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Background Affected by concentration, composition, and population tolerance of air pollutants, the relationship between air pollutants and population health has regional differences. There is still a research gap in Guiyang. Objective To explore the short-term effects of air pollutant concentrations in low-pollution areas on the outpatient volume of respiratory diseases. Methods Spearman correlation analysis was used to evaluate the correlation between air pollutants, meteorological factors, and respiratory outpatient volume from January 1, 2013 to December 31, 2020 in Guiyang City. A single pollutant distribution lag nonlinear model and a multi-pollutant interaction model were established based on Poisson distribution. A three-dimensional diagram was drawn to display the relationship between air pollutants and respiratory outpatient volume. Quantitative analysis was conducted on the attribution risk and lag effect of air pollutant concentration on outpatient volume of respiratory diseases in Guiyang City. Results The results of the single pollutant model showed that fine particulate matter (PM2.5), nitrogen dioxide (NO2), carbon monoxide (CO), and sulfur dioxide (SO2) elevated the outpatient volume of respiratory diseases. The maximum relative risk (RR) and 95%CI values of PM2.5, NO2,CO, and SO2 appeared on Day 2, 0, 5, and 6, respectively, which were 1.019 (1.015, 1.023), 1.146 (1.122, 1.171), 1.129 (1.116, 1.143), and 1.046(1.040, 1.052), respectively. For every quartile concentration increment of PM2.5, NO2, CO, or SO2, the outpatient volume of respiratory diseases increased by 0.943% (0.111%, 1.782%), 4.050% (3.573%, 4.529%), 0.595% (0.317%, 0.874%), or 0.667% (0.235%, 1.100%), respectively. The maximum RR (95%CI) of O3 was 1.015 (1.007, 1.023) and appeared on Day 0. The results of multi-pollutant model showed that PM2.5, NO2, CO, SO2, and O3 all elevated the outpatient volume of respiratory diseases. The maximum RR values of PM2.5, NO2, CO, SO2 and O3 appeared on Day 14, 0, 5, 7 and 0, respectively, which were 1.027 (1.021, 1.034), 1.213 (1.179, 1.248), 1.059 (1.043, 1.074), 1.016 (1.005, 1.026), and 1.024 (1.015, 1.033), respectively. Compared with the single pollutant model, the RR values of PM2.5, NO2, and O3 on the outpatient volume of respiratory diseases in the multi-pollutant model showed an upward trend, while the RR values of CO and SO2 in the multi-pollutant model showed a downward trend. Conclusion The impact of low concentrations of PM2.5, NO2, CO, and SO2 on human health cannot be ignored.
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Objective To analyze the relationship between diurnal temperature range (DTR) and the hospitalization of stroke in Lanzhou,so as to provide a scientific basis for probing into the mechanism of temperature changes in inducing stroke and formulating comprehensive prevention and control measures for stroke by relevant departments.Methods The information of the patients hospitalized due to stroke in Lanzhou during January 2014 to December 2019 and the air pollutants (PM10,SO2,and NO2) and meteorological data in the same period were collected for statistical analysis.Spearman rank correlation analysis was performed to analyze the correlations between air pollutants and meteorological factors.The distributed lag nonlinear model was adopted to fit the relationship between DTR and the number of stroke inpatients,and three-dimensional diagrams and the correlation diagrams of DTR against stroke risk were established.The stratified analysis was performed according to gender and age (< 65 years and ≥65 years).Results From 2014 to 2019,a total of 92 812 stroke patients were hospitalized in Lanzhou,with a male-to-female ratio of 1.35:1.There was a nonlinear relationship between DTR and the number of stroke inpatients in Lanzhou,which presented a lag effect.The low DTR at 4.5 ℃ had the largest RR value of 1.25 (95%CI=1.16-1.35) for stroke inpatients at a cumulative lag of 18 d.The effect of high DTR (18.5 ℃) on the hospitalization of stroke patients peaked at a cumulative lag of 21 d,with an RR value of 1.09 (95%CI=1.01-1.18).The stratified analysis results suggested that low levels of DTR had greater effects on the hospitalization of male stroke patients and stroke patients <65 years.Conclusions Short-term exposure to different levels of DTR had an impact on the number of stroke inpatients,and low levels of DTR had a slightly greater impact on stroke inpatients than high levels of DTR.Importance should be attached to the protection of males and people aged <65 years at low levels of DTR.
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Humans , Male , Female , Temperature , Stroke , Cold Temperature , Hot Temperature , Air Pollutants , China/epidemiologyABSTRACT
Objective To explore the effect of temperature on the risk of hand-foot-and-mouth disease (HFMD) and population susceptibility. Methods The data of HFMD cases in Chengdu from January 1, 2016 to October 31, 2022 were collected, and local meteorological data during the same period were also collected. Distributional lag nonlinear models were developed. The relative risk (RR) of morbidity at different temperatures and different lags was calculated. Differences in the relative risk levels of different populations were analyzed and compared. Results A total of 263 776 cases of HFDM were reported in Chengdu during the study period. The distribution of HFMD was periodic. For the overall population, the short-term average temperature and RR showed a “U”-shaped relationship. When the lag time was 0-7 days, the cumulative RR was 1.59 (95%CI: 1.18-2.14) at the average temperature of -0.5℃ and 2.16 (95%CI: 1.60-2.91) at the average temperature of 34.5℃. The RR values under high and low temperatures decreased with increasing lag period. When the lag time was extended, the average temperature and RR showed an inverted “U”-shaped relationship, with higher RR at moderate temperatures and increasing as the lag period increased. The results of the subgroups showed that the RR of onset among scattered children was higher at high and low temperatures. Conclusion The risk effect of temperature on the onset of HFMD in different populations is variable and changes with the lag period, and the prevention and control measures should be adjusted in a timely and targeted manner.
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Objective To investigate the effect of diurnal temperature difference on hospitalization volume of patients with cardiovascular and cerebrovascular diseases in Urumqi City. Methods The daily hospitalization data for cardiovascular and cerebrovascular diseases in Urumqi City from 2019-2021, and meteorological and pollutant data for the same period were collected. The relationship between diurnal temperature range and hospitalizations for cardiovascular and cerebrovascular diseases was analyzed using a distribution lag non-linear model (DLNM), controlling for the long-term trends, the day-of-week effects and other factors. Results The greater the diurnal temperature range, the longer the lag time, and the higher the risk of hospitalization for cardiovascular and cerebrovascular diseases. The lag effect increased significantly when the maximum diurnal temperature range reached 21.0°C. The risk effect appeared on the day of exposure and lasted until day 20, with a maximum RR of 1.266 (95% CI: 1.129-1.421) at a lag of 13 days. At very high diurnal temperature range, the risk of hospitalization for cardiovascular and cerebrovascular diseases was higher in the cold season than that in the warm season. Results after stratified analysis by sex and age showed that men and people aged ≥65 years were more susceptible to diurnal temperature range. Conclusion Extremely high diurnal temperature range is a potential trigger for hospitalization for cardiovascular and cerebrovascular diseases in Urumqi. Men and people aged ≥65 years are more vulnerable to the impact of diurnal temperature range. In the cold season, more attention should be paid to protecting vulnerable people from the impact of the extremely high diurnal temperature difference.
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Objective:To investigate the correlation between atmospheric particulate matter 2.5 (PM 2.5) concentration and the number of chronic kidney disease (CKD) hospital admissions in the elderly in Taiyuan city. Methods:The atmospheric PM 2.5 concentration in Taiyuan city during 2019—2021 was used as the environmental exposure data, and the number of CKD admission of the elderly patients (> 60 years old) in Taiyuan city at the same time was used as the disease progression index. The distributed lag nonlinear model was used to analyze overall and lag effects of PM 2.5 average daily concentration on the elderly patients admitted to CKD. Results:A total of 6 037 cases elderly patients with CKD admitted to hospital were included, with a male-to-female ratio of 1.36∶1. The average daily concentration of PM 2.5 was 52.80 μg/m 3, which did not exceed China's air quality standard (75 μg/m3); But in autumn and winter, the average daily concentration of PM 2.5 significantly exceeded the normal reference value, with the highest value reaching 302 μg/m 3. The relationship between the average daily concentration of PM 2.5 and the number of elderly patients admitted to CKD was nonlinear and there was a lag effect. The relative risk ( RR) value reached the maximum when PM 2.5 average daily concentration was 87 μg/m 3 with lag time of 11 days [1.074(95% CI 1.018-1.321)]. The subgroup analysis results showed that the risk of admission of elderly female CKD patients was higher than that of male patients with lag time of 10 days, and the RR was 1.073(95% CI 1.001-1.151). Elderly CKD patients with hypertension (PM 2.5 87 μg/m 3) and diabetes (PM 2.5 88 μg/m 3) had a higher risk of admission when exposed to PM 2.5, with maximum RR values of 1.067(95% CI 1.002-1.136) and 1.162(95% CI 1.021-1.320), respectively. Conclusions:High atmospheric PM 2.5 concentration in Taiyuan city can increase the risk of admission in elderly patients with CKD, especially in women and patients with hypertension or diabetes.
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Background In the context of global warming, the impact of meteorological factors on human health has gradually become a research hotspot at home and abroad. Objective To describe the distribution of children's bronchopneumonia in Huzhou City, and explore the influence of diurnal temperature range (DTR) on children with bronchopneumonia, so as to provide guidance for identifying vulnerable populations and developing targeted measures. Methods A distributed lag nonlinear model (DLNM) was used to explore the potential nonlinear lag effect of DTR on admission of children with bronchopneumonia in Huzhou City from 2014 to 2019. Then a generalized additive model (GAM) was used to calculate the hospital admission risk of exposure to DTR in total population and sex-, age-, season-stratified populations. Results A total of 17658 hospitalized children with bronchopneumonia were included in the study. When DTR exceeded 7.5 ℃, the relative risk rose abruptly. When DTR reached 17 ℃, the risk of admission to hospital of children with bronchopneumonia was the greatest. In terms of the single-day lag effect, the admission risk of DTR for bronchopneumonia in children began on the same day and persisted until lag day 2; it peaked on the same day, and RR was 1.353 (95%CI: 1.220-1.502). The cumulative lag effect occurred from lag0 to lag0-6, and the highest RR value was at lag0-3, which was 1.938 (95%CI:1.483-2.533). The results of stratified analysis showed that the maximum effect values for boys and girls appeared at lag0-3 (RRboys=2.301, 95%CI: 1.671-3.169) and lag0-2(RRgirls=1.566, 95%CI: 1.152-2.129) respectively, and the effect value and duration of DTR in boys were higher and longer than those in girls. Among different age groups, both children of 0-3 years old and 4-14 years old had the maximum effect value at lag 0-3, the RR values were 1.734 (95%CI: 1.454-2.572) and 1.998 (95%CI: 1.226-2.254) respectively, and the effect value and duration of DTR on the children of 4-14 years old were higher and longer than those of the children of 0-3 years old. As to seasons, no significant increase was found in cumulative effect in summer and autumn (P>0.05); in winter and spring, the maximum effect value appeared at lag0-10, and the RR value was 4.164 (95%CI:1.191-14.561). Conclusion The impact of DTR on bronchopneumonia in children is acute. Boys and children aged 4-14 years old are more sensitive to DTR changes. Therefore, we should be alert to severe DTR changes and take protective measures in advance
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Objective To investigate the modification effect of atmospheric temperature on outpatient visits caused by O3 in Linzhi City. Methods The daily outpatient data, the daily O3 concentration and daily meteorological data (including daily average temperature, average relative humidity, etc.) in Linzhi City from 2018 to 2019 were collected. The distributed lag non-liner-model (DLNM) was used to quantitatively evaluate the impact of O3 in different temperature layers on the risk of outpatient visits. Results At low temperature layers, the cumulative relative risk (CRR) of total outpatient visits and non-injury outpatient visits increased by 53.8%（4.2% -126.9%) and 59.1%（5.8% -139.2%）for every 10 μg/m3 increase of O3 concentration, respectively. The subgroup analysis showed that for every 10 μg/m3 increase of O3 concentration at low temperature, the CRR of patients with circulatory diseases, men, women, and people being 3 in Linzhi City. In general, the cumulative risk increases as the temperature decreases.
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Objective To determine the relationship between air pollutants [SO
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Female , Humans , Male , Acne Vulgaris , Air Pollution/adverse effects , China/epidemiology , Environmental Pollutants , Gases , OutpatientsABSTRACT
Objective To investigate the effect of meteorological factors on the number of outpatients with pulmonary heart disease in Liangzhou district of Gansu province. Methods We collected the daily meteorological data (temperature, air pressure, precipitation, sunshine hours, etc.) of Liangzhou district of Gansu province and the number of daily outpatients with the pulmonary heart disease from 2014 to 2016, and used the distribution lag model to analyze the impact relationship and hysteresis effect of the meteorological factors on the number of outpatients to pulmonary heart disease clinics. Results The total number of outpatients with pulmonary heart disease was 20 462 in Liangzhou district from 2014 to 2016, and the average number of outpatients per day was 18.67. The number of outpatients with pulmonary heart disease per day was positively correlated with temperature and sunshine hours, and negatively correlated with air pressure, relative humidity and precipitation. Among them, the average daily temperature had the most significant effect on the number of outpatients with pulmonary heart disease (r=0.133, P<0.001). At the highest daily average temperature, lagging 16 days,the relative risk coefficient (RR value) was the highest (1.26, 95% CI:1.13-1.40). For every 1 ℃ increase in temperature, the number of outpatients with pulmonary heart disease increased by 1.26 (95% CI: 1.13-1.40). There was no risk of morbidity at an extreme low temperature (-18 ℃), and the relative risk of the number of the pulmonary heart disease outpatients was the greatest at lag 0-15 at an extreme high temperatures (29 ℃). Conclusion Meteorological factor is an important factor affecting the number of outpatients with pulmonary heart disease in Liangzhou district. The risk of pulmonary heart disease will increase due to temperature changes, and the impact will occur immediately on the same day. The high temperature effect is short-lived and the relative risk is high, while the relative risk of low temperature to the number of outpatients is relatively low and the lag time is long.
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Objective To evaluate the effect of high air temperature on diabetes mortality in six cities in China.Methods Daily diabetes mortality and meteorological data were collected from January 1,2008 to December 31,2013 in Beijing,Tianjin,Shanghai,Chongqing,Guangzhou,and Shenyang.Distributed lag nonlinear model was used to evaluate the association between high air temperature and diabetes mortality after controlling for the long-term trend and the effect of "day of week".Results The effect of high air temperature on diabetes mortality varied in different cities,the maximum cumulative relative risk of Beijing,Tianjin,Shanghai,Chongqing,Guangzhou and Shenyang were 1.37 (lag 2 days),1.32 (lag 0 days),1.40 (lag 0 days),1.26 (lag 2 days),1.48 (lag 2 days) and 1.67 (lag 3 days).The daily diabetes death numbers were similar in men and women,but the death number in women were slightly higher than that in men,no gender specific characteristics were found.The death number was highest in age group 65-84 years,accounting for ＞60％ of the total deaths,the difference was significant.Conclusion The mortality of diabetes increased obviously in the context of high air temperature environment.
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Objective To evaluate the effect of high air temperature on diabetes mortality in six cities in China.Methods Daily diabetes mortality and meteorological data were collected from January 1,2008 to December 31,2013 in Beijing,Tianjin,Shanghai,Chongqing,Guangzhou,and Shenyang.Distributed lag nonlinear model was used to evaluate the association between high air temperature and diabetes mortality after controlling for the long-term trend and the effect of "day of week".Results The effect of high air temperature on diabetes mortality varied in different cities,the maximum cumulative relative risk of Beijing,Tianjin,Shanghai,Chongqing,Guangzhou and Shenyang were 1.37 (lag 2 days),1.32 (lag 0 days),1.40 (lag 0 days),1.26 (lag 2 days),1.48 (lag 2 days) and 1.67 (lag 3 days).The daily diabetes death numbers were similar in men and women,but the death number in women were slightly higher than that in men,no gender specific characteristics were found.The death number was highest in age group 65-84 years,accounting for ＞60％ of the total deaths,the difference was significant.Conclusion The mortality of diabetes increased obviously in the context of high air temperature environment.
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Objective@#To explore the effects of temperature on the daily cases of varicella.@*Methods@#The data of daily cases of varicella was collected during 2008 to 2016 in Lanzhou from National Notifiable Disease Report System, and the meteorological data at the same period was integrated from Gansu Meteorological Administration. Distributed lag nonlinear model was fitted to reveal the relationship between the daily mean temperature and the daily cases of varicella and susceptible population. The minimum morbidity temperature was defined as the reference for the estimation of RRs in different temperature level (-5.2 ℃, 1.7 ℃, 20.1 ℃ and 25.4 ℃).@*Results@#The total of 21 254 cases were reported from 2008 to 2016, of which the ratio of male to female was 1.28 (11 951/9 303) and people aged 6-14 years accounted for 52.87%. The relationship between the daily mean temperature and the daily cases of varicella was M type. For all subjects, the accumulative effects of temperature had statistical significance from lag 0-14 d when temperatures was at -5.2 ℃, 1.7 ℃ and 20.1 ℃,while the RRs (95%CI) were 1.87 (1.64-2.12) , 1.33 (1.10-1.62) ,1.60 (1.38-1.86) ,while from lag 0-7 d when temperatures was at 25.4 ℃,and the RR (95%CI) was 2.51 (1.93-3.27) . The RR value of accumulative effects was 6.23(95%CI: 4.38-8.86) on lag 7 d when temperatures was at -5.2 ℃, which was the highest value at different temperature during lag days. The cumulative effects trends of different temperatures were similar for different gender population or different age subjects. However, the cumulative effects of was highest for children aged 6-14 years among all subjects, and the value of RR was 6.12 (95%CI:3.71-10.10) on lag 5d when temperatures was at -5.2 ℃.@*Conclusion@#We conclude that the increasing risk of varicella is associative with low and high temperature in Lanzhou. The effects of low temperature are stronger than those of high temperature. The children aged 6-14 years belong to the high-risk population of varicella.
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Objective To investigate the effect of humidex combined with mean temperature and relative humidity on the incidence of bacillary dysentery in Hefei. Methods Daily counts of bacillary dysentery cases and weather data in Hefei were collected from January 1, 2006 to December 31, 2013. Then, the humidex was calculated from temperature and relative humidity. A Poisson generalized linear regression combined with distributed lag non-linear model was applied to analyze the relationship between humidex and the incidence of bacillary dysentery, after adjusting for long-term and seasonal trends, day of week and other weather confounders. Stratified analyses by gender, age and address were also conducted. Results The risk of bacillary dysentery increased with the rise of humidex. The adverse effect of high humidex (90 percentile of humidex) appeared in 2- days lag and it was the largest at 4-days lag (RR=1.063, 95%CI:1.037-1.090). Subgroup analyses indicated that all groups were affected by high humidex at lag 2-5 days. Conclusion High humidex could significantly increase the risk of bacillary dysentery, and the lagged effects were observed.
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Objective To assess the acute effects of daily mean temperature,cold spells,and heat waves on stroke mortality in 12 counties across Hubei province,China.Methods Data related to daily mortality from stroke and meteorology in 12 counties across Hubei province during 2009-2012,were gathered.Distributed lag nonlinear model (DLNM) was first used,to estimate the county-specific associations between daily mean temperature,cold spells,heat waves and stroke mortality.Multivariate Meta-analysis was then applied to pool the community-specific relationships between temperature and stroke mortality (exposure-response relationship) as well as both cold-and-heatassociated risks on mortality at different lag days (lag-response relationship).Results During 2009-2012,a total population of 6.7 million was included in this study with 42 739 persons died of stroke.An average of 2.7 (from 0.5 to 6.0) stroke deaths occurred daily in each county,with annual average mean temperature as 16.6 ℃ (from 14.7 ℃ to 17.4 ℃)during the study period.An inverse J-shaped association between temperature and stroke mortality was observed at the provincial level.Pooled mortality effect of cold spells showed a 2-3-day delay and lasted about 10 days,while effect of heat waves appeared acute but attenuated within a few days.The mortality risks on cold-spell days ranged from 0.968 to 1.523 in 12 counties at lag 3-14,with pooled effect as 1.180 (95％ CI:1.043-1.336).The pooled mortality risk (ranged from 0.675 to 2.066) on heat-wave days at lag 0-2 was 1.114 (95％CI:1.012-1.227).Conclusions An inverse J-shaped association between temperature and stroke mortality was observed in Hubei province,China.Both cold spells and heat waves were associated with increased stroke mortality,while different lag patterns were observed in the mortality effects of heat waves and cold spells.
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Objective To investigate the effect of humidex combined with mean temperature and relative humidity on the incidence of bacillary dysentery in Hefei. Methods Daily counts of bacillary dysentery cases and weather data in Hefei were collected from January 1, 2006 to December 31, 2013. Then, the humidex was calculated from temperature and relative humidity. A Poisson generalized linear regression combined with distributed lag non-linear model was applied to analyze the relationship between humidex and the incidence of bacillary dysentery, after adjusting for long-term and seasonal trends, day of week and other weather confounders. Stratified analyses by gender, age and address were also conducted. Results The risk of bacillary dysentery increased with the rise of humidex. The adverse effect of high humidex (90 percentile of humidex) appeared in 2- days lag and it was the largest at 4-days lag (RR=1.063, 95%CI:1.037-1.090). Subgroup analyses indicated that all groups were affected by high humidex at lag 2-5 days. Conclusion High humidex could significantly increase the risk of bacillary dysentery, and the lagged effects were observed.
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Objective To assess the acute effects of daily mean temperature,cold spells,and heat waves on stroke mortality in 12 counties across Hubei province,China.Methods Data related to daily mortality from stroke and meteorology in 12 counties across Hubei province during 2009-2012,were gathered.Distributed lag nonlinear model (DLNM) was first used,to estimate the county-specific associations between daily mean temperature,cold spells,heat waves and stroke mortality.Multivariate Meta-analysis was then applied to pool the community-specific relationships between temperature and stroke mortality (exposure-response relationship) as well as both cold-and-heatassociated risks on mortality at different lag days (lag-response relationship).Results During 2009-2012,a total population of 6.7 million was included in this study with 42 739 persons died of stroke.An average of 2.7 (from 0.5 to 6.0) stroke deaths occurred daily in each county,with annual average mean temperature as 16.6 ℃ (from 14.7 ℃ to 17.4 ℃)during the study period.An inverse J-shaped association between temperature and stroke mortality was observed at the provincial level.Pooled mortality effect of cold spells showed a 2-3-day delay and lasted about 10 days,while effect of heat waves appeared acute but attenuated within a few days.The mortality risks on cold-spell days ranged from 0.968 to 1.523 in 12 counties at lag 3-14,with pooled effect as 1.180 (95％ CI:1.043-1.336).The pooled mortality risk (ranged from 0.675 to 2.066) on heat-wave days at lag 0-2 was 1.114 (95％CI:1.012-1.227).Conclusions An inverse J-shaped association between temperature and stroke mortality was observed in Hubei province,China.Both cold spells and heat waves were associated with increased stroke mortality,while different lag patterns were observed in the mortality effects of heat waves and cold spells.
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OBJECTIVE:To provide theoretical basis for the detection of paracetamol by infrared spectroscopy. METHODS:0.002-0.02 g paracetamol was accurately weighed,added into 0.2 g potassium bromide,respectively,fully ground and well mixed, potassium bromide pressing plate method was used for to-be-tested test sample. Using hollow cathode lamp as light,scanning fre-quency was 30 times,resolution was 0.5 cm-1,scan range was 4000-400 cm-1,infrared absorption spectrum was determined and recorded to select the characteristic absorption peaks,then determine the optimized characteristic absorption peaks. Linear and non-linear models were respectively established by using mathematics modeling methods. RESULTS:1 016 cm-1 absorption peak with weaker absorbance but stronger features was selected for the analysis. According to the model establishing and calculation,the accu-racy of the nonlinear model was much higher than the linear model,r=0.942. CONCLUSIONS:Nonlinear quantitative model for quantitatively determining the content of paracetamol is feasible,and suitable for the on-destructive and rapid on-line quality control of paracetamol.
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Objective To study the impact of daily mean temperature on mortality in Shanghai.Methods With data on daily mortality,meteorological and air pollution,we used a distributed lag nonlinear model (DLNM) to assess the effects of daily mean temperature on deaths (caused by non-accidental,cardiovascular and respiratory) adjusted for both secular,seasonal trends and other confounders.Results A J-shaped relationship was found consistently between daily mean temperature and non-accidental,cardiovascular and respiratory deaths in Shanghai.Cold effects were delayed by 1 day to 4 days and persisted for 14-30 days.Hot effects appeared acute and the highest at the first day,but lasted for 2 days and followed by mortality displacement.Conclusion In Shanghai,both cold and hot temperatures increased the risk of mortality with delayed effects.Cold effects seemed last longer than heat did.
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Utilizou-se análise de agrupamento para classificar e selecionar modelos não lineares de crescimento de bovinos Nelore, tendo em vista os resultados de diferentes avaliadores de qualidade de ajuste. Ajustaram-se 12 modelos não lineares. A qualidade de ajuste dos modelos foi medida pelo coeficiente de determinação (R²), quadrado médio do erro (QME), critério de informação de Akaike (AIC), critério de informação Bayesiano (BIC), erro quadrático médio de predição (MEP) e coeficiente de determinação de predição (R²p). O modelo Brody foi o que apresentou o melhor ajuste para o conjunto de dados.
This study aimed to evaluate cluster analysis in classifying and selecting non linear models to describe Nelore beef cattle growth based on different goodness of fit criteria tests. A total of 12 non linear models were evaluated based on the following criteria: the determination coefficient (R²), error mean square (QME), Akaike information criterion (AIC), Bayesian information criterion (BIC), mean quadratic error of prediction (MEP) and predicted determination coefficient (R²p). The Brody model showed the best adjustment for the data set.
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Animals , Cattle , Growth/genetics , Models, Animal , Nonlinear DynamicsABSTRACT
BACKGROUND: Ventilation is a major determinant of the alveolar concentration of inhaled anesthetics. Hyperventilation accelerates the equilibration of anesthetic in the lungs, but decelerates it in the brain. We evaluated this phenomenon for desflurane. METHODS: Twenty healthy subjects were enrolled after IRB approval. End-tidal concentrations of desflurane (P.DESF) were recorded during 10 minutes of mask induction with 8% desflurane. P.DESF was modeled with time and end-tidal concentrations of CO2 (P.ETCO2) using a two-exponential pharmacokinetic equation. Bispectral index (BIS) values were also measured to find out the component reflecting the cerebral concentration of desflurane. RESULTS: During induction, the rise of P.DESF could be separated into two components: early and late rises. Individual BIS values showed a higher correlation with the late component of P.DESF (P = 0.000). P.ETCO2 had two different effects on the rise of P.DESF. CONCLUSIONS: Hyperventilation hastened the early rise and delayed the late rise of P.DESF (P = 0.00, P = 0.00). Hyperventilation should be avoided to obtain rapid anesthesia induction with desflurane.