A Longitudinal Analysis Examining the Associations of Tummy Time With Active Playtime, Screen Time, and Sleep Time

2021 ◽  
pp. 1-8
Author(s):  
Limin Buchanan ◽  
Huilan Xu ◽  
Lyndel Hewitt ◽  
Sarah Taki ◽  
Li Ming Wen
Keyword(s):  
Longitudinal Analysis ◽  
Screen Time ◽  
Demographic Data ◽  
Sleep Time ◽  
Time Data ◽  
Nocturnal Sleep ◽  
Early Introduction ◽  
Logistic Regression Models ◽  
Tummy Time ◽  
Using Data

Background: Evidence links tummy time (ie, the time spent in awake prone positioning that is encouraged and supervised by an adult) to infants’ health outcomes such as gross motor and total development. However, the associations between tummy time and other movement and sleep behaviors as the child develops remain unknown. The aim of this study was to examine whether early introduction and practice of tummy time within the first 6 months of age were associated with active and outdoor playtime, screen time, and nocturnal sleep time of children when they were 12 and 24 months old. Methods: A longitudinal analysis was conducted using data extracted from an Australian trial. Using telephone surveys with mothers, demographic data were collected from third trimester of pregnancy and tummy time data were collected at 6 months of age. Data on playtime, screen time, and nocturnal sleep duration as dependent variables were collected at 12 and 24 months of age. Multiple logistic regression models were built to investigate the associations. Results: Children who started tummy time within 4 weeks of age were more likely to have >10 hours sleep at night at 12 months (adjusted odds ratio 1.54, 95% confidence interval, 1.08–2.19). They were more likely to have >3 hours per day of outdoor play and have <1 hour per day of screen time at 24 months. Children who practiced tummy time every day were more likely to have >2 hours per day of active play at 12 months and have <1 hour per day of screen time at 24 months. Conclusions: Starting tummy time earlier and frequently was associated with more favorable movement and sleep of young children at 12 and 24 months of age.

scholarly journals Understanding Correlates of Physical Activity in American Indian Families: The Healthy Children Strong Families-2 Study

2018 ◽  
Vol 15 (11) ◽  
pp. 866-873
Author(s):  
Vernon M. Grant ◽  
Emily J. Tomayko ◽  
Ronald J. Prince ◽  
Kate Cronin ◽  
Alexandra Adams
Keyword(s):  
Physical Activity ◽  
American Indian ◽  
Screen Time ◽  
Family Income ◽  
Healthy Lifestyle ◽  
Sleep Time ◽  
Healthy Children ◽  
Logistic Regression Models ◽  
Child Sleep ◽  
Adults And Children

Background: Little is known about factors contributing to physical activity (PA) in American Indian (AI) populations. Addressing this gap is paramount as sedentary activity and obesity continue to increase in this population. The purpose of this study was to determine factors associated with PA among AI families with young children. Methods: Height and weight of both adult (n = 423) and child (n = 390) were measured, and surveys assessed demographics, PA, stress (adult only), sleep, and screen time. Separate multivariate logistic regression models were constructed for adults and children (reported as adjusted odds ratios, aORs). Results: For adults, age (aOR = 0.952; P ≤ .001), television viewing (aOR = 0.997; P = .01), and computer use (aOR = 0.996; P = .003) decreased the odds of being active. For children, high adult activity (aOR = 1.795; P ≤ .01), longer weekday sleep (aOR = 1.004; P = .01), and family income >$35,000 (aOR = 2.772; P = .01) increased the odds of being active. We found no association between adult PA with stress or adult sleep or between child PA with body mass index and screen time. Conclusions: Given the complexity of the factors contributing to obesity among AI families, multigenerational interventions focused on healthy lifestyle change such as decreasing adult screen time and increasing child sleep time may be needed to increase PA within AI families.

scholarly journals Association of CSF orexin-A levels and nocturnal sleep stability in patients with hypersomnolence

Neurology ◽  
2020 ◽  
Vol 95 (21) ◽  
pp. e2900-e2911
Author(s):  
Lucie Barateau ◽  
Régis Lopez ◽  
Sofiene Chenini ◽  
Anna-Laura Rassu ◽  
Sabine Scholz ◽  
...  
Keyword(s):  
Sleep Time ◽  
Dependent Manner ◽  
Nocturnal Sleep ◽  
Orexin A ◽  
Logistic Regression Models ◽  
Wake Time ◽  
Dose Response Effect ◽  
Nocturnal Polysomnography ◽  
Post Hoc ◽  
Nighttime Sleep

ObjectiveTo evaluate the associations between CSF orexin-A (ORX) levels and markers of nocturnal sleep stability, assessed by polysomnography.MethodsNocturnal polysomnography data and ORX levels of 300 drug-free participants (55% men, 29.9±15.5 years, ORX level 155.1±153.7 pg/mL) with hypersomnolence were collected. Several markers of nocturnal sleep stability were analyzed: sleep and wake bouts and sleep/wake transitions. Groups were categorized according to ORX levels, in 2 categories (deficient ≤110; >110), in tertiles (≤26, 26–254, >254), and compared using logistic regression models. Results were adjusted for age, sex, and body mass index.ResultsWe found higher number of wake bouts (43 vs 25, p < 0.0001), sleep bouts (43 vs 25.5, p < 0.0001), and index of sleep bouts/hour of sleep time, but lower index of wake bouts/hour of wake time (41.4 vs 50.6, p < 0.0001), in patients with ORX deficiency. The percentage of wake bouts <30 seconds was lower (51.3% vs 60.8%, p < 0.001) and of wake bouts ≥1 minutes 30 seconds higher (7.7% vs 6.7%, p = 0.02) when ORX deficient. The percentage of sleep bouts ≤14 minutes was higher (2–5 minutes: 23.7% vs 16.1%, p < 0.0001), and of long sleep bouts lower (>32 minutes 30 seconds: 7.3% vs 18.3%, p < 0.0001), when ORX deficient. These findings were confirmed when groups were categorized according to ORX tertiles, with a dose–response effect of ORX levels in post hoc comparisons, and in adjusted models.InterpretationThis study shows an association between ORX levels and nocturnal sleep stabilization in patients with hypersomnolence. Sleep and wake bouts are reliable markers of nighttime sleep stability that correlate with CSF ORX levels in a dose-dependent manner.

scholarly journals Study of occupation and amyotrophic lateral sclerosis in a Danish cohort

2018 ◽  
Vol 75 (9) ◽  
pp. 630-638 ◽  
Author(s):  
Aisha S Dickerson ◽  
Johnni Hansen ◽  
Marianthi-Anna Kioumourtzoglou ◽  
Aaron J Specht ◽  
Ole Gredal ◽  
...  
Keyword(s):  
Physical Activity ◽  
Amyotrophic Lateral Sclerosis ◽  
Conditional Logistic Regression ◽  
Demographic Data ◽  
Physical Exertion ◽  
Positive Association ◽  
Logistic Regression Models ◽  
Danish Cohort ◽  
Using Data ◽  
Lateral Sclerosis

ObjectivesSeveral manuscripts have proposed associations between amyotrophic lateral sclerosis (ALS) and occupational toxicant exposures—not to mention physical activity and trauma/injury. Some have also reported associations in investigations of specific occupations. Using data from a prospective Danish cohort study, we investigated the association between employment in certain industries and ALS diagnosis.MethodsWe identified 1826 ALS cases who were 25 years old or less in 1964 and diagnosed from 1982 to 2013 from the Danish National Patient Registry then matched 100 population controls to each case based on birth year and sex. Demographic data were linked to the Danish Pension Fund to determine occupation history. Conditional logistic regression models were adjusted for socioeconomic status, marital status and residential location at the index date.ResultsThere was an increase in odds of ALS among men who worked in agriculture, hunting, forestry or fishing (adjusted OR (aOR)=1.21; 95% CI 1.02 to 1.45). There was also a positive association for men employed in construction (aOR=1.21; 95% CI 1.05 to 1.39). In women, a protective association was seen with employment in the cleaning industry (aOR=0.69; 95% CI 0.52 to 0.93).ConclusionsOur study shows various occupations with exposure to toxicants, such as diesel exhaust and lead, and strenuous physical activity associated with increased odds of ALS in men. Future studies should have a particular focus on gathering detailed information on physical exertion and toxicant exposures specific to certain job tasks.

Intensifiers on Tyneside

2010 ◽  
Vol 31 (3) ◽  
pp. 252-287 ◽  
Author(s):  
Katie Barnfield ◽  
Isabelle Buchstaller
Keyword(s):  
Real Time ◽  
Longitudinal Analysis ◽  
Developmental Trajectories ◽  
Time Data ◽  
Longitudinal Changes ◽  
Real Time Data ◽  
Quantitative Development ◽  
First Time

We report on longitudinal changes in the system of intensification in an innovative corpus that spans five decades of dialectal speech. Our analyses allow us — for the first time in a British context — to trace the quantitative development in the variable across four generations. Longitudinal analysis across real and apparent time determines the effect of extralinguistic and intralinguistic variables on intensification in Tyneside and tests to what extent real time data corroborates trends reported from previous apparent time analyses. Long-term competition within the variable manifests itself in distinctive developmental trajectories: expansion — both proportionally within the variable as well as across adjectival categories — tends to follow one of three types of patterns, exemplified, respectively, by really, so and dead. Variant retraction, however, follows only one schema. Importantly, numerical decline in the system does not necessarily go hand in hand with a reduction in breadth of application.

Support for cigarette filter waste policies among US adults

2021 ◽  
pp. tobaccocontrol-2020-056451
Author(s):  
Minal Patel ◽  
Alison F Cuccia ◽  
Shanell Folger ◽  
Adam F Benson ◽  
Donna Vallone ◽  
...  
Keyword(s):  
Smoking Status ◽  
Population Based ◽  
Tobacco Product ◽  
Cross Sectional ◽  
Cigarette Filter ◽  
Logistic Regression Models ◽  
Knowledge And Beliefs ◽  
Cigarette Butts ◽  
Using Data ◽  
The Impact

IntroductionLittle is known on whether cigarette filter-related knowledge or beliefs are associated with support for policies to reduce their environmental impact.MethodsA cross-sectional, population-based sample of US adults aged 18–64 years (n=2979) was used to evaluate filter-related knowledge and beliefs by smoking status using data collected between 24 October 2018 and 17 December 2018. Multivariate logistic regression models explored whether these knowledge and belief items were associated with support for two policies, a US$0.75 litter fee and a ban on sales of filtered cigarettes, controlling for demographic characteristics and smoking status.ResultsRegardless of smoking status, 71% did not know plastic was a cigarette filter component and 20% believed filters were biodegradable. Overall, 23% believed filters reduce health harms and 60% believed filters make it easier to smoke; 90% believed cigarette butts are harmful to the environment. Individuals believing cigarette butts harmed the environment were more likely to support a litter fee (adjusted OR (aOR)=2.33, 95% CI: 1.71 to 3.17). Individuals believing that filters are not biodegradable had higher odds of supporting a litter fee (OR=1.47, 95% CI: 1.15 to 1.88). Respondents believing that filters do not make cigarettes less harmful were more likely to support a litter fee (aOR=1.50, 95% CI: 1.20 to 1.88) and filter ban (aOR=2.03, 95% CI: 1.64 to 2.50). Belief that filters make it easier to smoke was associated with decreased support for a filter ban (aOR=0.69, 95% CI: 0.58 to 0.83).ConclusionsComprehensive efforts are needed to educate the public about the impact of cigarette filters in order to build support for effective tobacco product waste policy.

Trends in end-of- life (EOL) systemic oncologic treatment in contemporary clinical practice: Insights from real-world data.

2021 ◽  
Vol 39 (28_suppl) ◽  
pp. 253-253
Author(s):  
Maureen Canavan ◽  
Xiaoliang Wang ◽  
Mustafa Ascha ◽  
Rebecca A. Miksad ◽  
Timothy N Showalter ◽  
...  
Keyword(s):  
Cancer Treatment ◽  
End Of Life ◽  
Real World ◽  
Cost Of Care ◽  
Real World Data ◽  
Logistic Regression Models ◽  
Oncolytic Therapy ◽  
Immune Therapies ◽  
Using Data ◽  
Over Time

253 Background: Among patients with cancer, receipt of systemic oncolytic therapy near the end-of-life (EOL) does not improve outcomes and worsens patient and caregiver experience. Accordingly, the ASCO/NQF measure, Proportion Receiving Chemotherapy in the Last 14 Days of Life, was published in 2012. Over the last decade there has been exponential growth in high cost targeted and immune therapies which may be perceived as less toxic than traditional chemotherapy. In this study, we identified rates and types of EOL systemic therapy in today’s real-world practice; these can serve as benchmarks for cancer care organizations to drive improvement efforts. Methods: Using data from the nationwide Flatiron Health electronic health record (EHR)-derived de-identified database we included patients who died during 2015 through 2019, were diagnosed after 2011, and who had documented cancer treatment. We identified the use of aggressive EOL systemic treatment (including, chemotherapy, immunotherapy, and combinations thereof) at both 30 days and 14 days prior to death. We estimated standardized EOL rates using mixed-level logistic regression models adjusting for patient and practice-level factors. Year-specific adjusted rates were estimated in annualized stratified analysis. Results: We included 57,127 patients, 38% of whom had documentation of having received any type of systemic cancer treatment within 30 days of death (SD: 5%; range: 25% - 56%), and 17% within 14 days of death (SD: 3%; range: 10% - 30%). Chemotherapy alone was the most common EOL treatment received (18% at 30 days, 8% at 14 days), followed by immunotherapy (± other treatment) (11% at 30 days, 4% at 14 days). Overall rates of EOL treatment did not change over the study period: treatment within 30 days (39% in 2015 to 37% in 2019) and within 14 days (17% in 2015 to 17% in 2019) of death. However, the rates of chemotherapy alone within 30 days of death decreased from 24% to 14%, and within 14 days, from 10% to 6% during the study period. In comparison, rates for immunotherapy with chemotherapy (0%-6% for 30 days, 0% -2% for 14 days), and immunotherapy alone or with other treatment types (4%-13% for 30 days, 1%-4% for 14 days) increased over time for both 30 and 14 days. Conclusions: End of life systemic cancer treatment rates have not substantively changed over time despite national efforts and expert guidance. While rates of traditional chemotherapy have decreased, rates of costly immunotherapy and targeted therapy have increased, which has been associated with higher total cost of care and overall healthcare utilization. Future work should examine the drivers of end-of-life care in the era of immune-oncology.

scholarly journals Gender Differences in Neuropsychiatric Symptoms Among Community-Dwelling Mexican Americans Aged 80 and Older

2021 ◽  
Vol 36 ◽  
pp. 153331752110429
Author(s):  
Sadaf Arefi Milani ◽  
Phillip A Cantu ◽  
Abbey B. Berenson ◽  
Yong-Fang Kuo ◽  
Kyriakos S. Markides ◽  
...  
Keyword(s):  
Gender Differences ◽  
Mexican Americans ◽  
Neuropsychiatric Symptoms ◽  
The Elderly ◽  
Community Dwelling ◽  
Treatment Programs ◽  
Depression And Anxiety ◽  
Logistic Regression Models ◽  
Using Data ◽  
Design And Methods

Background and Objectives To assess gender differences in prevalence of neuropsychiatric symptoms (NPS) among community-dwelling Mexican Americans ≥80 years. Research Design and Methods: Using data from Wave 7 (2010–2011) of the Hispanic Established Population for the Epidemiological Study of the Elderly, we analyzed the NPS of 914 participants as determined by the Neuropsychiatric Inventory (NPI) with assessments conducted by their caregivers. Multivariate logistic regression models were used to test the association of individual NPS with gender, adjusting for relevant characteristics. Results: The average age of our sample was 86.1 years, and 65.3% were women. Over 60% of participants had at least one informant/caregiver reported NPS. After adjustment, women had lower odds than men of agitation/aggression but higher odds of dysphoria/depression and anxiety. Discussion: Recognizing gender differences in NPS phenotype could help guide development of culturally appropriate NPS screening and treatment programs.

scholarly journals Google Traffic sebagai Masukan Kebijakan Transportasi Perkotaan (Studi Kasus: Kota Bandar Lampung)

2020 ◽  
Vol 22 (3) ◽  
pp. 409-417
Author(s):  
Muhammad Zainal Ibad ◽  
Rahayu Sulistyorini ◽  
Chania Rahmah
Keyword(s):  
Urban Areas ◽  
Urban Transportation ◽  
Transportation Policy ◽  
Time Data ◽  
Global Positioning ◽  
Transportation Policies ◽  
Movement System ◽  
Using Data ◽  
The Impact

Congestion in urban areas is vulnerable because of the impact of the growth of activities and an increasingly specialized and complex economy. For this reason, it is necessary to formulate a good urban transportation policy to accommodate increased urban transportation needs. Google Traffic is a feature found on Google Maps to see the level of congestion in an area. Google Traffic can detect an area with red, yellow or green indications through the principle of Real Time Data using data from the Global Positioning System (GPS). This study wanted to see how the use of the Google Traffic Feature as input to urban transportation policies by looking at existing urban transportation policies, analyzing the movement system model on Google Traffic, and analyzing the development of Google Traffic model policies, which would be useful for the development of Urban Transportation Policies, especially Bandar Lampung City as a case study.

Characterizing Intelligent Intrusion Detection and Prevention Systems Using Data Mining

2014 ◽  
pp. 89-102
Author(s):  
Mrutyunjaya Panda ◽  
Manas Ranjan Patra
Keyword(s):  
Data Mining ◽  
Intrusion Detection ◽  
Computer Networks ◽  
Time Data ◽  
Security Risks ◽  
Security Systems ◽  
Online Data ◽  
Audit Data ◽  
Using Data ◽  
Intrusion Detection And Prevention

Intrusion Detection and Prevention Systems (IDPS) are being widely implemented to prevent suspicious threats in computer networks. Intrusion detection and prevention systems are security systems that are used to detect and prevent security threats to computer networks. In order to understand the security risks and IDPS, in this chapter, the authors make a quick review on classification of the IDPSs and categorize them in certain groups. Further, in order to improve accuracy and security, data mining techniques have been used to analyze audit data and extract features that can distinguish normal activities from intrusions. Experiments have been conducted for building efficient intrusion detection and prevention systems by combining online detection and offline data mining. During online data examination, real-time data are captured and are passed through a detection engine that uses a set of rules and parameters for analysis. During offline data mining, necessary knowledge is extracted about the process of intrusion.

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