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Wang KH, Wen CP, Tang Y, Su CW. Mitigating environmental pollution in China: Unlocking the potential for high-quality innovation. iScience 2024; 27:110231. [PMID: 39027373 PMCID: PMC11255844 DOI: 10.1016/j.isci.2024.110231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2023] [Revised: 03/09/2024] [Accepted: 06/06/2024] [Indexed: 07/20/2024] Open
Abstract
The nexus between environmental pollution (EP) and technological innovation is crucial for achieving sustainable development. However, existing literature has paid less attention to the new form of high-quality innovation (HI) in environmental management. This paper uses panel data from 31 Chinese provinces from 2008 to 2020, employing the two-stage least squares method to investigate the relationship between HI and EP. The empirical results reveal that HI can effectively reduce the EP, which holds after multiple robustness tests, and this effect is more obvious in southern China. Meanwhile, HI drives clean and efficient energy transition and decreases EP. Moreover, increased environmental regulation weakens the influence of HI on EP. The major contributions of this study are constructing an HI index including innovation, human capital, and government support and examining its influence on EP in China. The findings encourage government to implement policies of innovation-driven transformation, energy conservation and emissions reduction.
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Affiliation(s)
- Kai-Hua Wang
- School of Economics, Qingdao University, Qingdao 266100, P.R. China
| | - Cui-Ping Wen
- School of Economics, Qingdao University, Qingdao 266100, P.R. China
| | - Yun Tang
- School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, P.R. China
| | - Chi-Wei Su
- School of Economics, Qingdao University, Qingdao 266100, P.R. China
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Delclòs-Alió X, Rodríguez DA, Olmedo NL, Ferrer CP, Moore K, Stern D, de Menezes MC, de Oliveira Cardoso L, Wang X, Guimaraes JM, Miranda JJ, Sarmiento OL. Is city-level travel time by car associated with individual obesity or diabetes in Latin American cities? Evidence from 178 cities in the SALURBAL project. CITIES (LONDON, ENGLAND) 2022; 131:103899. [PMID: 36277810 PMCID: PMC7613723 DOI: 10.1016/j.cities.2022.103899] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
There is growing evidence that longer travel time by private car poses physical and mental risks. Individual-level obesity and diabetes, two of the main public health challenges in low- and middle-income contexts, could be associated to city-level travel times by car. We used individual obesity and diabetes data from national health surveys from individuals in 178 Latin American cities, compiled and harmonized by the SALURBAL project. We calculated city-level travel times by car using the Google Maps Distance Matrix API. We estimated associations between peak hour city-level travel time by car and obesity and diabetes using multilevel logistic regression models, while adjusting for individual characteristics and other city-level covariates. In our study we did not observe a relationship between city-level peak-hour travel time by car and individual obesity and diabetes, as reported in previous research for individual time spent in vehicles in high-income settings. Our results suggest that this relationship may be more complex in Latin America compared to other settings, especially considering that cities in the region are characterized by high degrees of population density and compactness and by a higher prevalence of walking and public transportation use.
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Affiliation(s)
- Xavier Delclòs-Alió
- Institute of Urban and Regional Development, University of California, Berkeley, CA, USA
- Research Group on Territorial Analysis and Tourism Studies (GRATET), Department of Geography, Universitat Rovira i Virgili, Spain
| | - Daniel A. Rodríguez
- Department of City and Regional Planning & Institute for Transportation Studies, University of California, Berkeley, 228 Wurster Hall, Berkeley, CA 94720, USA
| | - Nancy López Olmedo
- Instituto Nacional de Salud Pública, Mexico, Avenida Universidad 655, 62100 Cuernavaca, Morelos, Mexico
| | - Carolina Pérez Ferrer
- CONACyT-Instituto Nacional de Salud Pública, Cerrada de Fray Pedro de Gante 50, 14080 Mexico City, Mexico
| | - Kari Moore
- Dornsife School of Public Health, Drexel University, 3600 Market Street, Philadelphia, PA 19104, USA
| | - Dalia Stern
- CONACyT-Instituto Nacional de Salud Pública, Cerrada de Fray Pedro de Gante 50, 14080 Mexico City, Mexico
| | - Mariana Carvalho de Menezes
- Department of Clinical and Social Nutrition, Federal University of Ouro Preto, Av. Pres. Antônio Carlos, 6627, Belo Horizonte 31270-901, Minas Gerais, Brazil
| | - Letícia de Oliveira Cardoso
- Oswaldo Cruz Foundation, National School of Public Health, Av. Brasil 4365, Rio de Janeiro, 21040-900, Rio de Janeiro, Brazil
| | - Xize Wang
- Department of Real Estate, National University of Singapore, 4 Architecture Dr, 117566, Singapore
| | - Joanna M.N. Guimaraes
- Oswaldo Cruz Foundation, National School of Public Health, Av. Brasil 4365, Rio de Janeiro, 21040-900, Rio de Janeiro, Brazil
| | - J. Jaime Miranda
- CRONICAS Centre of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Av. Armendariz 445, 15074 Lima, Peru
| | - Olga L. Sarmiento
- School of Medicine, Universidad de Los Andes, Carrera 1, 111711 Bogotá, Colombia
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Sun B, Yao X, Yin C. An N-Shaped Association between Population Density and Abdominal Obesity. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:9577. [PMID: 35954934 PMCID: PMC9368206 DOI: 10.3390/ijerph19159577] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 07/28/2022] [Accepted: 08/03/2022] [Indexed: 11/16/2022]
Abstract
Abdominal obesity is a threat to public health and healthy cities. Densification may reduce abdominal obesity, but current evidence of the relationship between population density and abdominal obesity is not conclusive. The aim of this study was to disentangle the nonlinear association between population density and abdominal obesity. Data came from the 2004-2015 China Health and Nutrition Survey, which included 36,422 adults aged between 18 and 65 years. Generalized additive models (GAMs) were applied to explore how population density was associated with objectively measured waist circumference (WC) and waist-to-height ratio (WHtR), after controlling for other built environmental attributes, socioeconomic characteristics, and regional and year fixed effects. We found that population density had N-shaped associations with both WC and WHtR, and the two turning points were 12,000 and 50,000 people/km2. In particular, population density was positively correlated with abdominal obesity when it was below 12,000 people/km2. Population density was negatively associated with abdominal obesity when it was between 12,000 and 50,000 people/km2. Population density was also positively related to abdominal obesity when it was greater than 50,000 people/km2. Therefore, densification is not always useful to reduce abdominal obesity. Policy-makers need to pay more attention to local density contexts before adopting densification strategies.
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Affiliation(s)
- Bindong Sun
- The Center for Modern Chinese City Studies, East China Normal University, Shanghai 200241, China
- Research Center for China Administrative Division, East China Normal University, Shanghai 200241, China
- Institute of Eco-Chongming, 20 Cuiniao Rd., Chenjia Zhen, Chongming, Shanghai 202162, China
- School of Urban and Regional Science, East China Normal University, Shanghai 200241, China
- Future City Laboratory, East China Normal University, Shanghai 200241, China
| | - Xiajie Yao
- Research Center for China Administrative Division, East China Normal University, Shanghai 200241, China
- Institute of Eco-Chongming, 20 Cuiniao Rd., Chenjia Zhen, Chongming, Shanghai 202162, China
- School of Urban and Regional Science, East China Normal University, Shanghai 200241, China
- Future City Laboratory, East China Normal University, Shanghai 200241, China
| | - Chun Yin
- Research Center for China Administrative Division, East China Normal University, Shanghai 200241, China
- Institute of Eco-Chongming, 20 Cuiniao Rd., Chenjia Zhen, Chongming, Shanghai 202162, China
- School of Urban and Regional Science, East China Normal University, Shanghai 200241, China
- Future City Laboratory, East China Normal University, Shanghai 200241, China
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Nonlinear Relationships among the Natural Environment, Health, and Sociodemographic Characteristics across US Counties. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19116898. [PMID: 35682481 PMCID: PMC9180717 DOI: 10.3390/ijerph19116898] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Revised: 05/26/2022] [Accepted: 05/31/2022] [Indexed: 01/25/2023]
Abstract
Background: The aim of this study was to explore the nonlinear relationships between natural amenities and health at the intersection of sociodemographic characteristics among primary care patients with chronic conditions. Methods: We used survey data from 3409 adults across 119 US counties. PROMIS-29 mental and physical health summary scores were the primary outcomes. The natural environment (measured using the County USDA Natural Amenities Scale (NAS)) was the primary predictor. Piecewise spline regression models were used to explore the relationships between NAS and health at the intersection of sociodemographic factors. Results: We identified a nonlinear relationship between NAS and health. Low-income individuals had a negative association with health with each increase in NAS in high-amenity areas only. However, White individuals had a stronger association with health with each increase in NAS in low-amenity areas. Conclusions: In areas with low natural amenities, more amenities are associated with better physical and mental health, but only for advantaged populations. Meanwhile, for disadvantaged populations, an increase in amenities in high-amenity areas is associated with decreases in mental and physical health. Understanding how traditionally advantaged populations utilize the natural environment could provide insight into the mechanisms driving these disparities.
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