ArticleInternational journal of biometeorology2017
Socio-ecological factors and hand, foot and mouth disease in dry climate regions: a Bayesian spatial approach in Gansu, China.
Article in International journal of biometeorology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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.
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.
Who cites it
12 citing papers in PubMed.
- Bayesian spatiotemporal analysis for association of environmental factors with hand, foot, and mouth disease in Guangdong, China.Scientific reports · 2018Trial
- Transmission components of hand, foot, and mouth disease in Guangdong Province and their association with meteorological factors: a modelling study.BMC infectious diseases · 2025Article
- Spatiotemporal Distribution of Hand, Foot, and Mouth Disease and the Influence of Air Pollutants and Socioeconomic Factors on Incidence in Fujian, China.Tropical medicine and infectious disease · 2025Article
- The non-stationary and spatially varying associations between hand, foot and mouth disease and multiple environmental factors: A Bayesian spatiotemporal mapping model study.Infectious Disease Modelling · 2024Article
- Article
- Climate and human health: a review of publication trends in the International Journal of Biometeorology.International journal of biometeorology · 2023Review
- Prototypes virus of hand, foot and mouth disease infections and severe cases in Gansu, China: a spatial and temporal analysis.BMC infectious diseases · 2022Article
- Association between Meteorological Parameters and Hand, Foot and Mouth Disease in Mainland China: A Systematic Review and Meta-Analysis.Iranian journal of public health · 2021Review
- Using a Bayesian spatiotemporal model to identify the influencing factors and high-risk areas of hand, foot and mouth disease (HFMD) in Shenzhen.PLoS neglected tropical diseases · 2020Article
- Transmission center and driving factors of hand, foot, and mouth disease in China: A combined analysis.PLoS neglected tropical diseases · 2020Article
- How Socio-Environmental Factors Are Associated with Japanese Encephalitis in Shaanxi, China-A Bayesian Spatial Analysis.International journal of environmental research and public health · 2018Article
- Geographical variations and influential factors in prevalence of cardiometabolic diseases in South Korea.PloS one · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The influence of socio-ecological factors on hand, foot and mouth disease (HFMD) were explored in this study using Bayesian spatial modeling and spatial patterns identified in dry regions of Gansu, China. Notified HFMD cases and socio-ecological data were obtained from the China Information System for Disease Control and Prevention, Gansu Yearbook and Gansu Meteorological Bureau. A Bayesian spatial conditional autoregressive model was used to quantify the effects of socio-ecological factors on the HFMD and explore spatial patterns, with the consideration of its socio-ecological effects. Our non-spatial model suggests temperature (relative risk (RR) 1.15, 95 % CI 1.01-1.31), GDP per capita (RR 1.19, 95 % CI 1.01-1.39) and population density (RR 1.98, 95 % CI 1.19-3.17) to have a significant effect on HFMD transmission. However, after controlling for spatial random effects, only temperature (RR 1.25, 95 % CI 1.04-1.53) showed significant association with HFMD. The spatial model demonstrates temperature to play a major role in the transmission of HFMD in dry regions. Estimated residual variation after taking into account the socio-ecological variables indicated that high incidences of HFMD were mainly clustered in the northwest of Gansu. And, spatial structure showed a unique distribution after taking account of socio-ecological effects.
Indexed as
Identifiers
27329324What OpenQuestion holds
Registered trials
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.