Association between multisite musculoskeletal pain and disability trajectories among community-dwelling older adults.

BACKGROUND: Pain is linked to disability, but how multisite musculoskeletal pain leads to disability over time is not well elaborated. OBJECTIVE: To examine the associations of multisite musculoskeletal pain with disability among a nationally representative cohort. DESIGN: We used data from the National Health and Aging Trends Study (NHATS) 2015-22. Disability was assessed by basic activities of daily living (ADL) and instrumental activities of daily living (IADL). PARTICIPANTS: A total of 5557 individuals with multisite musculoskeletal pain dwelling in the community were included in this study. METHODS: Group-based trajectory models were applied to identify distinct profiles of disability in ADL and IADL. Design-based logistic regressions were used to examine associations among multisite musculoskeletal pain, disability, and dual trajectory group memberships, adjusted for sociodemographic, health status, behavioral, and mental characteristics. RESULTS: Persons who experienced multisite musculoskeletal pain were at higher risk of disability in ADL and IADL. We identified five heterogeneous disability trajectories and named them based on baseline levels and rates of increase over time. Approximately, 52.42% of older adults with multisite musculoskeletal pain were in trajectories with ADL and IADL declines, and 33.60% experienced a rapid decline. Multisite musculoskeletal pain was associated with elevated relative risk for the adverse disability trajectories, which generally increases with multisite musculoskeletal pain frequency and number of sites. CONCLUSIONS: Persons with multisite musculoskeletal pain had a higher risk of disability. It is essential to adopt effective pain management strategies to maintain the independent living ability of older adults and to realize active aging.

Ambient fine particulate matter is associated with daily outpatient visits for ankylosing spondylitis: A time-series analysis in Beijing, China.

Exposure to ambient fine particulate matter (PM2.5) has a great impact on human body's immune system, but the correlation between PM2.5 and ankylosing spondylitis has not yet been clarified. We extracted 58,600 outpatient visits for ankylosing spondylitis from the Beijing Medical Claim Data for Employees database from 2010 to 2017. The percentage of outpatient visits following PM2.5 concentrations was estimated using generalized additive models with Poisson connections. Increase by 10 µ g/m3, PM2.5 is associated with daily outpatient visits for ankylosing spondylitis. In this test, the average concentration of PM2.5 was 86.8 ± 74.3 µ g/m3. For every 10 µg/m3 increase in PM2.5 concentration, there was a 0.34% (95% CI, 0.26-0.42%) increase in the risk of patients who visited the doctor on the same day. Females and younger patients were most susceptible to the impact of PM2.5 exposure (P＜0.05). This study revealed the relationship between exposure to PM2.5 and ankylosing spondylitis, and future research can further confirm this finding and explore the potential mechanisms.

Physical frailty trajectories in older stroke survivors: Findings from a national cohort study.

BACKGROUND: Physical frailty (PF) is highly prevalent and associated with undesirable outcomes in stroke survivors aged 65 years or older. However, the long-term trajectories of PF are understudied in those older stroke survivors. AIMS: To identify PF trajectories and relative predictors associated with the PF trajectories in older stroke survivors. DESIGN: This is a secondary analysis of a population-based cohort study in the United States. METHODS: Six hundred and sixty-three older stroke survivors from the National Health and Ageing Trends Study from 2015 to 2021 were included. PF was operationally assessed based on the Fried Frailty Phenotype. Trajectories were identified by group-based trajectory modelling. The associations between sociodemographic characteristics, clinical factors, symptoms, cognitive factors and PF trajectories were examined using the design-based logistic regression method. RESULTS: Most older stroke survivors were 75 and older (63.32%), female (53.99%), white (80.54%) and partnered (50.64%). Two PF trajectory groups were identified (Group 1: low risk, robust; 49.47%; Group 2: high risk, deteriorating; 50.53%). Individuals were at a higher risk to be assigned to Group 2 if they were 75-84 years (adjusted odds ratio [aOR]: 2.16, 95% CI: 1.23-3.80) or 85+ years (aOR: 2.77, 95% CI: 1.52-5.04), had fair self-reported health (aOR: 2.78, 95% CI: 1.53-5.07) or poor self-reported health (aOR: 3.37, 95% CI: 1.51-7.52), had comorbidities (aOR: 8.44, 95% CI: 1.31-54.42), had breathing problems (aOR: 2.18, 95% CI: 1.18-4.02) and had balance problems (aOR: 1.70, 95% CI: 1.06-2.73). CONCLUSION: PF trajectories in older stroke survivors were heterogeneous and were associated with age, self-rated health status, comorbidities, breathing problems and balance problems. IMPLICATION TO CLINICAL PRACTICE: Early, routine, dynamic screening for stroke-related physical frailty (PF) and relative predictors might be beneficial for identifying the most vulnerable individuals. Our findings might help develop strategies to manage PF progression. REPORTING METHOD: The reporting followed the STROBE guideline.

Trajectories and predictors of anxiety and depression among older cancer survivors: a nationally representative cohort study.

PURPOSE: The study aimed to describe the long-term trajectories of anxiety and depression among older cancer survivors and examine sociodemographic and health-related predictors of different trajectories. METHODS: Data were from the National Health and Aging Trends Study. Patient Health Questionnaire-4 was used to assess anxiety and depression. Group-based trajectory model was used to identify the distinct trajectories of anxiety and depression from 2015 to 2021. Design-based multinomial logistic regression was used to examine predictors of different trajectories. All analyses accounted for the complex sample design and survey weights. RESULTS: A total of 1766 older cancer survivors were included representing 8.9 million older cancer survivors. The prevalence of anxiety and depression from 2015 to 2021 ranged from 25.12 to 29.11%. Four trajectories were identified: sustained low-risk (49.0%), deteriorating (24.1%), meliorating (11.0%), and sustained high-risk (16.1%). Potential predictors of high-risk anxiety and depression include older age, female, lower annual income, abnormal BMI, poorer self-rated health, more difficulty in activities of daily living (ADL), and worse cognitive function (P < 0.05). CONCLUSIONS: The anxiety and depression progression patterns are heterogeneous among older cancer survivors. The trajectory affiliations could be predicted by sociodemographic and health-related factors, which have the potential to inform targeted clinical strategies (e.g., improve ADL and ameliorate cognitive function). IMPLICATIONS FOR CANCER SURVIVORS: Anxiety and depression are common among older cancer survivors, and long-term trajectories identified by this study might help realize early-stage identification and individualized interventions for mental disorders.

Clinical prediction models for knee pain in patients with knee osteoarthritis: a systematic review.

OBJECTIVE: To identify and describe existing models for predicting knee pain in patients with knee osteoarthritis. METHODS: The electronic databases PubMed, EMBASE, CINAHL, Web of Science, and Cochrane Library were searched from their inception to May 2023 for any studies to develop and validate a prediction model for predicting knee pain in patients with knee osteoarthritis. Two reviewers independently screened titles, abstracts, and full-text qualifications, and extracted data. Risk of bias was assessed using the PROBAST. Data extraction of eligible articles was extracted by a data extraction form based on CHARMS. The quality of evidence was graded according to GRADE. The results were summarized with descriptive statistics. RESULTS: The search identified 2693 records. Sixteen articles reporting on 26 prediction models were included targeting occurrence (n = 9), others (n = 7), progression (n = 5), persistent (n = 2), incident (n = 1), frequent (n = 1), and flares (n = 1) of knee pain. Most of the studies (94%) were at high risk of bias. Model discrimination was assessed by the AUROC ranging from 0.62 to 0.81. The most common predictors were age, BMI, gender, baseline pain, and joint space width. Only frequent knee pain had a moderate quality of evidence; all other types of knee pain had a low quality of evidence. CONCLUSION: There are many prediction models for knee pain in patients with knee osteoarthritis that do show promise. However, the clinical extensibility, applicability, and interpretability of predictive tools should be considered during model development.

Lubricating Microneedles System with Multistage Sustained Drug Delivery for the Treatment of Osteoarthritis.

Osteoarthritis (OA) is a typical joint degenerative disease that is prevalent worldwide and significantly affects the normal activities of patients. Traditional treatments using diclofenac (DCF) as an anti-inflammatory drug by oral administration and transdermal delivery have many inherent deficiencies. In this study, a lubricating microneedles (MNs) system for the treatment of osteoarthritis with multistage sustained drug delivery and great reduction in skin damage during MNs penetration is developed. The bilayer dissolvable MNs system, namely HA-DCF@PDMPC, is prepared by designating the composite material of hyaluronic acid (HA) and covalently conjugated drug compound (HA-DCF) as the MNs tips and then modifying the surface of MNs tips with a self-adhesive lubricating copolymer (PDMPC). The MNs system is designed to achieve sustained drug release of DCF via ester bond hydrolysis, physical diffusion from MNs tips, and breakthrough of lubrication coating. Additionally, skin damage is reduced due to the presence of the lubrication coating on the superficial surface. Therefore, the lubricating MNs with multistage sustained drug delivery show good compliance as a transdermal patch for OA treatment, which is validated from anti-inflammatory cell tests and therapeutic animal experiments, down-regulating the expression levels of pro-inflammatory factors and alleviating articular cartilage destruction.

Association of body composition and physical activity with pain and function in knee osteoarthritis patients: a cross-sectional study.

OBJECTIVE: The objective of this study is to delineate disparities between patients with knee osteoarthritis (KOA) based on obesity status, investigate the interplay among body composition, physical activity and knee pain/function in patients with KOA and conduct subgroup analyses focusing on those with KOA and obesity. DESIGN: Cross-sectional study. SETTING: Residents of eight communities in Shijiazhuang, Hebei Province, China, were surveyed from March 2021 to November 2021. PARTICIPANTS: 178 patients with symptomatic KOA aged 40 years or older were included. MAIN OUTCOMES AND MEASURES: The primary outcome measure was knee pain, assessed using the Western Ontario and McMaster Universities Osteoarthritis Index-pain (WOMAC-P) scale. Secondary outcome measures included function, evaluated through the WOMAC-function (WOMAC-F) scale and the Five-Time-Sit-to-Stand Test (FTSST). Data analysis involved t-tests, Wilcoxon rank-sum tests, χ2 tests, linear and logistical regression analysis. RESULTS: Participants (n=178) were 41-80 years of age (median: 65, P25-P75: 58-70), and 82% were female. Obese patients (n=103) had worse knee pain and self-reported function (p<0.05). In general patients with KOA, body fat mass was positively associated with bilateral knee pain (ß=1.21 (95% CI 0.03 to 0.15)), WOMAC-P scores (ß=0.25 (95% CI 0.23 to 1.22)), WOMAC-F scores (ß=0.28 (95% CI 0.35 to 1.29)) and FTSST (ß=0.19 (95% CI 0.03 to 0.42)), moderate-intensity to low-intensity physical activity was negatively associated with bilateral knee pain (ß=-0.80 (95% CI -0.10 to -0.01)) and Skeletal Muscle Index (SMI) was negatively associated with WOMAC-F scores (ß=-0.16 (95% CI -0.66 to -0.03)). In patients with KOA and obesity, SMI was negatively associated with FTSST (ß=-0.30 (95% CI -3.94 to -0.00)). CONCLUSION: Patients with KOA and obesity had worse knee pain and self-reported function compared with non-obese patients. Greater fat mass, lower muscle mass and lower moderate-intensity to low-intensity physical activity were associated with increased knee pain and poor self-reported function. More skeletal muscle mass was associated with the improvement of objective function.

The impact of heat waves and cold spells on pneumonia risk: A nationwide study.

Climate change affects human health and has been linked to several infectious diseases in recent year. However, there is limited assessment on the impact of heat waves and cold spells on pneumonia risk. This study aims to examine the association of heat waves and cold spells with daily pneumonia hospitalizations in 168 cities in China. Data on pneumonia hospitalizations between 2014 and 2017 were extracted from a national claim database of 280 million beneficiaries. We consider combining temperature intensity and duration to define heat waves and cold spells.This association was quantified using a quasi-Poisson generalized linear model combined with a distributed lag nonlinear model. Exposure-response curves and potential effect modifiers were also estimated. We found that the peak relative risk (RR) of cold spells on daily hospitalizations for pneumonia was observed in relatively mild cold spells with a threshold below the 3 days at the 2nd percentile (RR = 1.69, 95% CI: 1.46-1.92). The risk of heat waves increased with the thresholds, and the greatest risk was found for extremely heatwave period of 4 days at the 98th percentile (RR = 1.69, 95% CI: 1.46-1.92). Heat waves and cold spells are more likely to adversely affect women. In conclusion, our study provided novel and strong evidence that exposure to heat waves and cold spells was associate with increased hospital visits for pneumonia, especially in females. This is the first national study in China to comprehensively evaluate the influence of heat waves and cold spells on pneumonia risk, and the findings may offer valuable insights into the impact of climate change on public health.

Long-term cognitive effects of electroconvulsive therapy in major depressive disorder: A systematic review and meta-analysis.

OBJECTIVE: Electroconvulsive therapy (ECT) is endorsed as a principal treatment approach for major depressive disorder (MDD) worldwide. Despite prior studies highlighting potential short-term cognitive deficits post-ECT, the debate regarding its long-term implications persists. This study endeavors to elucidate the reasons for this contention using an evidence-based approach. METHODS: This investigation, meticulously aligned with PRISMA guidelines, was prospectively enlisted on PROSPERO (CRD42023439259). A comprehensive search was performed across various databases, including PubMed, Cochrane Library, Web of Science, Embase, SCOPUS, PsycINFO, CINAHL Plus, and OpenGrey. This review, traversing the literature from inception until June 2023, encapsulated 10 studies (five RCTs and five quasi-experimental studies) involving a cohort of 868 individuals diagnosed with major depressive disorder. RESULTS: The meta-analysis revealed that the persistent discourse on ECT-induced long-term cognitive impairment chiefly emanates from the inadequacies in the specificity and sensitivity of conventional assessment instruments. Conversely, subgroup analyses showed that cognitive impairment in ECT, as gauged by the nascent assessment tool, Electroconvulsive Therapy Cognitive Assessment (ECCA) (SMD = -0.94, 95 % CI [-1.33, -0.54], p < 0.00001), exerted a detrimental influence on the long-term trajectory of individuals with MDD. Notably, there was an adverse effect of ECT on the subdomain of long-term learning cognitive abilities in patients with MDD (SMD = -0.37, 95 % CI [-0.55, -0.18], p < 0.0001). Contrarily, memory (SMD = 0.16, 95 % CI [-0.02, 0.34], p = 0.08), attention (SMD = 0.23, 95 % CI [-0.07, 0.54], p = 0.14), language (SMD = -0.10, 95 % CI [-0.25, 0.05], p = 0.19), spatial perception, and orientation (SMD = -0.04, 95 % CI [-0.28, 0.20], p = 0.75) exhibited no significant detriments. Intriguingly, ECT showed favorable effects on executive function and processing speed among patients with MDD (SMD = 0.52, 95 % CI [0.29, 0.74], p < 0.00001). CONCLUSION: This meta-analysis underscores ECCA's superior sensitivity of the ECCA compared to the MMSE or MoCA in detecting cognitive changes in patients with post-ECT MDD. Following Electroconvulsive Therapy (ECT), deterioration was observed in overall cognitive function and learning capabilities, while memory, attention, language, and spatial perception remained stable. Notably, enhancements were discerned in executive function and processing speed, which not only augmented academic perspectives but also steered the formulation of international clinical guidelines, accentuating the progressive role of ECT in the therapeutic approach to MDD.

[A Health Education Program for Home Emergency Management of Acute Complications of Diabetes in the Elderly].

Objective To establish a health education program for home emergency management of acute complications of diabetes in the elderly.Methods The program was drafted by literature review and panel discussion.The final draft was formed after two rounds of correspondence from 13 experts.Results The recovery rate of the two rounds of expert correspondence was 100%,and the expert authority coefficient was 0.98.The Kendall's harmony coefficients of the two rounds of correspondence were 0.263 and 0.212 respectively(both P<0.001).The established health education program included indicators of three categories:early stage of acute complications of diabetes at home(understanding the inducing factors),emergency warning(quick and early identification in case of emergency),and emergency treatment at home.Conclusion The contents of the health education program are systematic and reliable and meet the needs of health education for home emergency management of the elderly with diabetes.

Long-term trajectories of frailty phenotype in older cancer survivors: a nationally representative longitudinal cohort study.

BACKGROUND: Frailty is a dynamic process associated with adverse health outcomes. However, little is known about the long-term trajectories of frailty in older cancer survivors. OBJECTIVES: To describe the trajectories of frailty phenotype over time amongst older cancer survivors and examine the socio-demographic and health-related predictors of different trajectories. DESIGN: Population-based longitudinal cohort study. SETTING: Community-dwelling older adults in the United States. SUBJECTS: 1,763 older adults who were diagnosed with cancer from the National Health and Ageing Trends Study. METHODS: Frailty was assessed by the Fried Frailty Phenotype. The group-based trajectory model was used to identify the trajectories of frailty. Multinomial logistic regression analyses were used to examine the socio-demographic and health-related predictors of different trajectories. RESULTS: Three frailty trajectories were identified; 52.8% of older cancer survivors had a sustained low risk of frailty over time, 25.0% had a low frailty risk at baseline but the risk increased steadily, and 22.3% had a high frailty risk with a slight change in the observed period. Older cancer survivors were at a high-risk frailty trajectory if they were older, female, African American, had lower education status, had lower annual income, were underweight or obese, self-rated poorer health, had more chronic conditions and difficulties with activities of daily living (ADL), and had worse cognitive functions (P < 0.05). CONCLUSIONS: Long-term frailty trajectories in older cancer survivors are heterogeneous. This study helps identify patients at high risk of sustained or deteriorating frailty and has the potential to inform targeted frailty management strategies addressing modifiable factors identified (e.g. body mass index, ADL).

Comorbidities were associated with cancer clinical trial discussion and participation: findings from the Health Information National Trends Survey-Surveillance, Epidemiology, and End Results Program (2021).

OBJECTIVES: Oncology clinical trials are recommended to better reflect real-world cancer patient populations and to increase patient access to new treatments in trials. The influence of comorbidities on trial participation is unclear. This study examined the association of having comorbidities and patients' experiences with clinical trial discussion or actual participation. STUDY DESIGN AND SETTING: We included 958 cancer survivors from Health Information National Trends Survey-Surveillance, Epidemiology, and End Results Program. Trial discussion was defined as whether their medical team discussed cancer clinical trials, and trial participation was defined as whether they participated. Comorbidities included diabetes, hypertension, heart condition, chronic lung disease, and depression/anxiety disorder. Design-based logistic regression results were conducted. RESULTS: Seventy-five percent of patients had one or more comorbidities, commonly having hypertension (56%) and diabetes (26%). Only 15% of participants reported trial discussion and 8% reported trial participation. Having one or more comorbidities was significantly associated with lower rates of trial discussion in univariate analysis (22.9% vs. 12.1%, odds ratio = 0.46, P = 0.001), and such association was pertained in adjusted logistic regression (20.5% vs. 12.8%, adjusted odds ratio = 0.54, P = 0.02). CONCLUSION: Findings suggest patients with comorbidities were underrepresented in cancer clinical trials, implying a potential lack of representativeness among trial participants.

[Latest Findings in Key Research Areas of Precision Nursing for Chronic Diseases in Older Adults].

The advent of the era of biomedical big data has helped promote the development of precision nursing. Precision nursing for chronic diseases in older adults is an interdisciplinary research field in which accurate individualized data are utilized to carry out early screening and health management of older adult populations at high risk for chronic diseases and early intervention of diseases, which plays an important role in improving the prognosis of diseases and the health level of the older adult population. Herein, we introduced the concept of precision nursing, and discussed the latest research findings in the key areas of precision nursing for chronic diseases in older adults, including precision symptom management in cancer patients and precision nursing in older patients with multimorbidity. At present, research concerning precise symptom management of cancer patients is mainly focused on prediction modelling for risks of symptoms, longitudinal change trajectories, core symptom identification, etc. Investigations in the precise nursing of cancer patients are conducted in the following areas, risk prediction, the timing of interventions, and intervention targets. Research on precision nursing for multimorbidity is mainly focused on assessment of chronic disease multimorbidity, multimorbidity pattern recognition, and health management of multimorbidity. We also discussed potential opportunities and challenges of precision nursing in the future, in order to provide a scientific basis for the improving the practice and theories of precision nursing. In the future, precision nursing will play an ever more important role in uncovering pathogenic information, the diagnosis and treatment of diseases, the health of the research population, and the promotion of medical research.

Development of a nomogram prediction model for gait speed trajectories in persons with knee osteoarthritis.

To examine heterogeneous trajectories of 8-year gait speed among patients with symptomatic knee osteoarthritis (KOA) and to develop a nomogram prediction model. We analyzed data from the Osteoarthritis Initiative (OAI) assessed at baseline and follow-up over 8 years (n = 1289). Gait speed was measured by the 20-m walk test. The gait speed trajectories among patients with KOA were explored by latent class growth analysis. A nomogram prediction model was created based on multivariable logistic regression. Three gait speed trajectories were identified: the fast gait speed group (30.4%), moderate gait speed group (50.5%) and slow gait speed group (19.1%). Age ≥ 60 years, female, non-white, nonmarried, annual income < $50,000, obesity, depressive symptoms, comorbidity and WOMAC pain score ≥ 5 were risk factors for the slow gait trajectory. The area under the ROC curve of the prediction model was 0.775 (95% CI 0.742-0.808). In the external validation cohort, the AUC was 0.773 (95% CI 0.697-0.848). Heterogeneous trajectories existed in the gait speed of patients with KOA and could be predicted by multiple factors. Risk factors should be earlier identified, and targeted intervention should be carried out to improve physical function of KOA patients.

Use of Digital Health Technology Among Older Adults With Cancer in the United States: Findings From a National Longitudinal Cohort Study (2015-2021).

BACKGROUND: Despite the benefits of digital health technology use, older adults with cancer (ie, aged 65 years) have reported challenges to technology adoption. However, there has been a lack of a good understanding of their digital health technology use patterns and the associated influential factors in the past few years. OBJECTIVE: This study aimed to examine the trends in and factors associated with digital health technology use among older adults with cancer. METHODS: The National Health and Aging Trends Study (NHATS) data set is a national longitudinal cohort study with annual survey waves of Medicare beneficiaries 65 years and older. Participants were community-dwelling older adults who self-reported previous or current cancer diagnoses in each round. The study sample size of each round ranged from 1996 (2015) to 1131 (2021). Digital health technology use was defined as using the internet or online in the last month to order or refill prescriptions, contact medical providers, handle Medicare or other insurance matters, or get information about their health conditions. The association of sociodemographics, clinical factors (self-rated health, chronic conditions, difficulties in activities of daily living, dementia, anxiety, and depression), and physical function (Short Physical Performance Battery and grip strength) with digital health technology use was examined using design-based logistic regression. All statistical analyses accounted for the complex sample design. RESULTS: The prevalence of any digital health technology use increased from 36% in 2015 to 45% in 2019. In 2020-2021, which was amid the COVID-19 pandemic, it ranged from 51% to 52%. In terms of each digital health technology use behavior, in 2015, overall, 28% of older cancer survivors used digital health technology to obtain health information, followed by contacting clinicians (19%), filling prescriptions (14%), and handling insurance (11%). Greater use of digital health technology was associated with younger age, being White, having a college or higher education, having a higher income, having more comorbidities, nondementia, and having a higher gait speed. CONCLUSIONS: Digital health technology use in older adults with cancer has gradually increased, particularly during the COVID-19 pandemic. However, socioeconomic and racial disparities have remained in older cancer survivors. Additionally, older adults with cancer may have some unique features associated with digital health technology use; for example, their use of digital health may be increased by their comorbidities (ie, health care needs) and reduced by their frailty.

Association between depression and lung function in college students.

Background: Depression is positively associated with lung dysfunction in middle-aged and older adults, but the correlation between depression and lung dysfunction in healthy young adults has not been well researched. Methods: This cross-sectional study used a spirometer to evaluate the lung function of 352 college students (mean age: 24.1 years). The spirometry measurements included the peak expiratory flow (PEF), predicted percentage of the peak expiratory flow (PEF pp), forced expiratory volume in 1 s (FEV1), predicted percentage of the FEV1 (FEV1 pp), forced vital capacity (FVC), predicted percentage of the FVC (FVC pp), FEV1/FVC ratio and the predicted percentage of the FEV1/FVC ratio (FEV1/FVC pp). A validated Chinese version of the 20-item Zung Self-rating Depression Scale (SDS) was used to assess the severity of depression among young adults, with scores of ≥ 40 and ≥ 45 points indicating mild and moderate-to-severe depression, respectively. The Kruskal-Wallis tests were used to analyze the continuous variables, to estimate differences in lung function among the different levels of depression. Chi-square tests or Fisher's exact tests were used to analyze the categorical variables, to estimate differences in characteristics among the different levels of depression. Several multiple logistic regression models were used to examine the associations between participants' level of depression and each of the variables measuring lung function. Results: Mild and moderate-to-severe depression were observed in 9.9 and 7.4% of the students, respectively. In particular, mild depression was associated with reduced FEV1 in both unadjusted (OR = 1.498, p = 0.003) and adjusted models (OR = 1.290, p = 0.018; OR = 1.199, p = 0.044). On the other hand, moderate-to-severe depression was significantly but negatively related to FEV1 in both unadjusted (OR = 3.546, p = 0.005) and adjusted models (OR = 3.137, p = 0.020; OR = 2.980, p = 0.048). Furthermore, the unadjusted model indicated that mild depression was associated with a higher risk of a lower PEF (OR = 3.546, p = 0.008). Conclusion: Severe depression is an independent predictor of decreased FEV1 among Chinese college students.

Body mass index increases the risk of breast cancer-related lymphedema at 6-18 months after surgery: a retrospective study.

PURPOSE: Breast cancer-related lymphedema (BCRL) is an incurable complication occurring after breast cancer treatment. The influence of obesity/overweight on the development of BCRL at different points after surgery was seldom verified. We aimed to determine the cut-off BMI/weight value associated with an increased risk of BCRL at different postoperative time in Chinese breast cancer survivors. METHODS: Patients who underwent breast surgery plus axillary lymph node dissection (ALND) were retrospectively evaluated. Disease and treatment characteristics of participants were collected. BCRL was diagnosed by circumference measurements. Univariate and multivariable logistic regression was used to assess the relationship of lymphedema risk with BMI/weight and other disease- and treatment-related factors. RESULTS: 518 patients were included. Lymphedema occurred more frequently among breast cancer patients with preoperative BMI ≥ 25 kg/m2 (37.88%) than among those with preoperative BMI < 25 kg/m2(23.32%), with significant differences at 6-12 and 12-18 months after surgery (χ2 = 23.183, P = 0.000; χ2 = 5.279, P = 0.022). By multivariable logistics analysis, preoperative BMI ≥ 30 kg/m2 presented a significantly greater risk of lymphedema than a preoperative BMI < 25 kg/m2 (OR [95% CI] = 2.928 [1.565, 5.480]). Other factors, including radiation (breast/chest wall + axilla vs. none: OR [95% CI] = 3.723[2.271-6.104]), was an independent risk factor for lymphedema. CONCLUSIONS: Preoperative obesity was an independent risk factor for BCRL in Chinese breast cancer survivors, and a preoperative BMI ≥ 25 kg/m2 indicated greater likelihood of lymphedema development within 6-18 months postoperatively.