) at P <.25, as suggested by Mickey and Greenland, 42 was also included.

For example, death rates among Aboriginal people from pneumonia have dropped by 40 per cent since 1996, following the roll - out of pneumococcal vaccinations, The «Strong Babies, Strong Culture» maternal health program has shown that significant reductions in the number of low birth weight babies can occur within a matter of years.