Hasil untuk "Demography. Population. Vital events"

Shuntaro Suzuki, Shuitsu Koyama, Shinnosuke Hirano et al.

Photoplethysmography (PPG) plays a crucial role in continuous cardiovascular health monitoring as a non-invasive and cost-effective modality. However, PPG signals are susceptible to motion artifacts and noise, making accurate estimation of vital signs such as arterial blood pressure (ABP) challenging. Existing estimation methods are often restricted to a single-task or environment, limiting their generalizability across diverse PPG decoding scenarios. Moreover, recent general-purpose approaches typically rely on predictions over multi-second intervals, discarding the morphological characteristics of vital signs. To address these challenges, we propose PENGUIN, a generative flow-matching framework that extends deep state space models, enabling fine-grained conditioning on PPG for reconstructing multiple vital signs as continuous waveforms. We evaluate PENGUIN using six real-world PPG datasets across three distinct vital sign reconstruction tasks (electrocardiogram reconstruction, respiratory monitoring, and ABP monitoring). Our method consistently outperformed both task-specific and general-purpose baselines, demonstrating PENGUIN as a general framework for robust vital sign reconstruction from PPG.

Fábio Vital, Alberto Sardinha, Francisco S. Melo

Conversational repair is a mechanism used to detect and resolve miscommunication and misinformation problems when two or more agents interact. One particular and underexplored form of repair in emergent communication is the implicit repair mechanism, where the interlocutor purposely conveys the desired information in such a way as to prevent misinformation from any other interlocutor. This work explores how redundancy can modify the emergent communication protocol to continue conveying the necessary information to complete the underlying task, even with additional external environmental pressures such as noise. We focus on extending the signaling game, called the Lewis Game, by adding noise in the communication channel and inputs received by the agents. Our analysis shows that agents add redundancy to the transmitted messages as an outcome to prevent the negative impact of noise on the task success. Additionally, we observe that the emerging communication protocol's generalization capabilities remain equivalent to architectures employed in simpler games that are entirely deterministic. Additionally, our method is the only one suitable for producing robust communication protocols that can handle cases with and without noise while maintaining increased generalization performance levels.

Christian Eckrich, Abdelhak M. Zoubir, Vahid Jamali

Vital sign monitoring plays a critical role in healthcare and well-being, as parameters such as respiration and heart rate offer valuable insights into an individual's physiological state. While wearable devices allow for continuous measurement, their use in settings like in-home elderly care is often hindered by discomfort or user noncompliance. As a result, contactless solutions based on radar sensing have garnered increasing attention. This is due to their unobtrusive design and preservation of privacy advantages compared to camera-based systems. However, a single radar perspective can fail to capture breathing-induced chest movements reliably, particularly when the subject's orientation is unfavorable. To address this limitation, we integrate a reconfigurable intelligent surface (RIS) that provides an additional sensing path, thereby enhancing the robustness of respiratory monitoring. We present a novel model for multi-path vital sign sensing that leverages both the direct radar path and an RIS-reflected path. We further discuss the potential benefits and improved performance our approach offers in continuous, privacy-preserving vital sign monitoring.

Jacob Bor, Evelyn Lauren

Background Epidemiologists increasingly work with linked “big data”. Uncertainty in record linkage may lead to biased inferences but is often overlooked. We evaluate the impact of linkage uncertainty on statistical inference in linked big data. Methods We developed a graphical framework for describing linkage uncertainty when linking multiple representations of the same entity, applied to de-identified data from South Africa’s national laboratory database. Through simulation, we systematically introduced linkage errors and measured their impact on overall accuracy (sensitivity, positive predictive value (PPV)). We evaluate how linkage errors affect bias and variance in point estimates for a hypothetical parameter of interest in clinical epidemiology: 24-month retention in care for HIV patients. We compare the roles of sampling error vs. linkage error as fundamental sources of uncertainty in datasets of varying sizes. Results We simulated a population of 14,393 HIV patients, with a “true” 24-month retention of 38.7%. There were 338,056 true links. Introducing 4,200 false links reduced PPV by 5%. Removing 21,500 existing links decreased sensitivity by 5%. From 10 simulation runs, a 95% sensitivity led, on average, to a 7.4% overestimate in entries to care and a 2.2% (range: 2.1-2.4%) underestimate in 24-month retention. A 95% PPV resulted, on average, in a 7.5% underestimate in entries to care and a 1.8% (range: 1.5-2.0%) overestimate in 24-month retention. Conclusion We observe that in a large sample, linkage uncertainty minimally impacts variance in point estimates but has a potentially large influence on the magnitude and direction, distinguishing it from typical sampling errors.

Наталья Викторовна Чернышева , Альбина Исламовна Ажигулова , Сергей Николаевич Уваров

В статье рассматриваются этнодемографические процессы у удмуртов во второй половине 1930-х – 1950-х годах. В рамках исследования определены этнодемографические изменения у удмуртов, произошедшие на старте демографического перехода данной этнической общности. Авторы используют сведения Всесоюзных переписей населения 1937, 1939, 1959 г. и данные текущего учета, а именно форму 3, позволившую проанализировать процессы воспроизводства у удмуртов в региональном разрезе. Исследователи выделяют основные регионы присутствия удмуртов, анализируют динамику численности, состав удмуртов в изучаемых регионах. Вследствие индустриализации удельный вес удмуртов в наиболее урбанизированных регионах их присутствия увеличился, данная тенденция сохранилась и в послевоенный период. В Удмуртской АССР численность и удельный вес этнических удмуртов сократились. Во второй половине 1930-х годов у удмуртов еще сохраняется традиционный тип воспроизводства. Показатели рождаемости были высокими, так же как и уровень смертности, в общей структуре которого существенной была смертность младенцев. Голод, социально-экономические преобразования, внутри- и внешнеполитические процессы оказали сильное воздействие на воспроизводство населения. К концу 1930-х годов у удмуртов, проживающих в городах, прослеживаются изменения в демографическом поведении. К концу 1950-х годов в результате воздействия Великой Отечественной войны и социально-экономических изменений послевоенного времени у удмуртов происходят существенные изменения в процессах воспроизводства населения.

Dingding Liang, Yang Chen, Jiawei Gao et al.

Real-time vital sign monitoring is gaining immense significance not only in the medical field but also in personal health management. Facing the needs of different application scenarios of the smart and healthy city in the future, the low-cost, large-scale, scalable, and distributed vital sign monitoring system is of great significance. In this work, a seamlessly integrated contact and contactless vital sign monitoring system, which can simultaneously implement respiration and heartbeat monitoring, is proposed. In contact vital sign monitoring, the chest wall movement due to respiration and heartbeat is translated into changes in the optical output intensity of a fiber Bragg grating (FBG). The FBG is also an important part of radar signal generation for contactless vital sign monitoring, in which the chest wall movement is translated into phase changes of the radar de-chirped signal. By analyzing the intensity of the FBG output and phase of the radar de-chirped signal, real-time respiration and heartbeat monitoring are realized. In addition, due to the distributed structure of the system and its good integration with the wavelength-division multiplexing optical network, it can be massively scaled by employing more wavelengths. A proof-of-concept experiment is carried out. Contact and contactless respiration and heartbeat monitoring of three people are simultaneously realized. During a monitoring time of 60 s, the maximum absolute measurement errors of respiration and heartbeat rates are 1.6 respirations per minute and 2.3 beats per minute, respectively. The measurement error does not have an obvious change even when the monitoring time is decreased to 5 s.

Saúl Antonio Obregón Biosca

Las zonas metropolitanas concentran población y atraen actividades económicas, induciendo la necesidad de realizar viajes dentro de su territorio. Por ello, la presente investigación analiza las características y distribución espacial de los viajes por motivos tanto obligados como opcionales en los principales medios de transporte, y se emplea la encuesta Origen Destino para analizar el modelo clásico de la movilidad. Los resultados muestran que el autobús es el principal medio para realizar desplazamientos por motivo educativos, mientras el automóvil es mayormente utilizado con propósitos de compras y de trabajo, además que la centralidad de la residencia se relaciona directamente con la del empleo.

Surender Baswana, Koustav Bhanja

Let G be a directed weighted graph (DiGraph) on n vertices and m edges with source s and sink t. An edge in G is vital if its removal reduces the capacity of (s,t)-mincut. Since the seminal work of Ford and Fulkerson, a long line of work has been done on computing the most vital edge and all vital edges of G. Unfortunately, after 60 years, the existing results are for undirected or unweighted graphs. We present the following result for DiGraph, which solves an open problem stated by Ausiello et al. 1. There is an algorithm that computes all vital edges as well as the most vital edge of G using O(n) maxflow computations. Vital edges play a crucial role in the design of Sensitivity Oracle (SO) for (s,t)-mincut. For directed graphs, the only existing SO is for unweighted graphs by Picard and Queyranne. We present the first and optimal SO for DiGraph. 2. (a) There is an O(n) space SO that can report in O(1) time the capacity of (s,t)-mincut and (b) an O($n^2$) space SO that can report an (s,t)-mincut in O(n) time after failure/insertion of an edge. For unweighted graphs, Picard and Queyranne designed an O(m) space DAG that stores and characterizes all mincuts for all vital edges. Conversely, there is a set containing at most n-1 (s,t)-cuts such that at least one mincut for every vital edge belongs to the set. We generalize these results for DiGraph. 3. (a) There is a set containing at most n-1 (s,t)-cuts such that at least one mincut for every vital edge is present in the set. (b) We design two compact structures for storing and characterizing all mincuts for all vital edges, (i) O(m) space DAG for partial characterization and (ii) O(mn) space structure for complete characterization. To arrive at our results, we develop new techniques, especially a generalization of maxflow-mincut theorem by Ford and Fulkerson, which might be of independent interest.

Philipp V. Rouast

This report introduces VitalLens, an app that estimates vital signs such as heart rate and respiration rate from selfie video in real time. VitalLens uses a computer vision model trained on a diverse dataset of video and physiological sensor data. We benchmark performance on several diverse datasets, including VV-Medium, which consists of 289 unique participants. VitalLens outperforms several existing methods including POS and MTTS-CAN on all datasets while maintaining a fast inference speed. On VV-Medium, VitalLens achieves mean absolute errors of 0.71 bpm for heart rate estimation, and 0.76 bpm for respiratory rate estimation.

Hadi Alidoustaghdam, Min Chen, Ben Willetts et al.

Radio technology enabled contact-free human posture and vital sign estimation is promising for health monitoring. Radio systems at millimeter-wave (mmWave) frequencies advantageously bring large bandwidth, multi-antenna array and beam steering capability. \textit{However}, the human point cloud obtained by mmWave radar and utilized for posture estimation is likely to be sparse and incomplete. Additionally, human's random body movements deteriorate the estimation of breathing and heart rates, therefore the information of the chest location and a narrow radar beam toward the chest are demanded for more accurate vital sign estimation. In this paper, we propose a pipeline aiming to enhance the vital sign estimation performance of mmWave FMCW MIMO radar. The first step is to recognize human body part and posture, where we exploit a trained Convolutional Neural Networks (CNN) to efficiently process the imperfect human form point cloud. The CNN framework outputs the key point of different body parts, and was trained by using RGB image reference and Augmentative Ellipse Fitting Algorithm (AEFA). The next step is to utilize the chest information of the prior estimated human posture for vital sign estimation. While CNN is initially trained based on the frame-by-frame point clouds of human for posture estimation, the vital signs are extracted through beamforming toward the human chest. The numerical results show that this spatial filtering improves the estimation of the vital signs in regard to lowering the level of side harmonics and detecting the harmonics of vital signs efficiently, i.e., peak-to-average power ratio in the harmonics of vital signal is improved up to 0.02 and 0.07dB for the studied cases.

Fábio Vital, Miguel Vasco, Alberto Sardinha et al.

We present Perceive-Represent-Generate (PRG), a novel three-stage framework that maps perceptual information of different modalities (e.g., visual or sound), corresponding to a sequence of instructions, to an adequate sequence of movements to be executed by a robot. In the first stage, we perceive and pre-process the given inputs, isolating individual commands from the complete instruction provided by a human user. In the second stage we encode the individual commands into a multimodal latent space, employing a deep generative model. Finally, in the third stage we convert the multimodal latent values into individual trajectories and combine them into a single dynamic movement primitive, allowing its execution in a robotic platform. We evaluate our pipeline in the context of a novel robotic handwriting task, where the robot receives as input a word through different perceptual modalities (e.g., image, sound), and generates the corresponding motion trajectory to write it, creating coherent and readable handwritten words.

Amtul Haq Ayesha, Donghao Qiao, Farhana Zulkernine

With a surge in online medical advising remote monitoring of patient vitals is required. This can be facilitated with the Remote Photoplethysmography (rPPG) techniques that compute vital signs from facial videos. It involves processing video frames to obtain skin pixels, extracting the cardiac data from it and applying signal processing filters to extract the Blood Volume Pulse (BVP) signal. Different algorithms are applied to the BVP signal to estimate the various vital signs. We implemented a web application framework to measure a person's Heart Rate (HR), Heart Rate Variability (HRV), Oxygen Saturation (SpO2), Respiration Rate (RR), Blood Pressure (BP), and stress from the face video. The rPPG technique is highly sensitive to illumination and motion variation. The web application guides the users to reduce the noise due to these variations and thereby yield a cleaner BVP signal. The accuracy and robustness of the framework was validated with the help of volunteers.

Tomáš Matějček

The aim of this article is to summarize actual results of the field research of invasive neophytes’ occurrence in the riverbank vegetation of the Labe River from Špindlerův Mlyn to Těchlovice (Děčin district). In total more than 190 km of the riverbank vegetation was mapped using author’s own method. The occurrence of 22 most important invasive neophytes (17 taxons) was registered for each of the 500 m long segments (in total 284 segments was mapped). The number of specimen was registered using a logarithmical scale and both simple and weighted index of total load of invasive neophytes was calculated for each segment. Results are presented for series (i. e. groups of neighbouring segments with similar geographical and ecological conditions) and also the comparation with other water courses in the Czech Republic is presented. The occurence of invasive neophytes is near of the average for other water courses, but the number of specimen is lower. The most frequent taxons were Solidago sp. and Impatiens glandulifera. Mutual dependence between occurence of invasive species and the vertical position of the segment of the watercourse wasn’t confirmed. Development in the years 2006 and 2007 was compared, but only small changes was discovered in this short time horizon. <b>Zatížení břehové vegetace Labe invazivními rostlinnými druhy</b> Tento příspěvek shrnuje výsledky mapování invazních neofytů (v pojetí Richardsona et al. 2000, Pyška et. al. 2002) v břehové vegetaci Labe. Mapování bylo provedeno pomocí vlastní metodiky (Matějček in Langhammer 2005), a to v předem stanovených 500 m dlouhých úsecích, které byly obvykle vymezeny na základě říční kilometráže nebo byly odměřovány od významných bodů (mosty, jezy apod.). Celkem bylo sledováno 284 segmentů v úseku mezi Špindlerovým Mlýnem a Těchlovicemi (okr. Děčín). Za břehovou vegetaci byl podle Nováka et al. (1986) považován pás vegetace podél vodního toku, omezený na jedné straně vodní hladinou, na druhé straně břehovou hranou. Šířka tohoto pásu se v praxi pohybovala obvykle v rozmezí 5–15 m. Výskyt 22 druhů (resp. 17 taxonů) nejvýznamnějších invazních neofytů byl zaznamenáván pomocí logaritmické stupnice. Pro jednotlivé segmenty a pro jednotlivé části toku byl vypočítán celkový počet zaznamenaných taxonů, celkový počet jedinců, prostý index zatížení invazními neofyty a vážený index zatížení invazními neofyty. Zatímco prostý index zatížení invazními neofyty přikládá podobnou váhu počtu přítomných druhů a počtu jedinců, vážený index zatížení invazními neofyty zohledňuje také velikost jednotlivých druhů, jejich stabilitu na stanovišti a potenciální nebezpečnost pro přirozenou vegetaci nebo pro člověka a jeho aktivity. Počet jedinců jednotlivých taxonů je při výpočtu vážen určitým koeficientem (viz tab. 1). Z celkového počtu 17 sledovaných taxonů bylo v břehové vegetaci Labe nalezeno 15 taxonů. Průměrný počet jedinců na jeden segment byl 516, průměrný počet zaznamenaných taxonů v segmentu činil 2,65. V 11,6 % segmentů nebyl zaznamenán žádný ze sledovaných invazních neofytů. Hodnota prostého indexu zatížení invazními neofyty činila 4,67, hodnota váženého indexu zatížení invazními neofyty činila 2,63. Ve srovnání s ostatními dosud sledovanými vodními toky (Matějček 2008) je v břehové vegetaci Labe spíše podprůměrný počet jedinců na jeden segment, naopak vyšší je průměrný počet zaznamenaných taxonů v jednom segmentu, prostý index zatížení invazními neofyty a vážený index zatížení invazními neofyty. Podíl segmentů bez invazních neofytů je spíše nižší. Nejvyšší podíl obsazených segmentů byl zaznamenán u Solidago sp. (S. canadensis a S. gigantea) a Impatiens glandulifera, nejvyšší průměrný počet jedinců v jednom segmentu byl zaznamenán u Conyza canadensis a Solidago sp., nejvyšší průměrný počet jedinců na jeden obsazený segment byl zaznamenán u Helianthus tuberosus a Conyza canadensis. Ve srovnání s ostatními dosud sledovanými vodními toky v České republice je z hlediska podílu obsazených segmentů pro Labe charakteristické nadprůměrné zastoupení Solidago sp., Conyza canadensis, Erigeron annuus a Robinia pseudacacia, výrazně podprůměrné je naopak zastoupení Impatiens parviflora a Reynoutria sp. Průměrný počet jedinců v obsazeném segmentu byl u většiny taxonů podprůměrný. Poměrně značná je diferenciace výskytu invazních neofytů v jednotlivých částech toku, který byl pro přehlednost rozdělen do sérií (obr. 3). Jako úseky s nejvyšším zastoupením invazních neofytů byly shledány úsek těsně pod Kolínem a úsek u Těchlovic. Zcela zanedbatelný počet jedinců i taxonů invazních neofytů byl naopak zaznamenán v úseku nad Špindlerovým Mlýnem. S výjimkou těchto extrémních poloh však nebyla závislost zastoupení invazních neofytů na pořadí segmentu v rámci toku potvrzena. V období let 2006–2007 došlo k relativně malým změnám v zastoupení invazních neofytů v břehové vegetaci Labe. Výraznější změny byly zaznamenány pouze u některých početně slaběji zastoupených taxonů.

Apolline Louvet

We introduce a new model for plant metapopulations with a seed bank component, living in a fragmented environment in which local extinction events are frequent. This model is an intermediate between population dynamics models with a seed bank component, based on the classical Wright-Fisher model, and Stochastic Patch Occupancy Models (SPOMs) used in metapopulation ecology. Its main feature is the use of "ghost" individuals, which can reproduce but with a very strong selective disadvantage against "real" individuals, to artificially ensure a constant population size. We show the existence of an extinction threshold above which persistence of the subpopulation of "real" individuals is not possible, and investigate how the seed bank characteristics affect this extinction threshold. We also show the convergence of the model to a SPOM under an appropriate scaling, bridging the gap between individual-based models and occupancy models.

Robert J. Taggart

We present a method for comparing point forecasts in a region of interest, such as the tails or centre of a variable's range. This method cannot be hedged, in contrast to conditionally selecting events to evaluate and then using a scoring function that would have been consistent (or proper) prior to event selection. Our method also gives decompositions of scoring functions that are consistent for the mean or a particular quantile or expectile. Each member of each decomposition is itself a consistent scoring function that emphasises performance over a selected region of the variable's range. The score of each member of the decomposition has a natural interpretation rooted in optimal decision theory. It is the weighted average of economic regret over user decision thresholds, where the weight emphasises those decision thresholds in the corresponding region of interest.

Siddharth R. Mohite, Priyadarshini Rajkumar, Shreya Anand et al.

We present ${\tt nimbus}$ : a hierarchical Bayesian framework to infer the intrinsic luminosity parameters of kilonovae (KNe) associated with gravitational-wave (GW) events, based purely on non-detections. This framework makes use of GW 3-D distance information and electromagnetic upper limits from multiple surveys for multiple events, and self-consistently accounts for finite sky-coverage and probability of astrophysical origin. The framework is agnostic to the brightness evolution assumed and can account for multiple electromagnetic passbands simultaneously. Our analyses highlight the importance of accounting for model selection effects, especially in the context of non-detections. We show our methodology using a simple, two-parameter linear brightness model, taking the follow-up of GW190425 with the Zwicky Transient Facility (ZTF) as a single-event test case for two different prior choices of model parameters -- (i) uniform/uninformative priors and (ii) astrophysical priors based on surrogate models of Monte Carlo radiative transfer simulations of KNe. We present results under the assumption that the KN is within the searched region to demonstrate functionality and the importance of prior choice. Our results show consistency with ${\tt simsurvey}$ -- an astronomical survey simulation tool used previously in the literature to constrain the population of KNe. While our results based on uniform priors strongly constrain the parameter space, those based on astrophysical priors are largely uninformative, highlighting the need for deeper constraints. Future studies with multiple events having electromagnetic follow-up from multiple surveys should make it possible to constrain the KN population further.

Zhaoyi Xu, Cong Shi, Tianfang Zhang et al.

Vital sign monitoring plays a critical role in tracking the physiological state of people and enabling various health-related applications (e.g., recommending a change of lifestyle, examining the risk of diseases). Traditional approaches rely on hospitalization or body-attached instruments, which are costly and intrusive. Therefore, researchers have been exploring contact-less vital sign monitoring with radio frequency signals in recent years. Early studies with continuous wave radars/WiFi devices work on detecting vital signs of a single individual, but it still remains challenging to simultaneously monitor vital signs of multiple subjects, especially those who locate in proximity. In this paper, we design and implement a time-division multiplexing (TDM) phased-MIMO radar sensing scheme for high-precision vital sign monitoring of multiple people. Our phased-MIMO radar can steer the mmWave beam towards different directions with a micro-second delay, which enables capturing the vital signs of multiple individuals at the same radial distance to the radar. Furthermore, we develop a TDM-MIMO technique to fully utilize all transmitting antenna (TX)-receiving antenna (RX) pairs, thereby significantly boosting the signal-to-noise ratio. Based on the designed TDM phased-MIMO radar, we develop a system to automatically localize multiple human subjects and estimate their vital signs. Extensive evaluations show that under two-subject scenarios, our system can achieve an error of less than 1 beat per minute (BPM) and 3 BPM for breathing rate (BR) and heartbeat rate (HR) estimations, respectively, at a subject-to-radar distance of $1.6~m$. The minimal subject-to-subject angle separation is $40°$, corresponding to a close distance of $0.5~m$ between two subjects, which outperforms the state-of-the-art.

Josie Plachta, Charlie Tomlin, Rachel Shipsey

Introduction Data Linkage of hashed datasets is much more difficult than linking in-the-clear data. Hashing prevents the use of matching tools that overcome messy data such as ‘contained-within’ functions and edit distance metrics. Hashing sensitive data received from third parties is becoming more common due to increased Data Security concerns. Institutions need to be ready to link hashed data with high accuracy, otherwise the quality of outputs from these linked datasets will suffer. Objectives and Approach We designed an innovative matching method, Derive and Conquer (D&C). We derived variables containing substrings or patterns of the full variable (e.g. Soundex or first 4 characters of a string) to match on instead. However, using lots of combinations of these derived variables would require thousands of traditional match keys to be programmed, run, and reviewed. Instead, D&C runs matchkeys on a derived agreement variable which amalgamates information stored in multiple derived variables into one value, reducing the number of matchkeys to a manageable amount. D&C runs on distributing computing systems using PySpark to link datasets containing millions of records in a timely manner. Results D&C was developed using in-the-clear UK Census and health records with results comparable to the in-the-clear gold standard. It is currently being tested on hashed data to link UK tax and benefits data to UK health records. 66.4 million records were declared matched - a realistic match rate for the UK population. Research into the linkage quality is ongoing to produce estimates on the amount of bias in the linkage and the precision and recall. We will be excited to present these results at the Conference in October. These results will be used to improve D&C. Conclusion / Implications Using these derived variables, we have been able to overcome the challenge of matching massive hashed datasets with a realistic match rate and in a realistic time frame.

Philip Rees

Alice Goisis, Melissa Martinson, Wendy Sigle

<b>Background</b>: A range of studies report a robust association between family socioeconomic position and the prevalence of child overweight/obesity. On average, children from poorer backgrounds are more likely to be overweight/obese than children from more advantaged families. However, a small number of US studies have shown that, for ethnic minority children, the association is either nonexistent or reversed. <b>Objective</b>: We test if the link between socioeconomic position and child overweight/obesity at age 7 is heterogeneous in the United Kingdom where rates of obesity are particularly high for some groups of ethnic minority children. <b>Methods</b>: We use nationally representative data from the UK Millennium Cohort Study as well as descriptive analyses and logistic regression models. <b>Results</b>: Poorer White children are at higher risk of overweight/obesity than higher income White children. However, socioeconomic disparities are reversed for Black African/Caribbean children and nonexistent for children of Indian and Pakistani/Bangladeshi origin. Moreover, the health behaviours that explain socioeconomic disparities in child overweight/obesity for the White group appear to be irrelevant in explaining differences by socioeconomic position for the Black Caribbean and African groups. <b>Conclusions</b>: We should be careful in assuming that higher socioeconomic position is protective against child overweight/obesity for all groups of the population. <b>Contribution</b>: This study shows for the first time important variation by ethnicity in the link between socioeconomic position and child overweight/obesity - and in the underlying mechanisms linking them - in the United Kingdom.