Diabetes/metabolism research and reviews · 2025
Contributions of Clinical Obesity and Preclinical Obesity to the All-Cause Mortality Risk: Findings From the UK Biobank Cohort.
СтатьяПоддержка NIH: внешняя программаПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Xu Manrong, Li Menghan, Zhang Yawen, Li Lianxi, Shen Yun, Hu Gang
Аннотация
BACKGROUND: The definition of clinical obesity was newly announced. The aim of our study was to investigate the association of preclinical obesity and clinical obesity either at baseline or determined during follow-ups with the risk of all-cause mortality.
METHODS: Data were collected from 232,721 participants in the UK Biobank. Dysfunctions caused by obesity, in combination with an excess of anthropometric parameters, were used to diagnose clinical obesity. Participants were categorised into six clusters according to their baseline and follow-up dysfunction status. Time-dependent Cox proportional hazards regression was used to compare hazard ratios (HRs) for mortality across six clusters.
RESULTS: In a total of 19,704 deaths over a mean follow-up of 13.4 years, participants in Cluster 6 (clinical obesity at baseline; HR = 2.30, 95% CI: 2.16-2.44) and Cluster 3 (non-obesity with baseline dysfunctions; HR = 2.02, 95% CI: 1.85-2.20) exhibited the highest multivariable-adjusted mortality risk compared with participants without obesity and dysfunction at baseline and during follow-up (Cluster 1). This was followed by participants in Cluster 2 (non-obesity without baseline but with follow-up dysfunctions; HR = 1.99, 95% CI: 1.88-2.10), Cluster 5 (preclinical obesity with follow-up dysfunctions; HR = 1.97, 95% CI: 1.87-2.07), and Cluster 4 (preclinical obesity without follow-up dysfunctions; HR = 1.15, 95% CI: 1.09-1.22). Subgroup analyses showed consistently higher mortality risks in Cluster 6 across various demographics, notably among individuals with higher educational qualifications.
CONCLUSIONS: Clinical obesity was significantly associated with elevated all-cause mortality risk. These findings underscore the importance of early screening and intervention for dysfunctions in patients with obesity.
METHODS: Data were collected from 232,721 participants in the UK Biobank. Dysfunctions caused by obesity, in combination with an excess of anthropometric parameters, were used to diagnose clinical obesity. Participants were categorised into six clusters according to their baseline and follow-up dysfunction status. Time-dependent Cox proportional hazards regression was used to compare hazard ratios (HRs) for mortality across six clusters.
RESULTS: In a total of 19,704 deaths over a mean follow-up of 13.4 years, participants in Cluster 6 (clinical obesity at baseline; HR = 2.30, 95% CI: 2.16-2.44) and Cluster 3 (non-obesity with baseline dysfunctions; HR = 2.02, 95% CI: 1.85-2.20) exhibited the highest multivariable-adjusted mortality risk compared with participants without obesity and dysfunction at baseline and during follow-up (Cluster 1). This was followed by participants in Cluster 2 (non-obesity without baseline but with follow-up dysfunctions; HR = 1.99, 95% CI: 1.88-2.10), Cluster 5 (preclinical obesity with follow-up dysfunctions; HR = 1.97, 95% CI: 1.87-2.07), and Cluster 4 (preclinical obesity without follow-up dysfunctions; HR = 1.15, 95% CI: 1.09-1.22). Subgroup analyses showed consistently higher mortality risks in Cluster 6 across various demographics, notably among individuals with higher educational qualifications.
CONCLUSIONS: Clinical obesity was significantly associated with elevated all-cause mortality risk. These findings underscore the importance of early screening and intervention for dysfunctions in patients with obesity.