Evidence map›Paper›PMID 37033027›Full record

ArticleFrontiers in public health2023

Optimal utilization of ecological economic resources and low-carbon economic analysis from the perspective of Public Health.

Qi Wang, Yan Feng, Ao Hu

Abstract read
In one paragraph

Article in Frontiers in public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Qi WangManagement School, Hunan City University, Yiyang, China.
Yan FengManagement School, Hunan City University, Yiyang, China.
Ao HuLocal Governance Research Institute, Central South University, Changsha, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: China's urbanization process continues to deepen with social development, but the optimal utilization of ecological, economic resources and Public Health (PH) problems are becoming increasingly severe. Methods: This paper analyses the optimal use of urban resources based on PH. Here, the public space of urban settlements is selected as the research object. Firstly, the connotation and essence of the ecological economy and Low-Carbon Economy (LCE) are analyzed. Secondly, the characteristics of public space in urban settlements are studied based on PH. The public space satisfaction evaluation model in urban settlements is constructed with five first-level and 12 second-level indicators. Finally, a questionnaire is designed to analyze urban households' outdoor activities and evaluate public space in settlements. Results: The influencing factors of residents' satisfaction with public space in settlements are obtained through regression analysis. The results show that residents' satisfaction with the public space of the settlement is mainly evaluated from three aspects: the accessibility of public space, the integrity of public space, and the pleasure of public space. The influence coefficients are 0.355, 0.346, and 0.223, respectively, indicating that the influence degree of the three principal factors decreases in turn. Conclusion: We can optimize the utilization of urban residential public space resources from the aspects of accessibility, integrity and pleasure, so as to promote residents to go to public spaces for outdoor activities and physical exercise, which is more conducive to the public health of residents.

Indexed as

CarbonPublic HealthEnvironmentExerciseUrbanizationCarbonecological economyLow-Carbon EconomyPublic Healthpublic spaces in settlementssatisfaction evaluation indicators

Identifiers

PMID37033027
PMCPMC10076761

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.