Regional Level Variations Research Articles

Do regional labor market conditions matter for temporary work disability duration? A multilevel analysis of workers' compensation claims in five Canadian provinces.

Research has shown how regionally varying labor market conditions are associated with differences in work disability duration. However, the majority of these studies have not used multilevel models to appropriately account for the hierarchical clustering of individuals nested within contextual units (e.g., regions). Studies that have used multilevel models have focused on privately insured workers or on disability not specifically caused by work-related injury or illness. Using claims data from five Canadian provincial workers' compensation systems, linear random-intercept models were used to estimate how much variance in temporary work disability duration ('work disability duration' for brevity) for work-related injuries and musculoskeletal disorders was due to differences between economic regions, what economic region-level labor market characteristics were associated with work disability duration, and what characteristics best explained economic region differences in work disability duration. Economic region characteristics, such as the unemployment rate and proportion of goods-producing employment, were independently associated with individual-level work disability duration. However, economic region variation only accounted for 1.5%-2% of total variation in work disability duration. The majority (71%) of economic region-level variation was explained by the provincial jurisdiction where the worker livedand was injured. Regional variation tended to be greater for female workers than males. The findings suggest that while regional labor market conditions matter for work disability duration, system-level differences in workers' compensation and health care are more important factors influencing work disability duration. Furthermore, while this study includes both temporary and permanent disability claims, the work disability duration measure only captures temporary disability.

Spatially Explicit Assessment of the USDA Forest Service as a Representative Bureaucracy

Abstract Diverse workforce representation helps organizations achieve their goals and is important for government agencies that seek to gain public trust. Prior research has examined patterns of representation in the USDA Forest Service (Forest Service) and found an overall lack of representation despite advances at leadership levels. Federal agencies are required to report total workforce demographics; however, representation relative to local communities is rarely known. Using data from the US Census Bureau, we examined demographic profiles of populations within a 1-hour drive time around Forest Service workplaces relative to workforce demographics at each workplace. The Forest Service had a greater proportion of white employees than the US population as a whole, and racial/ethnicity diversity was lower than surrounding communities at 99.7% of Forest Service workplaces. Region-level summaries reinforce this pattern, suggesting the Forest Service is not a representative bureaucracy in any region or at any geographic scale. Given the Forest Service’s size, role in natural resources management, and geographic distribution of its workforce, disparities between demographic composition of the agency’s workforce and surrounding communities are striking. These results set a standard for spatially explicit assessments of workforce diversity as it relates to representative bureaucracy in geographically dispersed organizations like the Forest Service. Study Implications: Prior research showed that the USDA Forest Service had proportionally fewer Black/African American (~3 times fewer) and Asian (~2 times fewer) employees than the US civilian labor force as a whole. However, aggregate agency-level statistics and national comparisons may conceal local and regional level variation. To understand how the racial and ethnic diversity at each workplace compared with its surrounding geographic area’s local population, 690 workplaces were examined. Results were consistent across multiple drive times and levels of aggregation; the Forest Service’s workforce is less diverse than surrounding communities, which may potentially affect its ability to serve its many stakeholders.

Cluster and regional level variation of hemoglobin concentration of ever-married women in Bangladesh: a linear mixed model approach

Background: The hemoglobin protein plays an essential role in health and development in the human body. Women with inadequate Hb levels develop anemia. In light of the regional heterogeneity in Bangladesh, the aim of this study is to identify the risk factors associated with low Hb concentration in ever-married women. Methods: The study extracted data from the Bangladesh Demographic Health Surveys (BDHS) conducted in 2011. Since the hemoglobin level was not measured in BDHS 2014 and BDHS 2017, the study used BDHS 2011. A total of 5,699 ever-married women aged (15-49) years were used in the study. Both descriptive and inferential statistics applied to answer the research questions. Multilevel linear mixed effect modelling was applied to identify the risk factors of hemoglobin level at different hierarchical levels simultaneously and the different level variations were observed. Results: The average age of women was 31 years with standard deviation of 9.33 years. The mean (SD) of hemoglobin level of women was 120.95 (81) g/L. The highest mean (SD) level of hemoglobin was found in the Khulna 122.48 (13.26) g/L and the lowest in the Barisal 119.61 (13.21) g/L. The multilevel model resulted that using the contraceptive method, pregnant women, married women, breastfeeding mother, age of mother, body mass index, and total children ever born had significant effect on the low hemoglobin level. Conclusion: Analyzing the individual, cluster, and regional influence, the current study determined the most relevant socioeconomic, demographic, and environmental risk factors for low hemoglobin levels of women in Bangladesh.

A regional perspective to the study of affective polarization

AbstractThis research note investigates the scope of regional variations in levels of affective polarization across Europe and contrasts it with national scores to highlight the theoretical and empirical interest of a disaggregated approach. Using all waves of the Comparative Study of Electoral Systems (CSES) dataset, we compute an affective polarization score for 143,857 individuals and aggregate these scores in 190 regions nested in 30 countries, across a period ranging from 1996 to 2019, covering 105 elections. We map variations in affective polarization across regions, both cross‐sectionally and longitudinally. Our results reveal that the range of scores is larger across regions than between countries and that approximately half of the variation in affective polarization scores can be attributed to within‐country heterogeneity. Second, we find that some countries display rather homogeneous regional patterns, while others display heterogeneous scores. Third, we show how the increase in the affective polarization scores over time at the national level can be driven by sharp changes in some regions only, while other regions remain stable. Overall, these results point to the added value of adopting a regional approach to the study of affective polarization.

Regional disparities in SARS-CoV-2 infections by labour market indicators: a spatial panel analysis using nationwide German data on notified infections

BackgroundRegional labour markets and their properties are named as potential reasons for regional variations in levels of SARS-CoV-2 infections rates, but empirical evidence is missing.MethodsUsing nationwide data on notified laboratory-confirmed SARS-CoV-2 infections, we calculated weekly age-standardised incidence rates (ASIRs) for working-age populations at the regional level of Germany’s 400 districts. Data covered nearly 2 years (March 2020 till December 2021), including four main waves of the pandemic. For each of the pandemic waves, we investigated regional differences in weekly ASIRs according to three regional labour market indicators: (1) employment rate, (2) employment by sector, and (3) capacity to work from home. We use spatial panel regression analysis, which incorporates geospatial information and accounts for regional clustering of infections.ResultsFor all four pandemic waves under study, we found that regions with higher proportions of people in employment had higher ASIRs and a steeper increase of infections during the waves. Further, the composition of the workforce mattered: rates were higher in regions with larger secondary sectors or if opportunities of working from home were comparatively low. Associations remained consistent after adjusting for potential confounders, including a proxy measure of regional vaccination progress.ConclusionsIf further validated by studies using individual-level data, our study calls for increased intervention efforts to improve protective measures at the workplace, particularly among workers of the secondary sector with no opportunities to work from home. It also points to the necessity of strengthening work and employment as essential components of pandemic preparedness plans.

Regional pattern of child undernutrition, calorie consumption, non-food expenditure and wealth in India

Background/objectiveAlthough, proximate and contextual determinants of malnutrition have been studied previously, there are a limited number of studies on association of calories consumption, economic wellbeing of household and measures of child undernutrition. In this context, this study examined the regional level variation in child undernutrition in terms of calories consumption, monthly per capita non-food expenditure (MPCNFE) and mean wealth score. MethodsThis study is based upon NFHS, 2015-16 and NSS, 2011-12 datasets. Compiling the necessary information at the regional level, this study employed bi-variate cross-tabulation, correlation analysis and multivariate OLS regression analysis. ResultsRegions where calories intake is more than 2200 Kcal, the prevalence of stunting (31%), underweight (27%) and wasting (19%) are comparatively low. A low MPCNFE (<1000 R/-) shows higher prevalence of stunting (39%), underweight (33%) and wasting (21%) across regions. Similarly, a low wealth score also shows higher prevalence of undernutrition across regions of India. OLS estimation shows that calories intake significantly predicts all the three measures of undernutrition at the regional level explaining 45% of the regional variation in stunting, 52% in the prevalence of underweight and 38% in wasting. The MPCNFE measure significantly predicts the regional level variation in stunting (Adjusted R2 = 0.54) and underweight (Adjusted R2 = 0.35) but not wasting. The wealth framework is observed to be weak and shows statistically significant association with stunting only and the explained variation is also found low (Adjusted R2 = 0.16). ConclusionThis study provides compelling evidence on the regional variation in child undernutrition parameters in terms of calories intake, MPCNFE and wealth score.

Estimation of soil properties with mid-infrared soil spectroscopy across yam production landscapes in West Africa

Abstract. Low soil fertility is challenging the sustainable production of yam and other staple crops in the yam belt of West Africa. Quantitative soil measures are needed to assess soil fertility decline and to improve crop nutrient supply in the region. We developed and tested a mid-infrared (mid-IR) soil spectral library to enable timely and cost-efficient assessments of soil properties. Our collection included 80 soil samples from four landscapes (10 km × 10 km) and 20 fields per landscape across a gradient from humid forest to savannah and 14 additional samples from one landscape that had been sampled within the Land Health Degradation Framework. We derived partial least squares regression models to spectrally estimate soil properties. The models produced accurate cross-validated estimates of total carbon, total nitrogen, total sulfur, total iron, total aluminum, total potassium, total calcium, exchangeable calcium, effective cation exchange capacity, and diethylenetriaminepentaacetic acid (DTPA)-extractable iron and clay content (R2&gt;0.75). The estimates of total zinc, pH, exchangeable magnesium, bioavailable copper, and manganese were less predictable (R2&gt;0.50). Our results confirm that mid-IR spectroscopy is a reliable and quick method to assess the regional-level variation of most soil properties, especially the ones closely associated with soil organic matter. Although the relatively small mid-IR library shows satisfactory performance, we expect that frequent but small model updates will be needed to adapt the library to the variation of soil quality within individual fields in the regions and their temporal fluctuations.

Variation in Rates of Hospital Admission from the Emergency Department Among Medicare Patients at the Regional, Hospital, and Physician Levels

Rates of admission from the emergency department (ED) vary widely across regions of the country, hospitals within regions, and physicians within hospitals. Our objective was to determine the extent to which variation in admission decisions was described by differences in admission rates at these 3 levels. This understanding will serve to better target interventions to modify rates of admission where appropriate. In this cross-sectional observational cohort study, we analyzed Medicare fee-for-service claims for ED visits from 2012 to 2015 in a 20% random sample of beneficiaries. We first estimated the total regional-, hospital-, and physician-level variations in rates of admission and their proportions of the total variation after adjusting for patient and each level's covariates. We then estimated the extent to which each level's characteristics accounted for variation at that respective level. Our study sample included 5,778,218 visits with 45,491 physicians at 3,480 EDs across 306 hospital referral regions. The mean rate of admission was 38.9% and ranged from 21.4% to 53.0% for physicians at the 10th and 90th percentile of the distribution, respectively. The residual (unexplained) variations at the regional, hospital, and physician levels were 13.3% (95% confidence interval [CI], 11.2 to 15.5%), 60.1% (57.1 to 62.9%), and 26.7% (26.4 to 26.9%), respectively. Regional, hospital, and physician characteristics accounted for 9.1% (95% CI, -5.6 to 23.8%), 51.1% (48.8 to 53.5%), and 2.7% (1.3 to 4.1%), respectively, of the explained variation at their respective levels. Within-area variation, both across hospitals within a region and across physicians within a hospital, is a more substantial component of observed variation in admission rates from the ED than regional level variation. These findings suggest that variation in admission rates is at least in part related to institutional norms and cultures as well as heterogeneity of physician decisionmaking within hospitals, both of which could be targets of interventions to modify rates of admission.

Variation in treatment strategy for non-ST segment elevation myocardial infarction: A multilevel methodological approach

BackgroundVariations by hospital and region in the selection of an early invasive strategy (EIS) after non–ST-segment elevation myocardial infarction (NSTEMI) in patients with high-risk criteria are unknown. MethodsWe evaluated the data of 7037 patients with NSTEMI from 20 hospitals of 3 regions from the Korean Acute Myocardial Infarction Registry–National Institute of Health database. We used hierarchical generalized linear mixed-models to estimate region- and hospital-level variation in the selection of an EIS after adjusting for patient-level high-risk criteria. We explored the variation using the median rate ratio (MRR), which estimates the relative difference in the risk ratios of two hypothetically identical patients at two different sites. ResultsAn EIS was selected in 84.4% of patients. At the hospital level, the median selection rate was 80.4%. At the region level, the median selection rate was 74.9% in the east region, 81.3% in the north region, and 83.9% in the west region, respectively. After adjusting for patient-level covariates, we found significant hospital- (MRR 2.19, 95% confidence interval [CI]: 1.74–3.03) and region-level (MRR 1.88, 95%CI: 1.26–5.44) variation in the selection of an EIS. Among patient-level factors, male sex, ongoing chest pain, history of coronary artery disease or acute heart failure, and GRACE risk score > 140 were independently associated with the selection of an EIS. ConclusionsWe observed significant hospital- and region-level variation in the selection of an EIS after NSTEMI in high-risk patients. Quality improvement efforts are required to standardize decision making and to improve clinical outcomes.

SIGNIFICANT NATIONWIDE VARIATION EXISTS IN OPIOID PRESCRIPTION RATES AMONGST PEDIATRIC PATIENTS WITH ACL INJURIES: A RETROSPECTIVE COHORT STUDY

Background: Prescription opioid rates have been found to vary on a county and state level. We aim to find if significant hospital-level and regional-level variation in opioid prescription rates exists in a pediatric orthopedic setting. Methods: We conducted a retrospective cohort study of children ages 10-18 who sustained an ACL injury between 2012-2016, from 39 hospitals throughout the United States, found through the Pediatric Health Information System. Patients were divided into four regions according to the regional census of hospital admission, and demographics were recorded. Primary outcomes were hospital-level variation in opioid prescription rates using a mixed effects linear regression model to compare mean differences in average opioid prescription rate. Results: 11,452 pediatric patients were analyzed for regional-level variation in opioid prescription rates. Of those patients 7,879 were analyzed for hospital-level variation in opioid prescription rates based on if the hospital of incidence had a sample size of at least 250 patients over the five-year span (16 of the 43 hospitals fit this criteria). The most common demographics were patients ages 16-18 (n=5,613; 49.01%), white (n=6,588; 57.53%), and male (n=5,905; 51.56%). The 11,452 patients were divided into four regions: (1) Northeast (n=2,409; 21.04%), (2) Midwest (n=2,499; 21.82%), (3) South (n=3,869; 33.78%), and (4) West (n=2,675; 23.36%). After adjustment, significant variation in opioid prescription rates was found to exist at both a hospital-level using a random intercept and random slope model (-2LL=17882.381, p&lt;.05) and at a regional-level by comparing mean differences in average opioid prescription rate (p&lt;.05). Conclusions: Significant variation of opioid prescription rates exists at both a hospital-level and a regional-level over the last five years in a pediatric orthopedic setting. The findings of this study build off previous findings from the Centers for Disease Control, which found significant variation existed in opioid prescription rates on a state-wide level. Given the recent guidelines proposed by the CDC to control and limit prescription opioids (as of March 2016), future studies finding the impact of the guidelines on variation of prescription rates in a pediatric orthopedic setting could be beneficial. [Table: see text][Figure: see text]

Family, Place and the Intergenerational Transmission of Union Membership

AbstractThis article examines the importance of family, gender and place to the intergenerational transmission of trade union membership. Using data from the British Household Panel Survey, we show that union membership among parents influences the union joining behaviour of young workers. These effects are particularly apparent among daughters and where both parents are members of unions. The effects of parental membership are also stronger among those born in areas characterized by relatively high levels of union density. Parental effects are therefore important to our understanding of the persistence of regional variations in levels of trade union membership.

Geographic Variation in Sex Ratios of the US Immigrant Population: Identifying Sources of Difference

This paper describes geographic variation in the sex composition of the foreign-born population in the US since 1990, and uses Blinder-Oaxaca decomposition to identify key sources of variation in regional sex ratios. We use data from the 1990 and 2000 US Censuses, and from the 2007–2011 American Community Survey, to create estimates of the size and characteristics of foreign-born populations at the level of Consistent Public-Use Microdata Areas. We find substantial local- and region-level variation in population sex ratios, with the highest sex ratios in the South and Midwest. This variation is partly explained by differences in the age- and national origin-composition of immigrants, but the effects of immigration history, age, and national origin on sex ratio vary substantially by region. The West in particular stands out as having high levels of unexplained difference from other regions. Future research is necessary to understand these regional differences in gendered immigration patterns.

A Comparative Study Between Two Communities &amp; Regional Variation in level of MDA with respect to Waist Hip Ratio and BMI in Response to an Exclusive Fibre Diet

A Comparative Study Between Two Communities &amp; Regional Variation in level of MDA with respect to Waist Hip Ratio and BMI in Response to an Exclusive Fibre Diet

The geography of Brexit – What geography? Modelling and predicting the outcome across 380 local authorities

Most of the analysis before the 2016 referendum on the UK’s continued membership of the European Union based on opinion polling data focused on which groups were more likely to support each of the two options, with less attention to the geography of that support – although some regions, especially London and Scotland, were expected to provide substantial support for Remain. Using a recently developed procedure for detailed exploration of large tables derived from survey data, this paper presents the result of a prediction of the outcome across local authorities in Great Britain using just two variables – age and qualifications. In relative terms, that prediction was reasonably accurate – although, reflecting the polls’ overestimate of support for Remain it underestimated the number of places where Leave gained a majority, as was also the case within local authorities where data were published by ward. The model’s predictive value was enhanced by post hoc incorporation of information on turnout and the number of registered electors, and taking these into account there was little evidence of substantial, additional regional variation in levels of support for Leave. Overall, regions were relatively unimportant as influences on the referendum outcome once the characteristics of the people living there were taken into account.

Variations in antibiotic use for respiratory tract infections

ABSTRACT&#x0D; ObjectivesAntibiotic resistance is a significant public health issue, driven in large part by selection pressure induced by antibiotic use. Despite knowledge that a reduction in inappropriate antibiotic use is important, significant and sustained behaviour change has remained difficult to achieve. Previous studies have suggested that prescribing decisions vary with patient comorbidities and age, as well as the physician’s age, claim volume, specialty, and continuity of care with the particular patient. Regional level variation has also been reported. The goal of this study is to explore variations in antibiotic prescribing for respiratory tract infections (RTIs) at the levels of patients, physicians, and regions.&#x0D; ApproachWe used data on fee-for-service physician visits from the universal Medical Services Plan (MSP) for all residents of British Columbia, Canada from 2002 to 2012. We identified a cohort of patient visits for RTI (ICD-9 codes 460-466, 480, or 487). We derived measures of healthcare use and comorbidities at the patient level, and measures of physician claim volume and frequency of respiratory tract infection management, at the level of the physician. We used data on antibiotics filled by individuals, the number of all medications filled by individuals each year, and counts of prescriptions written by physicians (and filled) by month, from the provincial drug insurance database. We linked antibiotic prescriptions to physician visits by patient and prescriber as antibiotics dispensed within 5 days after the RTI visit. We calculated measures of regional population distributions. We used data on meteorological temperature readings assigned to each region, for each day, and calculated 28-day moving averages. We linked data on patient demographics, physician demographics, and hospitalizations to our dataset. Our analysis will use hierarchical generalized linear mixed models (GLMMs) with logit link to account for the clustering effects of patients among physicians and regions, to model the odds of an antibiotic prescription being dispensed. Measures of variation will be discussed.&#x0D; ResultsBetween April 1, 2005 and March 31, 2012, there were over 10.5 million visits by nearly 3 million individuals, served by over 8000 physicians in 88 regions. Antibiotics were prescribed in 37% of all visits.&#x0D; ConclusionThese are preliminary results, with full analytic results available in the coming months. These results will have implications for better understanding the extent of variations in antibiotic prescribing, and some of the drivers of these variations, as well as the potential to inform ongoing efforts to improve the appropriateness of antibiotic use.

How to refer to people with disease in research outputs: The disconnection between academic practise and that preferred by people with multiple sclerosis

BackgroundIncreasingly, Government and Charity funders require public engagement in research. Invariably these research outputs describe the condition of someone with the disease of interest. We therefore sought to identify the preferred descriptor of someone with a disease, such as multiple sclerosis (MS) and to determine what descriptors are currently used by academics. MethodsSeveral surveys were undertaken: one from the Research Network of the MS Society (MSSRN), a major MS Charity within the United Kingdom, who are involved in reviewing grant applications, priority setting and research governance (n=146), and surveys from both the United Kingdom MS register (MSR; n=1713) and the North American Research Committee on Multiple Sclerosis (NARCOMS) registry (n=518). People were asked to rate descriptors of someone affected with MS. These were compared to that used by academic experimenters in basic science and clinical science research papers. ResultsAlthough the frequency of responses varied between surveys the overall findings showed many consistencies. This included use of person/people with MS (pwMS) as the preferred descriptor for someone with MS for social media and scientific publications. This was the preferred choice in about 55–60% people from the MRS and in over 70% in the NARCOMS and the MSSRN, respectively. Although MSer was the second preferred–choice for use in social media, there was as a large range of preferences from the ‘most-preferred’ to the ‘most-disliked.’ This reflected an earlier survey by UK-based research blogs using the term MSer (n=173). In contrast, pwMS had few ‘dislikes’ and results were skewed towards the ‘liked’ and ‘most-preferred’ choices. Client and sufferer were generally disliked terms, although there was some regional variation in levels of choice. Patient was generally seen as a neutral term that was neither strongly liked nor disliked. However, patient gained more public support for use within scientific publications (~20–25%) compared to social media (~10–15%). This descriptor was however most commonly used (98–99%) within both pre-clinical (searched in 6-month output of preclinical autoimmune MS models; n=161) and in clinical publications (specialist MS journals; n=220), whereas pwMS was not reported in over 75% of papers published in some specialised MS journals, and did not appear in the pre-clinical animal studies examined. ConclusionThere is a clear disconnection between preferences by individuals living with MS and current academic practise. As pwMS are increasingly reading primary research publications and are involved in patient and public involvement in research and grant review activities, the sensitivities of lay readers should be considered when writing research outputs. This issue may affect other diseases and a change in writing style could be adopted to show that we respect the wishes of the people that we study and wish to help.

A Narrative Review of Factors Affecting Job Satisfaction among Nurses in Africa

Background: There is a renewed interest in job satisfaction among healthcare workers including nurses in Africa and the West African sub-region due to the perception that global shifts in the internal structures and employment practices are inducing changes in the ties that bind employees to their job. Therefore, it is necessary to examine various studies in order to establish an empirical base and utility for the theory of knowledge. Objective: This paper reviewed some of the available literatures on factors affecting job satisfaction among nurses around the world with special focus on the African continent. Methods: Electronic search of Medline, PubMed, Health Internetwork Access to Research Initiative (HINARI), and Google Scholar databases up to 2014 was carried out for studies which analyzed the factors affecting job satisfaction of nurses around the world, Africa and West Africa. Results: Although regional variations in levels of job satisfaction exist among nurses globally, there is more general trend of dissatisfaction and these are because of various factors related to the work environment. Nigerian nurses are generally more satisfied (as high as 92%) with their jobs when compared with their colleagues in other African countries. Socio-demographic and socioeconomic variables do not affect job satisfaction as much as leadership styles, promotion and other features related to the work environment. Conclusion: Strong leadership style is a probable reason why nurses in Nigeria are more satisfied with their jobs when compared with their colleagues in other countries even though they may work for longer hours or earn relatively less salaries.

The success of radical right-wing parties in Western European regions – new challenging findings

This study tries to explain regional level variation in the far right-wing vote across more than 160 regions in 17 Western European countries from 1990 to 2013. With the help of a panel Tobit model, I first examine the impact of nine regional-level structural indicators on the dependent variable, the percentage of the far right-wing vote. I find that the far right performs better in territorial units with a high percentage of university-educated individuals, in rural regions and in areas that have a high percentage of foreigners. Second, I use a dynamic specification in first differences to evaluate how changes in the independent variables trigger changes in the dependent variable. The results of this second specification highlight that increases in unemployment rates and in the number of college-educated citizens trigger a better performance of the far right.

Erodibility of permafrost exposures in the coasts of Eastern Chukotka

Coastal retreat caused by coastal erosion decreases the territory of Russia by 50 km2 annually. Erosion of the Arctic coasts composed by fine-grained permafrost turns coastlines into badlands dozens of meters wide and is harmful to the coastal infrastructure. Regional-level variations in the coastal retreat rate in the Arctic tend to follow the climate change dynamics and its consequences, mainly the shrinkage of the perennial sea ice area. This study considers the lower level local-scale variability linked to permafrost features, lithology, and morphology of the coasts in the remote region on the western shore of the Bering Sea within Lorino settlement (Chukotka, Russia). The coastal dynamics was tracked by means of geodesy and remote sensing in 2012–14, and the archival engineering survey data available since 1967. We have derived the erodibility of sediments from the conventional soil properties measured by engineers, and linked the coastal retreat rates to erodibility of the sediments, so that it could be extrapolated to other coastal areas of Eastern Chukotka with similar sediment structure.

Associated Microscale Spine Density and Macroscale Connectivity Disruptions in Schizophrenia

BackgroundSchizophrenia is often described as a disorder of dysconnectivity, with disruptions in neural connectivity reported on the cellular microscale as well as the global macroscale level of brain organization. How these effects on these two scales are related is poorly understood. MethodsFirst (part I of this study), we collated data on layer 3 pyramidal spine density of the healthy brain from the literature and cross-analyzed these data with new data on macroscale connectivity as derived from diffusion imaging. Second (part II of this study), we examined how alterations in regional spine density in schizophrenia are related to changes in white matter connectivity. Data on group differences in spine density were collated from histology reports in the literature and examined in a meta-regression analysis in context of alterations in macroscale white matter connectivity as derived from diffusion imaging data of a (separately acquired) group of 61 patients and 55 matched control subjects. ResultsDensely connected areas of the healthy human cortex were shown to overlap with areas that display high pyramidal complexity, with pyramidal neurons that are more spinous (p = .0027) compared with pyramidal neurons in areas of low macroscale connectivity. Cross-scale meta-regression analysis showed a significant association between regional variation in level of disease-related spine density reduction in schizophrenia and regional level of decrease in macroscale connectivity (two data sets examined, p = .0028 and p = .0011). ConclusionsOur study presents evidence that regional disruptions in microscale neuronal connectivity in schizophrenia go hand in hand with changes in macroscale brain connectivity.