Evidence and theory for lower rates of depression in larger US urban areas.
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ABSTRACT:
SUBMITTER: Stier AJ
PROVIDER: S-EPMC8346882 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectiveTo assess rural-urban differences in electronic medical record (EMR) adoption among office-based physician practices in the United States.MethodsSurvey data on over 270 000 office-based physician sites (representing over 1 280 000 physicians) in the United States from 2012 was used to assess differences in EMR adoption rates among practices in rural and urban areas. Logistic regression tests for differences in the determinants of EMR adoption by geography, and a nonlinear decomposition is used to quantify how much of the rural-urban gap is due to differences in measureable characteristics (such as type of practice or affiliation with a health system).ResultsOverall EMR adoption rates were significantly higher for practices in rural areas (56%) vs those in urban areas (49%) in 2012 (P < 0.001). Twenty-nine states had statistically significantly different adoption rates between rural and urban areas, with only two states demonstrating higher rates in urban areas. EMR adoption continues to be higher for primary care practices when compared to specialists (51% vs 49%, P < 0.001), and state-level rural-urban differences in adoption are more pronounced for specialists. The decomposition technique finds that only 14% of the rural-urban gap can be explained by differences in measurable characteristics between practices.ConclusionsAt the national level, rates of EMR adoption are higher for rural practices than for their urban counterparts, reversing earlier trends. This suggests that outreach efforts, namely the Regional Extension Centers created by the Office of the National Coordinator, have been particularly effective in increasing EMR adoption in rural areas.
| S-EPMC8485927 | biostudies-literature
Project description:PurposeUrban areas are usually found to have higher rates of self-harm, with deprivation the strongest predictor at area-level. We use a disease mapping approach to examine how self-harm is patterned within an urban area and its associations with deprivation, urbanness and ethnicity.MethodsData from clinical records on individuals admitted for self-harm for 725 small areas in South East London were included. Bayesian hierarchical models explored the spatio-temporal patterns of self-harm admission rates and potential associations with proximity to city centre, population density, percentage greenspace and non-white ethnic-minority populations. All models were adjusted for area-level deprivation, social fragmentation and hospital of admission.ResultsThere were 8327 first admissions for self-harm during the study period. Self-harm admission rates varied fourfold across the study area, with lower rates close to the city centre [adjusted standardised admission ratio, closest versus furthest quartile 0.71(95% CrI 0.54-0.96)]. Deprivation was associated with self-harm but partially masked rather than explained the spatial pattern, which strengthened after adjustment. After adjustment for deprivation, hospital of admission and social fragmentation, greenspace, population density and ethnicity were not associated with self-harm rates.ConclusionProximity to the city centre was associated with lower rates of self-harm, but the usual operationalisations of urbanness, population density and greenspace, were not. Deprivation did not explain the spatial patterning, nor did ethnicity. While nationally self-harm rates are higher in urban and deprived areas, this cannot be extrapolated to mean that within cities the inner-city is the highest risk area nor that risk will be principally patterned according to deprivation.
| S-EPMC6336929 | biostudies-literature
Project description:Background Rates of major lower extremity amputation in patients with peripheral artery disease are higher in rural communities with markers of low socioeconomic status, but most Americans live in metropolitan areas. Whether amputation rates vary within US metropolitan areas is unclear, as are characteristics of high amputation rate urban communities. Methods and Results We estimated rates of major lower extremity amputation per 100 000 Medicare beneficiaries between 2010 and 2018 at the ZIP code level among ZIP codes with ≥100 beneficiaries. We described demographic characteristics of high and low amputation ZIP codes, and the association between major amputation rate and 3 ZIP code-level markers of socioeconomic status-the proportion of patients with dual eligibility for Medicaid, median household income, and Distressed Communities Index score-for metropolitan, micropolitan, and rural ZIP code cohorts. Between 2010 and 2018, 188 995 Medicare fee-for-service patients living in 31 391 ZIP codes with ≥100 beneficiaries had a major lower extremity amputation. The median (interquartile range) ZIP code-level number of amputations per 100 000 beneficiaries was 262 (75-469). Though nonmetropolitan ZIP codes had higher rates of major amputation than metropolitan areas, 78.2% of patients undergoing major amputation lived in metropolitan areas. Compared with ZIP codes with lower amputation rates, top quartile amputation rate ZIP codes had a greater proportion of Black residents (4.4% versus 17.5%, P<0.001). In metropolitan areas, after adjusting for clinical comorbidities and demographics, every $10 000 lower median household income was associated with a 4.4% (95% CI, 3.9-4.8) higher amputation rate, and a 10-point higher Distressed Communities Index score was associated with a 3.8% (95% CI, 3.4%-4.2%) higher amputation rate; there was no association between the proportion of patients eligible for Medicaid and amputation rate. These findings were comparable to the associations identified across all ZIP codes. Conclusions In metropolitan areas, where most individuals undergoing lower extremity amputation live, markers of lower socioeconomic status and Black race were associated with higher rates of major lower extremity amputation. Development of community-based tools for peripheral artery disease diagnosis and management targeted to communities with high amputation rates in urban areas may help reduce inequities in peripheral artery disease outcomes.
| S-EPMC8649262 | biostudies-literature
Project description:Much research has examined how crime rates vary across urban neighborhoods, focusing particularly on community-level demographic and social characteristics. A parallel line of work has treated crime at the individual level as an expression of certain behavioral patterns (e.g., impulsivity). Little work has considered, however, whether the prevalence of such behavioral patterns in a neighborhood might be predictive of local crime, in large part because such measures are hard to come by and often subjective. The Facebook Advertising API offers a special opportunity to examine this question as it provides an extensive list of "interests" that can be tabulated at various geographic scales. Here we conduct an analysis of the association between the prevalence of interests among the Facebook population of a ZIP code and the local rate of assaults, burglaries, and robberies across 9 highly populated cities in the US. We fit various regression models to predict crime rates as a function of the Facebook and census demographic variables. In general, models using the variables for the interests of the whole adult population on Facebook perform better than those using data on specific demographic groups (such as Males 18-34). In terms of predictive performance, models combining Facebook data with demographic data generally have lower error rates than models using only demographic data. We find that interests associated with media consumption and mating competition are predictive of crime rates above and beyond demographic factors. We discuss how this might integrate with existing criminological theory.
| S-EPMC6361434 | biostudies-literature
Project description:SPATIO-TEMPORAL VARIABILITY AND COMMUNITY-ASSEMBLY PROCESSES OF AIRBORNE BACTERIA ACROSS TWO URBAN AREAS
| PRJEB7001 | ENA
Project description:Sex differences exist in behaviors, disease and neuropsychiatric disorders. Sexual dimorphisms however, have yet to be studied across the whole brain and across a comprehensive time course of postnatal development. Here, we use manganese-enhanced MRI (MEMRI) to longitudinally image male and female C57BL/6J mice across 9 time points, beginning at postnatal day 3. We recapitulate findings on canonically dimorphic areas, demonstrating MEMRI's ability to study neuroanatomical sex differences. We discover, upon whole-brain volume correction, that neuroanatomical regions larger in males develop earlier than those larger in females. Groups of areas with shared sexually dimorphic developmental trajectories reflect behavioral and functional networks, and expression of genes involved with sex processes. Also, post-pubertal neuroanatomy is highly individualized, and individualization occurs earlier in males. Our results demonstrate the ability of MEMRI to reveal comprehensive developmental differences between male and female brains, which will improve our understanding of sex-specific predispositions to various neuropsychiatric disorders.
| S-EPMC6033927 | biostudies-literature
Project description:We provide a map of wildland urban interface (WUI) areas at national scale in Greece, using as primary data the Corine Land Cover (CLC) 2018 product. The WUI areas distribution in Greece is calculated for all the regional units of the county. The regional units correspond to NUTS (Nomenclature of Territorial Units for Statistics) level 2 for Greece, being important for the national to regional fire risk management and mitigation within the country. Furthermore, spatially explicit information regarding the fire affected areas and the changes in WUI areas between 2006 and 2018 on the basis of the CLC data for each regional unit is also provided. This geospatial information can provide valuable, concurrent information at no-cost to all responsible and competent authorities involved in landscape fire management in Greece and represent a valuable contribution to assist in national and regional scale planning.
| S-EPMC7372015 | biostudies-literature
Project description:Do large mammals evolve faster than small mammals or vice versa? Because the answer to this question contributes to our understanding of how life-history affects long-term and large-scale evolutionary patterns, and how microevolutionary rates scale-up to macroevolutionary rates, it has received much attention. A satisfactory or consistent answer to this question is lacking, however. Here, we take a fresh look at this problem using a large fossil dataset of mammals from the Neogene of the Old World (NOW). Controlling for sampling biases, calculating per capita origination and extinction rates of boundary-crossers and estimating survival probabilities using capture-mark-recapture (CMR) methods, we found the recurring pattern that large mammal genera and species have higher origination and extinction rates, and therefore shorter durations. This pattern is surprising in the light of molecular studies, which show that smaller animals, with their shorter generation times and higher metabolic rates, have greater absolute rates of evolution. However, higher molecular rates do not necessarily translate to higher taxon rates because both the biotic and physical environments interact with phenotypic variation, in part fueled by mutations, to affect origination and extinction rates. To explain the observed pattern, we propose that the ability to evolve and maintain behavior such as hibernation, torpor and burrowing, collectively termed "sleep-or-hide" (SLOH) behavior, serves as a means of environmental buffering during expected and unexpected environmental change. SLOH behavior is more common in some small mammals, and, as a result, SLOH small mammals contribute to higher average survivorship and lower origination probabilities among small mammals.
| S-EPMC2329699 | biostudies-literature
Project description:In a world in which the pace of cities is increasing, prompt access to relevant information is crucial to the understanding and regulation of land use and its evolution in time. In spite of this, characterization and regulation of urban areas remains a complex process, requiring expert human intervention, analysis and judgment. Here we carry out a spatio-temporal fractal analysis of a metropolitan area, based on which we develop a model which generates a cartographic representation and classification of built-up areas, identifying (and even predicting) those areas requiring the most proximate planning and regulation. Furthermore, we show how different types of urban areas identified by the model co-evolve with the city, requiring policy regulation to be flexible and adaptive, acting just in time. The algorithmic implementation of the model is applicable to any built-up area and simple enough to pave the way for the automatic classification of urban areas worldwide.
| S-EPMC3402843 | biostudies-other
Project description:Background: Many regions worldwide reported a decline of stroke admissions during the early phase of the coronavirus disease 2019 (COVID-19) pandemic. It remains unclear whether urban and rural regions experienced similar declines and whether deviations from historical admission numbers were more pronounced among specific age, stroke severity or treatment groups. Methods: We used registry datasets from (a) nine acute stroke hospitals in Berlin, and (b) nine hospitals from a rural TeleNeurology network in Northeastern Germany for primary analysis of 3-week-rolling average of stroke/TIA admissions before and during the COVID-19 pandemic. We compared course of stroke admission numbers with regional cumulative severe acute respiratory syndrome coronavirus 2 (Sars-CoV-2) infections. In secondary analyses, we used emergency department logs of the Berlin Charité University hospital to investigate changes in age, stroke severity, and thrombolysis/thrombectomy frequencies during the early regional Sars-CoV-2 spread (March and April 2020) and compared them with preceding years. Results: Compared to past years, stroke admissions decreased by 20% in urban and 20-25% in rural hospitals. Deviations from historical averages were observable starting in early March and peaked when numbers of regional Sars-CoV-2 infections were still low. At the same time, average admission stroke severity and proportions of moderate/severe strokes (NIHSS >5) were 20 and 20-40% higher, respectively. There were no relevant deviations observed in proportions of younger patients (<65 years), proportions of patients with thrombolysis, or number of thrombectomy procedures. Stroke admissions at Charité subsequently rebounded and reached near-normal levels after 4 weeks when the number of new Sars-CoV-2 infections started to decrease. Conclusions: During the early pandemic, deviations of stroke-related admissions from historical averages were observed in both urban and rural regions of Northeastern Germany and appear to have been mainly driven by avoidance of admissions of mildly affected stroke patients.
| S-EPMC7815522 | biostudies-literature