The TCIs (tourism climate indices) are applications of the human comfort in climate health tourism. TCIs aim to characterize the climate and environmental status of tourist destinations and provide a comprehensive measure of tourists’ climatic well-being. In this study, the Web of Science and China National Knowledge Infrastructure (CNKI) databases were searched for visualization analysis, explained the connotation of the TCIs and human comfort index, summarized the historical evolution of TCIs and the human comfort index, and discussed the existing problems and countermeasures of TCIs researches. In order to provide theoretical support for the indepth research and sustainable development of TCIs in the future. The results are as follows: (1) The English studies were more concerned with tourism satisfaction and competitiveness, whereas the Chinese studies were more concerned with human comfort, climate comfort, and climate tourism. (2) Human comfort indices were primarily composed of meteorological factors and clothing insulation, which aims to reflect the human body's feeling of environmental comfort. The TCIs not only covers meteorological factors and aesthetic factors, but also considers health factors such as air quality and oxygen content, aiming to comprehensively evaluate the suitability of tourism activities and the effect of climate health of travelers.

Based on daily conventional observation data at 19 meteorological stations of Hainan Island from 1980 to 2018, the climatic season in Hainan Island was divided according to China’s meteorological industry standard (QX/T152-2012). Then, the comfortable degree of human body was calculated by using sensible temperature of human body based on ‘golden ratio’ method. And on this basis the comprehensive division of human body comfortable degree was done in each season in Hainan Island by using rotated empirical orthogonal function (REOF), further the optimum comfortable zones of climatotherapy rehabilitation were obtained in Hainan Island. The results are as follows: (1) The climate was mild and moist in Hainan Island, and the annual average temperature was 22.9 to 25.3 ℃, the average annual precipitation was 1157 to 2615 mm, the annual average relative humidity was 74% to 86%, and the annual average specific humidity was 14.8 to 16.4 g·kg^-1, which was suitable to rehabilitation. (2) Compared with the conventional climate statistical method, the meteorological industry standard was more in accordance with season division in Hainan Island. According to the climate division, the summer was from mid-March to mid-November in Hainan Island, the autumn and spring were from mid-November to next mid-March, which indicated that there wasn’t winter in Hainan Island, and the optimum period of climatotherapy rehabilitation appeared in spring and autumn. (3) The comfortable region of human body in spring and autumn located in northern Hainan, central Hainan and southern Hainan. Overall, the climate in central Hainan was the most optimal, and the climate in three regions was stable from 1980 to 2018.

The 36 458 cases of coronary heart disease (CHD) and cerebral infarction (CI) in Beijing from 2008 to 2012 were collected. Based on the fundamental impact of solarterrestrial relationship on temperature change between neighboring days (TCN), a year was divided into two periods dominated by opposite TCN period in this study. The results show that high morbidity of CHD generally occurred in periods from awakening of insects to grain rain, as well as from white dew to winter solstice, which accompanied by large TCN period. In contrast, low morbidities of both CHD and CI took place in the period from grain in ear to summer solstice, which accompanied by small TCN period. Stronger effects of positive TCN period were revealed on young and middleaged (less than and equal to 65 years old) CHD patients than that on the old group (more than 65 years old) by timeseries models, whose relative risk (RR) was up to 1.31. The elderly suffering from CHD were sensitive to negative TCN period, regardless of background temperature trends. Furthermore, in negative TCN period, positive TCN could elevate the highest CI risk for young individuals (less than 45 years old) immediately (RR was equal to 1.23). In conclusion, the shortterm effects of TCN on cardiovascular and cerebrovascular diseases were significant, and seasonal temperature trends modified TCNcardiovascular morbidity associations significantly.

Based on the daily meteorological observation data at 17 weather stations of China and NCEP reanalysis data along the migration route of Siberian Crane during 1959-2018, the variation ranges of main meteorological elements in habitats and resting places of Siberian Crane were analyzed. Combined with the meteorological observation data at 547 weather stations in mainland of China from 1961 to 2019, the human body comfort degrees were respectively calculated and classified in habitats of Siberian Crane and mainland of China by using the human body comfort index and classification standard based on ‘the Golden Section’, and the characteristics of inner climatotherapy life during the migration of Siberian Crane were probed. The results show that the temperature in habitats and stopover places of Siberian Crane was from 0 ℃ to 15 ℃, and the relative humidity, average wind velocity and atmospheric pressure changed from 60% to 80%, 2 to 3 m·s^-1 and 1005 hPa to 1018 hPa, respectively. In general, Siberian Crane aimed to the cool, humid, breezy and clear meteorological environment, they spent 90.83% time of a year living in cool, cooler or slightly cold zones. By migrating seasonally, they stayed away from extreme cold or heat to ensure longevity, which could provide better reference for the migratory-bird sojourn of elder people in China. The human body comfort degrees in mainland of China had obvious spatial difference and seasonal complementary characteristics. The climate in Northeast China, Northwest China and part areas of Southwest China was comfortable in summer, while in coastal areas of South China and Hainan it was comfortable in winter. The periods of generalized comfort level in major cities of China could be used as a reference for the migratory-bird sojourn of the elderly. In addition, the suitable stopover could buffer the significant change of meteorological environment between the origin and destination and make the body gradually to adapt the change during the travelling to escape the heat or cold, which would effectively reduce or avoid the travelling health risks due to the wide change of meteorological environment in short period.

The daily number of patients with upper respiratory tract infection (URI) in 49 community health service centers in Luohu of Shenzhen from 2014 to 2018 and meteorological data in the same period were collected to analyze the changing characteristics of the number of patients with URI at different time scales. The distributed lag non-linear model (DLNM) and generalized linear model (GLM) were used to study the relationship between different meteorological factors and the number of patients with URI in Shenzhen. The results show that there was a significant seasonal change for the number of patients with URI in Luohu of Shenzhen. The peak periods of cases were March to April in spring, July in summer and December to next January in winter, corresponding to Pure Brightness, Lesser Heat and Lesser Cold of the 24 solar terms, respectively. The DLNM model showed that air temperature was the main impact factor, and its effect on the number of patients with URI presented mainly cold effect, the relative risk (RR) reached the peak after 4 days lag (RR was equal to 1.041, the 95% confidence interval was between 1.022 and 1.060). Women were more affected by cold effect than men, and middle-aged and elderly people were more affected by cold effect than children. Another important factors were thermal effect in summer and the variable temperature in spring. The influence of humidity presented mainly low humidity effect, and the relative risk reached the peak (RR was equal to 1.058, the 95% confidence interval was between 1.049 and 1.068) on the same day. Pressure and wind speed showed high pressure effect and strong wind effect, and RR reached the highest after 1 day lag. In conclusion, cold air activities in winter and spring and their cold effects such as low temperature, low humidity and strong wind were the key factors to induce URI, followed by the impact of continuous high temperature in summer, both of them should be focused on timely prevention.