Environmental sustainability and the residential environment of the elderly: A literature review

Hu, Xin

doi:10.1016/j.buildenv.2021.108337

Cited by 20 publications

(13 citation statements)

References 99 publications

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“…The calculation formula for each criterion is defined in Table 1 . Another important evaluation criterion used in this paper is the area under the curve of the receiver operating characteristics curve (AUC-ROC), which determines the extent to which the model can differentiate between classes [ 73 ]. Furthermore, the fivefold cross-validation method was adopted to evaluate the performance of the algorithms.…”

Section: Methodsmentioning

confidence: 99%

Prediction of successful aging using ensemble machine learning algorithms

Varzaneh

Yazdani

Kazemi-Arpanahi³

2022

BMC Med Inform Decis Mak

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Background Aging is a chief risk factor for most chronic illnesses and infirmities. The growth in the aged population increases medical costs, thus imposing a heavy financial burden on families and communities. Successful aging (SA) is a positive and qualitative view of aging. From a biomedical perspective, SA is defined as the absence of diseases or disability disorders. This is distinct from normal aging, which is associated with age-related deterioration in physical and cognitive functions. From a social perspective, SA highlights life satisfaction and individual well-being, usually attained through socialization. It is an abstract and multidimensional concept surrounded by imprecision about its definition and measurement. Our study attempted to find the most effective features of SA as defined by Rowe and Kahn's theory. The determined features were used as input parameters of six machine learning (ML) algorithms to create and validate predictive models for SA. Methods In this retrospective study, the raw data set was first pre-processed; then, based on the data of a sample of 983, five basic ML techniques including artificial neural network, decision tree, support vector machine, Naïve Bayes, and k-nearest neighbors (K-NN) with one ensemble method (that gathers 30 K-NN algorithms as weak learners) were trained. Finally, the prediction result was yielded using the majority vote method based on the output of the generated base models. Results The experimental results revealed that the predictive system has been more successful in predicting SA with a 93% precision, 92.40% specificity, 87.80% sensitivity, 90.31% F-measure, 89.62% accuracy, and a ROC of 96.10%, using a five-fold cross-validation procedure. Conclusions Our results showed that ML techniques potentially have satisfactory performance in supporting the SA-related decisions of social and health policymakers. The KNN-based ensemble algorithm is superior to the other ML models in classifying people into SA and non-SA classes.

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Section: Methodsmentioning

confidence: 99%

Prediction of successful aging using ensemble machine learning algorithms

Varzaneh

Yazdani

Kazemi-Arpanahi³

2022

BMC Med Inform Decis Mak

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“…By classifying and organizing acquired data, the approach can simplify information into content-related categories, making it easier to identify study subjects in the area (Hu, 2021).…”

Section: Methodsmentioning

confidence: 99%

“…Content analysis is a method for drawing inferences from messages by systematically and objectively identifying unique qualities, which also helps measure and assess the existence, meanings, and linkages. By classifying and organizing acquired data, the approach can simplify information into content‐related categories, making it easier to identify study subjects in the area (Hu, 2021).…”

Section: Methodsmentioning

confidence: 99%

A systematic review on the role of geographical information systems in monitoring and achieving sustainable development goal 6: Clean water and sanitation

Baskaran¹,

Velkennedy²

2022

Sustainable Development

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The world has changed dramatically in the last two decades due to human intervention at regional and global levels. The fates of humanity and our planet are in our hands. Governments, international agencies, the corporate sector, and individuals must work together to shift away from unsustainable practices. The U.N. General Assembly endorsed the 2030 agenda for Sustainable Development, which comprises 17 Sustainable Development Goals (SDGs). Several published research supports SDG strategies in the last 5 years. Despite initial efforts, the U.N. declared that the world is not really on pace to achieve most SDG targets. Geographic information system (GIS) has been identified as an effective tool in accessing, monitoring, and achieving goals that have 15 years lifespan. This paper presents a systematic review of published articles that combined GIS and SDG in their research. Because these 17 goals include 169 targets, the assessment may be more difficult if all the goals were addressed. This study focused only on “SDG 6: Clean water and sanitation” literature. Google scholar was used to find the most relevant 25 studies. The variable attributes like SDG target addressed, study area, monitoring and improving strategies dealt, the particularity of GIS were analyzed in the literature review through content analysis. The systematic review has found that target 6.1 received enormous attention, and the inverse distance weightage (IDW) interpolation tool from the geostatistical analysis toolset was widely employed in the monitoring stage.

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“…A living environment is the home and its neighbourhood space offered to inhabitants for the purpose of performing various activities. It has been identified and confirmed as a crucial factor impacting the well-being of older adults through its three functions of maintenance, simulation and support (Hu, 2021; Lawton, 1989; Wahl and Oswald, 2016). As people age, their daily independence relies heavily on the quality of their living environments (e.g.…”

Section: Background Literaturementioning

confidence: 99%

Social sustainability of continuing care retirement communities in China

2023

Self Cite

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Purpose China’s population is ageing. Continuing care retirement communities (CCRCs) are an emerging living arrangement of older Chinese. Incorporating social sustainability features into CCRCs helps to create age-friendly residential environments for residents. However, it is still unclear what kinds of social sustainability features are incorporated into the residential environments of CCRCs in China. Therefore, this study aims to address this research gap. Design/methodology/approach Qualitative content analysis is adopted to analyse the retrieved business information of representative CCRC developers in China. Findings This study revealed 36 social sustainability features in CCRCs, with the top-ranked ones being health care and management, social connection and engagement, high-quality and diverse services and daily life support and assistance. Additionally, a preliminary social sustainability framework of CCRCs was proposed, and this framework includes the five components of care and health, environment and management, service and facility, age-friendly life philosophy and social support and inclusion. Originality/value In theory, this research’s findings clarify the meaning of social sustainability within the context of CCRCs, which supports future relevant explorations in the CCRC research community. In practice, these findings enhance stakeholders’ understanding of the social sustainability in CCRCs, which promotes the development of age-friendly living environments for older people in an ageing society.

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Environmental sustainability and the residential environment of the elderly: A literature review

Cited by 20 publications

References 99 publications

Prediction of successful aging using ensemble machine learning algorithms

Prediction of successful aging using ensemble machine learning algorithms

A systematic review on the role of geographical information systems in monitoring and achieving sustainable development goal 6: Clean water and sanitation

Social sustainability of continuing care retirement communities in China

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