Neighborhoods, Activity Spaces, and the Span of Adolescent Exposures

2021 ◽  
pp. 000312242199421
Author(s):  
Christopher R. Browning ◽  
Catherine A. Calder ◽  
Bethany Boettner ◽  
Jake Tarrence ◽  
Kori Khan ◽  
...  

Since the inception of urban sociology, the “neighborhood” has served as the dominant context to capture developmentally significant youth experiences beyond the home. Yet no large-scale study has examined patterns of exposure to the most commonly used operationalization of neighborhood—the census tract—among urban youth. Using smartphone GPS data from the Adolescent Health and Development in Context study ( N = 1,405), we estimate the amount of time youth spend in residential neighborhoods and consider explanations for variation in neighborhood exposure. On average, youth (ages 11 to 17) spend 5.7 percent of their waking-time in their neighborhood but not at home, 60 percent at home, and 34.3 percent outside their neighborhood. Multilevel negative binomial regression models indicate that residence in economically disadvantaged neighborhoods is associated with less time in one’s neighborhood. Higher levels of local violence and the absence of a neighborhood school are negatively associated with time in-neighborhood and mediate the concentrated disadvantage effect. Fractional multinomial logit models indicate that higher violence is linked with increased time at home, and school absence is associated with increased outside-neighborhood time. Theoretical development and empirical research on neighborhood effects should incorporate findings on the extent and nature of neighborhood and broader activity space exposures among urban youth.

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Siddharth Subramaniyam ◽  
Michael A. DeJesus ◽  
Anisha Zaveri ◽  
Clare M. Smith ◽  
Richard E. Baker ◽  
...  

Abstract Background Deep sequencing of transposon mutant libraries (or TnSeq) is a powerful method for probing essentiality of genomic loci under different environmental conditions. Various analytical methods have been described for identifying conditionally essential genes whose tolerance for insertions varies between two conditions. However, for large-scale experiments involving many conditions, a method is needed for identifying genes that exhibit significant variability in insertions across multiple conditions. Results In this paper, we introduce a novel statistical method for identifying genes with significant variability of insertion counts across multiple conditions based on Zero-Inflated Negative Binomial (ZINB) regression. Using likelihood ratio tests, we show that the ZINB distribution fits TnSeq data better than either ANOVA or a Negative Binomial (in a generalized linear model). We use ZINB regression to identify genes required for infection of M. tuberculosis H37Rv in C57BL/6 mice. We also use ZINB to perform a analysis of genes conditionally essential in H37Rv cultures exposed to multiple antibiotics. Conclusions Our results show that, not only does ZINB generally identify most of the genes found by pairwise resampling (and vastly out-performs ANOVA), but it also identifies additional genes where variability is detectable only when the magnitudes of insertion counts are treated separately from local differences in saturation, as in the ZINB model.


2021 ◽  
Author(s):  
Audrey M Dorelien ◽  
Narmada Venkateswaran ◽  
Jiuchen Deng ◽  
Kelly Searle ◽  
Eva Enns ◽  
...  

SARS-CoV-2 is primarily transmitted through person-to-person contacts. It is important to collect information on age-specific contact patterns because SARS-CoV-2 susceptibility, transmission, and morbidity vary by age. To reduce risk of infection, social distancing measures have been implemented. Social contact data, which identify who has contact with whom especially by age and place are needed to identify high-risk groups and serve to inform the design of non-pharmaceutical interventions. We estimated and used negative binomial regression to compare the number of daily contacts during the first wave (April-May 2020) of the Minnesota Social Contact Study, based on respondents age, gender, race/ethnicity, region, and other demographic characteristics. We used information on age and location of contacts to generate age-structured contact matrices. Finally, we compared the age-structured contact matrices during the stay-at-home order to pre-pandemic matrices. During the state-wide stay-home order, the mean daily number of contacts was 5.6. We found significant variation in contacts by age, gender, race, and region. Adults between 40 and 50 years had the highest number of contacts. Respondents in Black households had 2.1 more contacts than respondent in White households, while respondents in Asian or Pacific Islander households had approximately the same number of contacts as respondent in White households. Respondents in Hispanic households had approximately two fewer contacts compared to White households. Most contacts were with other individuals in the same age group. Compared to the pre-pandemic period, the biggest declines occurred in contacts between children, and contacts between those over 60 with those below 60.


Land ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 44
Author(s):  
Jie Gao ◽  
Yan Song ◽  
Jiang Zhou ◽  
Dingxin Wu

This article aims to examine the characteristics of cities where New Urbanism (NU) developments are located as of 2019. We first develop a set of hypotheses to explore why some cities are welcoming NU developments more than other cities and how the cities differ in terms of general real estate development determinants, fiscal capacity and regulatory authority, advocacy group support, and cultural diversity. We then employ a Negative Binomial Regression to test the relationship between concentrations of NU developments and a variety of city characteristics by using a data set of 6923 urban cities. The results suggest that NU developments are advocated by cities with a higher level of environmental awareness, better fiscal and regulatory status, and better cultural diversity. The research results highlight the importance of continuously gaining support from environmental groups and the general public for effective expansion of New Urbanist developments within the U.S. These findings also indicate that for noteworthy changes in growth patterns to arise at a large scale across the U.S., there must be changes in values and preferences, and institutional capacity in updating land-use regulations that allow for sustainable growth.


2019 ◽  
Author(s):  
Siddharth Subramaniyam ◽  
Anisha Zaveri ◽  
Michael A. DeJesus ◽  
Clare Smith ◽  
Richard E. Baker ◽  
...  

AbstractDeep sequencing of transposon mutant libraries (or TnSeq) is a powerful method for probing essentiality of genomic loci under different environmental conditions. Various analytical methods have been described for identifying conditionally essential genes whose tolerance for insertions varies between two conditions. However, for large-scale experiments involving many conditions, a method is needed for identifying genes that exhibit significant variability in insertions across multiple conditions. In this paper, we introduce a novel statistical method for identifying genes with significant variability of insertion counts across multiple conditions based on Zero-Inflated Negative Binomial (ZINB) regression. Using likelihood ratio tests, we show that the ZINB fits TnSeq data better than either ANOVA or a Negative Binomial (in a generalized linear model). We use ZINB regression to identify genes required for infection of M. tuberculosis H37Rv in C57BL/6 mice. We also use ZINB to perform a retrospective analysis of genes conditionally essential in H37Rv cultures exposed to multiple antibiotics. Our results show that, not only does ZINB generally identify most of the genes found by pairwise resampling (and vastly out-performs ANOVA), but it also identifies additional genes where variability is detectable only when the magnitudes of insertion counts are treated separately from local differences in saturation, as in the ZINB model.


2018 ◽  
Vol 15 (1) ◽  
pp. 93-110 ◽  
Author(s):  
Alfonso Serrano-Maíllo

Situational Action Theory (SAT) is an important theoretical development with relatively broad empirical content, reflected in highly specific hypotheses about crime causation. It offers an alternative concept of self-control to that of the General Theory of Crime and predicts that the effect of self-control on crime depends on crime contemplation. Crime contemplation is the tendency to consider crime as an action alternative. This paper is a test of SAT using data on 1304 juveniles from four Latin American cities with relatively high crime rates and impunity levels. It therefore contributes to cross-national testing. Both ordinary least squares and negative binomial regression techniques are applied. Three different ways to test interactions in non-linear models are used. Findings support the hypothesis. Results and limitations are discussed.


Author(s):  
Zoe Schroder ◽  
James B. Elsner

AbstractEnvironmental variables are routinely used in estimating when and where tornadoes are likely to occur, but more work is needed to understand how tornado and casualty counts of severe weather outbreak vary with the larger scale environmental factors. Here the authors demonstrate a method to quantify ‘outbreak’-level tornado and casualty counts with respect to variations in large-scale environmental factors. They do this by fitting negative binomial regression models to cluster-level environmental data to estimate the number of tornadoes and the number of casualties on days with at least ten tornadoes. Results show that a 1000 J kg−1 increase in CAPE corresponds to a 5% increase in the number of tornadoes and a 28% increase in the number of casualties, conditional on at least ten tornadoes, and holding the other variables constant. Further, results show that a 10 m s−1 increase in deep-layer bulk shear corresponds to a 13% increase in tornadoes and a 98% increase in casualties, conditional on at least ten tornadoes, and holding the other variables constant. The casualty-count model quantifies the decline in the number of casualties per year and indicates that outbreaks have a larger impact in the Southeast than elsewhere after controlling for population and geographic area.


PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0254192
Author(s):  
Véronique Chevalier ◽  
Holl Davun ◽  
Sopheak Sorn ◽  
Pitou Ly ◽  
Vutha Pov ◽  
...  

Cambodia is a rabid-endemic country. However, data on dog population characteristics are lacking, and there is no national dog vaccination program. We implemented the first extensive door-to-door longitudinal survey in 2 Cambodian provinces, namely Kandal and Battambang, to estimate dog population demographic parameters, identify dog ownership determinants, analyze dog management practices and estimate the yearly cumulative bite incidence and associated factors. During the first session, more than 5000 dogs were recorded and identified. Data on families, dogs and cats characteristics, as well as the number of bites experienced the year before in the family, were recorded. One year later, a second session was performed in both provinces to record missing dogs and the reasons for missing. Age-specific survival rates of the dog populations were computed using Kaplan-Meier estimates. Ownership determinants and bite risk factors were identified using a negative binomial regression model. Dog trade and dog meat consumption were often reported. We estimated high dog-to-human ratios (1:3.8 in Kandal, and 1:3.3 in Battambang). The mean age of dog populations was 26.4 months in Kandal against 24.3 in Battambang, with a survival rate of 52% at 24 months in Kandal (34% only in Battambang). They were no feral dogs, but the large majority of recorded dogs were free roaming. In both provinces, the number of dogs significantly increased in families with children younger than 15, and when the head of the family was a male. The estimated yearly cumulative bite incidences were 2.3 and 3.1% in Kandal and Battambang provinces respectively, and are among the highest in the world. Our survey provides valuable data to focus information programs, parametrize transmission models and identify efficient vaccination strategies to control rabies in Cambodia in the future.


2021 ◽  
pp. jech-2020-215039 ◽  
Author(s):  
Anders Malthe Bach-Mortensen ◽  
Michelle Degli Esposti

IntroductionThe COVID-19 pandemic has disproportionately impacted care homes and vulnerable populations, exacerbating existing health inequalities. However, the role of area deprivation in shaping the impacts of COVID-19 in care homes is poorly understood. We examine whether area deprivation is linked to higher rates of COVID-19 outbreaks and deaths among care home residents across upper tier local authorities in England (n=149).MethodsWe constructed a novel dataset from publicly available data. Using negative binomial regression models, we analysed the associations between area deprivation (Income Deprivation Affecting Older People Index (IDAOPI) and Index of Multiple Deprivation (IMD) extent) as the exposure and COVID-19 outbreaks, COVID-19-related deaths and all-cause deaths among care home residents as three separate outcomes—adjusting for population characteristics (size, age composition, ethnicity).ResultsCOVID-19 outbreaks in care homes did not vary by area deprivation. However, COVID-19-related deaths were more common in the most deprived quartiles of IDAOPI (incidence rate ratio (IRR): 1.23, 95% CI 1.04 to 1.47) and IMD extent (IRR: 1.16, 95% CI 1.00 to 1.34), compared with the least deprived quartiles.DiscussionThese findings suggest that area deprivation is a key risk factor in COVID-19 deaths among care home residents. Future research should look to replicate these results when more complete data become available.


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