Maternal diet in early and late pregnancy in relation to weight gain

To access Publisher full text version of this article. Please click on the hyperlink in Additional Links fieldOBJECTIVE: To identify dietary factors related to the risk of gaining weight outside recommendations for pregnancy weight gain and birth outcome.Design:An observational study with free-living conditions.Subjects:Four hundred and ninety five healthy pregnant Icelandic women. METHODS: The dietary intake of the women was estimated with a semiquantitative food frequency questionnaire covering food intake together with lifestyle factors for the previous 3 months. Questionnaires were filled out at between 11 and 15 weeks and between 34 and 37 weeks gestation. Comparison of birth outcome between the three weight gain groups was made with ANOVA and Bonferroni post hoc tests. Dietary factors related to at least optimal and excessive weight gain during pregnancy were represented with logistic regression controlling for potential confounding. RESULTS: Of the women, 26% gained suboptimal and 34% excessive weight during pregnancy. Women in late pregnancy with at least optimal, compared with women with suboptimal, weight gain were eating more (OR = 3.32, confidence interval (CI)=1.81-6.09, P < 0.001) and drinking more milk (OR = 3.10, CI = 1.57-6.13, P = 0.001). The same dietary factors were related to excessive, compared with optimal, weight gain. Furthermore, eating more sweets early in pregnancy increased the risk of gaining excessive weight (OR=2.52, CI=1.10-5.77, P=0.029). Women with a body mass index of 25.0-29.9 kg/m(2) before pregnancy were most likely to gain excessive weight (OR = 7.37, CI 4.13-13.14, P < 0.001). Women gaining suboptimal weight gave birth to lighter children (P < 0.001) and had shorter gestation (P = 0.008) than women gaining optimal or excessive weight. CONCLUSION: Women who are overweight before pregnancy should get special attention regarding lifestyle modifications affecting consequent weight gain during pregnancy. They are most likely to gain excessive weight and therefore most likely to suffer pregnancy and delivery complications and struggle with increasing overweight and obesity after giving birth

SciKit-SurgeryGlenoid, an Open Source Toolkit for Glenoid Version Measurement

Correct understanding of the geometry of the glenoid (the socket of the shoulder joint) is key to successful planning of shoulder replacement surgery. This surgery typically involves placing an implant in the shoulder joint to restore joint function. The most relevant geometry is the glenoid version, which is the angular orientation of the glenoid surface relative to the long axis of the scapula in the axial plane. However, measuring the glenoid version is not straightforward and there are multiple measurement methods in the literature and used in commercial planning software. In this paper we introduce SciKit-SurgeryGlenoid, an open source toolkit for the measurement of glenoid version. SciKit-SurgeryGlenoid contains implementations of the 4 most frequently used glenoid version measurement algorithms enabling easy and unbiased comparison of the different techniques. We present the results of using the software on 10 sets of pre-operative CT scans taken from patients who have subsequently undergone shoulder replacement surgery. We further compare these results with those obtained from a commercial implant planning software. SciKit-SurgeryGlenoid currently requires manual segmentation of the relevant anatomical features for each method. Future work will look at automating the segmentation process to build an automatic and repeatable pipeline from CT or radiograph to quantitative glenoid version measurement

Individual risk assessment and information technology to optimise screening frequency for diabetic retinopathy.

To access publisher full text version of this article. Please click on the hyperlink in Additional Links field.AIMS/HYPOTHESIS: The aim of this study was to reduce the frequency of diabetic eye-screening visits, while maintaining safety, by using information technology and individualised risk assessment to determine screening intervals. METHODS: A mathematical algorithm was created based on epidemiological data on risk factors for diabetic retinopathy. Through a website, www.risk.is , the algorithm receives clinical data, including type and duration of diabetes, HbA(1c) or mean blood glucose, blood pressure and the presence and grade of retinopathy. These data are used to calculate risk for sight-threatening retinopathy for each individual's worse eye over time. A risk margin is defined and the algorithm recommends the screening interval for each patient with standardised risk of developing sight-threatening retinopathy (STR) within the screening interval. We set the risk margin so that the same number of patients develop STR within the screening interval with either fixed annual screening or our individualised screening system. The database for diabetic retinopathy at the Department of Ophthalmology, Aarhus University Hospital, Denmark, was used to empirically test the efficacy of the algorithm. Clinical data exist for 5,199 patients for 20 years and this allows testing of the algorithm in a prospective manner. RESULTS: In the Danish diabetes database, the algorithm recommends screening intervals ranging from 6 to 60 months with a mean of 29 months. This is 59% fewer visits than with fixed annual screening. This amounts to 41 annual visits per 100 patients. CONCLUSION: Information technology based on epidemiological data may facilitate individualised determination of screening intervals for diabetic eye disease. Empirical testing suggests that this approach may be less expensive than conventional annual screening, while not compromising safety. The algorithm determines individual risk and the screening interval is individually determined based on each person's risk profile. The algorithm has potential to save on healthcare resources and patients' working hours by reducing the number of screening visits for an ever increasing number of diabetic patients in the world

The interaction of adiposity with the CRP gene affects CRP levels: age, gene/environment susceptibilty-Reykjavik study

To access publisher full text version of this article. Please click on the hyperlink in Additional Links fieldOBJECTIVE: Common diseases often have an inflammatory component reflected by associated markers such as serum C-reactive protein (CRP) levels. Circulating CRP levels have also been associated with adipose tissue as well as with specific CRP genotypes. We examined the interaction between measures of body mass index (BMI), waist circumference and fat percent (total fat measured by bioimpedance) with genotypes of the CRP gene in the determination of CRP levels. METHODS: The first 2296 participants (mean age 76+/-6 years, 42% men) in the Age, Gene/Environment Susceptibility-Reykjavik Study, a multidisciplinary epidemiological study to determine risk factors in aging, were genotyped for 10 single nucleotide polymorphisms (SNPs) in the CRP gene. General linear models with age and terms for interaction of CRP genotypes with BMI, waist circumference and percent fat were used to evaluate the association of genotypes to CRP levels (high-sensitivity method, range 0-10 mg l(-1)) in men and women separately. RESULTS: We focused on the SNP rs1205 that represents the allele that captures the strongest effects of the gene on CRP levels. Carriers of the rs1205 G allele had significantly higher CRP levels than noncarriers in a dose-dependent manner. Compared to the AA genotype, the slope of the increase in CRP with increasing BMI (P=0.045) and waist circumference (P=0.014) was different for the G allele carriers and of similar magnitude in both men and women. The rs1205 interactions were not significant for fat mass percent, suggesting a possible association with fat localization. CONCLUSIONS: This study further illuminates the known association between measures of adiposity and CRP levels and is shown to be dependent on variation in the rs1205 SNP of the CRP gene. The correlated increase in CRP levels with adiposity is accentuated by presence of the G allele

Glycemic status and brain injury in older individuals: the age gene/environment susceptibility-Reykjavik study

To access publisher full text version of this article. Please click on the hyperlink in Additional Links fieldOBJECTIVE: To examine the association of glycemic status to magnetic resonance imaging indicators of brain pathological changes. RESEARCH DESIGN AND METHODS: This was a cross-sectional, population-based study of 4,415 men and women without dementia (mean age 76 years) participating in the Age Gene/Environment Susceptibility-Reykjavik Study. Glycemic status groups included the following: type 2 diabetes (self-report of diabetes, use of diabetes medications, or fasting blood glucose > or =7.0 mmol/l [11.1%]); impaired fasting glucose (IFG) (fasting blood glucose 5.6-6.9 mmol/l [36.2%]); and normoglycemic (52.7%). Outcomes were total brain volume, white and gray matter volume, white matter lesion (WML) volume, and presence of cerebral infarcts. RESULTS: After adjustment for demographic and cardiovascular risk factors, participants with type 2 diabetes had significantly lower total brain volume (72.2 vs. 71.5%; P < 0.001) and lower gray and white matter volumes (45.1 vs. 44.9%, P < 0.01 and 25.7 vs. 25.3%, P < 0.001, respectively) and were more likely to have single (odds ratio 1.45 [95% CI 1.14-1.85]) or multiple (2.27 [1.60-3.23]) cerebral infarcts compared with normoglycemic participants. Longer duration of type 2 diabetes was associated with lower total brain volume and gray and white matter volume, higher WML volume (all P(trend) < 0.05), and a greater likelihood of single and multiple cerebral infarcts (all P(trend) < 0.01). CONCLUSIONS: Type 2 diabetic participants have more pronounced brain atrophy and are more likely to have cerebral infarcts. Duration of type 2 diabetes is associated with brain changes, suggesting that type 2 diabetes has a cumulative effect on the brain

Rate of Iceland Sea acidification from time series measurements

The Iceland Sea is one part of the Nordic Seas. Cold Arctic Water prevails there and the deep-water is an important source of North Atlantic Deep Water. We have evaluated time series observations of measured &lt;i&gt;p&lt;/i&gt;CO&lt;sub&gt;2&lt;/sub&gt; and total CO&lt;sub&gt;2&lt;/sub&gt; concentration from discrete seawater samples during 1985–2008 for the surface and 1994–2008 for deep-water, and following changes in response to increasing atmospheric carbon dioxide. The surface pH in winter decreases at a rate of 0.0024 yr&lt;sup&gt;&amp;minus;1&lt;/sup&gt;, which is 50% faster than average yearly rates at two subtropical time series stations, BATS and ESTOC. In the deep-water regime (&amp;gt;1500 m), the rate of pH decline is a quarter of that observed in surface waters. The surface seawater carbonate saturation states (Ω) are about 1.5 for aragonite and 2.5 for calcite, about half of levels found in subtropical surface waters. During 1985–2008, the degree of saturation (Ω) decreased at an average rate of 0.0072 yr&lt;sup&gt;&amp;minus;1&lt;/sup&gt; for aragonite and 0.012 yr&lt;sup&gt;&amp;minus;1&lt;/sup&gt; for calcite. The aragonite saturation horizon is currently at 1710 m and shoaling at 4 m yr&lt;sup&gt;&amp;minus;1&lt;/sup&gt;. Based on this rate of shoaling and on the local hypsography, each year another 800 km&lt;sup&gt;2&lt;/sup&gt; of seafloor becomes exposed to waters that have become undersaturated with respect to aragonite

Producing valid statistics when legislation, culture, and medical practices differ for births at or before the threshold of survival: Report of a European workshop

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