Environmental, individual and personal goal influences on older adults’ walking in the helsinki metropolitan area

Physical activity is a fundamental factor in healthy ageing, and the built environment has been linked to individual health outcomes. Understanding the linkages between older adult’s walking and the built environment are key to designing supportive environments for active ageing. However, the variety of different spatial scales of human mobility has been largely overlooked in the environmental health research. This study used an online participatory mapping method and a novel modelling of individual activity spaces to study the associations between both the environmental and the individual features and older adults’ walking in the environments where older adult’s actually move around. Study participants (n = 844) aged 55+ who live in Helsinki Metropolitan Area, Finland reported their everyday errand points on a map and indicated which transport mode they used and how frequently they accessed the places. Respondents walking trips were drawn from the data and the direct and indirect effects of the personal, psychological as well as environmental features on older adults walking were examined. Respondents marked on average, six everyday errand points and walked for transport an average of 20 km per month. Residential density and the density of walkways, public transit stops, intersections and recreational sports places were significantly and positively associated with older adult’s walking for transport. Transit stop density was found having the largest direct effect to older adults walking. Built environment had an independent effect on older adults walking regardless of individual demographic or psychological features. Education and personal goals related to physical activities had a direct positive, and income a direct negative, effect on walking. Gender and perceived health had an indirect effect on walking, which was realized through individuals’ physical activity goals

Examining the effects of residential location and stated residential preferences on activity space size and centricity

Activity spaces are used to capture patterns in urban mobility and to portray the spatial distribution of day-to-day activities. The literature exploring variation in individual activity spaces identifies strong associations between several activity space characteristics and the built environment of the residential location. This cross-sectional study adds to this evidence by examining whether these associations persist after adjusting for residential self-selection. Adults’ everyday mobility was studied using public participation GIS, a participatory mapping method allowing the large-scale collection of laymen-produced spatial data. Activity spaces were defined with a customized minimum convex polygon modelled on the respondents’ frequently visited locations. We used linear regression and multinomial logistic regression analyses to study the associations between residential preferences, residential location, and activity space size and centricity. According to our results, residential location significantly influences activity space size and polycentricity in models adjusted for stated residential preferences and individual-level covariates

The implication of business intelligence in risk management: a case study in agricultural insurance

The increasing data scales in today’s business sectors coupled with the necessity of risk management raise the importance of business intelligence tools as an integrated solution for the insurance industry. These tools have mostly been used to achieve effective risk management. Although methods of risk management in the insurance industry have been proposed many years ago, the research effort has primarily been focused on predictive analyses. This study aimed to investigate the role of business intelligence as a solution to illustrate its potential in risk management particularly for decision-makers in agricultural insurance. We hypothesized that this would make a preferable decision in uncertain conditions. Sample data from the online transaction process system of Iran agricultural insurance fund were preprocessed in SQL server. Multidimensional online analytical processing architecture was analyzed using Targit business intelligence tool. Our results identified financial risks that lead to a framework of controlling risk based on business intelligence in the agricultural insurance fund

Identifying multiple knee pain trajectories and the prediction of opioid and NSAID medication used: a latent class growth approach

Background: Knee pain is a major source of distress and disability, with pain progression highly variable between individuals. Previous studies defining pain trajectories have all used a single measure of pain, and these differ across studies. Different measures reflect diverse pain mechanisms. To ascertain the clinical utility of pain trajectories, we explored associations between opioid and non-steroidal anti-inflammatory drug (NSAID) use. Methods: We model pain trajectories using two measures—Intermittent and Constant Osteoarthritis Pain (ICOAP) and the painDETECT, in 2141 participants, across 3 waves (the baseline, 1- and 3-year assessments) of the Knee Pain In the Community (KPIC) cohort. Results: Latent class growth analysis identified six trajectories using ICOAP subscales (High-Stable, Low-Stable, Moderate Worsening, Moderate Recovering, Worsening, and Recovering) and four trajectories using painDETECT (High-stable, Low-stable, Moderate Worsening, and Moderate Recovering). There was a high degree of correspondence between people assigned to pain trajectories between ICOAP intermittent and constant subscales, but less so using painDETECT. Opioid use was associated with ICOAP trajectories only (e.g., High-Stable and Worsening intermittent ICOAP trajectories) and in women. Conclusion: Different measures of pain produce different patterns of pain progression and these are differentially related to medication use. Opioid use is linked to trajectories of pain based on the impact of pain on behavior and not pain symptoms. Thus, managing pain's behavioral impact is more central to understanding opioid use than managing pain symptoms. These findings support more in-depth questioning about the type of pain and its progression in clinical practice

Relationship Between Organizational Justice and Organizational Safety Climate: Do Fairness Perceptions Influence Employee Safety Behaviour?

This study investigated the relationships between organizational justice, organizational safety climate, job satisfaction, safety compliance and accident frequency. Ghanaian industrial workers participated in the study (N = 320). Safety climate and justice perceptions were assessed with Hayes, Parender, Smecko, et al.’s (1998) and Blader and Tyler’s (2003) scales respectively. A median split was performed to dichotomize participants into 2 categories: workers with positive and workers with negative justice perceptions. Confirmatory factors analysis confirmed the 5-factor structure of the safety scale. Regression analyses and t tests indicated that workers with positive fairness perceptions had constructive perspectives regarding workplace safety, expressed greater job satisfaction, were more compliant with safety policies and registered lower accident rates. These findings provide evidence that the perceived level of fairness in an organization is closely associated with workplace safety perception and other organizational factors which are important for safety. The implications for safety research are discussed