BackgroundThe aging of Chinese society has increased interest in improving the health-related quality of life (HRQoL) of the elderly, including their oral health-related quality of life (OHRQoL). This study aims to evaluate the OHRQoL of elders living in Sichuan Province (China) and to explore the explanatory factors of their OHRQoL.MethodsA cross-sectional study conducted in 2016 in the Sichuan Province analyzed data from 744 elders, aged 65 to 74 years (mean age 69.3, 51.3% female). Clinical examinations and questionnaires were completed to collect information on the participants’ socio-demographic characteristics, health-related behaviors, dental status, subjective health conditions and General Oral Health Assessment Index (GOHAI) score.ResultsThe mean GOHAI score was 48.23 (SD 7.62), and the median score was 49. After adjustment for age and gender, the multiple linear regression analysis showed that participants who were female, had fair or poor self-rated oral health, decayed, missing and filled teeth (DMFT) score ≥ 20, fair or poor self-rated general health, and ≥ 2 teeth with root caries had worse OHRQoL, and participants who were edentulous had better OHRQoL (F = 29.58, p < 0.001).ConclusionThe OHRQoL of the elders living in Sichuan Province was relatively good. The explanatory variables were gender; self-rated oral health; DMFT score; self-rated general health; number of natural teeth; and number of teeth with root caries. More attention should be paid to caries status and retention of healthy teeth to improve the OHRQoL of elders in Sichuan Province, preserving a healthy mouth contributes to better OHRQoL.

To explore the future development state of urban and rural settlements, we combined random forest algorithm (RFA) and cellular automata (CA) to simulate high precision in urban and rural settlements in Aksu city. The settlement distribution was predicted for the next 10 years, and suggestions for urban and rural settlements were proposed based on a “production–life–ecology” space. The results show the following: Transportation factors and administrative location have an important influence on the development of settlements, and infrastructure has a greater impact on the development of settlements. The overall accuracy of the 2019 settlement distribution obtained through the RFA–CA model simulation is 93.8%, with a G-mean coefficient of 0.815. The simulation accuracy is better and more suitable for the simulation and prediction of settlement expansion than the logistic-CA model. The forecasted settlement expansion in 2029 for Aksu city is 58.36 km2 of settlement expansion compared to the 2019 settlement distribution, with an overall growth trend for sparse north-south and dense central areas. This study analyzed the causes of settlement expansion in 19 regions of Aksu city, explored the main function of “production–life–ecology” space in different areas, and proposed layout optimizations from the perspective of production, life, and ecology. The results of this study can provide a reference for the spatial planning and rural revitalization strategy of Aksu city.

Hand, foot, and mouth disease (HFMD) remains a serious health threat to young children. Urumqi is one of the most severely affected cities in northwestern China. This study aims to identify the spatiotemporal distribution characteristics of HFMD, and explore the relationships between driving factors and HFMD in Urumqi, Xinjiang. Methods: HFMD surveillance data from 2014 to 2018 were obtained from the China Center for Disease Control and Prevention. The center of gravity and geographical detector model were used to analyze the spatiotemporal distribution characteristics of HFMD and identify the association between these characteristics and socioeconomic and meteorological factors. Results: A total of 10,725 HFMD cases were reported in Urumqi during the study period. Spatially, the morbidity number of HFMD differed regionally and the density was higher in urban districts than in rural districts. Overall, the development of HFMD in Urumqi expanded toward the southeast. Temporally, we observed that the risk of HFMD peaked from June to July. Furthermore, socioeconomic and meteorological factors, including population density, road density, GDP, temperature and precipitation were significantly associated with the occurrence of HFMD. Conclusions: HFMD cases occurred in spatiotemporal clusters. Our findings showed strong associations between HFMD and socioeconomic and meteorological factors. We comprehensively considered the spatiotemporal distribution characteristics and influencing factors of HFMD, and proposed some intervention strategies that may assist in predicting the morbidity number of HFMD.

Background: As the global climate changes, the number of cases of hand-foot-and-mouth disease (HFMD) is increasing year by year. This study comprehensively considers the association of time and space by analyzing the temporal and spatial distribution changes of HFMD in the Ili River Valley in terms of what climate factors could affect HFMD and in what way. Methods: HFMD cases were obtained from the National Public Health Science Data Center from 2013 to 2018. Monthly climate data, including average temperature (MAT), average relative humidity (MARH), average wind speed (MAWS), cumulative precipitation (MCP), and average air pressure (MAAP), were obtained from the National Meteorological Information Center. The temporal and spatial distribution characteristics of HFMD from 2013 to 2018 were obtained using kernel density estimation (KDE) and spatiotemporal scan statistics. A regression model of the incidence of HFMD and climate factors was established based on a geographically and temporally weighted regression (GTWR) model and a generalized additive model (GAM). Results: The KDE results show that the highest density was from north to south of the central region, gradually spreading to the whole region throughout the study period. Spatiotemporal cluster analysis revealed that clusters were distributed along the Ili and Gongnaisi river basins. The fitted curves of MAT and MARH were an inverted V-shape from February to August, and the fitted curves of MAAP and MAWS showed a U-shaped change and negative correlation from February to May. Among the individual climate factors, MCP coefficient values varied the most while MAWS values varied less from place to place. There was a partial similarity in the spatial distribution of coefficients for MARH and MAT, as evidenced by a significant degree of fit performance in the whole region. MCP showed a significant positive correlation in the range of 15–35 mm, and MAAP showed a positive correlation in the range of 925–945 hPa. HFMD incidence increased with MAT in the range of 15–23 °C, and the effective value of MAWS was in the range of 1.3–1.7 m/s, which was positively correlated with incidences of HFMD. Conclusions: HFMD incidence and climate factors were found to be spatiotemporally associated, and climate factors are mostly non-linearly associated with HFMD incidence.

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