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An association between body mass index (BMI; weight (kg)/height (m)2) and low back pain (LBP) has long been debated, but inconsistent measurements of BMI and varying definitions of LBP have produced conflicting findings. We explored this association using measured BMI and physician documentation of recurrent LBP among healthy young adults. Data were extracted from the Israel Defense Forces electronic medical record system. All Israeli citizens with compulsory military service during January 2008–March 2019 were included (n  = 705,840). Exclusion criteria were spine deformities, disc pathologies, spinal surgeries, arthropathies, connective tissue diseases, pain syndromes, low bone density disorders, cancers, and psychiatric illnesses. LBP was defined as electronic medical record system documentation of 1) 2 medical visits at least 6 weeks apart with a diagnosis of LBP or "LBP with radiation" or 2) 1 medical visit resulting in referral to an orthopedic surgeon. Logistic regression models were used to explore the association between BMI category and LBP; 619,969 (87.8%) individuals (mean age = 18.9 (standard deviation, 0.97) years; 56.9% male) were included. LBP prevalence was 9.2% (n  = 56,918) and higher among males (9.7%) than females (8.5%). Overweight (odds ratio = 1.123, 95% confidence interval: 1.096, 1.151) and obesity (odds ratio = 1.137, 95% confidence interval: 1.096, 1.179) were associated with LBP. The association remained significant after accounting for various sociodemographic factors. Maintaining a healthy BMI may aid in the prevention of LBP in young adults. [ABSTRACT FROM AUTHOR]

Objective To assess the clinical features and infectivity of variant B.1.1.7 among healthy young adults in a military setting. Materials and Methods Positive cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in a single military base (March 23, 2020 and February 16, 2021) were included. An epidemiological investigation conducted via phone included questions regarding symptoms, exposure history, smoking status, list of contacts, and recently visited places. Symptoms surveyed included fever, cough, shortness of breath, sore throat, loss of smell or taste, gastrointestinal symptoms (GI), headache, chest pain, and constitutional symptoms. Cases were divided before B.1.1.7 first reported case in Israel (December 23, 2020) (period 1) and after its identification (period 2). Symptom distribution and the risk of a contact to be infected were compared between the periods, using a chi-square test, and a negative binominal regression model, respectively. Results Of 293 confirmed cases, 89 were reported in the first period and 204 in the second. 56.0% were men with a median age of 19.5 years (interquartile range 18.6-20.5). GI symptoms, loss of taste or smell, headache, fever, and chills were more prevalent in the first period (P  < .001, P  = .026, P  = .034, P  = .001, and P  < .001, respectively), while fatigue was more common in the second period (P  = .008). The risk of a contact to be infected was three times higher in the second period (relative risk  = 3.562 [2.414-5.258]). Conclusion An outbreak of SARS-CoV-2 in young healthy adults, during a period with high national-wide B.1.1.7 variant prevalence, is characterized by decreased prevalence of fever, loss of taste or smell and GI symptoms, increased reports of fatigue, and more infected contacts for each index case. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 outbreak required prompt actions by health authorities around the world, in response to a novel threat. With enormous amounts of information originating in sources with uncertain degree of validation and accuracy, it is essential to provide executive level decision makers with the most actionable, pertinent and updated data analysis to enable them to adapt their strategy swiftly and competently.Objective: We report here the origination of a COVID-19 dedicated response in the Israel Defense Force (IDF) with the assembly of an operational Data Center for the Campaign against Coronavirus (ID3C).Methods: Spearheaded by directors with clinical, operational and data analytics orientation a multidisciplinary team utilized existing and newly developed platforms to collect and analyze large amounts of information for on an individual-level in the context of SARS-CoV2 contraction and infection.Results: Nearly 300,000 responses for daily questionnaires were recorded and were merged with other datasets to form unified data lake. By using basic as well as advanced analytic tools ranging from simple aggregation and display of trends to data-science application we provided commanders and clinicians with access to trusted, accurate and personalized information and tools that were designed to foster operational changes and mitigate the propagation of the pandemic. The developed tools aided in the in the identification of high-risk individuals for severe disease, resulted in a 30% decline of their attendance to their units. Moreover, the Corona lab exams queue was optimized by using a predictive model resulted in a high true positive rate of 20%, which is more than twice as high as the baseline rate (2.28 with 95% CI of 1.63-3.19).Conclusions: In times of ambiguity and uncertainty mixed with unprecedented flux of information, health organizations may find multidisciplinary teams working to provide intelligence from diverse and rich data, a key factor in providing executives relevant and actionable support for decision making.Clinicaltrial: [ABSTRACT FROM AUTHOR]

Background: Morbidities related to obesity are usually associated with its severity and duration. Yet, the onset of serious morbidities in early adulthood among otherwise healthy adolescents with obesity is understudied. We aimed to investigate the association between adolescent BMI and serious morbidities before age 25 years., Methods: In this nationwide, retrospective cohort study, we included Israeli conscripts aged 17-21 years who underwent pre-recruitment medical evaluation between Jan 1, 1996, and Dec 31, 2017, were deemed medically eligible for military service, and were recruited to the Israeli Defense Forces between 1998 and 2018. Exclusion criteria were missing height or weight or service ineligibility for non-medical or medical reasons. Baseline BMI was converted into age-specific and sex-specific percentiles and classified using the US Centers for Disease Control and Prevention categories. The primary outcome was incidence of serious morbidity disqualifying individuals from completing mandatory service. Participants were followed from enlistment until end of service (3 years for males and 2 years for females), onset of serious morbidity, or Dec 31, 2021. Cox models with adjustment to various socio-economic confounders were applied to calculate the hazard ratio (HR) and 95% CI for serious morbidity for the BMI categories., Findings: A total of 1 264 355 adolescents aged 16-20 years were assessed for military service. 145 702 were excluded; 144 705 were considered ineligible for service (133 112 for non-medical reasons and 11 593 for medical reasons), and 2867 had missing height or weight data. The study included 1 118 653 individuals (622 989 [55·7%] males and 495 664 [44·3%] females), with 23 347 cases of serious morbidity recorded over 2 534 873 person-years. Incidence of serious morbidity increased across BMI groups in both sexes. Among males, compared with those with normal BMI, the adjusted HRs were 0·89 (95% CI 0·83-0·95) for underweight, 1·21 (1·16-1·27) for overweight, 1·39 (1·32-1·47) for obesity class 1, 2·82 (2·60-3·06) for obesity class 2, and 5·14 (4·37-6·04) for obesity class 3. For females, the respective ratios were HR 0·95 (95% CI 0·84-1·09) for underweight, 1·27 (1·17-1·37) for overweight, 1·63 (1·45-1·82) for obesity class 1, 4·00 (3·46-4·61) for obesity class 2, and 7·30 (5·65-9·43) for obesity class 3. Results persisted in sensitivity analyses restricted to those with unimpaired health at baseline or those in civilian-equivalent office employments., Interpretation: Obesity in otherwise healthy adolescents was linked with increased risk of serious morbidity before age 25 years. Reducing adolescent obesity will have substantial short-term and long-term health benefits in young adults., Funding: Sheba Medical Center., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2024 Published by Elsevier Ltd. All rights reserved, including those for text and data mining, AI training, and similar technologies.)

Background: The COVID-19 outbreak required prompt action by health authorities around the world in response to a novel threat. With enormous amounts of information originating in sources with uncertain degree of validation and accuracy, it is essential to provide executive-level decision-makers with the most actionable, pertinent, and updated data analysis to enable them to adapt their strategy swiftly and competently., Objective: We report here the origination of a COVID-19 dedicated response in the Israel Defense Forces with the assembly of an operational Data Center for the Campaign against Coronavirus., Methods: Spearheaded by directors with clinical, operational, and data analytics orientation, a multidisciplinary team utilized existing and newly developed platforms to collect and analyze large amounts of information on an individual level in the context of SARS-CoV-2 contraction and infection., Results: Nearly 300,000 responses to daily questionnaires were recorded and were merged with other data sets to form a unified data lake. By using basic as well as advanced analytic tools ranging from simple aggregation and display of trends to data science application, we provided commanders and clinicians with access to trusted, accurate, and personalized information and tools that were designed to foster operational changes and mitigate the propagation of the pandemic. The developed tools aided in the in the identification of high-risk individuals for severe disease and resulted in a 30% decline in their attendance to their units. Moreover, the queue for laboratory examination for COVID-19 was optimized using a predictive model and resulted in a high true-positive rate of 20%, which is more than twice as high as the baseline rate (2.28%, 95% CI 1.63%-3.19%)., Conclusions: In times of ambiguity and uncertainty, along with an unprecedented flux of information, health organizations may find multidisciplinary teams working to provide intelligence from diverse and rich data a key factor in providing executives relevant and actionable support for decision-making., (©Gil A Geva, Itay Ketko, Maya Nitecki, Shoham Simon, Barr Inbar, Itay Toledo, Michael Shapiro, Barak Vaturi, Yoni Votta, Daniel Filler, Roey Yosef, Sagi A Shpitzer, Nabil Hir, Michal Peri Markovich, Shachar Shapira, Noam Fink, Elon Glasberg, Ariel Furer. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 10.09.2021.)