Evidence map›Paper›PMID 38699420›Full record

ArticleFrontiers in public health2024

Study on the development characteristics and spatial and temporal patterns of population ageing in 31 central cities in China.

Le Zhang, Hengna Ren, Chen Li

Abstract read
In one paragraph

Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Observational
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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.

Le ZhangSchool of Marxism, Jiangnan University, Wuxi, China.
Hengna RenBusiness School, University of Shanghai for Science and Technology, Shanghai, China.
Chen LiSchool of Marxism, Shanghai University of Engineering Science, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Population ageing is inseparable from technological innovation, social progress and the development of human civilization, and constitutes a new element in the development of contemporary human history. Objective: To dynamically analyses the developmental, structural and growth characteristics of population ageing in 31 provincial capitals and municipalities in China, using the data of the fifth national census in 2000 and the seventh national census in 2020. Methods: The development characteristics and spatial and temporal patterns of population aging in the 31 cities were measured using the population aging index growth model, Theil's index, coefficient of variation, population aging index and other analytical methods. Results: (1) From 2000 to 2020, the population aging rate of the 31 central cities generally increased, and the population aging level of the cities showed the characteristics of "East-Central-Northeast-West" to "Northeast-East-Central-West" decreasing. (2) Regional differences in the ratio of old to young are relatively high, while regional differences in the level of population ageing are relatively small. The level of population ageing is classified with the indicators of size structure, family structure and age structure in the first and third quadrants, and with the geographic concentration rate in the second and fourth quadrants. (3) China's population ageing has a T-shaped spatial distribution characteristic pointing along the coast - along the Yangtze Rivers. Conclusion: The 31 central cities are the center of gravity of China's economy and have strong economic power in dealing with the challenges of population ageing, but how to make population ageing compatible with the economy and society, and then promote sustainable population development, is a topic that needs further attention in the study.

Indexed as

CitiesPopulation DynamicsSpatio-Temporal AnalysisAgedChinaHumanscentral citiesdynamic characteristicspopulation ageingquadrant analysisregional differences

Identifiers

PMID38699420
PMCPMC11063271

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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.