Underestimation Of Size Research Articles

The Effects of Depth and Altitude on Image-Based Shark Size Measurements Using UAV Surveillance

Drones are an ecological tool used increasingly in shark research over the past decade. Due to their high-resolution camera and GPS systems, they have been used to estimate the sizes of animals using drone-based photogrammetry. Previous studies have used drone altitude to measure the target size accuracy of objects at the surface; however, target depth and its interaction with altitude have not been studied. We used DJI Mavic 3 video (3960 × 2160 pixel) and images (5280 × 3960 pixel) to measure an autonomous underwater vehicle of known size traveling at six progressively deeper depths to assess how sizing accuracy from a drone at 10 m to 80 m altitude is affected. Drone altitudes below 40 m and target depths below 2 m led to an underestimation of size of 76%. We provide evidence that accounting for the drone’s altitude and the target depth can significantly increase accuracy to 5% underestimation or less. Methods described in this study can be used to measure free-swimming, submerged shark size with accuracy that rivals hand-measuring methods.

Higher Accuracy of Arthroscopy Compared to MRI in the Diagnosis of Chondral Lesions in Acute Ankle Fractures: A Prospective Study.

Even after successful surgery for acute ankle fractures, many patients continue having complaints. A possible explanation is the presence of concomitant chondral lesions. The aim of this study is to investigate the accuracy of MRI compared to that of arthroscopy in the assessment of chondral lesions in acute ankle fractures. In this prospective single-center study, patients presenting with acute ankle fractures over a period of three years were identified. A preoperative MRI was performed within a maximum of 10 days after trauma. During surgery, ankle arthroscopy was also performed. The International Cartilage Repair Society (ICRS) cartilage lesion classification was used to grade the detected chondral lesions. To localize the chondral lesions, the talar dome was divided into eight zones and the tibial/fibular articular surfaces into three zones. In total, 65 patients (28 females) with a mean age of 41.1 ± 15 years were included. In the MRI scans, 70 chondral lesions were detected (69.2% of patients) affecting mostly the tibial plafond (30%) and mostly graded as ICRS 3. The mean lesion area measured was 20.8 mm2. In the arthroscopy, 85 chondral lesions were detected (70.8% of patients) affecting mostly the medial surface of the talar dome (25.9%) and mostly graded ICRS 3. The mean lesion area measured was 43.4 mm2. The highest agreement between the two methods was observed in the size estimation of the chondral lesions. The present study shows the reduced accuracy of MRI when compared to arthroscopy in the assessment of traumatic chondral lesions in the setting of acute ankle fractures especially regarding lesion size. MRI remains an essential instrument in the evaluation of such lesions; however, surgeons should take this discrepancy into consideration, particularly the underestimation of chondral lesions' size in the preoperative planning of surgical treatment and operative technique.

Decoding air passenger flows: Identifying the role of network autocorrelation in air travel

With the rapid expansion of the global aviation industry, especially in the Eurasian continent, understanding the factors driving interregional air passenger flow is of increasing importance. While most existing studies emphasize node-level and edge-level influencing factors such as economic scale, population size, and geographic distance, they often neglect the pivotal variable of network autocorrelation. This research is the first to introduce network autocorrelation within the Eurasian context and systematically analyze it using the Eigenvector Spatial Filtering Negative Binomial Gravity Model. Our findings highlight: (1) A significant network autocorrelation in the Eurasian continental aviation network. The eigenvector spatial filtering negative binomial regression model effectively captures this autocorrelation, considerably reducing model estimation bias. Specifically, the leading 3.28% of eigenvectors capture a high degree of this network autocorrelation. (2) The presence of network autocorrelation introduces estimation biases in related variables, resulting in underestimations of economic size, population size, visa restriction, and international trade, while overestimating cultural and institutional differences, geographical distance, colonial relationship. (3) Various factors affect the Eurasian continental sub-region's air passenger flows differently, indicating regional variations. This study takes a step towards improving our understanding of network autocorrelation in air passenger flows research.

Nonresponse in name generators across countries and survey modes

Past research indicates interviewer effects lead to an underestimation of network size and higher nonresponse to the “important matters” name generator. Self-administered surveys offer a potential solution, but evidence is mixed and context-specific. We employ a logistic multilevel regression, estimated using a Bayesian Markov Chain Monte Carlo approach, to analyze nonresponse to this name generator from 33 post-electoral surveys across 21 countries in the Comparative National Election Project. We find higher nonresponse in interviewer-administered surveys compared to self-administered surveys, particularly among specific demographic groups. Finally, we discuss the trade-offs in selecting survey modes for collecting ego-network data using this instrument.

Coxa valga and antetorta configuration leads to underestimation of the femoral component size: a matched case-control study of patients undergoing cementless total hip arthroplasty.

Total hip arthroplasty (THA) is the gold standard procedure for patients with end-stage osteoarthritis after failed conservative therapy. Digital templating is commonly employed in preoperative preparation for THA and contributes positively to its outcome. However, the impact of coxa valga and antetorta (CVA) configurations on stem size prediction accuracy remains not reported. Previous studies demonstrated that the size of the lesser trochanter (LT) can be used to determine femoral anteversion on pelvis radiographs. This study investigates the accuracy of preoperative digital templating in predicting stem size in patients with CVA undergoing cementless THA. Preoperative radiographs of 620 patients undergoing cementless THA were retrospectively investigated. Radiographs were standardized with patients standing and the leg internally rotated by 15°. A CVA group was established including patients with a CCD angle greater than 140° and a lesser trochanter (LT) size of at least 10mm for men and 8mm for women. For the control group, radiographs with a CCD angle ranging from 125-135° and LT size 3-10mm for men and 3-8mm for women were selected. Preoperative templating was performed using mediCAD. To reduce confounding factors, case-control matching was carried out for BMI and body height. After case-control matching, a total of thirty-one matches were analyzed. Stem size was underestimated in 74% (23/31) in the CVA and 13% (4/31) in the control group (p < 0.001). Moreover, patients with CVA were more likely to be underestimated by two sizes compared to controls (p < 0.004). In contrast, the exact stem size was predicted more frequently in the control group (p < 0.001). Stem size in patients with a CVA configuration are at high risk of being underestimated when using digital templating. These findings can be valuable for guiding in intraoperative decisions and lowering the risk of complications associated with an undersized femoral component.

Quantitative analysis of blooming artifact caused by calcification based on X-ray energy difference using computed tomography

Blooming artifacts caused by calcifications appearing on computed tomography (CT) images lead to an underestimation of the coronary artery lumen size, and higher X-ray energy levels are suggested to reduce the blooming artifacts with subjective visual assessment. This study aimed to evaluate the effect of higher X-ray energy levels on the quantitative measurement of adjacent pixels affected by calcification using CT images. In this two-part study, CT images were acquired from dual-energy CT scanners by changing the X-ray energy levels such as kilovoltage peak (kVp) and kilo-electron volts (keV). Adjacent pixels affected by calcification were measured using the brightened length, excluding the actual calcified length, as determined by the full width at third maximum. In a separate clinical study, the adjacent affected pixels associated with 23 calcifications across 10 patients were measured using the same method as that used in the phantom study. Phantom and clinical studies showed that the change in kVp (field of view [FOV] 300 mm: p = 0.167, 0.494, and 0.861 for vendors 1, 2, and 3, respectively) and keV levels (p = 0.178 for vendor 2) failed to reduce the adjacent pixels affected by calcification, respectively. Moreover, the change in keV levels showed different aspects of adjacent pixels affected by calcification in the phantom study (FOV 300 mm: no significant difference [p = 0.191], increase [p < 0.001], and decrease [p < 0.001] for vendors 1, 2, and 3, respectively). Quantitative measurements revealed no significant relationship between higher X-ray energy levels and the adjacent pixels affected by calcification.

Evaluation and correction of laser scattering-based particle size measurements at high obscurations using the Monte Carlo method.

High turbidity and its associated multiple scattering phenomena can often lead to an underestimation of the particle size for the laser scattering method. To investigate the light scattering characteristics and evaluate the effect of high-obscuration particle systems, a Monte Carlo model has been developed based on Mie's theory. A compact setup was utilized to perform a series of experiments on three certified reference materials (CRMs) at different concentrations. Both the scattered light energy distribution and the obscuration were measured simultaneously. The inversion results of the particle size indicate a continuous increase in deviation from the nominal value as the obscuration rises. According to the conventional single scattering model, the inversion errors fall within 5% for obscuration levels ranging from 0.15 to 0.2. However, for a higher obscuration, the error can reach approximately 15%. Thus, a correction method has been proposed by introducing an improved model matrix that includes the multiple scattering contribution for the data inversion, which exhibits a significant enhancement in the accuracy of particle size measurements under high obscuration conditions. For all three types of particles being studied, the error was successfully reduced to within 5.0%.

A sensitivity study on radiative effects due to the parameterization of dust optical properties in models

Abstract. Most of the dust models underestimate the load of the large dust particles, consider spherical shapes instead of irregular ones, and have to deal with a wide range of the dust refractive index (RI) to be used. This leads to an incomplete assessment of the dust radiative effects and dust-related impacts on climate and weather. The current work aims to provide an assessment, through a sensitivity study, of the limitations of models to calculate the dust direct radiative effect (DRE) due to the underrepresentation of its size, RI, and shape. We show that the main limitations stem from the size and RI, while using a more realistic shape plays only a minor role, with our results agreeing with recent findings in the literature. At the top of the atmosphere (TOA) close to dust sources, the underestimation of size issues an underestimation of the direct warming effect of dust of ∼ 18–25 W m−2, for DOD = 1 (dust optical depth) at 0.5 µm, depending on the solar zenith angle (SZA) and RI. The underestimation of the dust size in models is less above the ocean than above dust sources, resulting in an underestimation of the direct cooling effect of dust above the ocean by up to 3 W m−2, for aerosol optical depth (AOD) of 1 at 0.5 µm. We also show that the RI of dust may change its DRE by 80 W m−2 above the dust sources and by 50 W m−2 at downwind oceanic areas for DOD = 1 at 0.5 µm at TOA. These results indicate the necessity of including more realistic sizes and RIs for dust particles in dust models, in order to derive better estimations of the dust DRE, especially near the dust sources and mostly for studies dealing with local radiation effects of dust aerosols.

No influence of emotional expression on size underestimation of upright faces.

Faces are a primary means of conveying social information between humans. One important factor modulating the perception of human faces is emotional expression. Face inversion also affects perception, including judgments of emotional expression, possibly through the disruption of configural processing. One intriguing inversion effect is an illusion whereby faces appear to be physically smaller when upright than when inverted. This illusion appears to be highly selective for faces. In this study, we investigated whether the emotional expression of a face (neutral, happy, afraid, and angry) modulates the magnitude of this size illusion. Results showed that for all four expressions, there was a clear bias for inverted stimuli to be judged as larger than upright ones. This demonstrates that there is no influence of emotional expression on the size underestimation of upright faces, a surprising result given that recognition of different emotional expressions is known to be affected unevenly by inversion. Results are discussed considering recent neuroimaging research which used population receptive field (pRF) mapping to investigate the neural mechanisms underlying face perception features and which may provide an explanation for how an upright face appears smaller than an inverted one. Elucidation of this effect would lead to a greater understanding of how humans communicate.

Simulation and evaluation study of atmospheric aerosol nonsphericity as a function of particle size

Aerosol nonsphericity causes great uncertainty in radiative forcing assessments and climate simulations. Although considerable studies have attempted to quantify this uncertainty, the relationship between aerosol nonsphericity and particle size is usually not considered, thus reducing the accuracy of the results. In this study, a coupled inversion algorithm combining an improved stochastic particle swarm optimization algorithm and angular light scattering is used for the nonparametric estimation of aerosol nonsphericity variation with particle size, and the optimal sample selection method is employed to screen the data. Based on the verification of inversion accuracy, the variation of aerosol aspect ratio with particle size based on the ellipsoidal model in global regions has been obtained from Aerosol Robotic Network (AERONET) data, and the effect of nonsphericity on radiative forcing and dry deposition has been studied. The results show that the aspect ratio increases with particle size in all regions, with the maximum ranging from 1.4 to 1.8 in the desert, reflecting the differences in aerosol composition at different particle sizes. In radiation calculations, considering aerosol nonsphericity makes the aerosol cooling effect weaker and surface radiative fluxes increase, but hardly changes the aerosol absorption, with maximum differences of 9.22% and 22.12% at the bottom and top of the atmosphere, respectively. Meanwhile, the differences in radiative forcing between aspect ratios as a function of particle size and not varying with particle size are not significant, averaging less than 2%. Besides, the aspect ratio not varying with particle size underestimates the deposition velocity of small particles and overestimates that of large particles compared to that as a function of particle size, with maximum differences of 7% and 4%, respectively.

Evaluation of the diffusion coefficient of cement paste from pore size distribution using three-dimensional simulation

A three-dimensional diffusion simulation was performed to evaluate the diffusion coefficient (D) of cementitious materials based on the pore structure determined by mercury intrusion porosimetry (MIP). In the numerical simulation, a simple cubic lattice was assumed. As a result, the simulated D agreed better with the measured D than in previous studies without adjusting the parameters. The quantitative evaluation of D was possible with a certain accuracy based on the numerical simulation using the pore structure information evaluated by MIP, even though the MIP results include the ink-bottle effect, which causes an underestimation of the pore size.

Perceived Body Size in Relation to 10-Year Weight Change in the Swedish Obese Subjects Intervention Study

Introduction: Body size underestimation in patients with obesity may be associated with long-term weight increase. In the current report, we analyse changes in body size perception in patients with obesity undergoing either bariatric surgery or usual obesity care, and in subgroups of patients who gain weight or maintain their body weight over 10 years. Materials and Methods: A total of 2,504 patients with obesity from the prospective, controlled Swedish Obese Subjects (SOS) intervention study were included in this report, 1,370 patients underwent bariatric surgery and 1,134 patients were usual care controls. Weight was measured and body size was self-estimated using the Stunkard’s figure rating scale at baseline and after 0.5, 1, 2, 3, 4, 6, 8 and 10 years of follow-up. A body perception index (BPI) was calculated as estimated/measured BMI. Weight (re)gain was defined as ≥10% increase between 1 and 10 years of follow-up. Results: Body size was underestimated by 12% in the surgery and 14% in the control group (i.e., >5 BMI units) at baseline and underestimation largely persisted over 10 years in both intervention groups. When stratified by long-term weight development, weight regainers from the surgery group underestimated their body size to a larger degree compared to weight maintainers (12 vs. 9%, p < 0.001) after 10 years. Likewise weight gainers in the control group also underestimated their body size to a larger degree (17% vs. 13%, p < 0.001). In both groups, the change in BPI was significantly different between weight regainers and maintainers during follow-up (time-BPI interactions both p < 0.001). Conclusion: Patients with obesity underestimate their body size and this underestimation remains long-term even after major weight loss induced by bariatric surgery. In patients with obesity who maintain their weight, regardless of treatment, underestimation of body size persists but body size perception is slightly more accurate compared to patients who gain or regain weight long-term.

Assessing left atrial size to predict mortality in the overweight and obese population

Abstract Background Left atrial (LA) size provides important prognostic information. A larger LA is associated with a higher risk of death or cardiovascular complications. LA size is generally measured by indexing LA volume to body surface area (BSA). For individuals with a higher BSA, particularly those with obesity, this may lead to an underestimation of true LA size. Alternate indexation methods of measuring LA size have been proposed for this population. There is limited data showing if these indices provide better prognostic value compared to the standard BSA indexation in the overweight and obese population. Purpose To determine and compare the performance of various LA size indices in predicting all-cause mortality. Methods We obtained data from the National Echocardiography Database of Australia (NEDA), a large, observational registry, capturing routinely acquired echocardiographic data from individuals with potential or established heart disease. Our study outcome was all-cause mortality and LA size was our predictor variable. We evaluated ten indices for LA size: LA volume (obtained at time of scan), and LA volume indexed to BSA, idealised BSA, height(^1, ^2, ^2.7, ^1.83), weight, body mass index (BMI), and estimated lean body mass. From the original NEDA dataset, we excluded observations with: missing values for LA volume, height, weight, and ejection fraction (EF); date of examination is after the census date; and indication of valvular disease. Finally, we selected only the earliest observation for each individual and obtained a sub-population with overweight and obesity for analysis (n = 113,786). We conducted a receiver operating characteristic (ROC) analysis and calculated the summary statistic of the area under the curve (AUC) to compare the accuracy of the ten LA size indices in predicting all-cause mortality. Results In the overweight and obese population, all the LA indices had similar predicting accuracy for all-cause mortality (Figure 1). Raw LA volume and LA volume/BMI had slightly lower AUC: AUC [95% confidence interval] values were 0.61 [0.605-0.614] and 0.61 [0.607-0.616], respectively. Other indices, including LA volume/BSA, LA volume/weight and LA volume/height, had equivalent predictive accuracy (0.62∼0.63) for all-cause mortality (Figure 2). Conclusion Overall, all LA size indices performed similarly in predicting all-cause mortality in this overweight and obese population, except for LA volume/BMI. Our results found no superior indexation method (including allometric ones) to the current practice (i.e., LA volume/BSA) in this population.ROC curves of indicesAUC, 95% confidence intervals of indices

Design and performance assessment of a pumped hydro power energy storage connected to a hybrid system of photovoltaics and wind turbines

Worldwide, the overdependence on conventional power plants for electricity generation has been one of the most significant economic and environmental challenges. Renewable energy sources have become the most viable option to overcoming this issue. Recently, a hybrid renewable energy system consisting of wind turbines and photovoltaics combined with a pumped hydroelectric energy storage system has received considerable interest. However, neglecting crucial parameters, such as head losses and evaporation rate, might reduce the accuracy of the total simulation performance, resulting in an underestimation of the correct size of each component. This study investigates this issue by proposing a robust approach with a strategy to establish the ideal pipe design through an in-depth techno-economic assessment. A comparative analysis between two different scenarios in which one considers head loss and the other does not is carried out. A wide range of proposed system configurations has been thoroughly investigated. The essential performance indicators employed for designing the proposed system are the renewable energy fraction and the loss of renewable energy, and the results reveal that these two indicators have improved by approximately 8.6% and 3%, respectively. The most significant annual variation between the two scenarios regarding the total demand satisfied by the proposed system and the amount of renewable energy loss is 218.23 GWh and 89.39 GWh, respectively. The pipe efficiency at the pumping and generating modes, which is determined through a sensitivity analysis, ranges between 91-99% and 76–95%, respectively. These findings could assist designers in making initial assumptions about such parameters with reasonable confidence.

Two-dimensional ultrasound results in underestimation of the ovarian follicle size compared to automated three-dimensional imaging in women undergoing IVF.

Traditionally, for the assessment of follicle growth during IVF, two-dimensional (2D) transvaginal ultrasound (US) is used. In the past few years three-dimensional (3D) US has also been introduced. To compare follicular sizes between 2 and 3D ultrasound imaging on the final day of controlled ovarian stimulation. A prospective observational cohort study including 121 women undergoing controlled ovarian stimulation (COS) between January 2017 and July 2018. All women were assessed by transvaginal 2D and 3D ultrasonography to measure ovarian follicle dimensions on the final day of COS. The mean difference in paired comparisons between the 3D and 2D US measurements in 25 women with monofollicular development was + 1.6 ± 2.5mm for the x-dimension and + 1.7 ± 2.4mm for the y-dimension; and in the total number of 1197 paired measurements of follicles the mean difference + 2.1 ± 3.3mm and + 1.8 ± 3.9mm for the x- and y-dimension respectively. In all cases the paired t-test showed that differences were statistically significant (p < 0.01). Further it was conjectured that the 2D underestimation results from the inherent difficulty to precisely place the US probe simultaneously on the perpendicular maximal of the x and y follicle diameters, leading to measurement errors that, by theory, are normally distributed. Running Monte-Carlo simulations based on these measurement errors it was found that both the mean difference and standard deviation are of the same magnitude as the ones found in real measurements, thus proving the conjecture. The utilisation of 3D US results in different measurements of the follicular dimensions, and volumes, when compared to conventional 2D US. The differences in the x- and y-dimensions may affect the outcome of an IVF cycle as they are used to define the day of triggering final oocyte maturation, which is associated with the yield of mature oocytes and the probability of live birth.

IMG-05. A MULTI-INSTITUTIONAL AND MULTI-HISTOLOGY PEDIATRIC-SPECIFIC BRAIN TUMOR SUBREGION SEGMENTATION TOOL: FACILITATING RAPNO-BASED ASSESSMENT OF TREATMENT RESPONSE

Abstract Current response assessment in pediatric brain tumors (PBTs), as recommended by the Response Assessment in Pediatric Neuro-Oncology (RAPNO) working group, relies on 2D measurements of changes in tumor size. However, there is growing evidence of underestimation of tumor size in PBTs using 2D compared to volumetric (3D) measurement approach. Accordingly, automated methods that reduce manual burden and intra- and inter-rater variability in segmenting tumor subregions and volumetric evaluations are warranted to facilitate tumor response assessment of PBTs. We have developed a fully automatic deep learning (DL) model using the nnUNet architecture on a large cohort of multi-institutional and multi-histology PBTs. The model was trained on widely available standard multiparametric MRI sequences (T1-pre, T1-post, T2, T2-FLAIR) for segmentation of the whole tumor and RAPNO-recommended subregions, including enhancing tumor (ET), non-enhancing tumor (NET), cystic components (CC), and peritumoral edema (ED). As a prerequisite step for accurate tumor segmentation, we also generated another DL model based on DeepMedic for brain extraction from mpMRIs. The models were trained on an institutional cohort of 151 subjects and independently tested on 64 subjects from the internal and 29 patients from external institutions. The trained models showed excellent performance with median Dice scores of 0.98±0.02/0.97±0.02 for brain tissue segmentation, 0.92±0.08/0.90±0.17 for whole tumor segmentation, 0.76±0.31/0.87±0.29 for ET subregion, and 0.82±0.15/0.80±0.28 for segmentation of non-enhancing components (combination of NET, CC, and ED) in internal/external test sets, respectively. The automated segmentation demonstrated strong agreement with expert segmentations in volumetric measurement of tumor components, with Pearson’s correlation coefficients of 0.97, 0.97, 0.99, and 0.79 (p&amp;lt;0.0001) for ET, NET, CC, and ED regions, respectively. Our proposed multi-institutional and multi-histology automated segmentation method has the potential to aid clinical neuro-oncology practice by providing reliable and reproducible volumetric measurements for treatment response assessment.

Finite image size effects on the characterization of magnetic domain patterns via magnetic force microscopy

Optimizing magnetic thin films for nanotechnologies often requires imaging nanoscale magnetic domain patterns via magnetic microscopy. The finite size of the image may however significantly affect the characterization of the observed magnetic states. We evaluated finite image size effects on the characterization of a variety of stripe and bubble domain patterns exhibited by ferromagnetic Co/Pt multilayers with perpendicular magnetic anisotropy, where the domain size (stripe width and bubble diameter) is around 100 nm. If the image size is too small, below ∼5 μm, it may cause a significant underestimation of average domain size and overestimation of domain density by up to a factor 5 when reducing the image size from about 20 μm to about a 1 μm. Using a criterion based on how the excess density evolves with image size, we found that to obtain reliable statistical estimates of domain density and average domain size, the image needs to be large enough, and include at least about 100 stripes or about 2500 bubbles.

Honeycomb lung is a major risk factor for preoperative radiological tumor size underestimation in patients with primary lung cancer.

Lung cancer frequently occurs in lungs with background idiopathic interstitial pneumonias (IIPs). Limited resection is often selected to treat lung cancer in patients with IIPs in whom respiratory function is already compromised. However, accurate surgical margins are essential for curative resection; underestimating these margins is a risk for residual lung cancer after surgery. We aimed to investigate the findings of lung fields adjacent to cancer segments affect the estimation of tumor size on computed tomography compared with the pathological specimen. This analytical observational study retrospectively investigated 896 patients with lung cancer operated on at Fujita Health University from January 2015 to June 2020. The definition of underestimation was a ≥10 mm difference between the radiological and pathological maximum sizes of the tumor. The lung tumors were in 15 honeycomb, 30 reticulated, 207 emphysematous, and 628 normal lungs. The ratio of underestimation in honeycomb lungs was 33.3% compared to 7.4% without honeycombing (P=0.004). Multivariate analysis showed that honeycombing was a significant risk factor for tumor size underestimation. A Bland-Altman plot represented wide 95% limits of agreement, -40.8 to 70.2 mm, between the pathological and radiological maximum tumor sizes in honeycomb lungs.

Association between body shape misperception and unhealthy eating behaviors among Korean adolescents.

Body shape misperception (BSM) is the disagreement between the subjectively perceived body size and body mass index. This study investigated the association between BSM and unhealthy eating behaviors (UEB) among Korean adolescents. This cross-sectional study used data from the 2019 Korea Youth Risk Behavior Web-based Survey with 55,748 participants. UEB were measured according to the weekly consumption frequency of caffeinated energy drinks, fast food, carbonated beverages, and sugar-sweetened beverages. The covariates included demographic and socioeconomic characteristics and health-related factors. Multiple logistic regression analysis determined the association between BSM and UEB. Among the participants, 37,607 (67.5%) reported UEB. The gap between UEB among those with BSM was the largest between the underestimated and accurately estimated groups. Participants who underestimated their body shape were likelier to engage in UEB (adjusted odds ratio [AOR], 1.18; 95% confidence interval [CI], 1.11-1.25). Both sexes with underestimation of body size showed an association with UEB compared to those with accurate estimations (girls: AOR, 1.19; 95% CI, 1.09-1.30; boys: AOR, 1.16; 95% CI, 1.08-1.26). Underestimating body shape can provoke UEB among Korean adolescents. The need for appropriate school health interventional programs to prevent underestimating body shape is emphasized to avoid UEB.

Underestimation of endoscopic size in large gastric epithelial neoplasms.

Endoscopic submucosal dissection (ESD) is an effective method for resecting gastric adenomas and adenocarcinomas. A significant discrepancy was observed between endoscopic and pathological sizes in samples obtained from patients undergoing ESD. This study elucidates the factors affecting size discrepancy after formalin fixation. The records of 64 patients with 69 lesions were analyzed, including 50 adenomas and 19 adenocarcinomas. Data on location, gross shape, histology, and size after fixation in formalin were collected. The mean size of the resected specimen appeared to decrease after formalin fixation (37.5 mm prefixation vs. 35.8 mm postfixation, p<0.05). The mean long axis diameter of the lesions was 20.3±7.9 mm prefixation and 13.4±7.9 mm postfixation. Size differences in lesions smaller than 20 mm were significantly greater than those in lesions larger than 20 mm (7.6±5.6 mm vs. 2.5±5.8 mm, p<0.01). In multivariate analysis, a tumor size of ≥20 mm was found to be an independent factor affecting size postformalin fixation (p<0.05). The endoscopic size of lesions before ESD may be underestimated in tumors larger than 20 mm in size. Therefore, increased attention must be paid during ESD to avoid instances of incomplete resection.