Neighborhood Index Research Articles

Higher Childhood Adversity Reduces Environmental Satisfaction Among Older Adults

Housing insecurity, or limited/unreliable access to quality housing, is a powerful chronic stressor that can negatively affect individual health and well-being. This study extends prior research by examining the effect of multiple forms of housing insecurity on both the mental and physical health of aging adults using the Midlife in the United States study (MIDUS; N = 2532; M age = 63.42; 57% women; 16% black). Participants reported on experiences of anxiety/depression in the past year, number of chronic health conditions experienced in the last year, and experiences of housing insecurity since the 2008 recession (e.g., homelessness, threatened with foreclosure or eviction, missed rent or mortgage payment). 14% of participants reported experiencing one or more housing insecurity events in the aftermath of the recession. Higher levels of housing insecurity were experienced by midlife participants (ages 46-65) and black participants. Regression results showed that, even when controlling for prior health, housing insecurity was significantly associated with higher odds of experiencing anxiety/depression and additional chronic health conditions. These results suggest that housing insecurity experiences are fairly prevalent among midlife and aging adults, and that housing insecurity experiences leave these adults susceptible to compromised mental and physical health. This work has various implications for policy around addressing housing access and affordability issues for aging adults as a public health concern. Subsequent analyses will examine age, gender, and race/ethnic differences in these associations between housing insecurity and health outcomes.

Novel Data Compression Algorithm for Transmission Line Condition Monitoring

For the problem of data accumulation caused by massive sensor data in transmission line condition monitoring system, this paper analyzes the type and amount of data in the transmission line sensor network, compares the compression algorithms of wireless sensor network data at home and abroad, and proposes an efficient lossless compression algorithm suitable for sensor data in transmission line linear heterogeneous networks. The algorithm combines the wavelet compression algorithm and the neighborhood index sequence algorithm. It displays a fast operation speed and requires a small amount of calculation. It is suitable for battery powered wireless sensor network nodes. By combining wavelet correlation analysis and neighborhood index sequence coding, the compression algorithm proposed in this paper can achieve a high compression rate, has strong robustness to packet loss, has high compression performance, and can help to reduce network load and the packet loss rate. Simulation results show that the proposed method achieves a high compression rate in the compression of the transmission line parameter dataset, is superior to the existing data compression algorithms, and is suitable for the compression and transmission of transmission line condition monitoring data.

Exogenous Policy, Racial Avoidance, and the Qualified Relevance of Macroeconomic Change to Metropolitan Inequality

Context: The rich contextualization of educational processes brought about in the pioneering work of Jean Anyon pushed scientists to acknowledge that the education being provided to the least advantaged was shaped by factors with origins beyond school and family environments. Political economic work in education has subsequently argued that an unforgiving economy has lessened the educational fortunes of urban residents. Focus of Study: In response to claims that macroeconomic change created the confinement of educational disadvantage, this article reveals that political economic arguments predicated on macroeconomic change have yet to explain a period of decline on several dimensions of educational inequality from 1970 to 1990. Research Design: Through a juxtaposition of historical population trends and research with the ideas of Anyon and her contemporaries, this analysis considers racial forces emanating from desegregation policy as key to understanding test-score trends and metropolitan restructuring. Descriptive analyses of test-score trends and neighborhood indices of dissimilarities from 1970 to the mid-1990s form the basis of analysis. Conclusions: The analysis demonstrates that not only does desegregation policy align with anomalous educational trends, but that its impact reverberated to other spatial strata through its encouragement of Whites’ school selection decisions intent on racial avoidance. Racial avoidance should therefore be considered as an architect of the racial and economic landscape of the modern metropolis.

Social and built neighborhood environments and blood pressure 6 years later: Results from the Hispanic Community Health Study/Study of Latinos and the SOL CASAS ancillary study

Neighborhood-level socioeconomic deprivation can increase risk for higher blood pressure or hypertension, while greater neighborhood safety and walkability may protect against hypertension. Large-scale prospective research, particularly among Hispanics/Latinos, is lacking. We examined cross-sectional and prospective associations between neighborhood environments and blood pressure and hypertension among 3851 Hispanic/Latinos enrolled in the Hispanic Community Health Study/Study of Latinos San Diego, CA cohort. Addresses from Visit 1 (2008–2011) were geocoded and neighborhood characteristics were determined as part of the SOL CASAS ancillary study. Home addresses were geocoded and home areas created using 800 m circular radial buffers. Neighborhood indices socioeconomic deprivation, residential stability, and social disorder were created using Census and other publicly available data. Walkability was computed as density of intersections, retail spaces, and residences. Greenness was measured via satellite imagery using the Normalized Difference Vegetation Index. Visit 1 and Visit 2 (2014–2017) clinical outcomes included systolic (SBP) and diastolic (DBP) blood pressure, as well as prevalent and 6-year incident hypertension, defined as SBP/DBP ≥140/90 mmHg or antihypertensive medication use. Complex survey regression models adjusted for covariates revealed cross-sectional associations between greater walkability and lower SBP (B = −0.05; 95% CI: −0.09, −0.003). In prospective analyses, greater neighborhood social disorder was related to increasing SBP (B = 0.05; 95% CI: 0.01, 0.09) and DBP (B = 0.07; 95% CI: 0.02, 0.12) over time. Greater socioeconomic deprivation (OR = 1.47; 95% CI: 1.06, 2.04) and greater social disorder (OR = 1.25; 95% CI: 1.02, 1.54) were associated with higher odds of incident hypertension. All other associations were not significant. Beyond individual-level characteristics, greater neighborhood social disorder and socioeconomic deprivation were related to adverse changes in blood pressure over 6 years among Hispanics/Latinos. Neighborhood social environment may help identify, or be an area for future intervention for, cardiovascular risk among Hispanics/Latinos.

Modified Reduced Neighborhood Topological Indices of Cycloalkanes, Clycloalkenes, and Cycloalkynes

In this paper, some newly introduced topological indices, namely, modified reduced neighborhood first Zagreb index (〖RNM〗_1^* (G)) and modified forgotten reduced neighborhood index (〖RNM〗_3^* (G)) of a graph, G are used to establish the general formula for the molecular graphs of cycloalkanes, cycloalkenes, and cycloalkynes. We also calculate the exact values of some special types of these molecular graphs by attaching the alkyls instead of hydrogen atoms. Also, the QSPR analysis for these newly introduced indices is studied, and we exhibit a good correlation with characteristics on these molecular graphs.

Using spatial patterns of seeds and saplings to assess the prevalence of heterospecific replacements among cloud forest canopy tree species

AbstractQuestionsTo gain insights into the role of species‐by‐species replacements in cloud forest community structuring, we asked: (1) What are the effects of the spatial distribution of standing individuals on the seed rain, soil seed bank, and sapling density and survival in this cloud forest?; and (2) What is the prevalence of conspecific vs heterospecific replacements in the regeneration of this forest?LocationSanto Tomás Teipan, Oaxaca State, southern Mexico.MethodsIn a 1‐ha cloud forest plot, we assessed seed rain, seed bank, and sapling density and survival of four canopy tree species (Chiranthodendron pentadactylon, Cornus disciflora, Quercus laurina and Oreopanax xalapensis). All standing individuals of these and other tree species (diameter at breast height [DBH] ≥ 2.5 cm) were mapped. We used neighbourhood models to examine the spatial patterns of the three life cycle stages relative to the spatial distribution of adults. The neighbourhood effect was assessed through the Neighbourhood Index, which integrates information on size (DBH) and distance to adults. Data analysis was based on maximum likelihood and model selection procedures.ResultsWe found large between‐species differences regarding the spatial patterns of seeds and saplings. Three species showed evidence for the Janzen–Connell effect operating at the seed (Chiranthodendron pentadactylon and Quercus laurina) or sapling (Oreopanax xalapensis) stage. We also found support for a critical role of specific microsite factors (i.e. niche differentiation) in the regeneration of two species (Chiranthodendron pentadactylon and Cornus disciflora).ConclusionsSeed and sapling distribution patterns suggest the prevalence of heterospecific replacements and that both Janzen–Connell and niche differentiation effects contribute to this pattern. Our results largely support the notion that the prevalence of heterospecific replacements among canopy species promotes species co‐existence in cloud forests.

Socioeconomic position and the COVID-19 care cascade from testing to mortality in Switzerland: a population-based analysis

SummaryBackgroundThe inverse care law states that disadvantaged populations need more health care than advantaged populations but receive less. Gaps in COVID-19-related health care and infection control are not well understood. We aimed to examine inequalities in health in the care cascade from testing for SARS-CoV-2 to COVID-19-related hospitalisation, intensive care unit (ICU) admission, and death in Switzerland, a wealthy country strongly affected by the pandemic.MethodsWe analysed surveillance data reported to the Swiss Federal Office of Public Health from March 1, 2020, to April 16, 2021, and 2018 population data. We geocoded residential addresses of notifications to identify the Swiss neighbourhood index of socioeconomic position (Swiss-SEP). The index describes 1·27 million small neighbourhoods of approximately 50 households each on the basis of rent per m2, education and occupation of household heads, and crowding. We used negative binomial regression models to calculate incidence rate ratios (IRRs) with 95% credible intervals (CrIs) of the association between ten groups of the Swiss-SEP index defined by deciles (1=lowest, 10=highest) and outcomes. Models were adjusted for sex, age, canton, and wave of the epidemic (before or after June 8, 2020). We used three different denominators: the general population, the number of tests, and the number of positive tests.FindingsAnalyses were based on 4 129 636 tests, 609 782 positive tests, 26 143 hospitalisations, 2432 ICU admissions, 9383 deaths, and 8 221 406 residents. Comparing the highest with the lowest Swiss-SEP group and using the general population as the denominator, more tests were done among people living in neighbourhoods of highest SEP compared with lowest SEP (adjusted IRR 1·18 [95% CrI 1·02–1·36]). Among tested people, test positivity was lower (0·75 [0·69–0·81]) in neighbourhoods of highest SEP than of lowest SEP. Among people testing positive, the adjusted IRR was 0·68 (0·62–0·74) for hospitalisation, was 0·54 (0·43–0·70) for ICU admission, and 0·86 (0·76–0·99) for death. The associations between neighbourhood SEP and outcomes were stronger in younger age groups and we found heterogeneity between areas.InterpretationThe inverse care law and socioeconomic inequalities were evident in Switzerland during the COVID-19 epidemic. People living in neighbourhoods of low SEP were less likely to be tested but more likely to test positive, be admitted to hospital, or die, compared with those in areas of high SEP. It is essential to continue to monitor testing for SARS-CoV-2, access and uptake of COVID-19 vaccination and outcomes of COVID-19. Governments and health-care systems should address this pandemic of inequality by taking measures to reduce health inequalities in response to the SARS-CoV-2 pandemic.FundingSwiss Federal Office of Public Health, Swiss National Science Foundation, EU Horizon 2020, Branco Weiss Foundation.

Correlation Between Physiological and Performance-Based Metrics to Estimate Pilots' Cognitive Workload.

This paper discusses the utilization of pilots' physiological indications such as electroencephalographic (EEG) signals, ocular parameters, and pilot performance-based quantitative metrics to estimate cognitive workload. The study aims to derive a non-invasive technique to estimate pilot's cognitive workload and study their correlation with standard physiological parameters. Initially, we conducted a set of user trials using well-established psychometric tests for evaluating the effectiveness of pupil and gaze-based ocular metrics for estimating cognitive workload at different levels of task difficulty and lighting conditions. Later, we conducted user trials with the NALSim flight simulator using a business class Learjet aircraft model. We analyzed participants' ocular parameters, power levels of different EEG frequency bands, and flight parameters for estimating variations in cognitive workload. Results indicate that introduction of secondary task increases pilot's cognitive workload significantly. The beta frequency band of EEG, nearest neighborhood index specifying distribution of gaze fixation, L1 Norm of power spectral density of pupil diameter, and the duty cycle metric indicated variations in cognitive workload.

Blockchain-assisted secure image transmission and diagnosis model on Internet of Medical Things Environment

In recent days, the Internet of Medical Things (IoMT) is commonly employed in different aspects of healthcare applications. Owing to the increasing necessitates of IoT, a huge amount of sensing data is collected from distinct IoT gadgets. To investigate the generated data, artificial intelligence (AI) models plays an important role to achieve scalability and accurate examination in real-time environment. However, the characteristics of IoMT result in certain design challenges, namely, security and privacy, resource limitation, and inadequate training data. At the same time, blockchain, an upcoming technology, has offered a decentralized architecture, which gives secured data transmission and resources to distinct nodes of the IoT environment and is stimulated for eliminating centralized management and eliminates the challenges involved in it. This paper designs deep learning (DL) with blockchain-assisted secure image transmission and diagnosis model for the IoMT environment. The presented model comprises a few processes namely data collection, secure transaction, hash value encryption, and data classification. Primarily, elliptic curve cryptography (ECC) is applied, and the optimal key generation of ECC takes place using hybridization of grasshopper with fruit fly optimization (GO-FFO) algorithm. Then, the neighborhood indexing sequence (NIS) with burrow wheeler transform (BWT), called NIS-BWT, is employed to encrypt the hash values. At last, a deep belief network (DBN) is utilized for the classification process to diagnose the existence of disease. An extensive experimental validation takes place to determine the analysis of the optimal results of the presented model, and the results are investigated under diverse aspects.

Real-time optimizations in energy profiles and end-to-end delay in WSN using two-hop information

This paper proposes a routing protocol established upon the IEEE 802.15.4a that enhances the delay and energy efficiency in Wireless sensor networks (WSN) using two-hop information. Owing to the miniaturized form and non-rechargeable nature, nodes deployed in WSN suffer from resource constraints which affects its performance in terms of delay and energy consumption. Motivated by this, the proposed scheme exploits two-hop information to improve the performance of WSNs. First, a robust metric function known as the potential relay information (PRI) is formulated. Unlike other metric functions, the PRI leverages the residual energy, distance and delay and assesses the link quality of neighbor nodes to ascertain that the selected next-hop forwarder delivers data packets to the destination with the highest possible quality of service (QoS). Second, a preemptive neighborhood state index (NSI) algorithm which enable nodes view two-hops down its routing path to make good forwarding decisions that minimizes delay and balances load traffic across the system is devised. Last, a proactive feedback technique is integrated to simplify the update of two-hop information in order to address the excessive pursuing of energy consumption resulting from overhead packets. Simulation results validate the efficiency of the proposed scheme and demonstrates improvements in network lifetime, packet delivery ratio (PDR), end-to-end delay and energy consumption over the compared algorithms. Moreover, the results reflect QoS which supports real timeliness.

An intelligent internet of things-based secure healthcare framework using blockchain technology with an optimal deep learning model

Today, the internet of things (IoT) is becoming more common and finds applications in several domains, especially in the healthcare sector. Due to the rising demands of IoT, a massive quantity of sensing data gets generated from diverse sensing devices. Artificial intelligence (AI) techniques are vital for providing a scalable and precise analysis of data in real time. But the design and development of a useful big data analysis technique face a few challenges, like centralized architecture, security, and privacy, resource constraints, and the lack of adequate training data. On the other hand, the rising blockchain technology offers a decentralized architecture. It enables secure sharing of data and resources to the different nodes of the IoT network and is promoted for removing centralized control and resolving the problems of AI. This study develops an optimal deep-learning-based secure blockchain (ODLSB) enabled intelligent IoT and healthcare diagnosis model. The proposed model involves three major processes: secure transaction, hash value encryption, and medical diagnosis. The ODLSB technique comprises the orthogonal particle swarm optimization (OPSO) algorithm for the secret sharing of medical images. In addition, the hash value encryption process takes place using neighborhood indexing sequence (NIS) algorithm. At last, the optimal deep neural network (ODNN) is applied as a classification model to diagnose the diseases. The utilization of OPSO algorithm for secret sharing and optimal parameter tuning process shows the novelty of the work. We carried out detailed experiments to validate the outcome of the proposed method, and several aspects of the results are considered. At the time of the diagnosis process, the OPSO-DNN model has yielded superior results, with the highest sensitivity (92.75%), specificity (91.42%), and accuracy (93.68%).

The increase in child obesity in Switzerland is mainly due to migration from Southern Europe \u2013 a cross-sectional study

BackgroundNovel height, weight and body mass index (BMI) references for children in Switzerland reveal an increase in BMI compared to former percentile curves. This trend may be the result of children with parents originating from Southern European countries having a higher risk of being overweight compared to their peers with parents of Swiss origin. We examined the association of generational, migration-related and socioeconomic factors on BMI in Switzerland and expect the results to lead to more targeted prevention programs.MethodsFrom contemporary cross-sectional data, we calculated subgroup-specific BMI percentiles for origin. Results for children of Swiss origin were compared with historical BMI data from Zurich. We tested for the association of overweight and obesity with origin and compared the distributions of BMI percentile ranks. Logistic regression analyses were applied to predict probabilities of being overweight or obese by origin and the Swiss neighborhood index of socioeconomic position (SSEP).ResultsCompared to the BMI from two generations ago, the newly calculated BMI increased only slightly for children with both parents from Switzerland; 1.2% of these girls and 1.6% of these boys are obese. In the Swiss population, 13% of the children have parents from Southern Europe and the proportion of obesity is 57 and 42% in these boys and girls, respectively. Their BMI medians correspond to those of their parents’ countries of origin. For the probability of being overweight or obese, the SSEP differences are less important than the status of origin.ConclusionWe identified children with both parents from Southern Europe as the main influence driving the increase in BMI in Switzerland over the past 50 years. A differentiated consideration of the proportions of various migrant groups within cross-sectional samples is essential when monitoring BMI. Ignoring fluctuations can lead to false conclusions.

Parallel label propagation algorithm based on weight and random walk.

Community detection is a complex and meaningful process, which plays an important role in studying the characteristics of complex networks. In recent years, the discovery and analysis of community structures in complex networks has attracted the attention of many scholars, and many community discovery algorithms have been proposed. Many existing algorithms are only suitable for small-scale data, not for large-scale data, so it is necessary to establish a stable and efficient label propagation algorithm to deal with massive data and complex social networks. In this paper, we propose a novel label propagation algorithm, called WRWPLPA (Parallel Label Propagation Algorithm based on Weight and Random Walk). WRWPLPA proposes a new similarity calculation method combining weights and random walks. It uses weights and similarities to update labels in the process of label propagation, improving the accuracy and stability of community detection. First, weight is calculated by combining the neighborhood index and the position index, and the weight is used to distinguish the importance of the nodes in the network. Then, use random walk strategy to describe the similarity between nodes, and the label of nodes are updated by combining the weight and similarity. Finally, parallel propagation is comprehensively proposed to utilize label probability efficiently. Experiment results on artificial network datasets and real network datasets show that our algorithm has improved accuracy and stability compared with other label propagation algorithms.

Socioeconomic Position and the Cascade From SARS-CoV-2 Testing to COVID-19 Mortality: Population-Based Analysis of Swiss Surveillance Data

Background: The inverse care law states that disadvantaged populations need more health care than advantaged populations but receive less. Gaps in COVID-19 related health care and infection control are not well understood at present. We examined inequalities in health in the care cascade from testing for SARS-CoV-2 to COVID-19-related hospitalisation, ICU admission and death in Switzerland, a wealthy country strongly affected by the pandemic.Methods: We analysed surveillance data reported to the Federal Office of Public Health from March 1, 2020 to April 16, 2021 and 2018 population data. We geocoded residential addresses of notifications to determine the Swiss neighbourhood index of socioeconomic position (Swiss-SEP). The index describes 1.27 million small neighbourhoods of about 50 households, based on rent per square meter, education and occupation of household heads, and crowding. We used negative binomial regression models to calculate incidence rate ratios (IRR) with 95% credible intervals [CrI] of the association between ten groups of the Swiss-SEP index defined by deciles (1=lowest, 10=highest) and outcomes. Models were adjusted for sex, age, canton and wave of the epidemic (before or after June 8, 2020). We used three different denominators: the general population, the number of tests, and the number of positive tests.Findings: Analyses were based on 4,129,636 tests, 609,782 positive tests, 26,143 hospitalisations, 2,432 ICU admissions, 9,383 deaths, and 8,221,406 residents. Comparing the highest with the lowest Swiss-SEP group, and using the general population as the denominator, more tests were performed among people living in neighbourhoods of highest socioeconomic position (adjusted IRR 1.18; 95%CrI 1.02-1.36). Among tested people, test positivity was lower (adjusted IRR 0.75; 0.69-0.81) in neighbourhoods of highest socioeconomic position. Among people testing positive, the corresponding IRRs for hospitalisation, ICU admission and death were 0.68 (0.62-0.74), 0.54 (0.43-0.70) and 0.86 (0.76-0.99). The associations between neighbourhood socioeconomic position and outcomes were stronger in younger age groups, and there was heterogeneity between areas.Interpretation: The inverse care law and socioeconomic inequalities are evident in Switzerland throughout the care cascade. People living in neighbourhoods of low socioeconomic position were less likely to be tested but more likely to test positive, be hospitalised, or die. It is essential to continue to monitor testing for SARS-CoV-2, access and uptake of COVID-19 vaccination and outcomes of COVID-19. Governments and health care systems should address this pandemic of inequality by taking measures to reduce health inequalities in response to the SARS-CoV-2 pandemic.Funding Information: Federal Office of Public Health, Swiss National Science Foundation (grant 189498), European Union Horizon 2020 (grant 101003688).Declaration of Interests: The authors declare no competing interests.Ethics Approval Statement: We conducted this research using surveillance data according to the Swiss law on communicable diseases (EpG, SR 818.101). No ethical approval was required.

Spatial analysis of Archaeological and historical sites and their relationship with the Natural and Human Factors case study: Al Baha region

هدف هذا البحث إلى دراسة التوزيع الجغرافي للمواقع الأثرية والتاريخية في منطقة الباحة، وتحليل العلاقات المكانية بينها وبين باقي الظواهر الجغرافية والبشرية في المنطقة، مما يحقق لنا رؤية شاملة للوضع الراهن لهذه المواقع الأثرية والتاريخية، والسعي لتنمية الوعي بأهميتها السياحية لمنطقة الباحة. ولتحقيق أهداف البحث تم استخدام منهج التحليل المكاني في بيئة نظم المعلومات الجغرافية لقياس العلاقات المكانية بين الظاهرات في منطقة الدراسة من خلال ما تحتويه هذه التقنية من أدوات إحصاء وتحليل مكاني متعددة كما تم اعتماد الأسلوب الكارتوجرافى في التمثيل الخرائطي لعرض ورسم الخرائط باستخدام برنامج نظم المعلومات الجغرافية ArcGIS 10.6. وتوصلت الدراسة إلى حصر المواقع الأثرية والتاريخية في منطقة الباحة الذي بلغ حوالي 129 موقعاً توزعت بين 7 محافظات، كان توزيعها النسبي متباينا جدا بين الجزء الغربي والجزء الشرقي من المنطقة (حوالي 97 موقعا يقع شرق السروات و32 موقعاً غربها أي بنسبة توزيع 75% من المواقع في الشرق و25% من المواقع غرب السروات) في ارتباط وثيق بمظاهر السطح والموارد المائية والثروات المعدنية وطرق التجارة القديمة. وكان توزيع المواقع الأثرية والتاريخية في منطقة الباحة توزيعا متقاربا في مجمله (معامل صلة الجوار=0.63) وذلك لانحصار وصغر مساحات السهول الصالحة للاستيطان وطغيان المرتفعات شديدة الانحدار والصحراء الواسعة على مساحة منطقة الباحة. أما كثافة تركز المواقع الأثرية والتاريخية فقد كانت مرتفعة في الجزء الشرقي في حين انخفضت في الجزء الغربي من منطقة الدراسة. وأوصت الدراسة بأهمية استخدام تطبيقات نظم المعلومات الجغرافية للاستفادة منها في دراسة البعد المكاني للمواقع الأثرية والتاريخية ومدى التداخل المكاني بينها وبين مختلف الظواهر الطبيعية والبشرية في منطقة الدراسة. استغلال مخرجات التحليل المكاني في إعداد أطلس أثري يحتوي على خرائط ورسوم بيانية توضيحية وصور للمعالم والأماكن الأثرية في المنطقة لغرض استغلال وتسويق هذه الموارد الكامنة سياحيا. تشجيع الدراسات والأبحاث التي تسهم في إبراز أهمية المواقع الأثرية والتاريخية والتشجع على استغلالها في محاولة لدمج معمق لمنطقة الدراسة في المجالات السياحية.

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Assessing the Retail Environments of Licensed and Unlicensed Cannabis Dispensaries: Adapting the Marijuana Retail Surveillance Tool to Inform Cannabis Regulation in Los Angeles County.

After statewide legalization of recreational cannabis in California, the Los Angeles (LA) County Board of Supervisors requested a health equity impact assessment to inform its decisions on whether and how to regulate cannabis dispensaries in unincorporated areas of LA County. As part of this assessment, the LA County Department of Public Health compared the retail environments of licensed and unlicensed cannabis dispensaries in different parts of the county, using the Marijuana Retail Surveillance Tool (MRST), a validated instrument piloted in Colorado and Washington. Two waves of observational surveys were conducted, one comparing licensed and unlicensed dispensaries within and near unincorporated areas of LA County and another comparing licensed dispensaries across LA County in areas with varying levels of health advantage according to a neighborhood index measuring social determinants of health. Dispensaries were compared on measures of product types, promotional activities, security measures, regulatory compliance, and neighborhood context. Unlicensed dispensaries were more likely than licensed dispensaries to sell products in packaging designed to be attractive to children (71.8% vs 10.8%, P < .001) and in non-child-resistant packaging (98.9% vs 15.6%, P < .001) and were more likely allow on-site consumption (60.9% vs 0%, P < .001). Licensed dispensaries showed high compliance with regulations, regardless of whether they were in areas of high or low health advantage. The study points to the importance of efforts to eliminate illicit businesses as part of an overall strategy for regulating cannabis. It also demonstrates that the MRST is a flexible tool for regulatory surveillance and for continuing to study the relationships between cannabis retail environments and potential risks to public health.

MULTIPLICATIVE STATUS NEIGHBORHOOD INDICES OF GRAPHS

Many distance based indices of a graph have been studied in the literature. In this study, we introduce the multiplicative first and second status neighborhood indices, multiplicative sum and product connectivity status neighborhood indices, general multiplicative first and second status neighborhood indices, multiplicative Fstatus neighborhood index, general multiplicative status neighborhood index of a graph and compute exact formulas for some standard graphs and friendship graphs.

Deprivation, access and outcomes in health psychology treatment

PurposeIndividuals living in areas of higher deprivation are more likely to have requested mental health treatment but are less likely to have received treatment or benefitted from it. Less is known about the extent of access equality and treatment outcomes for individuals with a long-term health condition who experience mental health difficulties. The purpose of this paper is to evaluate the extent to which the neighbourhood Index of Multiple Deprivation predicted access to treatment, appointment attendance, treatment completion and clinical outcomes in a British health psychology clinic.Design/methodology/approachRetrospective data were used from 479 individuals referred to a health psychology clinic over 12 months. Clinical outcomes were measured using the Clinical Outcomes in Routine Evaluation – Outcome Measure. Patient data were linked with their neighbourhood Index of Multiple Deprivation decile. Data were analysed using correlation, linear regression and Fisher’s exact test.FindingsThere were no significant associations between deprivation and whether an individual attended assessment, attended treatment or completed treatment or between deprivation and patients’ clinical outcomes. Exploratory evidence indicated that individuals from higher deprivation neighbourhoods may be over-represented in clinic referrals, and individuals from lower deprivation neighbourhoods may be under-represented, compared with local population distribution estimates.Originality/valueThis evaluation provides insights into treatment outcomes and deprivation in those with physical health difficulties. Further evaluation using a larger sample and comparing referrals with local prevalence estimates of comorbid mental and physical health problems would enable greater confidence in the conclusion that no evidence of inequality on the basis of neighbourhood deprivation was found.