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Statistical Area (statistical + area)
Kinds of Statistical Area Selected AbstractsClimatology of cloud-to-ground lightning in Georgia, USA, 1992,2003INTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 15 2005Mace L. Bentley Abstract A 12-year climatology of lightning cloud-to-ground flash activity for Georgia revealed the existence of three primary regions of high lightning activity: the area surrounding the Atlanta Metropolitan Statistical Area, east-central Georgia along the fall line, and along the Atlantic coast. Over 8.2 million ground flashes were identified during the climatology. July was the most active lightning month and December was the least active. Annual, seasonal, and diurnal distributions of cloud-to-ground flashes were also examined. These patterns illustrated the interacting effects of land cover, topography, and convective instability in enhancing lightning activity throughout Georgia. A synoptic analysis of the ten highest lightning days during the summer and winter revealed the importance of frontal boundaries in organizing convection and high lightning activity during both seasons. The prominence of convective instability during the summer and strong dynamical forcing in the winter was also found to lead to outbreaks of high lightning activity. Copyright © 2005 Royal Meteorological Society. [source] Spatial segregation, segregation indices and the geographical perspectivePOPULATION, SPACE AND PLACE (PREVIOUSLY:-INT JOURNAL OF POPULATION GEOGRAPHY), Issue 2 2006Lawrence A. Brown Abstract What could be more inherently geographical than segregation? However, the richness of the spatial variations in segregation is seldom captured by the dominant genre of empirical research. Returning the ,geography' to segregation research, we argue that local areas need to be given considerably more attention, using measures that explicitly reveal the spatial fabric of residential clustering along racial/ethnic lines. We first critique global measures such as the Dissimilarity Index and its spatial counterparts. Attention then turns to local measures such as the Location Quotient and Local Moran's I, applying them to Franklin County, Ohio, the core of Columbus MSA (Metropolitan Statistical Area). Our interpretation of the findings also employs local knowledge concerning neighbourhood characteristics, ongoing urban processes, historical occurrences, and the like. Thus, while local indices based on secondary data expose the terrain of clustering/segregation, follow-up fieldwork and/or secondary data analysis in a mixed-methods framework provides a better understanding of the ground-level reality of clustering/segregation. Tangible evidence of the gain from this approach is provided by our evaluation of conventional frameworks for understanding racial/ethnic aspects of residential patterning , assimilation, stratification and resurgent ethnicity , and in our proposal for a new framework, ,market-led pluralism', which focuses on market makers who represent the supply side of housing. Copyright © 2006 John Wiley & Sons, Ltd. [source] Geography and segmented assimilation: examples from the New York ChinesePOPULATION, SPACE AND PLACE (PREVIOUSLY:-INT JOURNAL OF POPULATION GEOGRAPHY), Issue 1 2004K. Bruce Newbold Abstract Drawing upon the segmented assimilation framework, and using the 1990 5% PUMS file, the paper compares the assimilation of selected Chinese immigrant cohorts, based upon age and period of entry. Including a spatial component within the framework, we examine whether differences in the organisation and assimilation of immigrant groups exist across space. For each cohort, contrasts are made with reference to location in the New York Consolidated Metropolitan Statistical Area (CMSA), with the analysis focusing upon differences in spatial assimilation with respect to acculturation, socioeconomic characteristics, internal migration, and immigrant characteristics relative to other immigrant and native-born groups. The analysis is updated using Immigration and Naturalization Service (INS) data files from the 1990s. Results suggest that space, and location in space, alter the assimilation trajectory of similarly defined groups. Copyright © 2004 John Wiley & Sons, Ltd. [source] The Association Between Rural Residence and the Use, Type, and Quality of Depression CareTHE JOURNAL OF RURAL HEALTH, Issue 3 2010John C. Fortney PhD Abstract Objective: To assess the association between rurality and depression care. Methods: Data were extracted for 10,319 individuals with self-reported depression in the Medical Expenditure Panel Survey. Pharmacotherapy was defined as an antidepressant prescription fill, and minimally adequate pharmacotherapy was defined as receipt of at least 4 antidepressant fills. Psychotherapy was defined as an outpatient counseling visit, and minimally adequate psychotherapy was defined as , 8 visits. Rurality was defined using Metropolitan Statistical Areas (MSAs) and Rural Urban Continuum Codes (RUCCs). Results: Over the year, 65.1% received depression treatment, including 58.8% with at least 1 antidepressant prescription fill and 24.5% with at least 1 psychotherapy visit. Among those in treatment, 56.2% had minimally adequate pharmacotherapy treatment and 36.3% had minimally adequate psychotherapy treatment. Overall, there were no significant rural-urban differences in receipt of any type of formal depression treatment. However, rural residence was associated with significantly higher odds of receiving pharmacotherapy (MSA: OR 1.16 [95% CI, 1.01-1.34; P= .04] and RUCC: OR 1.04 [95% CI, 1.00-1.08; P= .05]), and significantly lower odds of receiving psychotherapy (MSA: OR 0.62 [95% CI, 0.53-0.74; P < .01] and RUCC: OR 0.91 [95% CI, 0.88-0.94; P < .001]). Rural residence was not significantly associated with the adequacy of pharmacotherapy, but it was significantly associated with the adequacy of psychotherapy (MSA: OR 0.53 [95% CI, 0.41-0.69; P < .01] and RUCC: OR 0.92 [95% CI, 0.86-0.99; P= .02]). Psychiatrists per capita were a mediator in the psychotherapy analyses. Conclusions: Rural individuals are more reliant on pharmacotherapy than psychotherapy. This may be a concern if individuals in rural areas turn to pharmacotherapy because psychotherapists are unavailable rather than because they have a preference for pharmacotherapy. [source] Change in the Concentration of Employment in Computer Services: Spatial Estimation at the U.S. Metro County LevelGROWTH AND CHANGE, Issue 1 2007DONALD GRIMES ABSTRACT This article models the concentration of computer services activity across the U.S. with factors that incorporate spatial relationships. Specifically, we enhance the standard home-area study with an analysis that allows conditions in neighboring counties to affect the concentration of employment in the home county. We use county-level data for metropolitan areas between 1990 and 1997. To measure change in employment concentration, we use the change in location quotients for SIC 737, which captures employment concentration changes caused by both the number of firms and the scale of their activity relative to the national average. After controlling for local demand for computer services, our results support the importance of the presence of a qualified labor supply, interindustry linkages, proximity to a major airport, and spatial processes in explaining changes in computer services employment concentration, finding little support for the influence of cost factors. Our enhanced model reveals interjurisdictional relationships among these metro counties that could not be captured with standard estimates by state, metropolitan statistical area (MSA), or county. Using counties within MSAs, therefore, provides more general results than case studies but still allows measurement of local interactions. [source] Presence of a Community Health Center and Uninsured Emergency Department Visit Rates in Rural CountiesTHE JOURNAL OF RURAL HEALTH, Issue 1 2009FAAFP, FACPM, George Rust MD ABSTRACT:,Context: Community health centers (CHCs) provide essential access to a primary care medical home for the uninsured, especially in rural communities with no other primary care safety net. CHCs could potentially reduce uninsured emergency department (ED) visits in rural communities. Purpose: We compared uninsured ED visit rates between rural counties in Georgia that have a CHC clinic site and counties without a CHC presence. Methods: We analyzed data from 100% of ED visits occurring in 117 rural (non-metropolitan statistical area [MSA]) counties in Georgia from 2003 to 2005. The counties were classified as having a CHC presence if a federally funded (Section 330) CHC had a primary care delivery site in that county throughout the study period. The main outcome measure was uninsured ED visit rates among the uninsured (all-cause ED visits and visits for ambulatory care sensitive conditions). Poisson regression models were used to examine the relationship between ED rates and the presence of a CHC. To ensure that the effects were unique to the uninsured population, we ran similar analyses on insured ED visits. Findings: Counties without a CHC primary care clinic site had 33% higher rates of uninsured all-cause ED visits per 10,000 uninsured population compared with non-CHC counties (rate ratio [RR] 1.33, 95% confidence interval [CI] 1.11-1.59). Higher ED visit rates remained significant (RR 1.21, 95% CI 1.02-1.42) after adjustment for percentage of population below poverty level, percentage of black population, and number of hospitals. Uninsured ED visit rates were also higher for various categories of diagnoses, but remained statistically significant on multivariate analysis only for ambulatory care sensitive conditions (adjusted RR = 1.22, 95% CI 1.01-1.47). No such relationship was found for ED visit rates of insured patients (RR 1.06, 95% CI 0.92-1.22). Conclusions: The absence of a CHC is associated with a substantial excess in uninsured ED visits in rural counties, an excess not seen for ED visit rates among the insured. [source] Rural,Urban Differences in Primary Care Physicians' Practice Patterns, Characteristics, and IncomesTHE JOURNAL OF RURAL HEALTH, Issue 2 2008William B. Weeks MD ABSTRACT:,Context:Low salaries and difficult work conditions are perceived as a major barrier to the recruitment of primary care physicians to rural settings. Purpose: To examine rural,urban differences in physician work effort, physician characteristics, and practice characteristics, and to determine whether, after adjusting for any observed differences, rural primary care physicians' incomes were lower than those of urban primary care physicians. Methods: Using survey data from actively practicing office-based general practitioners (1,157), family physicians (1,378), general internists (2,811), or pediatricians (1,752) who responded to the American Medical Association's annual survey of physicians between 1992 and 2002, we used linear regression modeling to determine the association between practicing in a rural (nonmetropolitan) or urban (standard metropolitan statistical area) setting and physicians' annual incomes after controlling for specialty, work effort, provider characteristics, and practice characteristics. Findings: Rural primary care physicians' unadjusted annual incomes were similar to their urban counterparts, but they tended to work longer hours, complete more patient visits, and have a much greater proportion of Medicaid patients. After adjusting for work effort, physician characteristics, and practice characteristics, primary care physicians who practiced in rural settings made $9,585 (5%) less than their urban counterparts (95% confidence intervals: ,$14,569, ,$4,602, P < .001). In particular, rural practicing general internists and pediatricians experienced lower incomes than did their urban counterparts. Conclusions: Addressing rural physicians' lower incomes, longer work hours, and greater dependence on Medicaid reimbursement may improve the ability to ensure that an adequate supply of primary care physicians practice in rural settings. [source] Beyond Material Explanations: Family Solidarity and Mortality, a Small Area-level AnalysisPOPULATION AND DEVELOPMENT REVIEW, Issue 1 2010Jon Anson Social solidarity, being embedded in a network of binding social relationships, tends to extend human longevity. Yet while average incomes in the Western world, and with them, life expectancies, have risen dramatically, the second demographic transition has occasioned a breakdown in traditional family forms. This article considers whether these trends in family life may have slowed the rise in life expectancy. I present a cross-sectional analysis of Israeli statistical areas (SAs), for which I construct indexes of Standard of Living (SOL), Traditional Family Structure (TFS), and Religiosity (R). I show that (1) increases in all three of these indexes are associated with lower levels of mortality, (2) male mortality is more sensitive to differences in SOL and TFS than is female mortality, and (3) net of differences in SOL and TFS, there is no difference in the mortality levels of Arab and Jewish populations. [source] | ||||||||||