A TODIM-based approach for the assessment of social vulnerability in Jiangsu province from 2012 to 2017

Social vulnerability assessment is of great significance for risk management and reduction. Carrying out the assessment is beneficial to the sustainability of the development of society and the economy. For this purpose, Jiangsu province in China is taken as the study area to explore the social vulnerability assessment at a city level. A framework has been constructed from three dimensions of demographics, economics, and social security. In our study, a new approach based on the maximizing deviation method and TODIM model is proposed to evaluate social vulnerability in Jiangsu province. For the sake of analysis, we divide 13 cities of Jiangsu province into three parts, namely the southern part, central part, and northern part, according to the geographical location. As a result, the north part performance of social vulnerability is the worst among the three regions. The average of the northern part has always obviously exceeded the others of Jiangsu province from 2012 to 2017, which indicates that the north part is the most vulnerable to natural hazards. In addition, the performance of the southern part is relatively better than that of the central region. Especially, Suqian has always been at the bottom from 2012 to 2017, which reveals the ability to withstand natural disasters is the most insufficient. Our findings also imply that social vulnerability is related to local economic development to some extent.

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Comparative analysis of the social vulnerability assessment to climate change applied to fisheries from Spain and Turkey

Scientific Reports ◽

10.1038/s41598-021-93165-0 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Mauro Gómez Murciano ◽

Yajie Liu ◽

Vahdet Ünal ◽

José Luis Sánchez LIzaso

Keyword(s):

Climate Change ◽

Vulnerability Assessment ◽

Social Vulnerability ◽

Aegean Sea ◽

Institutional Characteristics ◽

Vulnerability To Climate Change ◽

Fishing Sector ◽

The Social ◽

Social Vulnerability Assessment ◽

Structured Questionnaire

AbstractThe aim of this study is to assess the climate effects on fisheries from a bottom-up approach based on fishers’ fishing experience, knowledge, and perceptions. To perform this task, a social vulnerability assessment was conducted in two different fishing areas: one in Spain and the other one in Turkey. The vulnerability was measured using the collected data and information through a structured questionnaire, and surveys were carried out among fishers in the Castelló (Spain) and the Aegean Sea (Turkey) between 2018 and 2019. Overall, the results indicated that the two studied regions have a moderate to high vulnerability and that the Aegean Sea was slightly more vulnerable than Castelló. It was also found that storms and temperature are the main climatic stressors that affect the fishing sector, and the economic indicators such as revenue from fishing in both regions showed high degrees of sensitivity. To reduce the vulnerability to climate change, adaptive measures should be implemented while taking into consideration the specific socio-economic and institutional characteristics of each region. In conclusion, the effects of climate change on the fishing sector and their social vulnerability are diverse. Consequently, there is no single climate measure that can minimize the vulnerability of fishing sectors in different regions.

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Urban social vulnerability assessment with physical proxies and spatial metrics derived from air- and spaceborne imagery and GIS data

Natural Hazards ◽

10.1007/s11069-008-9264-0 ◽

2008 ◽

Vol 48 (2) ◽

pp. 275-294 ◽

Cited By ~ 89

Author(s):

Annemarie Ebert ◽

Norman Kerle ◽

Alfred Stein

Keyword(s):

Vulnerability Assessment ◽

Social Vulnerability ◽

Spatial Metrics ◽

Gis Data ◽

Social Vulnerability Assessment

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Social determinants of malnutrition in Chilean children aged up to five

BMC Public Health ◽

10.1186/s12889-021-12455-4 ◽

2022 ◽

Vol 22 (1) ◽

Author(s):

Sandra Alvear-Vega ◽

Héctor Vargas-Garrido

Keyword(s):

Social Determinants ◽

Reference Group ◽

Multinomial Logistic Regression ◽

Geographical Location ◽

Vulnerable Groups ◽

Outcome Variable ◽

Multinomial Logistic Regression Model ◽

The North ◽

The Social ◽

Child Nutritional Status

Abstract Background This study aimed to ascertain the Social Determinants (SDs) of malnutrition (over and undernutrition) of Chilean children aged up to five. Methods The study was carried out using a sample of children from zero to five years old (n = 1,270,485; 52.2% female) from the National Socioeconomic Characterization Survey (CASEN) 2017. A multinomial logistic regression model was used, where the “child nutritional status” outcome variable assumed three possible values: normal nutrition, overnutrition, and undernutrition, while taking those variables reported in previous literature as independent variables. Results The model, by default, set normal nutrition as the reference group, Count R2 = 0.81. Results show a higher likelihood of both overnutrition and undernutrition among male children from the lowest quintiles, with native ethnic backgrounds, reporting health problems, having public health insurance, and who attend kindergarten. Additionally, higher probabilities of undernutrition in younger than two and living in the north of the country, while overnutrition is more likely in the south. Conclusions Socioeconomic variables are fundamentally related to both over and undernutrition; the current single schema program to prevent malnutrition should consider SDs such as ethnicity and geographical location, among others; moreover, successful nutritional programs—which focused on the lowest quintiles, need to be expanded to other vulnerable groups and pay more attention to overnutrition.

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Social Vulnerability Assessment for Flood Risk Analysis

Water ◽

10.3390/w12020558 ◽

2020 ◽

Vol 12 (2) ◽

pp. 558 ◽

Cited By ~ 4

Author(s):

Laura Tascón-González ◽

Montserrat Ferrer-Julià ◽

Maurici Ruiz ◽

Eduardo García-Meléndez

Keyword(s):

Vulnerability Assessment ◽

Flood Risk ◽

Social Vulnerability ◽

Large Scale ◽

Vulnerability Index ◽

Social Vulnerability Index ◽

Coping Capacity ◽

High Exposure ◽

Public Data ◽

Social Vulnerability Assessment

This paper proposes a methodology for the analysis of social vulnerability to floods based on the integration and weighting of a range of exposure and resistance (coping capacity) indicators. It focuses on the selection and characteristics of each proposed indicator and the integration procedure based on the analytic hierarchy process (AHP) on a large scale. The majority of data used for the calculation of the indicators comes from open public data sources, which allows the replicability of the method in any area where the same data are available. To demonstrate the feasibility of the method, a study case is presented. The flood social vulnerability assessment focuses on the municipality of Ponferrada (Spain), a medium-sized town that has high exposure to floods due to potential breakage of the dam located upstream. A detailed mapping of the social vulnerability index is generated at the urban parcel scale, which shows an affected population of 34,941 inhabitants. The capability of working with such detailed units of analysis for an entire medium-sized town provides a valuable tool to support flood risk planning and management.

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Applying spatial clustering analysis to a township-level social vulnerability assessment in Taiwan

Geomatics Natural Hazards and Risk ◽

10.1080/19475705.2015.1084542 ◽

2015 ◽

Vol 7 (5) ◽

pp. 1659-1676 ◽

Cited By ~ 5

Author(s):

Wen-Yen Lin ◽

Chi-Tung Hung

Keyword(s):

Vulnerability Assessment ◽

Social Vulnerability ◽

Clustering Analysis ◽

Spatial Clustering ◽

Spatial Clustering Analysis ◽

Social Vulnerability Assessment

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Social Determinants of Malnutrition in Chilean Children Aged Under Five

10.21203/rs.3.rs-882775/v1 ◽

2021 ◽

Author(s):

Sandra Alvear-Vega ◽

Héctor Vargas-Garrido

Keyword(s):

Social Determinants ◽

Reference Group ◽

Multinomial Logistic Regression ◽

Geographical Location ◽

Vulnerable Groups ◽

Multinomial Logistic Regression Model ◽

Under Five ◽

The North ◽

The Social ◽

Child Nutritional Status

Abstract Background: This study aimed to ascertain the Social Determinants (SDs) of malnutrition (over and undernutrition) of Chilean children aged under five.Methods: The study was carried out using a sample of children from zero to five years old (n = 1,270,485; 52.2% female) from the National Socioeconomic Characterization Survey (CASEN) 2017. A multinomial logistic regression model was used, where the "child nutritional status" dependent variable assumed three possible values: normal nutrition, overnutrition, and undernutrition, while taking those variables reported in previous literature as control variables.Results: The model, by default, set normal nutrition as the reference group, Count R2 = 0.81. Results show a higher likelihood of both overnutrition and undernutrition among male children from the lowest quintiles, with native ethnic backgrounds, reporting health problems, having public health insurance, and who attend kindergarten. Additionally, higher probabilities of undernutrition in younger than two and living in the north of the country, while overnutrition is more likely in the south.Conclusions: Socioeconomic variables are fundamentally related to both over and undernutrition; the current single schema program to prevent malnutrition should consider SDs such as ethnicity and geographical location, among others; moreover, successful nutritional programs—which focused on the lowest quintiles, need to be expanded to other vulnerable groups and pay more attention to overnutrition.

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