OBJECTIVETo discuss the relationship between the onset of peptic ulcers (PU) and meteorological factors (MF).

METHODSIn reviewing records from 17 hospitals in the city of Nanning from 1992 to 1997, we found 24, 252 cases of PU in 104, 121 samples of gastroscopic examinations. We then calculated the detectable rate of PU (DRPU) during each season every five days (FD) and made a correlated analysis with the seasonal MF during the same period in Nanning. Finally, we made a multiple regressive correlated analysis of DRPU and the 5MF for the same period of the year. A forecast model based on the MF of the previous FD was established. The real value and the forecast value was being tested and verified.

RESULTSFrom 1992 to 1997, the DRPU is: winter and spring > summer and autumn (P < 0.005). There is a close relationship between the DRPU and the average temperature (AT), the average highest temperature (AHT), the average lowest temperature (ALT), average air pressure (AAP) and the average dew point temperature (ADT) of the five days of the same period of the year (the correlated coefficients are -0.5348, -05167, -0.5384, 0.4579 and -0.4936, respectively), with P < 0.01. The AT, AHT, ALT, AAP and ADT of the previous FD are of great value in forecasting the onset of PU, with its real value and forecast value corresponding to 66.6%.

CONCLUSIONSThere exists a close relationship between DRPU and the AT, AHT, ALT, AAP and ADT of the FD for the same period. A mid-term medical meteorological forecast of the onset of PU can be made more accurately and reliably according to the close relation between the DRPU and some MF of the previous FD.

Forecasting ; Humans ; Meteorological Concepts ; Peptic Ulcer ; epidemiology ; Pressure ; Seasons ; Temperature

BACKGROUND: Spontaneous pneumothorax is a common respiratory condition and has been postulated that it develops because of rupture of subpleural blebs. Although the morphology and ultrastructure of causative lesions are well known, the reason for rupture of sbupleural blebs is not absolutely clear. Broad consensus concerning the role of meteorological factors in spontaneous pneumothorax dose not exist. The aim of the study was to examine the influence of change of atmospheric pressure and temperature on the occurrence of spontaneous pneumothorax. MATERIAL AND METHOD: One hundred twenty eight consecutive spontaneous pnemothorax events that occurred between January 2003 and December 2004 were selected. Changes of meteorological factors of particular days from the day before for 5 consecutive days were calculated and compared between the days with pneumothorax occurrence (SP days) and the days without pneumothorax occurrence (Non SP days). The correation between change of pressure and temperature and the occurrence of SP was evaluated. RESULT: SP occurred on 117 days (16.0%) in the 2-year period. Although there was no significant differences in change of pressure factors prior 4 days of SP occurrence compare to the 4 days prior Non SP day, change of mean pressure was higher (+0.934 vs. -0.191hPa, RR 1.042, CI 1.003~1.082, p=0.033), and change of maximum pressure fall was lower (3.280 vs. 4.791 hPa, RR 1.051, CI 1.013~1.090, p=0.009) on the 4 days prior SP day. There were significant differences in change of temperature factors prior 2 days and the day of SP, Changes of mean temperature (-0.576 vs.+0.099 degrees C, RR 0.886, 95% CI 0.817~0.962, p=0.004) and maximum temperature rise (7.231 vs. 8.079 degrees C, RR 0.943 CI 0.896~0.993, p=0.027) were lower on the 2 days prior SP. But changes of mean temperature (0.533 vs. -0.103 degrees C, RR 1.141, CI 1.038~1.255, p=0.006) and maximum temperature rise (9.209 vs. 7.754 degrees C, RR 1.123, CI 1.061~1.190, p=0.000) were higher on the SP days. CONCLUSION: Change of atmospheric pressure and temperature seems to influence the chance of occurrence of SP. Meteorological phenomena that pressure rise 4 day prior to SP and following temperature fall and rise might explain the occurrence of SP. Further studies should be continued in the future.
Atmospheric Pressure* ; Blister ; Consensus ; Meteorological Concepts ; Pneumothorax* ; Rupture

PURPOSE: The aim of this study was to determine the relationships between weather and calendar variables and the admission volume at the emergency center in Daejon city. PATIENTS AND METHODS: Daily patient volume from January to November 2003 was matched with calendar and weather variables. Calendar variables included season, day of the week, holidays, and the day after a holiday. Weather variables included daily maximum, minimum, and average temperatures and other factors such as snowfall and rainfall. RESULTS: The average daily admission volume was 282 +/- 54 persons (187~605), and the most highly significant calendar and weather variables related with admission volume were holidays and maximal temperature, respectively. A regression model was calculated as follows: the daily patient volume = 214 + 2 x (maximal temperature) + 113 x (holiday) + 26.8 x (day after a holiday). This equation could estimate about 62.6% of the daily patient volumes. CONCLUSION: This study suggests that the temperature and a holiday may influence the number of visiting patients. Thus, the staffing level should be set appropriately by considering the estimated patient volume.
Daejeon ; Emergencies* ; Holidays ; Humans ; Meteorological Concepts ; Patient Admission ; Seasons ; Weather

OBJECTIVEIn order to provide reliable data for strategies development on prevention, a meteorological factors-based predicating model for malaria forecast was studied.

METHODSData on malaria occurrence and climate changes from 1994 to 1999 in counties in Yunnan province was collected and analyzed with software packages of FoxPro 6.0 and Excel 5.0. The forecasting model for malaria occurrence was established, using the Neural Network Toolbox of Matlab 6.1 software package. In the studies of forecasting model, data of malaria and meteorological factors from 1994 to 1999 in Honghe state in Yunnan province was chosen. The meteorological factors included average monthly pressure, air temperature, relative humidity, monthly maximum air temperature, minimum air temperature, rainfall, rainday, evaporation and sunshine hours in the study. The established forecasting model was also tested and verified.

RESULTSThe BP network model was established according to data of diseases and meteorological factors from Honghe state in Yunnan province. After training the neural network for 100 times, the error of performance decreased from 3.23608 to 0.035862. Verified by fact data of malaria, the efficiency of malaria forecasting was 84.85%.

CONCLUSIONNeural network model was effective for forecasting malaria. It showed advantages as: strong ability for analysis, lower claim for data, convenient and easy to apply etc. Neural network model might be used as a new method for malaria forecasting.

Humans ; Malaria ; etiology ; Meteorological Concepts ; Neural Networks (Computer)

BACKGROUND: The cases of Plasmodium vivax malaria in Korea are mixed with long and short incubation periods. This study aims to define clinico-epidemiologic chracteristcs of Plasmodium vivax malaria in Korea. MATERIALS AND METHODS: We selected the civilian cases infected with P. vivax malaria in Korea from the epidemiological investigation data of 2001 to 2010, whose incubation periods could be estimated. The long and short incubation periods were defined by duration of infection and onset time, and the cases were compared by demographic factors and clinical symptom, infection and onset time. The correlation was analyzed between the proportion of cases in the infected region with the long incubation period and meteorological factors along with latitude. RESULTS: The length of the mean short and long incubation periods for the cases were 25.5 days and 329.4 days, respectively. The total number of the study subjects was 897, and the number cases of short and long incubation periods was 575 (64.1%) and 322 (35.9%), respectively. The aspect of incubation period showed a significant difference by region of infection; there was a higher proportion of long incubation period infection cases in Gangwon-do than in Gyeonggi-do and Incheon. The proportion of long incubation period cases showed significant correlation with latitude and temperature of August and September of the infected regions. CONCLUSIONS: Incubation period of P. vivax malaria in Korea showed significant difference by infected region, infection and onset time and the proportion of long incubation period cases showed significant correlation with latitude and meteorological factors of the infected regions.
Demography ; Korea ; Malaria ; Malaria, Vivax ; Meteorological Concepts ; Plasmodium ; Plasmodium vivax

With the growth of disease incidence in allergic diseases of upper respiratory tract year by year, airborne pollen has been considered the most important cause of the diseases. There is an obvious positive correlation between the concentration of airborne pollen and the symptoms of the diseases. The data is collected which includes environment that patient lives in about the kinds of airborne pollen and their seasonal distribution and latest conditions of the airborne pollen at home and abroad. It is benefit for the further developments of the researches of airborne pollen and has a clinical significance for the prevention, diagnosis and treatments of allergic diseases in our country.
Allergens ; immunology ; Meteorological Concepts ; Particulate Matter ; immunology ; Pollen ; immunology ; Seasons

Humans ; Mississippi/epidemiology* ; Influenza, Human/epidemiology* ; Meteorological Concepts ; Virus Diseases

Objective: To understand the influence of meteorological factors on the morbidity of influenza in northern cities of China and explore the differences in the influence of meteorological factors on the morbidity of influenza in 15 cities. Methods: The monthly reported morbidity of influenza and monthly meteorological data from 2008 to 2020 were collected in 15 provincial capital cities, including Xi 'an, Lanzhou, Xining, Yinchuan and Urumqi (5 northwestern cities), Beijing, Tianjin, Shijiazhuang, Taiyuan, Hohhot, Ji'nan, Zhengzhou (7 northern cities), Shenyang, Changchun and Harbin (3 northeastern cities). The panel data regression model was applied to conduct quantitative analyze on the influence of meteorological factors on influenza morbidity. Results: The univariate and multivariate panel regression analysis showed that after controlling the population density and other meteorological factors, for each 5 ℃ drop of monthly average temperature, the morbidity change percentage (MCP) of influenza was 11.35%, 34.04% and 25.04% in the 3 northeastern cities, 7 northern cities and 5 northwestern cities, respectively, and the best lag period months was 1, 0 and 1 month; When the monthly average relative humidity decreased by 10%, the MCP was 15.84% in 3 cities in northeastern China and 14.80% in 7 cities in northern China respectively, and the best lag period months was 2 and 1 months respectively; The MCP of 5 cities in northwestern China was 4.50% for each 10 mm reduction of monthly accumulated precipitation, and the best lag period months was 1 month; The MCPs of 3 cities in northeastern China and 5 cities in northwestern China were 4.19% and 5.97% respectively when the accumulated sunshine duration of each month decreased by 10 hours, the best lag period months was 1 month. Conclusions: In northern cities of China from 2008 to 2020, the temperature, relative humidity, precipitation and sunshine duration all had negatively impact on the morbidity of influenza, and temperature and relative humidity were the main sensitive meteorological factors. Temperature had a strong direct impact on the morbidity of influenza in 7 cities in northern China, and relative humidity had a strong lag effect on the morbidity of influenza in 3 cities in northeastern China. The duration of sunshine in 5 cities in northwestern China had a greater impact on the morbidity of influenza compared with 3 cities in northeastern China.
Humans ; Cities ; Influenza, Human ; China ; Beijing ; Meteorological Concepts

China ; epidemiology ; Disease Outbreaks ; Female ; Humans ; Incidence ; Male ; Measles ; epidemiology ; Meteorological Concepts ; Seasons

OBJECTIVETo evaluate the associations between malaria risk and meteorological factors.

METHODSA negative binomial distribution regression analysis was built between the temperature, relative humidity, rainfall capacity and the monthly incidence of malaria, based on the temperature information provided by Guangdong Meteorological Department and the malaria incidence information provided by Guangdong Center of Disease Prevention and Control during year 1980 to 2004, adopting the time-series analysis method and by distributed lag non-linear model, in order to analyze the immediate factors.

RESULTSThe number of monthly malaria cases in Guangdong province reached 4010 between year 1984 and 2004, while the monthly maximal temperature, minimal temperature, average temperature, relative humidity and average rainfall capacity was separately 26.3°C, 18.8°C, 21.9°C, 88.0% and 5.6 mm. The immediate effect of monthly maximal temperature on malaria incidence showed non-linear relationships. When the temperature reached 32.3°C, the risk was highest, the relative risk (RR) was 2.51 (95%CI: 1.99 - 3.16); when the relative humidity was 60.0%, the relative risk of malaria was highest as 1.19 (95%CI: 0.66 - 2.11) and then decreased gradually; and when the relative humidity was 86.6%, the risk of malaria was lowest at 0.51 (95%CI: 0.34 - 0.76). The risk of malaria increased while the rainfall capacity was 14.5 mm, the risk of malaria was the highest at 1.29 (95%CI: 0.87 - 1.93). Strongest delayed effects on malaria incidence was observed when the monthly maximal temperature reached 31.5°C at lagged 2 months, with the value of RR at 1.81 (95%CI: 1.02 - 3.22). When the monthly rainfall capacity was over 15.2 mm, the delayed effects was strong but short. When the monthly maximal temperature of 33.7°C, the excess risk of malaria was comparatively high, the excess risk was 92.2% (95%CI: 30.5% - 183.2%) when lagging one month. When the relative humidity was low, the delayed effect of malaria lasted for a long time, and the cumulative effect was huge. When the relative humidity reached 87.0%, the excess risk lagging 3 months was only -66.6% (95%CI: -86.4% - -17.7%). When the rainfall capacity was 15.5 mm, the cumulative effect on malaria reached the peak after 3 months, while the excess risk was 40.7% (95%CI: -30.0% - -182.6%); afterwards the cumulative effect gradually weakened. Positive and negative interaction effects were significant between malaria risk and maximal temperature and monthly rainfall capacity, and monthly rainfall capacity and relative humidity at lagged 2 months, respectively.

CONCLUSIONHigh temperature and large rainfall capacity might be the risk factors of malaria in Guangdong province, and there was an obvious interaction between the two factors.

China ; epidemiology ; Climate ; Humans ; Incidence ; Malaria ; epidemiology ; Meteorological Concepts ; Models, Statistical ; Time Factors