Preventive medicine
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Preventive medicine · Sep 2023
School-level self-reported versus objective measurements of body mass index in public high school students.
Population-level surveillance of student weight status (particularly monitoring students with a body mass index (BMI) ≥95th percentile) remains of public health interest. However, there is mounting concern about objectively measuring student BMI in schools. Using data from the nation's largest school district, we determined how closely students' self-reported BMI approximates objectively-measured BMI, aggregated at the school level, to inform decision-making related to school BMI measurement practices. ⋯ Based on the objective measurement, 12.1% of students were classified as having obesity and 6.3% as having severe obesity (per CDC definition); the self-report data yielded 2.5 (95% CI: -1.964, -0.174) and 1.4 (95% CI: -2.176, -0.595) percentage point underestimates in students with obesity and severe obesity, respectively. This translates to 13% of students with obesity and 21% of students with severe obesity being misclassified if using self-reported BMI. School-level high school students' self-reported data underestimate the prevalence of students with obesity and severe obesity and is particularly poor at identifying highest-risk students based on BMI percentile.
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Preventive medicine · Sep 2023
Musculoskeletal pain intensity and risk of long-term sickness absence in the general working population: A prospective cohort study with register follow-up.
Determining predictors of sickness absence could allow for better screening, guidance, and development of preventive efforts aimed at those in increased risk. This study aimed to determine the prospective association between musculoskeletal pain intensity and risk of incident register-based long-term sickness absence in the general working population, as well as to determine the population attributable fraction. Drawing on data from a nation-wide questionnaire survey, this prospective cohort study followed a representative sample of the Danish general working population without recent long-term sickness absence (≥6 consecutive weeks) (n = 69,273) for long-term sickness absence up to two years (mean follow-up: 93 weeks) in a national register. ⋯ We observed a clear dose-response association between musculoskeletal pain intensity of the neck/shoulder or low-back and the risk of incident long-term sickness absence, with a lower threshold of increased risk of 4 and 3 (scale 0-10) for neck/shoulder (HR (95% CI): 1.25 (1.09-1.42)) and low-back pain (HR (95% CI): 1.13 (1.00-1.29)), respectively. Prevention of pain intensities at or above 4 out of 10 could potentially prevent 17% (population attributable fraction, PAF (95% CI): 16.8 (13.6-20.1)) of the total long-term sickness absence in the general working population. Large-scale interventions to prevent and manage musculoskeletal pain need to be documented and implemented.
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Preventive medicine · Sep 2023
Ultra-processed food consumption and exposure to acrylamide in a nationally representative sample of the US population aged 6 years and older.
Ultra-processed food (UPF) consumption has been associated with cardiovascular disease and cancer. Acrylamide is a probable human carcinogen commonly found in foods that are processed at high temperatures. The aim of this study was to examine the association between dietary energy contribution of UPF and acrylamide exposure, in the US. ⋯ These positive associations were statistically significant among males and in the young adult population and were largely driven by UPF which are known potential sources of acrylamide. The main effects remained unchanged when excluding current smokers. As both acrylamides and UPF have been previously associated with cardiovascular disease and cancer, our results suggest that acrylamides in UPF may partially explain previously observed links between UPF consumption and these health outcomes.
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Preventive medicine · Sep 2023
The effect of enteral nutrition nursing intervention on postoperative treatment of chronic critically ill patients: Health prevention data analysis.
The field of genomics has witnessed remarkable advancements, leading to the gradual clarification of the genetic mechanism underlying various cancers. As a result, there has been an increased emphasis on gene prevention and treatment. Against this backdrop, this paper aims to examine the impact of enteral nutrition nursing intervention on the postoperative treatment of patients with chronic critical illness, with a focus on health prevention. ⋯ The study's results provide valuable insights into the efficacy of enteral nutrition nursing intervention in the postoperative treatment of patients with chronic critical illness. By improving the nutritional status of patients, enteral nutrition nursing intervention can help reduce the risk of complications, shorten the length of hospital stay, and enhance the effectiveness of postoperative rehabilitation. These findings underscore the importance of adopting effective interventions such as enteral nutrition nursing to improve the therapeutic outcomes of chronic critical illness patients and achieve the goal of health prevention.
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Preventive medicine · Sep 2023
Athlete body fat rate monitoring and motion image simulation based on SDN data center network and sensors.
With the development of artificial intelligence technology, new software is also emerging in an endless stream. On the basis of sensors, the new software realizes the separation of network control layer and data layer, thereby improving network throughput and link utilization. With the gradual maturity of deep reinforcement learning technology, the redefined network architecture can be managed and controlled through software, making the network evolve toward a more intelligent direction. ⋯ This paper proposes a scheduling strategy based on machine learning, combining the reinforcement learning algorithm in machine learning and deep reinforcement learning algorithm, setting the key factors of reinforcement learning, and applying it to real-time sports images of athletes, combining the sports characteristics of athletes, Set the action and reward value. Then use the algorithm to allocate a reasonable path for data transmission according to the real-time status to reduce network delay. This article will use sensor technology and data center network to provide a new method for athletes' real-time motion images and body fat percentage.