Modelling individual infancy growth trajectories to predict excessive gain in BMI z-score:a comparison of growth measures in the ABCD and GECKO Drenthe cohorts

BACKGROUND: Excessive weight gain during childhood is a strong predictor for adult overweight, but it remains unknown which growth measures in infancy (0-2 years of age), besides predictors known at birth, are the strongest predictors for excessive weight gain between 2 and 5-7 years of age.METHODS: The Amsterdam Born Children and their Development (ABCD) study formed the derivation cohort, and the Groningen Expert Center for Kids with Obesity (GECKO) Drenthe study formed the validation cohort. Change (Δ) in body mass index (BMI) z-score between 2 and 5-7 years was the outcome of interest. The growth measures considered were weight, weight-for-length (WfL), and body mass index (BMI). Formats considered for each growth measure were values at 1, 6, 12, and 24 months, at the BMI peak, the change between aforementioned ages, and prepeak velocity. 10 model structures combining different variable formats and including predictors at birth were derived for each growth measure, resulting in 30 linear regression models. A Parsimonious Model considering all growth measures and a Birth Model considering none were also derived.RESULTS: The derivation cohort consisted of 3139 infants of which 373 (11.9%) had excessive gain in BMI z-score (&gt; 0.67). The validation cohort contained 2201 infants of which 592 (26.9%) had excessive gain. Across the 3 growth measures, 5 model structures which included measures related to the BMI peak and prepeak velocity (derivation cohort area under the curve [AUC] range = 0.765-0.855) achieved more accurate estimates than 3 model structures which included growth measure change over time (0.706-0.795). All model structures which used BMI were superior to those using weight or WfL. The AUC across all models was on average 0.126 lower in the validation cohort. The Parsimonious Model's AUCs in the derivation and validation cohorts were 0.856 and 0.766, respectively, compared to 0.690 and 0.491, respectively, for the Birth Model. The respective false positive rates were 28.2% and 20.1% for the Parsimonious Model and 70.0% and 74.6% for the Birth Model.CONCLUSION: Models' performances varied significantly across model structures and growth measures. Developing the optimal model requires extensive testing of the many possibilities.</p

Modelling individual infancy growth trajectories to predict excessive gain in BMI z-score:a comparison of growth measures in the ABCD and GECKO Drenthe cohorts

BACKGROUND: Excessive weight gain during childhood is a strong predictor for adult overweight, but it remains unknown which growth measures in infancy (0-2 years of age), besides predictors known at birth, are the strongest predictors for excessive weight gain between 2 and 5-7 years of age.METHODS: The Amsterdam Born Children and their Development (ABCD) study formed the derivation cohort, and the Groningen Expert Center for Kids with Obesity (GECKO) Drenthe study formed the validation cohort. Change (Δ) in body mass index (BMI) z-score between 2 and 5-7 years was the outcome of interest. The growth measures considered were weight, weight-for-length (WfL), and body mass index (BMI). Formats considered for each growth measure were values at 1, 6, 12, and 24 months, at the BMI peak, the change between aforementioned ages, and prepeak velocity. 10 model structures combining different variable formats and including predictors at birth were derived for each growth measure, resulting in 30 linear regression models. A Parsimonious Model considering all growth measures and a Birth Model considering none were also derived.RESULTS: The derivation cohort consisted of 3139 infants of which 373 (11.9%) had excessive gain in BMI z-score (&gt; 0.67). The validation cohort contained 2201 infants of which 592 (26.9%) had excessive gain. Across the 3 growth measures, 5 model structures which included measures related to the BMI peak and prepeak velocity (derivation cohort area under the curve [AUC] range = 0.765-0.855) achieved more accurate estimates than 3 model structures which included growth measure change over time (0.706-0.795). All model structures which used BMI were superior to those using weight or WfL. The AUC across all models was on average 0.126 lower in the validation cohort. The Parsimonious Model's AUCs in the derivation and validation cohorts were 0.856 and 0.766, respectively, compared to 0.690 and 0.491, respectively, for the Birth Model. The respective false positive rates were 28.2% and 20.1% for the Parsimonious Model and 70.0% and 74.6% for the Birth Model.CONCLUSION: Models' performances varied significantly across model structures and growth measures. Developing the optimal model requires extensive testing of the many possibilities.</p

Longitudinal associations of air pollution and green space with cardiometabolic risk factor clustering among children in the Netherlands

Background: This study examines longitudinal associations of air pollution and green space with cardiometabolic risk among children in the Netherlands. Methods: Three Dutch prospective cohorts with a total of 13,822 participants aged 5 to 17 years were included: (1) the Amsterdam Born Children and their Development (ABCD) study from Amsterdam (n = 2,547), (2) the Generation R study from Rotterdam (n = 5,431), and (3) the Lifelines study from northern Netherlands (n = 5,844). Air pollution (PM2.5, PM10, NO2, and elemental carbon (EC)) and green space exposures (density in multiple Euclidean buffer sizes) from 2006 to 2017 at home address level were used. Cardiometabolic risk factor clustering was assessed by a MetScore, which was derived from a confirmatory factor analysis of six cardiometabolic risk factors to assess the overall risk. Linear regression models with change in Metscore as the dependent variable, adjusted for multiple confounders, were conducted for each cohort separately. Meta-analyses were used to pool cohort-specific estimates. Results: Exposure to higher levels of NO2 and EC was significantly associated with increases in MetScore in Lifelines (per SD higher exposure: βNO2 = 0.006, 95 % CI = 0.001 to 0.010; βEC = 0.008, 95 % CI = 0.002 to 0.014). In the other two cohort studies, these associations were in the same direction but these were not significant. Higher green space density in 500-meter buffer zones around participants’ residential addresses was not significantly associated with decreases of MetScore in all three cohorts. Higher green space density in 2000-meter buffer zones was significantly associated with decreases of MetScore in ABCD and Lifelines (per SD higher green space density: βABCD = -0.008, 95 % CI = -0.013 to −0.003; βLifelines = -0.002, 95 % CI = -0.003 to −0.00003). The pooled estimates were βNO2 = 0.003 (95 % CI = -0.001 to 0.006) for NO2, βEC = 0.003 (95 % CI = -0.001, 0.007) for EC, and β500m buffer = -0.0014 (95 % CI = -0.0026 to −0.0001) for green space. Conclusions: More green space exposure at residence was associated with decreased cardiometabolic risk in children. Exposure to more NO2 and EC was also associated with increased cardiometabolic risk.</p

Age-Specific Quantification of Overweight/Obesity Risk Factors From Infancy to Adolescence and Differences by Educational Level of Parents

Objectives: To explore the age-dependent associations between 26 risk factors and BMI in early life, and differences by parental educational level.Methods: Data of 10,310 children (24,155 measurements) aged 2–16 years participating in a multi-centre European cohort from 2007 to 2014 were utilized. Trajectories of overweight/obesity risk factors and their age-specific associations with BMI were estimated using polynomial mixed-effects models.Results: Exposure to most unfavourable factors was higher in the low/medium compared to the high education group, e.g., for PC/TV time (12.6 vs. 10.6 h/week). Trajectories of various risk factors markedly changed at an age of 9–11 years. Having a family history of obesity, maternal BMI, pregnancy weight gain and birth weight were positively associated with BMI trajectories throughout childhood/adolescence in both education groups; associations of behavioural factors with BMI were small. Parental unemployment and migrant background were positively associated with BMI in the low/medium education group.Conclusion: Associations of risk factors with BMI trajectories did not essentially differ by parental education except for social vulnerabilities. The age period of 9–11 years may be a sensitive period for adopting unfavourable behaviours

Similar adverse pregnancy outcome in native and nonnative dutch women with pregestational type 2 diabetes:a multicentre retrospective study

Objective. To assess the incidence of adverse pregnancy outcome in native and nonnative Dutch women with pregestational type 2 diabetes (T2D) in a multicenter study in The Netherlands. Methods. Maternal characteristics and pregnancy outcome were retrospectively reviewed and the influence of ethnicity on outcome was evaluated using independent t-test, Mann-Whitney U-test, and chi-square test. Results. 272 pregnant women (80 native and 192 non-native Dutch) with pregestational T2D were included. Overall outcome was unfavourable, with a perinatal mortality of 4.8%, major congenital malformations of 6.3%, preeclampsia of 11%, preterm birth of 19%, birth weight >90th percentile of 32%, and a Caesarean section rate of 42%. In nonnative Dutch women, the glycemic control was slightly poorer and the gestational age at booking somewhat later as compared to native Dutch women. However, there were no differences in incidence of preeclampsia/HELLP, preterm birth, perinatal mortality, macrosomia, and congenital malformations between those two groups. Conclusions. A high incidence of adverse pregnancy outcomes was found in women with pregestational T2D, although the outcome was comparable between native and non-native Dutch women. This suggests that easy access to and adequate participation in the local health care systems contribute to these comparable outcomes, offsetting potential disadvantages in the non-native group

Опыт использования акустического доплеровского измерителя течений (АDCP) в условиях Черного моря

В статье излагается методика проведения измерений Lowered ADCP и обработки первичной информации. При последующей обработке данных широко использовался опыт МГИ НАНУ с аналогичными акустическими измерителями течений в 80-е гг. В результате обобщен опыт применения Lowered ADCP в условиях Черного моря, даны алгоритмы обработки данных, приведены профили абсолютной скорости течений на ряде станций и показано, что предлагаемый подход дает более адекватную качественную и количественную оценку профиля скорости течения, чем известные методы.The methods of measurements with Lowered ADCP and processing of the initial information are presented. During the following data processing the experience of Marine Hydrophysical Institute of NAS of Ukraine with the similar acoustic currents meters in the 80-ies was widely applied. As a result the experience of Lowered ADCP application under the Black Sea conditions is generalized, the algorithms of data processing are given, the profiles of absolute speed of currents are given on the series of stations. It is shown that the proposed approach provides more adequate qualitative and quantitative estimation of the current velocity profile than the known methods do

Modelling individual infancy growth trajectories to predict excessive gain in BMI z-score: a comparison of growth measures in the ABCD and GECKO Drenthe cohorts

Abstract Background Excessive weight gain during childhood is a strong predictor for adult overweight, but it remains unknown which growth measures in infancy (0–2 years of age), besides predictors known at birth, are the strongest predictors for excessive weight gain between 2 and 5–7 years of age. Methods The Amsterdam Born Children and their Development (ABCD) study formed the derivation cohort, and the Groningen Expert Center for Kids with Obesity (GECKO) Drenthe study formed the validation cohort. Change (Δ) in body mass index (BMI) z-score between 2 and 5–7 years was the outcome of interest. The growth measures considered were weight, weight-for-length (WfL), and body mass index (BMI). Formats considered for each growth measure were values at 1, 6, 12, and 24 months, at the BMI peak, the change between aforementioned ages, and prepeak velocity. 10 model structures combining different variable formats and including predictors at birth were derived for each growth measure, resulting in 30 linear regression models. A Parsimonious Model considering all growth measures and a Birth Model considering none were also derived. Results The derivation cohort consisted of 3139 infants of which 373 (11.9%) had excessive gain in BMI z-score (> 0.67). The validation cohort contained 2201 infants of which 592 (26.9%) had excessive gain. Across the 3 growth measures, 5 model structures which included measures related to the BMI peak and prepeak velocity (derivation cohort area under the curve [AUC] range = 0.765–0.855) achieved more accurate estimates than 3 model structures which included growth measure change over time (0.706–0.795). All model structures which used BMI were superior to those using weight or WfL. The AUC across all models was on average 0.126 lower in the validation cohort. The Parsimonious Model’s AUCs in the derivation and validation cohorts were 0.856 and 0.766, respectively, compared to 0.690 and 0.491, respectively, for the Birth Model. The respective false positive rates were 28.2% and 20.1% for the Parsimonious Model and 70.0% and 74.6% for the Birth Model. Conclusion Models’ performances varied significantly across model structures and growth measures. Developing the optimal model requires extensive testing of the many possibilities

Microsimulation modeling of extended annual CT screening among lung cancer cases in the National Lung Screening Trial

Purpose: To microsimulate the effects of three additional annual CT screening rounds on lung cancer (LC) survival in the National Lung Screening Trial (NLST). Methods: We used multiple imputation to model the effect of additional screening in the full NLST cohort on the time to LC diagnosis and on LC death in those participants who were diagnosed with LC by the end of NLST. Nodule growth models were derived from a Dutch in-vivo study. Microsimulations were repeated 500 times. The method was validated by simulating three rounds of CT screening in the original chest radiography (CXR) cohort. The times up to which the simulations remained within the 95 % confidence bands of the CT cohort's original results were used to estimate the validity of the results in the CT cohort with three additional simulated screening rounds. Results: Validation of the simulation approach on the CXR cohort resulted in a LC mortality reduction which remained well within the 95 % confidence intervals of the original CT cohort up to 6.5 years after the start of simulations. Simulating additional CT screening in the CT cohort led to LCs being diagnosed earlier than originally, resulting in a relative risk reduction in LC mortality of 11 % (95 % confidence bands, 7 %–14 %) at 6.5 years. This is equivalent to preventing 71 % (48 %–94 %) more LC deaths than the original CT cohort achieved in comparison to the original CXR cohort. Conclusion: Three additional annual CT screening rounds in the NLST may have led to substantial further LC mortality reduction

Association between the number and size of intrapulmonary lymph nodes and chronic obstructive pulmonary disease severity

Contains fulltext : 225855.pdf (publisher's version ) (Open Access)Purpose: One of the main pathophysiological mechanisms of chronic obstructive pulmonary disease is inflammation, which has been associated with lymphadenopathy. Intrapulmonary lymph nodes can be identified on CT as perifissural nodules (PFN). We investigated the association between the number and size of PFNs and measures of COPD severity. Materials and Methods: CT images were obtained from COPDGene. 50 subjects were randomly selected per GOLD stage (0 to 4), GOLD-unclassified, and never-smoker groups and allocated to either "Healthy," "Mild," or "Moderate/severe" groups. 26/350 (7.4%) subjects had missing images and were excluded. Supported by computer-aided detection, a trained researcher prelocated non-calcified opacities larger than 3 mm in diameter. Included lung opacities were classified independently by two radiologists as either "PFN," "not a PFN," "calcified," or "not a nodule"; disagreements were arbitrated by a third radiologist. Ordinal logistic regression was performed as the main statistical test. Results: A total of 592 opacities were included in the observer study. A total of 163/592 classifications (27.5%) required arbitration. A total of 17/592 opacities (2.9%) were excluded from the analysis because they were not considered nodular, were calcified, or all three radiologists disagreed. A total of 366/575 accepted nodules (63.7%) were considered PFNs. A maximum of 10 PFNs were found in one image; 154/324 (47.5%) contained no PFNs. The number of PFNs per subject did not differ between COPD severity groups (p = 0.50). PFN short-axis diameter could significantly distinguish between the Mild and Moderate/severe groups, but not between the Healthy and Mild groups (p = 0.021). Conclusions: There is no relationship between PFN count and COPD severity. There may be a weak trend of larger intrapulmonary lymph nodes among patients with more advanced stages of COPD

Treatment of mid-bile duct carcinoma: Local resection or pancreatoduodenectomy?

Introduction: Whereas distal cholangiocarcinoma (DC) is treated by pancreatoduodenectomy (PD), consensus is lacking on treatment of mid-bile duct carcinoma (mid-BDC) without involvement of the pancreatic head. Both PD or a local resection (LR) of the extrahepatic bile duct with lymphadenectomy are being used. The aim of this study was to compare outcomes after PD and LR for mid-BDC and, for reference, PD for DC. Methods: Retrospective monocenter study including consecutive patients who underwent LR for mid-BDC (LR), PD for mid-BDC (PD-mid) and PD for DC (PD-distal) between 2000 and 2016. Clinicopathologic characteristics, postoperative outcomes and survival were compared. Results: A total of 184 patients were included (LR, 22; PD-mid, 38; PD-distal, 124). Postoperative mortality was 0% following LR, 5% (2/22) for PD-mid and 3% (4/124) for PD-distal, p = 0.542. Major complications occurred in 5/22 patients (23%), 19/39 (50%) and 46/124 (37%) respectively, p = 0.103 (LR versus PD-mid, p = 0.038). Tumor size, differentiation grade and resection margin status were comparable across groups. Median number of resected lymph nodes was 5 (range 3–7), 9 (7–14) and 12 (8–16) respectively, p < 0.001. Median overall survival was 46 months (95%CI 10–82), 19 months. (95%CI 11–27), and 29 months (95%CI 23–35) respectively, p = 0.39 (LR versus PD-mid, p = 0.20). Disease-free survival also did not differ. Conclusion: LR is an acceptable treatment for selected patients with mid-BDC, showing less morbidity and comparable survival despite smaller lymph node retrieval