RÉSUMÉ
Background: This study aims to assess the global incidence, mortality, and disability-adjusted life years (DALYs) of thyroid cancer between 1990 and 2030. Methods: Our study analysed Global Burden of Disease (GBD) 2019 data from 204 countries, spanning 1990-2019. It focused on age-standardised thyroid cancer incidence, mortality, and disability-adjusted life years (DALYs), using the sociodemographic index (SDI) for assessing socioeconomic levels. Generalised additive models (GAMs) projected thyroid cancer trends for 2020-2030. Results: The global burden of thyroid cancer is predicted to increase significantly from 1990 to 2030. The number of thyroid cancer incidence cases is projected to rise from 233 846.64 in 2019 to 305 078.08 by 2030, representing an approximate 30.46% increase. The ASIR (age-standardised incidence rate) is expected to continue its upward trend (estimated annual percentage change (EAPC) = 0.83). The age-standardised death rate (ASDR) for thyroid cancer is projected to decline in both genders, more notably in women (EAPC = -0.34) compared to men (EAPC = -0.17). The burden of disease escalates with advancing age, with significant regional disparities. Regions with lower SDI, particularly in South Asia, are anticipated to witness substantial increases in thyroid cancer incidence from 2020 to 2030. The overall disease burden is expected to rise, especially in countries with low to middle SDI, reflecting broader socio-economic and health care shifts. Conclusions: This study highlights significant regional and gender-specific variations in thyroid cancer, with notable increases in incidence rates, particularly in areas like South Asia. These trends suggest improvements in diagnostic capabilities and the influence of socio-economic factors. Additionally, the observed decline in mortality rates across various regions reflects advancements in thyroid cancer management. The findings underline the critical importance of regionally tailored prevention strategies, robust cancer registries, and public health initiatives to address the evolving landscape of thyroid cancer and mitigate health disparities globally.
Sujet(s)
Mort périnatale , Tumeurs de la thyroïde , Humains , Mâle , Femelle , Charge mondiale de morbidité , Années de vie ajustées sur la qualité , Coûts indirects de la maladie , Incidence , Tumeurs de la thyroïde/épidémiologie , Santé mondialeRÉSUMÉ
BACKGROUND: Falls pose a severe threat to the health of older adults worldwide. Determining gait and kinematic parameters that are related to an increased risk of falls is essential for developing effective intervention and fall prevention strategies. This study aimed to investigate the discriminatory parameter, which lay an important basis for developing effective clinical screening tools for identifying high-fall-risk older adults. METHODS: Forty-one individuals aged 65 years and above living in the community participated in this study. The older adults were classified as high-fall-risk and low-fall-risk individuals based on their BBS scores. The participants wore an inertial measurement unit (IMU) while conducting the Timed Up and Go (TUG) test. Simultaneously, a depth camera acquired images of the participants' movements during the experiment. After segmenting the data according to subtasks, 142 parameters were extracted from the sensor-based data. A t-test or Mann-Whitney U test was performed on the parameters for distinguishing older adults at high risk of falling. The logistic regression was used to further quantify the role of different parameters in identifying high-fall-risk individuals. Furthermore, we conducted an ablation experiment to explore the complementary information offered by the two sensors. RESULTS: Fifteen participants were defined as high-fall-risk individuals, while twenty-six were defined as low-fall-risk individuals. 17 parameters were tested for significance with p-values less than 0.05. Some of these parameters, such as the usage of walking assistance, maximum angular velocity around the yaw axis during turn-to-sit, and step length, exhibit the greatest discriminatory abilities in identifying high-fall-risk individuals. Additionally, combining features from both devices for fall risk assessment resulted in a higher AUC of 0.882 compared to using each device separately. CONCLUSIONS: Utilizing different types of sensors can offer more comprehensive information. Interpreting parameters to physiology provides deeper insights into the identification of high-fall-risk individuals. High-fall-risk individuals typically exhibited a cautious gait, such as larger step width and shorter step length during walking. Besides, we identified some abnormal gait patterns of high-fall-risk individuals compared to low-fall-risk individuals, such as less knee flexion and a tendency to tilt the pelvis forward during turning.