Sustainable development (SD) has become a fundamental strategy to guide the world’s social and economic transformation. However, in the process of practice, there are still misinterpretations in regards to the theory of SD. Such misinterpretations are highlighted in the struggle between strong and weak sustainable development paths, and the confusion of the concept of intra-generational and inter-generational justice. In this paper, the literature survey method, induction method, and normative analysis were adopted to clarify the gradual evolution and improvement process of the concept and objective of SD, to strengthen the comprehensive understanding of the SD theory. Moreover, we also tried to bring in the situation and concepts of China. The results show that the theory of SD has gone through three periods: the embryonic period (before 1972), the molding period (1972–1987), and the developing period (1987–present). SD is gradually implemented into a global action from the initial fuzzy concept, including increasing practical wisdom. The goal of SD evolves from pursuing the single goal of sustainable use of natural resources to Millennium Development Goals (MDGs) and Sustainable Development Goals (SDGs). This paper argues that the theory of strong sustainability should be the accepted concept of SD. Culture, good governance, and life support systems are important factors in promoting SD.

The Evolution of Sustainable Development Theory: Types, Goals, and Research Prospects

Although evidence shows that poor air quality can harm human health, we have a limited understanding about the behavioural impact of air quality forecasts Our aim was to understand to what extent air quality warning systems influence protective behaviours in the general public, and to identify the demographic and psychosocial factors associated with adherence and non-adherence to the health advice accompanying these warnings In August 2016 literature was systematically reviewed to find studies assessing intended or actual adherence to health advice accompanying air quality warning systems, and encouraging people to reduce exposure to air pollution Predictors of adherence to the health advice and/or self-reported reasons for adherence or non-adherence were also systematically reviewed Studies were included only if they involved participants who were using or were aware of these warning systems Studies investigating only protective behaviours due to subjective perception of bad air quality alone were excluded The results were narratively synthesised and discussed within the COM-B theoretical framework Twenty-one studies were included in the review: seventeen investigated actual adherence; three investigated intended adherence; one assessed both Actual adherence to the advice to reduce or reschedule outdoor activities during poor air quality episodes ranged from 97% to 57% (Median = 31%), whereas adherence to a wider range of protective behaviours (eg avoiding busy roads, taking preventative medication) ranged from 177% to 981% (Median = 46%) Demographic factors did not consistently predict adherence However, several psychosocial facilitators of adherence were identified These include knowledge on where to check air quality indices, beliefs that one’s symptoms were due to air pollution, perceived severity of air pollution, and receiving advice from health care professionals Barriers to adherence included: lack of understanding of the indices, being exposed to health messages that reduced both concern about air pollution and perceived susceptibility, as well as perceived lack of self-efficacy/locus of control, reliance on sensory cues and lack of time We found frequent suboptimal adherence rates to health advice accompanying air quality alerts Several psychosocial facilitators and barriers of adherence were identified To maximise their health effects, health advice needs to target these specific psychosocial factors

/pdf/psychosocial-and-demographic-predictors-of-adherence-and-non-40th8vvead.pdf

Psychosocial and demographic predictors of adherence and non-adherence to health advice accompanying air quality warning systems: a systematic review.

Exposure to air pollution is affected by human behaviour, and has consequences for individual and collective health. One way to lessen the health effects of air pollution is to change personal travel behaviour with the help of new information, communication and sensing technologies. Our social research tracked the experiences of participants, air quality and technology enthusiasts, based in London who financially contributed to participate in an early-stage technical trial of a new air pollution sensor and app providing individuals with air pollution information (specifically levels of NO2 and VOCs). This paper reports the results of a before and after survey (returning respondents n = 22) and 12 in-depth interviews with individuals who took part in the beta test of the sensor and phone app. The survey results show that travel-related behaviours and attitudes relevant to air pollution did not change after using the technology. In contrast, expectations of technology performance and the extent it would influence behaviours were significantly lower after the trial than before. Further exploration during semi-structured interviews found that the participants, given their already high level of engagement with the topic, felt the capacity for immediate individual behaviour change was limited. As well as time and practical constraints, most people in this sample felt they were already doing what they could to avoid high levels of air pollution in their daily lives. Despite this, they had some recommendations to improve the app, such as the inclusion of real-time and historic maps, and the ability to make self and other comparisons. Overwhelmingly, people saw a broader role for the technology to engage the public with air pollution through raising awareness, and harnessing citizen science to collect diverse reliable data to inform policy and influence local policymakers to reduce air pollution levels.

/pdf/the-role-of-personal-air-pollution-sensors-and-smartphone-4zaqar55gm.pdf

The role of personal air pollution sensors and smartphone technology in changing travel behaviour

Global association of air pollution and heart failure

Background With a higher proportion of older people in the UK population, new approaches are needed to reduce emergency hospital admissions, thereby shifting care delivery out of hospital when possible and safe. Study aim To evaluate the introduction of predictive risk stratification in primary care. Objectives To (1) measure the effects on service usage, particularly emergency admissions to hospital; (2) assess the effects of the Predictive RIsk Stratification Model (PRISM) on quality of life and satisfaction; (3) assess the technical performance of PRISM; (4) estimate the costs of PRISM implementation and its effects; and (5) describe the processes of change associated with PRISM. Design Randomised stepped-wedge trial with economic and qualitative components. Setting Abertawe Bro Morgannwg University Health Board, south Wales. Participants Patients registered with 32 participating general practices. Intervention PRISM software, which stratifies patients into four (emergency admission) risk groups; practice-based training; and clinical support. Main outcome measures Primary outcome – emergency hospital admissions. Secondary outcomes – emergency department (ED) and outpatient attendances, general practitioner (GP) activity, time in hospital, quality of life, satisfaction and costs. Data sources Routine anonymised linked health service use data, self-completed questionnaires and staff focus groups and interviews. Results Across 230,099 participants, PRISM implementation led to increased emergency admissions to hospital [ΔL = 0.011, 95% confidence interval (CI) 0.010 to 0.013], ED attendances (ΔL = 0.030, 95% CI 0.028 to 0.032), GP event-days (ΔL = 0.011, 95% CI 0.007 to 0.014), outpatient visits (ΔL = 0.055, 95% CI 0.051 to 0.058) and time spent in hospital (ΔL = 0.029, 95% CI 0.026 to 0.031). Quality-of-life scores related to mental health were similar between phases (Δ = –0.720, 95% CI –1.469 to 0.030); physical health scores improved in the intervention phase (Δ = 1.465, 95% CI 0.774 to 2.157); and satisfaction levels were lower (Δ = –0.074, 95% CI – 0.133 to –0.015). PRISM implementation cost £0.12 per patient per year and costs of health-care use per patient were higher in the intervention phase (Δ = £76, 95% CI £46 to £106). There was no evidence of any significant difference in deaths between phases (9.58 per 1000 patients per year in the control phase and 9.25 per 1000 patients per year in the intervention phase). PRISM showed good general technical performance, comparable with existing risk prediction tools (c-statistic of 0.749). Qualitative data showed low use by GPs and practice staff, although they all reported using PRISM to generate lists of patients to target for prioritised care to meet Quality and Outcomes Framework (QOF) targets. Limitations In Wales during the study period, QOF targets were introduced into general practice to encourage targeting care to those at highest risk of emergency admission to hospital. Within this dynamic context, we therefore evaluated the combined effects of PRISM and this contemporaneous policy initiative. Conclusions Introduction of PRISM increased emergency episodes, hospitalisation and costs across, and within, risk levels without clear evidence of benefits to patients. Future research (1) Evaluation of targeting of different services to different levels of risk; (2) investigation of effects on vulnerable populations and health inequalities; (3) secondary analysis of the Predictive Risk Stratification: A Trial in Chronic Conditions Management data set by health condition type; and (4) acceptability of predictive risk stratification to patients and practitioners. Trial and study registration Current Controlled Trials ISRCTN55538212 and PROSPERO CRD42015016874. Funding The National Institute for Health Research Health Services Delivery and Research programme.

/pdf/predictive-risk-stratification-model-a-randomised-stepped-2ysg88vrja.pdf

Predictive risk stratification model: a randomised stepped-wedge trial in primary care (PRISMATIC)

Background There is no evidence to date on whether an intervention alerting people to high levels of pollution is effective in reducing health service utilisation. We evaluated alert accuracy and the effect of a targeted personal air pollution alert system, airAware, on emergency hospital admissions, emergency department attendances, general practitioner contacts and prescribed medications. Methods Quasi-experimental study describing accuracy of alerts compared with pollution triggers; and comparing relative changes in healthcare utilisation in the intervention group to those who did not sign-up. Participants were people diagnosed with asthma, chronic obstructive pulmonary disease (COPD) or coronary heart disease, resident in an industrial area of south Wales and registered patients at 1 of 4 general practices. Longitudinal anonymised record linked data were modelled for participants and non-participants, adjusting for differences between groups. Results During the 2-year intervention period alerts were correctly issued on 208 of 248 occasions; sensitivity was 83.9% (95% CI 78.8% to 87.9%) and specificity 99.5% (95% CI 99.3% to 99.6%). The intervention was associated with a 4-fold increase in admissions for respiratory conditions (incidence rate ratio (IRR) 3.97; 95% CI 1.59 to 9.93) and a near doubling of emergency department attendance (IRR=1.89; 95% CI 1.34 to 2.68). Conclusions The intervention was associated with increased emergency admissions for respiratory conditions. While findings may be context specific, evidence from this evaluation questions the benefits of implementing near real-time personal pollution alert systems for high-risk individuals.

pdf/effects-of-an-air-pollution-personal-alert-system-on-health-2h4klr2upr.pdf

Effects of an air pollution personal alert system on health service usage in a high-risk general population: a quasi-experimental study using linked data.

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Effects of an air pollution personal alert system on health service usage in a high-risk general population: a quasi-experimental study using linked data.