Chicago supermarket data and food access analytics in census tract shapefiles for 2007-2014.
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ABSTRACT:
SUBMITTER: Kolak M
PROVIDER: S-EPMC6288981 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundUnhealthy food environments may be associated with higher risks of developing diet-related cancers, such as, colorectal cancer. We conducted an ecological analysis to evaluate the relationship between the local food environment and colorectal cancer incidence overall and separately for males and females.MethodsData from the Texas Cancer Registry was utilized to geocode individuals aged 40 years and older diagnosed with colorectal cancer from 2005 to 2015 to their residential 2010 census tract. Total number of establishments classified as Limited Service Restaurants for each census tract was retrieved from the 2005 Business Patterns Survey by using a crosswalk to map zip codes to census tract. Census tract unhealthy food availability was calculated by dividing the estimated number of Limited Service Restaurant establishments in each census tract by the census tract population and divided into quartiles. Generalized estimating equations were used to assess the association between unhealthy food availability quartiles and colorectal cancer incidence.ResultsAdjusting for the census tract level sociodemographic characteristics, the incidence of colorectal cancer was slightly higher in unhealthy food availability quartile 2 (Incidence Rate Ratio (IRR) = 1.03, 95 % CI: 1.00-1.05), but not quartile 3 (IRR = 1.02, 95 % CI: 1.00-1.05), and quartile 4 (highest availability, IRR = 1.02, 95 % CI: 0.99-1.05) compared to census tracts with lowest unhealthy food availability.ConclusionColorectal cancer incidence was not strongly associated with census tracts with higher unhealthy food availability. Future observational studies should be conducted to examine the influence of the built environment on colorectal cancer risk.
| S-EPMC8287297 | biostudies-literature
Project description:Citation is one of the important metrics that are used in measuring the relevance and the impact of research publications. The potentials of citation analytics may be exploited to understand the gains of publishing scholarly peer-reviewed research outputs in either Open Access (OA) sources or Subscription-Based (SB) sources in the bid to increase citation impact. However, relevant data required for such comparative analysis must be freely accessible for evidence-based findings and conclusions. In this data article, citation scores (CiteScores) of 2542 OA sources and 15,040 SB sources indexed in Scopus from 2014 to 2016 were presented and analyzed based on a set of five inclusion criteria. A robust dataset, which contains the CiteScores of OA and SB publication sources included, is attached as supplementary material to this data article to facilitate further reuse. Descriptive statistics and frequency distributions of OA CiteScores and SB CiteScores are presented in tables. Boxplot representations and scatter plots are provided to show the statistical distributions of OA CiteScores and SB CiteScores across the three sub-categories (Book Series, Journal, and Trade Journal). Correlation coefficient and p-value matrices are made available within the data article. In addition, Probability Density Functions (PDFs) and Cumulative Distribution Functions (CDFs) of OA CiteScores and SB CiteScores are computed and the results are presented using tables and graphs. Furthermore, Analysis of Variance (ANOVA) and multiple comparison post-hoc tests are conducted to understand the statistical difference (and its significance, if any) in the citation impact of OA publication sources and SB publication source based on CiteScore. In the long run, the data provided in this article will help policy makers and researchers in Higher Education Institutions (HEIs) to identify the appropriate publication source type and category for dissemination of scholarly research findings with maximum citation impact.
| S-EPMC5993002 | biostudies-literature
Project description:There is a growing recognition of social media data as being useful for understanding local area patterns. In this study, we sought to utilize geotagged tweets-specifically, the frequency and type of food mentions-to understand the neighborhood food environment and the social modeling of food behavior. Additionally, we examined associations between aggregated food-related tweet characteristics and prevalent chronic health outcomes at the census tract level. We used a Twitter streaming application programming interface (API) to continuously collect ~1% random sample of public tweets in the United States. A total of 4,785,104 geotagged food tweets from 71,844 census tracts were collected from April 2015 to May 2018. We obtained census tract chronic disease outcomes from the CDC 500 Cities Project. We investigated associations between Twitter-derived food variables and chronic outcomes (obesity, diabetes and high blood pressure) using the median regression. Census tracts with higher average calories per tweet, less frequent healthy food mentions, and a higher percentage of food tweets about fast food had higher obesity and hypertension prevalence. Twitter-derived food variables were not predictive of diabetes prevalence. Food-related tweets can be leveraged to help characterize the neighborhood social and food environment, which in turn are linked with community levels of obesity and hypertension.
| S-EPMC6466014 | biostudies-literature
Project description:The amount of plant biodiversity data available via the web has exploded in the last decade, but making these data available requires a considerable investment of time and work, both vital considerations for organizations and institutions looking to validate the impact factors of these online works. Here we used Google Analytics (GA), to measure the value of this digital presence. In this paper we examine usage trends using 15 different GA accounts, spread across 451 institutions or botanical projects that comprise over five percent of the world's herbaria. They were studied at both one year and total years. User data from the sample reveal: 1) over 17 million web sessions, 2) on five primary operating systems, 3) search and direct traffic dominates with minimal impact from social media, 4) mobile and new device types have doubled each year for the past three years, 5) and web browsers, the tools we use to interact with the web, are changing. Server-side analytics differ from site to site making the comparison of their data sets difficult. However, use of Google Analytics erases the reporting heterogeneity of unique server-side analytics, as they can now be examined with a standard that provides a clarity for data-driven decisions. The knowledge gained here empowers any collection-based environment regardless of size, with metrics about usability, design, and possible directions for future development.
| S-EPMC4238075 | biostudies-literature
Project description:BackgroundRace is an important predictor of TKA outcomes in the United States; however, analyses of race can be confounded by socioeconomic factors, which can result in difficulty determining the root cause of disparate outcomes after TKA.Questions/purposesWe asked: (1) Are race and socioeconomic factors at the individual level associated with patient-reported pain and function 2 years after TKA? (2) What is the interaction between race and community poverty and patient-reported pain and function 2 years after TKA?MethodsWe identified all patients undergoing TKA enrolled in a hospital-based registry between 2007 and 2011 who provided 2-year outcomes and lived in New York, Connecticut, or New Jersey. Of patients approached to participate in the registry, more than 82% consented and provided baseline data, and of these patients, 72% provided 2-year data. Proportions of patients with complete followup at 2 years were lower among blacks (57%) than whites (74%), among patients with Medicaid insurance (51%) compared with patients without Medicaid insurance (72%), and among patients without a college education (67%) compared with those with a college education (71%). Our final study cohort consisted of 4035 patients, 3841 (95%) of whom were white and 194 (5%) of whom were black. Using geocoding, we linked individual-level registry data to US census tracts data through patient addresses. We constructed a multivariate linear mixed-effect model in multilevel frameworks to assess the interaction between race and census tract poverty on WOMAC pain and function scores 2 years after TKA. We defined a clinically important effect as 10 points on the WOMAC (which is scaled from 1 to 100 points, with higher scores being better).ResultsRace, education, patient expectations, and baseline WOMAC scores are all associated with 2-year WOMAC pain and function; however, the effect sizes were small, and below the threshold of clinical importance. Whites and blacks from census tracts with less than 10% poverty have similar levels of pain and function 2 years after TKA (WOMAC pain, 1.01 ± 1.59 points lower for blacks than for whites, p = 0.53; WOMAC function, 2.32 ± 1.56 lower for blacks than for whites, p = 0.14). WOMAC pain and function scores 2 years after TKA worsen with increasing levels of community poverty, but do so to a greater extent among blacks than whites. Disparities in pain and function between blacks and whites are evident only in the poorest communities; decreasing in a linear fashion as poverty increases. In census tracts with greater than 40% poverty, blacks score 6 ± 3 points lower (worse) than whites for WOMAC pain (p = 0.03) and 7 ± 3 points lower than whites for WOMAC function (p = 0.01).ConclusionsBlacks and whites living in communities with little poverty have similar patient-reported TKA outcomes, whereas in communities with high levels of poverty, there are important racial disparities. Efforts to improve TKA outcomes among blacks will need to address individual- and community-level socioeconomic factors.Level of evidenceLevel III, therapeutic study.
| S-EPMC4965380 | biostudies-literature
Project description:IntroductionThis paper reports the key findings of the Faculty of Radiation Oncology 2014 workforce census and compares the results with earlier surveys.MethodsThe census was conducted in mid-2014 with distribution to all radiation oncologists, educational affiliates and trainees listed on the college database. There were six email reminders and responses were anonymous. The overall response rate was 76.1%.ResultsThe age range of fellows was 32-96 (mean = 49 years, median = 47 years). The majority of the radiation oncologists were male (n = 263, 63%). The minority of radiation oncologists were of Asian descent (n = 43, 13.4%). Radiation oncologists graduated from medical school on average 23 years ago (median = 22 years). A minority of fellows (n = 66, 20%) held another postgraduate qualification. Most radiation oncologists worked, on average, at two practices (median = 2, range 1-7). Practising radiation oncologists worked predominantly in the public sector (n = 131, 49%), but many worked in both the public and private sectors (n = 94, 37%), and a minority worked in the private sector only (n = 38, 14%). The largest proportion of the workforce was from New South Wales accounting for 29% of radiation oncologists. Radiation oncologists worked an average of 43 h/week (median = 43 h, range 6-80). Radiation oncologists who worked in the private sector worked less hours than their public sector or public/private sector colleagues. (38.3 vs. 42.9 vs. 44.3 h, P = 0.042). Victorians worked the fewest average hours per week at 38 h and West Australians the most at 46 h/week. Radiation oncologists averaged 48 min for each new case, 17 min per follow up and 11 min for a treatment review. Radiation oncologists averaged 246 new patients per year (median = 250, range = 20-600) with men (average = 268), Western Australians (average = 354) and those in private practice seeing more (average = 275). Most radiation oncologists considered themselves as specialists (n = 151, 60%), but nearly all those from South Australia were generalists (n = 15, 94%) as were three-quarters of those from private practice. A minority of radiation oncologist respondents (10%) intended to retire within 5 years with a further 16% within 10 years.There was a stabilisation of trainee numbers in Australia and New Zealand with no increase compared with 2010 (142 in 2014 vs. 143 in 2010). The most common age bracket for trainees remained 31-35 years. One-third of trainees were of Asian descent and nearly half held other degrees. The majority of trainees were satisfied with their career, but 30% were not entirely satisfied. Nearly half of trainee respondents would have reconsidered their choice of specialty had they known about the possible oversupply in the workforce with 12.4% undecided about continuing their career in radiation oncology. There were still 16% of trainees with no protected time during the working week, and a further 21% with only 1 h. Only one trainee respondent preferred to work in private practice, and job availability remained a concern for 89% of respondents.ConclusionsThe radiation oncologist workforce numbers have increased at a much slower rate, and unemployment remained low. Many parameters remained similar to the 2010 survey. However, there has been a decrease in the average number of new patients seen per year, working hours and also a slight decrease in the time spent per new patient. The trainee numbers have stabilised, but job availability remained a concern. A significant proportion of trainees were not satisfied with their career.
| S-EPMC5061100 | biostudies-literature
Project description:BackgroundShigella causes an estimated 500 000 enteric illnesses in the United States annually, but the association with socioeconomic factors is unclear.MethodsWe examined possible epidemiologic associations between shigellosis and poverty using 2004-2014 Foodborne Diseases Active Surveillance Network (FoodNet) data. Shigella cases (n = 21 246) were geocoded, linked to Census tract data from the American Community Survey, and categorized into 4 poverty and 4 crowding strata. For each stratum, we calculated incidence by sex, age, race/ethnicity, and FoodNet site. Using negative binomial regression, we estimated incidence rate ratios (IRRs) comparing the highest to lowest stratum.ResultsAnnual FoodNet Shigella incidence per 100 000 population was higher among children <5 years old (19.0), blacks (7.2), and Hispanics (5.6) and was associated with Census tract poverty (incidence rate ratio [IRR], 3.6; 95% confidence interval [CI], 3.5-3.8) and household crowding (IRR, 1.8; 95% CI, 1.7-1.9). The association with poverty was strongest among children and persisted regardless of sex, race/ethnicity, or geographic location. After controlling for demographic variables, the association between shigellosis and poverty remained significant (IRR, 2.3; 95% CI, 2.0-2.6).ConclusionsIn the United States, Shigella infections are epidemiologically associated with poverty, and increased incidence rates are observed among young children, blacks, and Hispanics.
| S-EPMC7032626 | biostudies-literature
Project description:Childhood obesity is one of the most pressing public health issues nowadays. The environmental factors have been identified as potential risks for obesity, as they may influence people's lifestyle behaviours. Lack of access to supermarkets that usually provide healthy food options has been found to be a risk factor for childhood obesity in several studies. However, findings remained inconclusive. We aimed to systematically review the association between access to supermarkets and childhood obesity. A literature search was conducted in the Cochrane Library, PubMed, Web of Science, and Embase for studies published before 1 January 2019. Twenty-four studies conducted in four countries were identified, from which data on the basic characteristics of studies and participants, measures of access to supermarkets, and associations between access to supermarkets and weight-related behaviours and outcomes were extracted. The median sample size was 1858 participants. Half of the included studies indicated a negative association, one fourth reported a positive association, and the remaining one fourth did not find a significant association. Better designed studies are necessary to achieve a robust understanding of this epidemiological relationship in the future.
| S-EPMC7988565 | biostudies-literature
Project description:ObjectivesTo help guide universal influenza vaccination efforts in the United States, it is important to know which demographic groups are currently at highest risk of costly complications of influenza infection. Few studies have examined the relationship between hospitalization with influenza and either socioeconomic status (SES) or sex. We examined associations between census tract-level SES and sex and incidence of influenza-related hospitalizations among adults.DesignDescriptive analysis of data collected by active population-based surveillance for persons >18 years old hospitalized with laboratory confirmed influenza during the 2007-2008 through 2010-2011 influenza seasons. Case residential addresses were geocoded and linked to data from the 2006-2010 American Community Survey to obtain census-tract level (neighborhood) SES measures. Census-tract level SES variables included measures of poverty, education, crowding, primary language, and median income. Four levels were created for each.SettingNew Haven, County, Connecticut.SampleEntire New Haven County population >18 years old.Main outcome measuresAge-adjusted incidence of influenza hospitalizations and relative risk by sex and by each of five SES measures.ResultsCrude and age-adjusted incidence progressively increased with decreasing neighborhood SES for each measure both overall and for each influenza season. Female incidence was higher than male for each age group, and female age-adjusted incidence was higher for each SES level and influenza season.ConclusionsFemale sex and lower neighborhood SES were independently and consistently associated with higher incidence of hospitalization of adults with influenza. If this is more broadly the case, these findings have implications for future influenza vaccination efforts. Analysis using census tract SES measures can provide additional perspective on health disparities.
| S-EPMC4181475 | biostudies-literature
Project description:Exponential rise of metagenomics sequencing is delivering massive functional environmental genomics data. However, this also generates a procedural bottleneck for on-going re-analysis as reference databases grow and methods improve, and analyses need be updated for consistency, which require acceess to increasingly demanding bioinformatic and computational resources. Here, we present the KAUST Metagenomic Analysis Platform (KMAP), a new integrated open web-based tool for the comprehensive exploration of shotgun metagenomic data. We illustrate the capacities KMAP provides through the re-assembly of ~ 27,000 public metagenomic samples captured in ~ 450 studies sampled across ~ 77 diverse habitats. A small subset of these metagenomic assemblies is used in this pilot study grouped into 36 new habitat-specific gene catalogs, all based on full-length (complete) genes. Extensive taxonomic and gene annotations are stored in Gene Information Tables (GITs), a simple tractable data integration format useful for analysis through command line or for database management. KMAP pilot study provides the exploration and comparison of microbial GITs across different habitats with over 275 million genes. KMAP access to data and analyses is available at https://www.cbrc.kaust.edu.sa/aamg/kmap.start .
| S-EPMC8169707 | biostudies-literature