Output Area Research Articles

Unravelling the dynamics of mental health inequalities in England: A 12-year nationwide longitudinal spatial analysis of recorded depression prevalence

BackgroundDepression is one of the most significant public health issues, but evidence of geographic patterns and trends of depression is limited. We aimed to examine the spatio-temporal patterns and trends of depression prevalence among adults in a nationwide longitudinal spatial study in England and evaluate the influence of neighbourhood socioeconomic deprivation in explaining patterns. MethodsInformation on recorded depression prevalence was obtained from the indicator Quality and Outcomes Framework: Depression prevalence that measured the annual percentage of adults diagnosed with depression for Lower Super Output Areas (LSOA) from 2011 to 2022. We applied Cluster and Outlier Analysis using the Local Moran’s I algorithm. Local effects of deprivation on depression in 2020 examined with Geographically Weighted Regression (GWR). Inequalities in recorded prevalence were presented using Prevalence Rate Ratios (PRR). ResultsThe North West Region of England had the highest concentration of High-High clusters of depression, with 17.4% of the area having high values surrounded by high values in both space and time and the greatest percentage of areas with a high rate of increase (43.1%). Inequalities widened among areas with a high rate of increase in prevalence compared to those with a lower rate of increase, with the PRR increasing from 1.66 (99% CI 1.61–1.70) in 2011 to 1.81 (99% CI 1.76–1.85) by 2022. Deprivation explained 3%–39% of the variance in depression in 2020 across the country. ConclusionsIt is crucial to monitor depression's spatial patterns and trends and investigate mechanisms of mental health inequalities. Our findings can help identify priority areas and target prevention and intervention strategies in England. Evaluating mental health interventions in different geographic contexts can provide valuable insights to policymakers on the most effective and context-sensitive strategies, enabling them to allocate resources towards preventing the worsening of mental health inequalities.

Classifying and mapping residential structure through the London Output Area Classification

This paper outlines the creation of the London Output Area Classification (LOAC) from the 2021 Census, set within the broader context of geodemographic classification systems in the United Kingdom. The LOAC 2021 was developed in collaboration with the Greater London Authority (GLA) and offers an enhanced, statistically robust typology adept at capturing the unique spatial, socio-economic and built characteristics of London’s residential neighbourhoods. The paper asserts the critical importance of nuanced, area-specific geodemographic classifications for urban areas with unique geography relative to the national extent.

Determining households from patient addresses and unique property reference numbers in general practitioner electronic health records

IntroductionHouseholds are increasingly studied in population health research as an important context for understanding health and social behaviours and outcomes. Identifying household units of analysis in routinely collected data rather than traditional surveys requires innovative and standardised tools, which do not currently exist. ObjectivesTo design a utility that identifies households at a point in time from pseudonymised Unique Property Reference Numbers (UPRNs) known as Residential Anonymised Linkage Fields (RALFs) assigned to general practitioner (GP) patient addresses in electronic health records (EHRs) in north east London (NEL). MethodsRule-based logic was developed to identify households based on GP registration, address date, and RALF validity. The logic was tested on a use case on the household clustering of childhood weight status, and bias in success of identifying households was examined in the use case cohort and in a full population cohort. Results92.1% of the use case cohort was assigned a household. The most frequent dominant reason (55.3%) for a household not assigned was that a person had no valid household RALFs available across their patient registration address records. Other reasons are having none or multiple valid household RALFs, or not being alive at the event date. In the use case, children not assigned to a household were more likely to attend schools in City & Hackney and living in the third most deprived quintile of lower super output areas. 88.9% of the population cohort was assigned a household. Patients not assigned to a household were more likely to be aged 18 to 45 years, living in City & Hackney, and living in the second quintile of most deprived lower super output areas. ConclusionsWe have developed a method for deriving households from primary care EHRs that can be implemented quickly and in real-time, providing timely data to support population health research on households.

Control and Analysis of a Hybrid-Rotor Bearingless Switched Reluctance Motor with One-Phase Full-Period Suspension

In the traditional control scheme of a 12/8-pole bearingless switched reluctance motor (BSRM), radial force and torque are usually controlled as a compromise due to the conflict between their effective output areas. Additionally, each phase requires individual power circuits and is excited in turn to produce a continuous levitation force, resulting in high power device requirements and high controller costs. This paper discusses a 12/8-pole single-winding hybrid-rotor bearingless switched reluctance motor (HBSRM) with a hybrid rotor consisting of cylindrical and salient-pole lamination segments. The asymmetric rotor of the HBSRM slightly increases the complexity of its structure and magnetic circuit, but makes it possible to generate the desired radial force at any rotor angular position. A control scheme for the HBSRM is developed to utilize the independent excitation of the four windings in one phase to generate the desired levitation force at any rotor angular position, and it requires only half the number of power circuits used in the conventional control scheme of a 12/8-pole single-winding BSRM. Different from the average torque chosen to be controlled in traditional methods, this scheme directly regulates the instantaneous total torque produced by all excited phases together and presents a current algorithm to optimize the torque contribution of each phase so as to reduce torque pulsation, and the improved performance of this bearingless motor is finally validated by simulation analysis.

USING THE CUBIC SPLINE INTERPOLATION METHOD TO APPROXIMATE SOME REAL DATA

In engineering and science problems, the data being considered are of-ten known in the form of sets of discrete points, not as a continuous function. In applications, the values of the discrete data at specific points may be required to estimate. To solve these problems, a common mathematical ap-proach is to use the interpolation method. In this paper, we use the cubic natural spline interpolation method to build approxi-mate functions for some real data in Vietnam such as data on rice out-put and rice area of cultivation, data on expenditure and income per capita. The data used in this paper are extracted from the General Statis-tics Office of Vietnam. We develop some Matlab programs to find the coefficients of splines and calculate the values of the interpolation functions at specific points. Using the obtained interpolation function, some missing values in the data on income and expenditure per capita in the Southeast region of Vietnam in 2019 and 2021 are estimated. Fur-ther-more, some unknown data on rice productivity and cultivation area are obtained in a similar manner. A good agreement between the calcu-lated values and actual values are found.

Neighbourhood Health Inequalities between Ethnic Groups in England: An Application of Ecological Inference

Ecological inference has had primarily political science applications, but this study considers an application to assess variations in neighbourhood mental health between population sub-groups. The methodology used has particular utility when neighbourhood health data are available only in aggregate form, without disaggregation (e.g. by ethnic or socioeconomic group). The ecological inference approach is shown to provide insights into contextual effects, where neighbourhood features influence disease variations between sub-groups (e.g. the ethnic density effect on psychosis among non-white groups). The present study also highlights important issues raised by the data’s geographic framework, namely strong spatial clustering in the outcome, and compares spatial error and spatial lag methods to represent this spatial patterning appropriately. The study considers neighbourhood variations in psychosis between four ethnic groups, with a spatial framework provided by 32,844 small areas (Lower Super Output Areas, LSOAs) in England.

Socio-hydrology pathway of grain virtual water flow in China

As the world's largest grain producer, China's activities in virtual water trade for grain are particularly noteworthy. The imbalance of grain production and consumption among regions poses challenges to agricultural development and the sustainable use of water resources. Most of the previous research focused on the driving analysis of factors affecting agricultural water use at the production end. It is necessary to further explore the driving factors of virtual water flow (VWF) caused by grain trade on the consumption side, and consider the impact of production and consumption on the entire process of agricultural water use. This study combines the Logarithmic Mean Divisia Index (LMDI) index decomposition method and multiple regression model to analyze the main natural and social driving factors of VWF. The study also initiates the construction of an analytical framework for the dynamic interaction of coupled social hydrology and Metacoupling systems. The results indicate that economic growth is the primary driver behind the increase in VWF. The water intensity effect and industrial structure effect act as constraints on VWF. Notably, water intensity has the most significant negative effect, with contributions of − 118.9 Gm³ and − 192.4 Gm³ to the virtual water output and input areas, respectively. Conversely, the economic, demographic, and dependence effect play a promoting role. Among these, the positive economic effect far exceeds population and dependence effects, contributing 189.7 Gm³ and 231.3 Gm³ to the virtual water output and input areas, respectively. The analytical framework of coupled social hydrology and the dynamic interaction of Metacoupling systems reveals that VWF couples water resources with multiple systems through the production-consumption-pollution chain. Simultaneously, it achieves long-distance interactions across spaces through cross-space VWF, exhibiting socio-hydrological interactions. The input area displays a forward cycle, while the output area exhibits the opposite. These findings can serve as a theoretical reference for controlling grain VWF.

Identifying employee, workplace and population characteristics associated with COVID-19 outbreaks in the workplace: a population-based study

ObjectivesTo identify risk factors that contribute to outbreaks of COVID-19 in the workplace and quantify their effect on outbreak risk.MethodsWe identified outbreaks of COVID-19 cases in the workplace and investigated...

Social and spatial inequalities of contemporary food deserts: A compound of store and online access to food in the United Kingdom

This research studies the social and spatial inequalities of contemporary food deserts in England and Wales. Two indices of the Store Food Desert Index and Online Food Desert Index are measured to examine store access and online access to food at the Lower Layer Super Output Areas geographical level. A detailed analysis is conducted to (i) identify “priority areas” where there is relatively lower store access and online access to food, (ii) synthesize population to understand the characteristics of “at-risk communities” that are disproportionately affected by food deserts, and (iii) examine the association between self-reported health conditions and a compound of store and online access to food. Three insights are provided. First, there is a clear urban-rural divide in which urban areas generally benefit from better provision of both store and online access to food. Second, about 23% of the population (13.8 million people) live in priority areas with limited access to both physical stores and online groceries. Within this group, 0.06% (8000 individuals) do not have cars, 2.17% (300,000 individuals) are Black, and 14.5% (2 million individuals) reside in deprived neighborhoods. This is an alarming picture. Third, people residing in areas with high store and online access to food reported better health conditions, and online access is as effective as store access in improving health conditions. The findings highlight the potential of combining online and store access to bridge geographical and economic gaps, thereby providing healthier food options to those in food deserts.

Patient-reported outcome and experience measures (POEM) of a community-based glaucoma clinic in Cambridge, UK: an observational study

ObjectivesGlaucoma care demand in UK hospitals has exploded in recent years. This has resulted in a push to community (shared, virtual, etc) care models to reduce the burden on hospital...

Surface electromyography of the vastus lateralis and gluteus medius muscles in post-operative T3-L3 hemilaminectomy dogs: a prospective controlled observational study.

The objective of this study was to determine if surface electromyography (sEMG) demonstrates differences in muscle activation between normal and dogs recovering from spinal cord injury due to intervertebral disk extrusion. Two groups of client-owned small-breed chondrodysplastic-type dogs were tested. Group 1 consisted of seven ambulatory paraparetic dogs that had undergone a hemilaminectomy procedure in the T3-L3 region for intervertebral disk extrusion 1 month prior. Group 2 was made up of seven normal dogs that had no history of intervertebral disk disease or spinal surgery. Each subject walked 10 feet on a nonslip surface for at least five gait cycles for the sEMG to capture muscle activation of the vastus lateralis and gluteus medius, bilaterally. Muscle activation was quantified as the total myoelectric output area under the curve, averaged across all gait cycles. Muscle activation was significantly greater in the post-operative hemilaminectomy group (p = 0.012). There was a significant difference in muscle activation between each hindlimb in the post-operative hemilaminectomy group, but not in the normal group. The muscle activation was significantly lower on the side that underwent surgery compared to the opposite limb (p = 0.0034). Post-operative hemilaminectomy dogs have greater hindlimb muscle activation compared to normal dogs, which likely represents a lack of descending inhibition secondary to upper motor neuron syndrome. The side of surgery is correlated with decreased muscle activation. Surface EMG can be used to evaluate muscle activity in dogs recovering from spinal decompression surgery.

Modeling and Forecasting of Spinach Production in Bangladesh

Background: In Bangladesh, spinach (Spinachia oleracea L.) is most frequently known as "Palong shak" or Bengal Spinach. Spinach is one of the most prominent vegetable crops grown around the earth. It is a quick-growing annual plant that only lives for one year. Although spinach can be cultivated at any time throughout the year, Bangladesh's production of spinach on a per-unit basis is very low in comparison to that of other advanced nations.
 Objective: This study explores the impacts of area, price, and weather parameter adaptability on the local production of spinach in Bangladesh employing annual data from time series covering 60 years.
 Materials and Methods: This investigation seeks to comprehend the linear relationship between spinach production, commercial price, geographic location, and meteorological characteristics in Bangladesh by applying stepwise regression analysis to find the most suitable model of Spinach production. In order to evaluate how well the multiple linear regression model fits the data, several diagnostic charts were constructed using the R programming language. To forecast the Spinach production, an autoregressive integrated moving average (ARIMA) model was applied.
 Results: According to the findings of the study, there was a positive correlation between spinach output and total harvest area under spinach cultivation. There is weak positive correlation between production and annual mean temperature and a weak negative correlation exists between production and annual mean rainfall. Also, production is perfectly positively correlated with price. Regression analysis revealed that the variables sales price and annual mean rainfall are the best predictors of spinach output. Every unit increase in the price of spinach is increases an additional 5.98 times the average of spinach being produced. An increase of 1 millimeter in annual mean rainfall (AMR) decreases 0.001 times spinach production while other predictors remain fixed. Also, ARIMA (1, 1, 0) with drift model forecasts for next fifteen years that the Spinach production is expected to increase considerably by 75000 tons.
 Conclusion: Finally, the study found that farmers' perspective on spinach cultivation could potentially experience a positive upward shift which is expected to last for the next fifteen years.

THE IMPACT OF LIVING IN MULTIGENERATIONAL NEIGHBOURHOODS ON LONELINESS IN LATER LIFE

Abstract Intergenerational solidarity has been identified as a key factor for effective social functioning. However, evidence suggests that divisions between younger and older generations within Great Britain (GB) have never been greater. Growing residential age segregation is thought to be driving intergenerational division. This, in turn, is assumed to lead to an increased risk of loneliness among older adults. However, to date, this has not been empirically tested. To examine this issue, we created a new measure of multigenerational neighbourhoods, for all lower super output areas in England and Wales. These were linked to individuals aged 50 and over living in England and Wales in 2018/2019 in the UK Household Longitudinal Survey (N = 14,196). Loneliness was measured using the UCLA-3 scale. Multilevel regression analyses were performed. Covariates included, area level deprivation, urban/rural, residential tax band, home ownership, individual age, sex, marital status and financial situation. The results show that the mix of generations within a neighbourhood has a weak (r = 0.33) and non-significant (p=.493) association with loneliness among older adults. To the best of our knowledge this is the first study to directly examine the impact of neighbourhood age diversity on loneliness in later life. Our findings suggest that the mere presence of different generations within a neighbourhood is not a sufficient condition to combat loneliness in later life

Exploring the Potential of Solar Energy in Mosque Buildings: A Case Study of Dumai Islamic Centre Mosque in Riau Province, Indonesia

This study investigated the implementation of solar panels in the Dumai Islamic Centre (DIC) Mosque, located in Dumai City, Riau Province, to reduce carbon emissions. The study presents an overview of the significance of solar energy utilization and its potential benefits in the context of mosque buildings. This research was aimed to assess the criteria for selecting the appropriate solar panel type, determine the power output and PV area required for the DIC Mosque, and estimate the carbon emissions reduction resulting from installing solar panels. The study employed a quantitative research design and utilizes the Analytic Hierarchy Process (AHP) to select the most suitable solar panel type. The results reveal that polycrystalline solar panels are the optimal choice based on efficiency, power peak, operation and maintenance, and price criteria. Installing solar panels on the DIC Mosque's roof, positioned at an optimal height, ensures maximum sunlight exposure and energy generation efficiency. Calculations demonstrate a significant reduction in carbon emissions post-installation. The carbon emissions reduction potential is estimated at 57.693 kg CO2 eq per day or 21,057.95 tons CO2 eq per year. This highlights the positive environmental impact of solar energy implementation in the DIC Mosque.

Computationally efficient localised spatial smoothing of disease rates using anisotropic basis functions and penalised regression fitting

The spatial variation in population-level disease rates can be estimated from aggregated disease data relating to N areal units using Bayesian hierarchical models. Spatial autocorrelation in these data is captured by random effects that are assigned a Conditional autoregressive (CAR) prior, which assumes that neighbouring areal units exhibit similar disease rates. This approach ignores boundaries in the disease rate surface, which are locations where neighbouring units exhibit a step-change in their rates. CAR type models have been extended to account for this localised spatial smoothness, but they are computationally prohibitive for big data sets. Therefore this paper proposes a novel computationally efficient approach for localised spatial smoothing, which is motivated by a new study of mental ill health across N=32,754 Lower Super Output Areas in England. The approach is based on a computationally efficient ridge regression framework, where the spatial trend in disease rates is modelled by a set of anisotropic spatial basis functions that can exhibit either smooth or step change transitions in values between neighbouring areal units. The efficacy of this approach is evidenced by simulation, before using it to identify the highest rate areas and the magnitude of the health inequalities in four measures of mental ill health, namely antidepressant usage, benefit claims, depression diagnoses and hospitalisations.

An ethnic group specific deprivation index for measuring neighbourhood inequalities in England and Wales

AbstractThe measurement of deprivation for small areas in the UK has provided the basis for the development of policies and targeting of resources aimed at reducing spatial inequalities. Most measures summarise the aggregate level of deprivation across all people in a given area, and no account is taken of differences between people with differing characteristics, such as age, sex or ethnic group. In recognition of the marked inequalities between ethnic groups in the UK, and the distinctive geographies of these inequalities, this paper presents a new ethnic group‐specific neighbourhood deprivation measure—the Ethnic Group Deprivation Index (EGDI). This index, using a custom cross‐tabulated 2021 Census dataset on employment, housing tenure, education and health by ethnic group, reveals the small area geographies of ethnic inequalities that have to date received scant attention, and yet have profound impacts on life chances and well‐being. Drawing on the methodological framework of the widely used English Index of Multiple Deprivation (IMD) and for the same geographies (Lower Layer Super Output Areas), the EGDI measures deprivation for each ethnic group using data from the 2021 Census of England and Wales. The EGDI reveals the complex geographies of ethnic inequality and demonstrates that while one ethnic group in a neighbourhood may have high relative levels of deprivation, another ethnic group in that same neighbourhood may experience very low relative levels. The EGDI explores ethnic inequalities within and between neighbourhoods, complementing and augmenting existing measures by offering an important means of better understanding ethnic inequalities. The EGDI can be used to help shape locally and culturally sensitive policy development and resource allocation.

Linking Individuals to Areas: Protecting Confidentiality While Preserving Research Utility

Modern computational capabilities have brought about concerns about risks associated with the level of information disclosed in public datasets. A tension exists between making data available that protects the confidentiality of individuals while containing sufficiently detailed geographic information to underpin the utility of research. Our aim is to inform data collectors and suppliers about geographic choices for confidentiality protection and to balance this with reassurance to the research community that data will still be fit-for-purpose. We test this using simple logistic regression models, by investigating the interplay between two geographical entities (points for the observations and polygons for area attributes) at a variety of scales, using a synthetic population of 22,000 people. In an England and Wales setting, we do this for individuals located by postcodes and by postal sector and postal district centroids and link these to a variety of census geographies. We also ‘jitter’ postcode coordinates to test the effect of moving people away from their original location. We find a smoothing of relationships up the geographical hierarchy. However, if postal sector centroids are used to locate individuals, linkages to Lower/Medium Super Output Area scales and subsequent results are very similar to the more detailed unit postcodes. Postcode locations jittered by 500–750 m in any direction are likely to allow the same conclusions to be drawn as for the original locations. Within these geographic scenarios, there is likely to be a sufficient level of confidentiality protection while statistical relationships are very similar to those obtained using the most detailed geographic locators.

Coordinated effect of green expansion and carbon reduction: Evidence from sustainable development of resource-based cities in China

Resource-based cities generally face the dual pressures of ecological damage and high carbon emissions. Taking the National Sustainable Development Plan for Resource-Based Cities (NSDP) issued in China as a quasi-natural experiment, this paper for the first time, uses the difference-in-difference method to test the coordinated effect of green expansion and carbon reduction brought by NSDP at the county level using rich remote sensing data. The results show that NSDP has significantly promoted the ecological quality improvement and CO2 emission mitigation in resource-based cities, and the above coordinated benefits mainly occur in energy, mature, declining, northeastern, and municipal resource-based cities. Through the mechanism analysis, we find that NSDP mainly works by promoting the transformation of industry sector to agriculture, animal husbandry, accommodation and catering, finance, and environment management sectors, which are reflected in output, employment, product yield, land type and land transaction area. Further discussion on the tertiary industry suggests that developing tourism, easing financing constraint and strengthening environment regulation, are the key channels to borne fruit in green expansion and carbon reduction.

CEO entrepreneurial orientation, human resource management systems, and employee innovative behavior: An attention‐based view

AbstractResearch SummaryChief executive officer (CEO) entrepreneurial orientation (EO) is an emerging topic within entrepreneurship research. This research offers the attention‐based view (ABV), and its principles of attentional focus, situated attention, and structural distribution of attention to explain how CEO EO fosters an innovative organizational workforce. We theorize that CEO EO predicts lower‐level employee innovative behavior when their top managerial attentional focus on entrepreneurship is translated into high‐performance work practices, which structurally distribute their strategic attention throughout the organization and promotes a situated attentional condition for employees emphasizing innovation. Moreover, we consider (a) human‐resource management (HRM) perceived importance and (b) departmental functional foci as boundary conditions. Using a multi‐level and multi‐source sample from 152 Chinese firms, results support our arguments.Managerial SummaryEmployee innovative behavior is critical to firm growth, renewal, and sustainability. By collecting and analyzing data on 2745 employees nested in 586 departments nested in 152 organizations, we examine the critical role that human resource management (HRM) systems and high‐performance work practices may play in translating a CEOs emphasis on entrepreneurial activity into employee innovative behavior. We offer and observe support for an attention‐based perspective that HRM systems serve as “attentional structures” which channel CEO preferences to lower‐organizational levels. Our results further indicate that an embrace of HRM as a strategic priority among top managers, as well as whether employees are in “boundary spanning” input–output areas of the business, to be meaningful factors which strengthen the effect of HRM‐based attentional structures upon employee innovative behavior.

Association between distance to nearest automated external defibrillator and socioeconomic deprivation in Great Britain

Abstract Background Disparities in socioeconomic status manifest in death from out of hospital cardiac arrest (OHCA). Inequalities in access to automated external defibrillators (AED) due to socioeconomically determined location of AEDs may be associated with OHCA survival. Purpose To investigate distances between nearest AED location and postcode by socioeconomic deprivation for the population of Great Britain (GB). Methods AED location data for 2022 were drawn from the British Heart Foundation The Circuit registry. All 1,677,466 unit postcodes in Great Britain were linked to the Index of Deprivation for the corresponding Lower Layer Super Output Area using the 2019 Ministry of Housing Communities and Local Government tool. The median distance by road from the centre of each postcode to the nearest AED was calculated using geographic information systems. The proportion available 24/7 was also reported. Multilevel linear mixed regression models fit by country and adjusted for urban/rural status and clustering to calculate predicted marginal mean distances to the nearest active AED, and nearest AED accessible 24/7 by deprivation decile. Results 78,425 unique AED locations were included in the analysis (Table 1). The median distance to nearest AED was 762.1m (IQR 410.8 - 1221.0) in GB; 742.7m (407.2 - 1340.7) in Scotland, 738.8m (422.6 - 1223.5) in England, and 511.5m (282.9 - 937.3) in Wales. For 24/7 access AEDs, median distances were greater: 964.0m (524.7 - 1667.5), 994.1m (538.5 – 1832.3), 990.8m (544.9 - 1683.3), and 569.7m (316.8 - 1033.4), respectively. Overall, there was little evidence of a trend in nearest AED distance by deprivation (fig 1). In Scotland the nearest AED was, on average, 108m further away in the most compared with the least deprived areas. In England, the nearest AED was closer to postcodes in the least deprived areas of England (predicted mean 20m) and Wales (predicted mean 95m). In England, AEDs with 24/7 access were further from postcodes with increasing deprivation (predicted mean 99m further than least deprived areas). In Scotland, nearest 24/7 access AEDs were 317m further away in the most deprived areas, and 62m closer in Wales, but with no evidence of a linear trend. At a typical walking speed (1.31m/sec), on average in GB it would take 17 minutes to retrieve an AED and 21 minutes out of hours. In England and Scotland out of hours, those in the most deprived areas would be delayed access to an AED by 2.5 and 8 minutes respectively compared the least deprived. Conclusions Overall, the median distance to nearest AED across postcodes in GB is at odds with the likelihood of successful resuscitation. Graded social inequalities were not observed in AED access across GB. However, substantive differences were observed in 24/7 AED access between most and least deprived areas of England and Scotland. Greater and more equitable access to AEDs has the potential to save lives and improve outcomes for people with OHCA.