Influence of Pokémon GO on Physical Activity and Psychosocial Well-Being in Children and Adolescents: Systematic Review.

BACKGROUND: Pokémon GO, an augmented reality game with widespread popularity, can potentially influence players' physical activity (PA) levels and psychosocial well-being. OBJECTIVE: This review aims to systematically examine the scientific evidence regarding the impact of Pokémon GO on PA and psychosocial well-being in children and adolescents. METHODS: Using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and the GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) framework, we conducted keyword and reference searches in the PubMed, CINAHL, Web of Science, and Scopus databases. We performed title and abstract screening, full-text review, evidence synthesis, and identified research gaps. RESULTS: Our review included 10 studies that explored the effect of Pokémon GO on PA or psychosocial well-being among children and adolescents. These studies used diverse designs across multiple countries and regions. Pokémon GO use measures encompassed frequency, experience, adherence, and motivation. PA assessment methods ranged from self-reported questionnaires to technology-based evaluations and qualitative approaches. Psychosocial well-being measures included emotional intelligence, personal well-being, self-control, emotionality, and sociability. In general, the estimated impact of Pokémon GO on PA was positive, with gaming elements and engagement correlating with increased PA levels. However, the effect on psychosocial well-being presented mixed results, with positive associations for sociability but a complex relationship involving well-being and internet gaming disorder. The limitations of these studies comprised the absence of randomized controlled trials, heterogeneity in study designs and outcome measures, and potential confounding bias. CONCLUSIONS: Overall, Pokémon GO tends to positively affect PA levels, while the impact on psychosocial well-being remains complex and requires further investigation. Future research should investigate the mechanisms connecting Pokémon GO use with PA and psychosocial well-being and the potential risks of excessive gameplay. These findings can help inform public health interventions to harness gaming technologies for promoting PA and enhancing well-being among the younger generation. TRIAL REGISTRATION: PROSPERO International Prospective Register of Systematic Reviews CRD42023412032; https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=412032.

Assessing the longitudinal relationship between whole egg consumption and cognition in Chinese older adults.

BACKGROUND: Given China's fast-growing aging population, cognitive decline is a leading public health concern. Eggs are an affordable food rich in several shortfall nutrients that may benefit cognitive health. AIM: This study assessed the longitudinal relationship between whole egg consumption and cognition among older adults in China. METHODS: Individual-level data of 4737 Chinese adults 55+ years came from the China Health and Nutrition Survey (CHNS) 1997-2006 waves. Daily egg consumption was measured using 3-day 24-h dietary recalls. Cognitive functioning was assessed with immediate and delayed recall of a 10-word list, counting backward from 20, and serial 7 subtraction. Multivariate mixed-effects regressions were performed to estimate the longitudinal associations between daily whole egg consumption and cognitive functioning in older Chinese adults. RESULTS: Approximately 46% of CHNS participants were whole egg consumers, and their daily intake averaged 47.4 g. The overall cognitive functioning test scores, separate scores for cognitive functioning subdomains, and the prevalence of cognitive impairment at the baseline were modestly higher among whole egg consumers than nonconsumers. However, after adjusting for individual characteristics, multivariate mixed-effects regressions did not find daily whole egg consumption to be associated with cognitive functioning among CHNS participants. By contrast, several demographic and socioeconomic factors, such as age, education attainment, and health insurance coverage, were found to correlate with older Chinese adults' cognition. CONCLUSION: This study has measurement and design limitations. Future research should investigate the causal impact of habitual egg intake on different domains of cognition using experimental designs with an extended follow-up period.

Building Machine Learning Models to Correct Self-Reported Anthropometric Measures.

Monitoring population obesity risk primarily depends on self-reported anthropometric data prone to recall error and bias. This study developed machine learning (ML) models to correct self-reported height and weight and estimate obesity prevalence in US adults. Individual-level data from 50 274 adults were retrieved from the National Health and Nutrition Examination Survey (NHANES) 1999-2020 waves. Large, statistically significant differences between self-reported and objectively measured anthropometric data were present. Using their self-reported counterparts, we applied 9 ML models to predict objectively measured height, weight, and body mass index. Model performances were assessed using root-mean-square error. Adopting the best performing models reduced the discrepancy between self-reported and objectively measured sample average height by 22.08%, weight by 2.02%, body mass index by 11.14%, and obesity prevalence by 99.52%. The difference between predicted (36.05%) and objectively measured obesity prevalence (36.03%) was statistically nonsignificant. The models may be used to reliably estimate obesity prevalence in US adults using data from population health surveys.

Sentiment Analysis of Tweets on Soda Taxes.

CONTEXT: As a primary source of added sugars, sugar-sweetened beverage (SSB) consumption may contribute to the obesity epidemic. A soda tax is an excise tax charged on selling SSBs to reduce consumption. Currently, 8 cities/counties in the United States have imposed soda taxes. OBJECTIVE: This study assessed people's sentiments toward soda taxes in the United States based on social media posts on Twitter. DESIGN: We designed a search algorithm to systematically identify and collect soda tax-related tweets posted on Twitter. We built deep neural network models to classify tweets by sentiments. SETTING: Computer modeling. PARTICIPANTS: Approximately 370 000 soda tax-related tweets posted on Twitter from January 1, 2015, to April 16, 2022. MAIN OUTCOME MEASURE: Sentiment associated with a tweet. RESULTS: Public attention paid to soda taxes, indicated by the number of tweets posted annually, peaked in 2016, but has declined considerably ever since. The decreasing prevalence of tweets quoting soda tax-related news without revealing sentiments coincided with the rapid increase in tweets expressing a neutral sentiment toward soda taxes. The prevalence of tweets expressing a negative sentiment rose steadily from 2015 to 2019 and then slightly leveled off, whereas that of tweets expressing a positive sentiment remained unchanged. Excluding news-quoting tweets, tweets with neutral, negative, and positive sentiments occupied roughly 56%, 29%, and 15%, respectively, during 2015-2022. The authors' total number of tweets posted, followers, and retweets predicted tweet sentiment. The finalized neural network model achieved an accuracy of 88% and an F1 score of 0.87 in predicting tweet sentiments in the test set. CONCLUSIONS: Despite its potential to shape public opinion and catalyze social changes, social media remains an underutilized source of information to inform government decision making. Social media sentiment analysis may inform the design, implementation, and modification of soda tax policies to gain social support while minimizing confusion and misinterpretation.

The Safety and Efficacy of Clonidine in Hemodialysis Patients: A Systematic Review and Meta-Analysis.

BACKGROUND: Clonidine is a frequently prescribed long-term antihypertensive medication in hemodialysis (HD) patients in the USA, but its safety and efficacy has not been clearly established in the HD population. OBJECTIVE: To evaluate, we conducted a systematic review and meta-analysis on the safety and efficacy of clonidine in HD patients. METHODS: Keyword search of "clonidine" and "dialysis" was conducted through April 2021 in PubMed, Cochrane Library, Web of Science, Scopus, and ClinicalTrials.gov databases. Inclusion criteria were as follows - study design: randomized controlled trials, cohort studies, prospective studies, retrospective studies, or case series; subjects: adult HD patients; main outcome: blood pressure (BP) and safety; language: English; and article type: peer-reviewed publications. Studies that examined the effects of clonidine in populations other than adult HD patients were excluded. Meta-analysis was performed on BP reduction outcomes. RESULTS: Eight studies met the inclusion criteria for the systematic review, including prospective pre-post studies (2), double-blind controlled trial (1), single-blinded placebo-controlled trial (1), crossover open-label clinical trial (1), retrospective analysis (1), and case report series (2). Three studies included in the meta-analysis ranged from 2 to 12 weeks duration, with a collective sample size of 24 (ages 12-77 years). Risk of bias, assessed using the ROBINS-1 tool, was high for all included studies. Significant adverse effects reported included hypotension, light-headedness, drowsiness, dry mouth, rebound hypertension, and contact dermatitis from patch application. Short-term clonidine use was associated with significant improvement in systolic BP (pooled effect: -12.985 mm Hg, 95% CI [-7.878, -18.092], p < 0.001), while changes in diastolic BP were not statistically significant (-11.119 mm Hg, 95% CI [-22.725, 0.487], p = 0.060). No data currently support the long-term efficacy of clonidine in HD patients. This study was unfunded and was developed using PRISMA guidelines and registered on PROSPERO (CRD42018112042). CONCLUSIONS: There is no evidence supporting the long-term use of clonidine in the HD population and a significant side-effect profile. There is low-quality evidence demonstrating the efficacy of clonidine in lowering BP in HD patients in short-term use, but significant safety concerns remain. Fluid removal strategies and other antihypertensives should be used over clonidine for long-term BP control in the HD population.

Social media-assisted interventions on human papillomavirus and vaccination-related knowledge, intention and behavior: a scoping review.

Social media holds the potential to engage adolescents and young adults and to facilitate interventions improving Human Papillomavirus Vaccine (HPVV). This article systematically reviewed the literature on Cochrane Library, PubMed, Web of Science, EMBASE, Scopus and CINAHL. Interventions delivered or facilitated by social media with outcomes of HPV-related knowledge, awareness, attitude, vaccination intention and behavior were included. Standardized forms were used to abstract the basic characteristics, settings, guiding theories and key findings of the interventions. Twenty-four studies met the eligibility criteria. Sixteen were educational interventions, and the other eight investigated the effect of social media message contents on improving Human Papillomavirus (HPV)-related outcomes. The studies were published between 2015 and 2021. The most frequently used social media platforms were Facebook, and the most commonly adopted theory was the health belief model (HBM). Existing interventions have shown preliminary but promising effects in improving HPV awareness and knowledge. Still, such improvements have not always been translated to improved behavioral intentions and vaccination rates. The contents and phrasing of social media messages and pre-existing individual characteristics of social media users moderated intervention effectiveness. Social media could be a valuable tool for engaging participants and delivering HPV interventions. Future interventions should apply stronger theory bases.

Parenting styles in relation to childhood obesity, smoking and drinking: A gene-environment interaction study.

BACKGROUND: The present study assessed gene-environment interactions linking maternal parenting styles to childhood obesity and alcohol and tobacco use. METHODS: Data were retrieved from the first wave of the German Twin Family Panel. Participants comprised three birth cohorts, aged 5, 11 and 17 years, with approximately 500 pairs of same-sex monozygotic twins and 500 pairs of same-sex dizygotic twins per cohort. Self-reported parenting styles were measured in five dimensions: emotional warmth, psychological control, negative communication, monitoring and inconsistent parenting. Outcome variables included children's body mass index z-score (BMIz) and smoking and alcohol drinking frequency. Gene-environment interaction models were used to assess how parenting styles might moderate genetic and environmental influences on BMIz and smoking and drinking behaviours. RESULTS: A positive interaction of genetic effects with psychological control was found for BMIz at age 5 years, indicating that genetic influences on BMIz increased with psychological control. No interaction effect was found for BMIz at ages 11 and 17 years. Regarding adolescent smoking, positive interaction between genetic effects and negative communication was found, indicating that genetic influences on smoking increased with negative communication. There was no significant moderating effect of parenting styles on adolescent drinking. CONCLUSIONS: The present study found preliminary evidence indicating that parenting styles moderated genetic and environmental impacts on body weight status and smoking. Moderation effects of parenting on BMIz were observed only at a very young age. The moderating effects of parenting influenced adolescent smoking but not drinking.

Whole egg consumption and cognitive function among US older adults.

BACKGROUND: Eggs are an affordable food providing many shortfall nutrients with the potential to improve cognitive health. We assessed the relationship between whole egg consumption and cognitive functioning among a US nationally representative sample of older adults. METHODS: Individual-level data (2816 adults, aged ≥ 60 years) were obtained from the National Health and Nutrition Examination Survey (NHANES) 2011-2012 and 2013-2014 waves. Cognitive assessments included the Consortium to Establish a Registry for Alzheimer's Disease Word List Learning Test (CERAD-WL), Word List Recall Test (CERAD-DR), Animal Fluency Test (AF) and Digit Symbol Substitution Test (DSST). A composite cognitive z-score was constructed based on the individual tests to represent one's overall cognitive functioning. Multiple linear and logistic regressions were performed to examine the effect of whole egg consumption on cognitive functioning, adjusting for individual characteristics and survey design. RESULTS: Approximately 57% of older adults consumed whole eggs, with an average daily intake of 34 g of whole egg equivalent among consumers. The average z-scores of the CERAD-WL, CERAD-DR, AF and DSST tests were -0.08, 0.23, 0.37 and 0.42, respectively, and the overall composite cognitive z-score was 0.24 among older adults. Regression analyses found that neither whole egg consumption status, nor daily intake quantity was associated with cognitive test scores. CONCLUSIONS: No association was found between whole egg consumption and cognitive functioning among US older adults. Study limitations included cross-sectional study design and measurement errors. Future studies with longitudinal or experimental design are warranted to examine the possible link between egg consumption and cognition in older adults.

Applications of Artificial Intelligence to Obesity Research: Scoping Review of Methodologies.

BACKGROUND: Obesity is a leading cause of preventable death worldwide. Artificial intelligence (AI), characterized by machine learning (ML) and deep learning (DL), has become an indispensable tool in obesity research. OBJECTIVE: This scoping review aimed to provide researchers and practitioners with an overview of the AI applications to obesity research, familiarize them with popular ML and DL models, and facilitate the adoption of AI applications. METHODS: We conducted a scoping review in PubMed and Web of Science on the applications of AI to measure, predict, and treat obesity. We summarized and categorized the AI methodologies used in the hope of identifying synergies, patterns, and trends to inform future investigations. We also provided a high-level, beginner-friendly introduction to the core methodologies to facilitate the dissemination and adoption of various AI techniques. RESULTS: We identified 46 studies that used diverse ML and DL models to assess obesity-related outcomes. The studies found AI models helpful in detecting clinically meaningful patterns of obesity or relationships between specific covariates and weight outcomes. The majority (18/22, 82%) of the studies comparing AI models with conventional statistical approaches found that the AI models achieved higher prediction accuracy on test data. Some (5/46, 11%) of the studies comparing the performances of different AI models revealed mixed results, indicating the high contingency of model performance on the data set and task it was applied to. An accelerating trend of adopting state-of-the-art DL models over standard ML models was observed to address challenging computer vision and natural language processing tasks. We concisely introduced the popular ML and DL models and summarized their specific applications in the studies included in the review. CONCLUSIONS: This study reviewed AI-related methodologies adopted in the obesity literature, particularly ML and DL models applied to tabular, image, and text data. The review also discussed emerging trends such as multimodal or multitask AI models, synthetic data generation, and human-in-the-loop that may witness increasing applications in obesity research.

We got nuts! use deep neural networks to classify images of common edible nuts.

BACKGROUND: Nuts are nutrient-dense foods that contribute to healthier eating. Food image datasets enable artificial intelligence (AI) powered diet-tracking apps to help people monitor daily eating patterns. AIM: This study aimed to create an image dataset of commonly consumed nut types and use it to build an AI computer vision model to automate nut type classification tasks. METHODS: iPhone 11 was used to take photos of 11 nut types-almond, brazil nut, cashew, chestnut, hazelnut, macadamia, peanut, pecan, pine nut, pistachio, and walnut. The dataset contains 2200 images, 200 per nut type. The dataset was randomly split into the training (60% or 1320 images), validation (20% or 440 images), and test sets (20% or 440 images). A neural network model was constructed and trained using transfer learning and other computer vision techniques-data augmentation, mixup, normalization, label smoothing, and learning rate optimization. RESULTS: The trained neural network model correctly predicted 338 out of 440 images (40 per nut type) in the validation set, achieving 99.55% accuracy. Moreover, the model classified the 440 images in the test set with 100% accuracy. CONCLUSION: This study built a nut image dataset and used it to train a neural network model to classify images by nut type. The model achieved near-perfect accuracy on the validation and test sets, demonstrating the feasibility of automating nut type classification using smartphone photos. Being made open-source, the dataset and model can assist the development of diet-tracking apps that facilitate users' adoption and adherence to a healthy diet.

Implementation of School Diabetes Care in the United States: A Scoping Review.

Diabetes management at school demands close collaboration of multiple stakeholders, including students with diabetes and parents, school nurses, teachers/staff, and local health care providers. This scoping review identified and synthesized evidence concerning factors that contributed to the quality and effectiveness of diabetes care implementation in U.S. K-12 schools. Forty-six studies met the eligibility criteria and were included. Five common factors emerged surrounding training and experiences, communications, parent engagement, resource allocations, and school environment. Complex interactions between multiple stakeholders jointly determined the quality of school diabetes care. A conceptual model was established to elucidate the complex interactions between multiple stakeholders and the relevant facilitators and barriers. Future research should improve sample representativeness, contrast school diabetes care practices to the national guidelines, and assess the impact of the social, economic, and political environment at federal, state, local/district levels on school diabetes care implementation.

Obesity and economic environments.

This review summarizes current understanding of economic factors during the obesity epidemic and dispels some widely held, but incorrect, beliefs. Rising obesity rates coincided with increases in leisure time (rather than increased work hours), increased fruit and vegetable availability (rather than a decline in healthier foods), and increased exercise uptake. As a share of disposable income, Americans now have the cheapest food available in history, which fueled the obesity epidemic. Weight gain was surprisingly similar across sociodemographic groups or geographic areas, rather than specific to some groups (at every point in time; however, there are clear disparities). It suggests that if one wants to understand the role of the environment in the obesity epidemic, one needs to understand changes over time affecting all groups, not differences between subgroups at a given time. Although economic and technological changes in the environment drove the obesity epidemic, the evidence for effective economic policies to prevent obesity remains limited. Taxes on foods with low nutritional value could nudge behavior toward healthier diets, as could subsidies/discounts for healthier foods. However, even a large price change for healthy foods could close only part of the gap between dietary guidelines and actual food consumption. Political support has been lacking for even moderate price interventions in the United States and this may continue until the role of environmental factors is accepted more widely. As opinion leaders, clinicians play an important role in shaping the understanding of the causes of obesity.

Greenspace exposure and sleep: A systematic review.

Green space is considered a critical environmental factor for sleep quality and quantity. However, no systematic review exploring this relationship exists. The purpose of this systematic review was to 1) explore research related to green space and sleep, and 2) examine the impact of green space exposure on sleep quality and quantity. Papers from eight electronic databases were eligible for inclusion if they met the following criteria: well-designed, any analysis exploring green space and sleep, provided sleep and green space measurement, published in peer-reviewed journals, and written in English. Thirteen eligible studies related to green space and sleep were selected after peer-review procedures. Cross-sectional studies (n = 7) used either a questionnaire or the combination of Geographic Information Systems and remote sensing images for green space measurement, while questionnaires were primarily used to measure both sleep quality and quantity. Intervention studies (n = 5) were categorized into three types: walking program, gardening, and working in a forest. Eleven out of thirteen studies concluded that green space exposure was associated with improvement in both sleep quality and quantity. The findings support the evidence of a positive association between green space exposures and sleep quality and quantity, and also suggest green exercise and therapeutic gardening as possible intervention methods to improve sleep outcomes.

Impact of neighbourhood food environment on diet and obesity in China: a systematic review.

OBJECTIVE: This study systematically reviewed literature on the neighbourhood food environment in relation to diet and obesity among residents in China. DESIGN: A keyword search of peer-reviewed articles was performed in Cochrane Library, PubMed, and Web of Science. Eligibility criteria include study designs: longitudinal/cohort studies or cross-sectional studies; study participants: people of all ages; exposures: neighbourhood food environment (e.g. restaurants, supermarkets, wet markets, fast-food restaurants, or convenience stores); outcomes: diet and/or body weight status; and country: China. RESULTS: Seventeen studies met all criteria and were included. Among the eight studies that assessed the neighbourhood food environment in relation to diet, six reported at least one statistically significant relationship in the expected direction, whereas the remaining two exclusively reported null effects. Among the eleven studies that assessed the neighbourhood food environment in relation to body weight or overweight/obesity, ten reported a significant association whereas the remaining one reported a null relationship. Variety, density, and proximity of food outlets were positively associated with local residents' dietary diversity, portion size, and daily caloric intake. Density and proximity of fast-food restaurants and convenience stores were positively associated with local residents' adiposity in some but not all studies. Evidence linking any specific food outlet type to diet/obesity remains lacking due to the small number of studies and heterogeneities in food environment measures, geographical locations, and population subgroups. CONCLUSIONS: The neighbourhood food environment may influence diet and obesity among Chinese residents but the evidence remains preliminary. Future studies adopting an experimental study design and objective/validated environment and dietary measures are warranted.

Motor Learning in People with Multiple Sclerosis: A Systematic Review and Meta-analysis.

OBJECTIVE: To systematically review and quantitatively synthesize the existing evidence of motor learning in persons with multiple sclerosis (PwMS). DATA SOURCES: PubMed, Cumulative Index to Nursing and Allied Health Literature, and Web of Science were searched using the following terms: multiple sclerosis, task learning, motor learning, skill learning, performance learning. STUDY SELECTION: Studies had to include PwMS with a main outcome being motor learning, be published in peer-reviewed journals, and be written in English. The search yielded 68 results, and the inclusion criteria were met by 17 studies. DATA EXTRACTION: Basic descriptors of each study, study protocol, and motor learning measures were extracted. The Grading of Recommendations Assessment, Development, and Evaluation approach revealed the quality of evidence was low with a high risk of bias. Meta-analysis was conducted to determine the difference in implicit and explicit learning in PwMS and controls without multiple sclerosis. DATA SYNTHESIS: Studies scored on average 15.9 of 18 for quality assessment. PwMS were able to learn functional mobility and upper limb manipulation motor skills as indicated by short-term acquisition, transfer, and retention. Implicit learning conditions from the meta-analysis showed that PwMS were able to learn at a similar rate to controls without multiple sclerosis (P<.001), yet explicit learning conditions did not display a significant rate of learning (P=.133). CONCLUSIONS: While this review indicated that PwMS are capable of motor learning, several knowledge gaps still exist. Future research should focus on using higher-quality evidence to understand motor learning in PwMS and translate the findings to rehabilitation and activities of daily living.

Internet-delivered cognitive behavioral therapies for late-life depressive symptoms: a systematic review and meta-analysis.

Background: This study aimed to review and synthesize evidence related to the effectiveness of internet-based cognitive behavioral therapy (iCBT) for reducing depressive symptoms in older adults.Method: The authors conducted a systematic review of intervention studies testing iCBT for symptoms of depression in older adults. An initial search of PubMed, PsychINFO, and Web of Science was undertaken, followed by a manual search of reference lists of the relevant articles. The Cochrane Risk of Bias Tool was used to appraise study quality. The mean effect size for included studies was estimated in a random effects model. Meta-regression was used to examine potential moderators of effect sizes.Results: Nine studies met the inclusion criteria, including 1272 participants averaging 66 years of age. The study design included randomized controlled trials (k = 3), controlled trials without randomization (k = 2), uncontrolled trials (k = 2), and naturalistic evaluation (k = 2). Seven studies tested iCBT with some level of therapist involvement and 2 examined self-guided iCBT. Six studies tested interventions specifically adapted for older adults. The mean within-group effect size was 1.27 (95% CI = 1.09, 1.45) and the mean between-group effect size was 1.18 (95% CI = 0.63, 1.73). Participants' age was negatively associated with within-group effect sizes (b = -0.06, p = .016).Conclusions: iCBT is a promising approach for reducing depressive symptoms among older adults with mild to moderate depressive symptoms. However, studies involving older adults in iCBT trials were limited, had considerable heterogeneity, and were of low quality, calling for more studies with rigorous designs to produce a best-practice guideline.

Disability type, depression, and antidepressants use among older adults in the United States.

Objectives: The study aimed to estimate the prevalence of depression and antidepressant use among older adults with different types of disability.Methods: The study sample consisted of 32,193 adults 50 years and older who participated in the Adult Functioning and Disability supplement of the National Health Interview Survey from 2010-2014. Logistic regression was used to estimate depressive symptoms and self-reported antidepressant use by disability type.Results: One in ten participants reported feeling depressed daily or weekly, and less than half of them reported using antidepressants. Adults with a disability in cognition (odds ratio [OR] = 5.55), mobility (OR = 1.92), vision (OR = 1.91), hearing (OR = 1.88), and self-care (OR = 1.66) were more likely to often feel depressed. Antidepressant use was higher among those with cognition and self-care disability compared with no disabilities. A dose-response association existed between the number of disabilities and depression (AOR = 2.3) and antidepressant use (AOR = 1.39).Conclusions: Various forms of disability are strongly associated with depression in older adults. Antidepressants may be underutilized among older adults with certain impairments, including vision, hearing, and mobility. Future research needs should elucidate the mechanisms linking different disabilities to depression and aim to develop treatments tailored to the needs of older adults with disabilities.

Effect of eccentric overload training on change of direction speed performance: A systematic review and meta-analysis.

This study systematically reviewed and quantified evidence regarding the effectiveness of eccentric overload training (EOT) on change-of-direction speed (CODS) performance. A keyword search was performed in 30 April 2020 in eight electronic bibliographic databases: SPORTDiscus, PubMed, Web of Science, Academic Search Complete, Cochrane Library, Scopus, CINAHL and Google Scholar. A meta-analysis was conducted to estimate the pooled effect size of EOT interventions on CODS performance compared to the control group. Study heterogeneity was assessed by the I 2 index. Publication bias was assessed by the Begg's and Egger's tests. Eleven studies, including nine randomized controlled trials, one randomized crossover trial, and one non-randomized controlled trial met the eligibility criteria and were included in the review. Time of overall change-of-direction task completion among the EOT group was 1.35 standard deviations (95% confidence interval [CI] = 0.18, 2.52) shorter than that in the control group. In conclusion, EOT was found effective in improving CODS performance compared to the control group. Future studies should adopt a randomized experimental design, recruit large and representative samples from professional team sports, and examine the effect of EOT on various measures of CODS performance among population subgroups.

Fresh- and lean-pork intake in relation to functional limitations among US older adults, 2005-2016.

BACKGROUND: Pork consumption, in particular fresh/lean-pork consumption, provides protein and other essential micronutrients that older adults need daily and may hold the potential to prevent functional limitations resulting from sub-optimal nutrition. AIM: Assess fresh/lean-pork intake in relation to functional limitations among older adults in the USA. METHODS: Individual-level data came from the National Health and Nutrition Examination Survey (NHANES) 2005-2016 waves. Nineteen validated questions assessed five functional limitation domains: activities of daily living (ADLs); instrumental activities of daily living (IADLs); leisure and social activities (LSAs); lower extremity mobility (LEM); and general physical activities (GPAs). Logistic regressions were performed to examine pork, fresh-pork and fresh lean-pork intake in relation to functional limitations among NHANES older adults (n = 6135). RESULTS: Approximately 21, 18 and 16% of older adults consumed pork, fresh pork and fresh lean pork, respectively. An increase in pork consumption by 1 oz-equivalent/day was associated with a reduced odds of ADLs by 12%, IADLs by 10% and any functional limitation by 7%. An increase in fresh-pork consumption by 1 oz-equivalent/day was associated with a reduced odds of ADLs by 13%, IADLs by 10%, GPAs by 8%, and any functional limitation by 8%. Similar effects were found for fresh lean-pork consumption on ADLs, IADLs, GPAs and any functional limitation. CONCLUSION: This study found some preliminary evidence linking fresh/lean-pork consumption to a reduced risk of functional limitations. Future studies with longitudinal/experimental designs are warranted to examine the influence of fresh/lean-pork consumption on functional limitations.

Impact of ambient air pollution on physical activity and sedentary behavior in China: A systematic review.

This study systematically reviewed scientific evidence linking ambient air pollution to physical activity and sedentary behavior in China. A keyword and reference search was conducted in PubMed, Web of Science, and the Cochrane Library. Predetermined selection criteria included-study designs: interventions or experiments, retrospective or prospective cohort studies, cross-sectional studies, and case-control studies; subjects: people of all ages; exposures: specific air pollutants and/or overall air quality; outcomes: physical activity and/or sedentary behavior; and country/area: mainland China. Ten studies met the selection criteria and were included in the review. Six adopted a cross-sectional design and the remaining four adopted a prospective cohort design. Four studies assessed a specific air pollutant namely particulate matter with diameter <2.5 µg/m3 (PM2.5), whereas the remaining six focused on overall air quality, defined using air quality indexes. Decline in overall air quality and increase in PM2.5 concentration were found to be associated with reduced daily/weekly duration of outdoor leisure-time and/or transportation-related physical activity such as walking but increased duration of daytime/nighttime sleeping among Chinese residents. In contrast, evidence linking overall air quality and PM2.5 concentration to sedentary behavior remains mixed and inconclusive. In conclusion, preliminary evidence indicates that ambient air pollution impacts Chinese residents' daily physical activity-related behaviors. Future studies adopting objective measures of physical activity and a longitudinal or experimental study design are warranted to examine the impact of air pollution on sensitive sub-populations such as children, older adults and people with pre-existing conditions, and in locations outside China.