scholarly journals Measuring the Temporal Stability of Near-Repeat Crime Patterns: A Longitudinal Analysis

2020 ◽  
pp. 001112872092254
Author(s):  
David Hatten ◽  
Eric L. Piza
Keyword(s):  
Longitudinal Analysis ◽  
Effect Size ◽  
Longitudinal Design ◽  
Temporal Trends ◽  
Temporal Stability ◽  
Descriptive Statistics ◽  
Crime Patterns ◽  
Time Periods ◽  
One Year ◽  
Near Repeat

This study investigates the temporal stability of identified near-repeat robbery patterns in Newark, New Jersey. With one noteworthy exception, scholars have yet to explore the temporal stability of identified spatiotemporal crime clusters. Furthermore, researchers have yet to measure the near-repeat phenomenon longitudinally. To fill this gap, this study employs a longitudinal design to measure variation in effect size and significance of identified near-repeat crime patterns across 13 “rolling” one-year time periods within a 2-year study period (January 2015–December 2016). Temporal instability was found within two out of six spatiotemporal crime clusters. Results are reported in the form of formalized descriptive statistics and visualizations of temporal trends.

scholarly journals Spatial–temporal trends in forced migrant mortality, 2014–2018

2020 ◽  
Vol 5 (10) ◽  
pp. e002885
Author(s):  
Danielle N Poole ◽  
Bethany Hedt-Gauthier ◽  
Till Bärnighausen ◽  
Stéphane Verguet ◽  
Marcia C Castro
Keyword(s):  
Temporal Trends ◽  
Forced Migration ◽  
Global Scale ◽  
International Organization ◽  
Temporal Heterogeneity ◽  
Percentage Point Increase ◽  
Humanitarian Response ◽  
Risk Of Mortality ◽  
Point Increase ◽  
Time Periods

IntroductionThe identification of spatial–temporal clusters of forced migrant mortality is urgently needed to inform preventative policies and humanitarian response. As a first step towards understanding the geography of forced migrant mortality, this study investigates spatial–temporal patterns in death at a global scale.MethodsWe used information on the location and dates of forced migrant deaths reported in the International Organization for Migration’s Missing Migrant Project from 2014 to 2018. Kulldorff’s spatial–temporal and seasonal scans were used to detect spatial–temporal and temporal heterogeneity in mortality.ResultsA total of 16 314 deaths were reported during the study period. A preponderance of deaths occurred at sea each year (range 26%–54% across 5 years). Twelve spatial–temporal clusters of forced migrant mortality were detected by maximum likelihood testing. Annually, the period of August–October was associated with a 40-percentage-point increase in the risk of mortality, relative to other time periods.ConclusionsDeath during forced migration occurs close to national borders and during periods of intense conflict. This evidence may inform the design of policies and targeting of interventions to prevent forced migration-related deaths.

Abstract 11133: The Incidence and Predicting Factors of Heart Failure After First Acute Myocardial Infarction: A Population[[Unable to Display Character: ‐]]Based Study in Taiwan

Circulation ◽  
2014 ◽  
Vol 130 (suppl_2) ◽  
Author(s):  
Cheng-Han Lee ◽  
Yi-Heng Li ◽  
Ching-Lan Cheng ◽  
Jyh-Hong Chen ◽  
Yea-Huei Kao Yang
Keyword(s):  
Myocardial Infarction ◽  
Heart Failure ◽  
Acute Myocardial Infarction ◽  
Coronary Revascularization ◽  
Temporal Trends ◽  
Population Based ◽  
Research Database ◽  
Index Hospitalization ◽  
Predicting Factors ◽  
One Year

Background: Early coronary revascularization and medical therapy advancement improve the survival of patients (pts) with acute myocardial infarction (AMI). However, survivors of AMI are at heightened risk of developing heart failure (HF) and there is a paucity of information regarding this issue in Asian countries. This study described the temporal trends in the incidence of HF after the first AMI and the predicting factors of HF development in Taiwan. Methods: We conducted a nationwide population-based cohort study by using 1999 to 2009 National Health Insurance Research Database. Pts aged≧18 years, with no history of HF, who hospitalized with a first AMI between January 2002 and December 2008 were identified and followed up for one year. The primary outcome was HF. We evaluated the incidence of HF during the index hospitalization, 30 days, 6 months, and one year after the discharge. The predicting factors of HF were identified by Cox proportional hazard model. Results: Overall, 42,011 first AMI pts (mean age 64.4 ± 13.8 years; male 75.0%) from 2002 to 2008 were identified. The HF incidence during the index hospitalization was 14.8%. After exclusion of HF during the hospitalization, the overall HF prevalence at 30 days, 6 months, and 1 year was 9.6%, 14.2%, and 16.8%, respectively. The HF prevalence at 1 year declined from 17.9% to 14.9% (p<0.05) from 2002 to 2008. The independent predicting factors of HF after the first AMI were elder age (≧65 years) (adjusted HR 1.81, 95% CI 1.51-2.18), diabetes mellitus (adjusted HR 1.30, 95% CI 1.21-1.41), chronic kidney disease (adjusted HR 1.41, 95% CI 1.20-1.65), use of loop diuretics within 30 days after the discharge (adjusted HR 2.21, 95% CI 2.00-2.43), and recurrent AMI (adjusted HR 2.43, 2.16-2.74). Conclusions: Survivors of AMI without prior HF remain at risk of developing HF in Taiwan and most episodes occur within 6 months after AMI. Five important clinical factors of HF were identified that may help us for risk stratification.

scholarly journals Epidemiology of Endometriosis in France: A Large, Nation-Wide Study Based on Hospital Discharge Data

2016 ◽  
Vol 2016 ◽  
pp. 1-6 ◽  
Author(s):  
Peter von Theobald ◽  
Jonathan Cottenet ◽  
Silvia Iacobelli ◽  
Catherine Quantin
Keyword(s):  
Hospital Discharge ◽  
Temporal Trends ◽  
Hospital Discharge Data ◽  
Women Of Childbearing Age ◽  
Childbearing Age ◽  
Discharge Data ◽  
Rehospitalization Rate ◽  
Number Of Patients ◽  
French Hospital ◽  
One Year

We aimed to assess the prevalence of hospitalization for endometriosis in the general population in France and in each French region and to describe temporal trends, rehospitalization rates, and prevalence of the different types of endometriosis. The analyses were carried out on French hospital discharge data and covered the period 2008–2012 and a population of 14,239,197 women of childbearing age. In this population, the prevalence of hospitalization for endometriosis was 0.9%, ranging from 0.4% to 1.6% between regions. Endometriosis affected 1.5% of hospitalized women of childbearing age, ranging from 1.0% to 2.4% between regions. The number of patients hospitalized for endometriosis significantly increased over the study period (p<0.01). Of these, 4.2% were rehospitalized at least once at one year: ranging from 2.7% to 6.3% between regions. The cumulative rehospitalization rate at 3 years was 6.9%. The types of endometriosis according to the procedures performed were as follows: ovarian (40–50%), peritoneal (20–30%), intestinal (10–20%), and ureteral or bladder (<10%), with significant differences between regions. This is the first detailed epidemiological study of endometriosis in France. Further studies are needed to assess the reasons for the increasing prevalence of endometriosis and for the significant differences in regional prevalence of this disease.

The experience of men who were managing symptoms of COPD

2005 ◽  
Author(s):  
◽  
Peeranuch Jantarakupt
Keyword(s):  
Phenomenological Study ◽  
Longitudinal Design ◽  
Local Health ◽  
Middle Aged ◽  
University Of Missouri ◽  
Hard Time ◽  
Management Interventions ◽  
Local Health Care ◽  
One Year ◽  
The University

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] The purpose of this phenomenological study was to describe the experience of middle-aged men who were managing symptoms of COPD. A longitudinal design with non-probability sampling was used. Participants were recruited through local health-care agencies. Data were obtained through three in-depth interviews with each of 8 men, aged 45 to 65 years, who lived with one or more family members and had been diagnosed with moderate (Stage II) COPD for at least one year. Interviews were tape-recorded and transcribed. Data pertaining to the participants' perceptions, actions, and intentions were analyzed using Porter's descriptive phenomenological method. Three-level taxonomies were created to describe the personal-social context of the experience (element, descriptor, and feature) and the experience (intention, component phenomenon, and phenomenon). The three contextual features were: (a) living with my physical limitations, (b) having a hard time breathing, and (d) living with a slow progressive disease. The three phenomena were: (a) adjusting to my limits in life, (b) dealing with my breathing problems, and (c) keeping my life stable with COPD. Findings led to new insights about how middle-aged men experience symptoms of COPD and develop skills to manage symptoms. Findings suggested new self-management interventions for pulmonary rehabilitation and for nursing.

Evaluation of Subjective and Objective Levels of Drowsiness, it’s Rating and its Relation with Facial Dynamics

2020 ◽  
Vol 2 (1) ◽  
Author(s):  
Sumaira Yasmeen ◽  
Qamar Uz Zaman ◽  
Hafeez Bibi ◽  
Nida Ilahi
Keyword(s):  
Descriptive Statistics ◽  
Facial Features ◽  
Medical Sciences ◽  
Normal Position ◽  
Efficient Tool ◽  
Dynamic Changes ◽  
Karolinska Sleepiness Scale ◽  
One Year ◽  
Eye Closure ◽  
Blink Frequency

Objective: To determine the subjective and observed levels of lethargy and changes in facial dynamics. Materials and Methods: This study was conducted at Department of community medicine, Services Institute of Medical Sciences Lahore for one-year duration from January 2017 to December 2018. The changes in facial dynamics, such as changes in eyes, lips and eyebrows, were tested in KKS (Karolinska Sleepiness Scale) in twenty-five drivers. And ORD (drowsiness observer rating). Repeated ANOVA measurements and repeated MANOVA measurements were used to analyze the data. In addition, a neural network and Viola-Jones were used to detect facial features. PERCLOS (percentage of eye closure), blink frequency and blink time were examined to see eye parameters. The size of the open mouth during sleep was examined for oral parameters. When examining the eyebrows, the number 50 indicates that the eyebrow is in the normal position. For eyebrows above the normal position, a range of 50 to 55 was specified; In addition, 45-50 was found to be a defined range for normal eyebrows. Results: Descriptive statistics of dynamic changes in the mouth and eyes showed increased drowsiness while driving, as well as changes in the eyes and mouth. However, statistical findings made while driving showed that dynamic eyebrow changes had a clear expression with a continuous trend. Similar studies on data obtained from CSR and ORD showed that both parameters increased at the same time and lethargy level. There was also a significant relationship between facial expressions and lethargy. Conclusion: This study will be an effective and efficient tool for alerting and detecting sleep in a timely and accurate manner.

scholarly journals Spatio-Temporal Crime Analysis Using KDE and ARIMA Models in the Indian Context

2020 ◽  
Vol 12 (4) ◽  
pp. 1-19
Author(s):  
Prathap Rudra Boppuru ◽  
Ramesha K.
Keyword(s):  
Data Mining ◽  
Predictive Analytics ◽  
Time Series Prediction ◽  
Arima Model ◽  
Estimation Method ◽  
Time Of Day ◽  
Crime Patterns ◽  
Model Time Series ◽  
Spatio Temporal ◽  
One Year

In developing countries like India, crime plays a detrimental role in economic growth and prosperity. With the increase in delinquencies, law enforcement needs to deploy limited resources optimally to protect citizens. Data mining and predictive analytics provide the best options for the same. This paper examines the news feed data collected from various sources regarding crime in India and Bangalore city. The crimes are then classified on the geographic density and the crime patterns such as time of day to identify and visualize the distribution of national and regional crime such as theft, murder, alcoholism, assault, etc. In total, 68 types of crime-related dictionary keywords are classified into six classes based on the news feed data collected for one year. Kernel density estimation method is used to identify the hotspots of crime. With the help of the ARIMA model, time series prediction is performed on the data. The diversity of crime patterns is visualized in a customizable way with the help of a data mining platform.

scholarly journals On the Temporal Stability of People’s Annoyance with Road Traffic Noise

2020 ◽  
Vol 17 (4) ◽  
pp. 1374 ◽  
Author(s):  
Truls Gjestland
Keyword(s):  
World Wide ◽  
Road Traffic ◽  
Traffic Noise ◽  
Temporal Trends ◽  
Temporal Stability ◽  
Road Traffic Noise ◽  
Reference Curve ◽  
Social Surveys

Sixty-one social surveys on annoyance caused by road traffic noise conducted world-wide over a period of forty-five years have been re-analyzed by various means for possible temporal trends. Eighteen of these surveys were conducted after 2000. People’s reactions to road traffic noise seem to have been stable across the study period. No indications were found that would warrant revision of the current EU reference curve for predicting the annoyance from road traffic noise.

scholarly journals Depressive Symptoms and Deliberate Self-Harm in a Community Sample of Adolescents: A Prospective Study

2011 ◽  
Vol 2011 ◽  
pp. 1-11 ◽  
Author(s):  
Lars-Gunnar Lundh ◽  
Margit Wångby-Lundh ◽  
My Paaske ◽  
Stina Ingesson ◽  
Jonas Bjärehed
Keyword(s):  
Risk Factor ◽  
Depressive Symptoms ◽  
Longitudinal Design ◽  
Community Sample ◽  
Deliberate Self Harm ◽  
Self Image ◽  
Bidirectional Relationship ◽  
Self Harm ◽  
One Year ◽  
A Prospective Study

The associations between depressive symptoms and deliberate self-harm were studied by means of a 2-wave longitudinal design in a community sample of 1052 young adolescents, with longitudinal data for 83.6% of the sample. Evidence was found for a bidirectional relationship in girls, with depressive symptoms being a risk factor for increased self-harm one year later and self-harm a risk factor for increased depressive symptoms. Cluster analysis of profiles of depressive symptoms led to the identification of two clusters with clear depressive profiles (one severe, the other mild/moderate) which were both characterized by an overrepresentation of girls and elevated levels of self-harm. Clusters with more circumscribed problems were also identified; of these, significantly increased levels of self-harm were found in a cluster characterized by negative self-image and in a cluster characterized by dysphoric relations to parents. It is suggested that self-harm serves more to regulate negative self-related feelings than sadness.

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