219 resultados para POISSON-DISTRIBUTION
em Scielo Saúde Pública - SP
Resumo:
Several studies have confirmed seasonal variation in suicide rates according to hours of sunshine. The suicide pattern was assessed in São Paulo, southeastern Brazil, at the tropic of Capricorn from 1996 to 2004. Poisson regression was employed to estimate parameters of seasonality, as well as to verify associations for each day between daylight duration and suicide. During the nine-year study period, there were 3,984 suicides (76.9% in men; median age=38.7 years old). Seasonal averages of suicides were similar, as were monthly averages. Poisson regression did not reveal any association between suicide rates and hours of sunshine (p=0.45) for both sexes. In conclusion, no seasonal pattern was observed for suicides.
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INTRODUCTION: The purpose of this ecological study was to evaluate the urban spatial and temporal distribution of tuberculosis (TB) in Ribeirão Preto, State of São Paulo, southeast Brazil, between 2006 and 2009 and to evaluate its relationship with factors of social vulnerability such as income and education level. METHODS: We evaluated data from TBWeb, an electronic notification system for TB cases. Measures of social vulnerability were obtained from the SEADE Foundation, and information about the number of inhabitants, education and income of the households were obtained from Brazilian Institute of Geography and Statistics. Statistical analyses were conducted by a Bayesian regression model assuming a Poisson distribution for the observed new cases of TB in each area. A conditional autoregressive structure was used for the spatial covariance structure. RESULTS: The Bayesian model confirmed the spatial heterogeneity of TB distribution in Ribeirão Preto, identifying areas with elevated risk and the effects of social vulnerability on the disease. We demonstrated that the rate of TB was correlated with the measures of income, education and social vulnerability. However, we observed areas with low vulnerability and high education and income, but with high estimated TB rates. CONCLUSIONS: The study identified areas with different risks for TB, given that the public health system deals with the characteristics of each region individually and prioritizes those that present a higher propensity to risk of TB. Complex relationships may exist between TB incidence and a wide range of environmental and intrinsic factors, which need to be studied in future research.
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The main object of the present paper consists in giving formulas and methods which enable us to determine the minimum number of repetitions or of individuals necessary to garantee some extent the success of an experiment. The theoretical basis of all processes consists essentially in the following. Knowing the frequency of the desired p and of the non desired ovents q we may calculate the frequency of all possi- ble combinations, to be expected in n repetitions, by expanding the binomium (p-+q)n. Determining which of these combinations we want to avoid we calculate their total frequency, selecting the value of the exponent n of the binomium in such a way that this total frequency is equal or smaller than the accepted limit of precision n/pª{ 1/n1 (q/p)n + 1/(n-1)| (q/p)n-1 + 1/ 2!(n-2)| (q/p)n-2 + 1/3(n-3) (q/p)n-3... < Plim - -(1b) There does not exist an absolute limit of precision since its value depends not only upon psychological factors in our judgement, but is at the same sime a function of the number of repetitions For this reasen y have proposed (1,56) two relative values, one equal to 1-5n as the lowest value of probability and the other equal to 1-10n as the highest value of improbability, leaving between them what may be called the "region of doubt However these formulas cannot be applied in our case since this number n is just the unknown quantity. Thus we have to use, instead of the more exact values of these two formulas, the conventional limits of P.lim equal to 0,05 (Precision 5%), equal to 0,01 (Precision 1%, and to 0,001 (Precision P, 1%). The binominal formula as explained above (cf. formula 1, pg. 85), however is of rather limited applicability owing to the excessive calculus necessary, and we have thus to procure approximations as substitutes. We may use, without loss of precision, the following approximations: a) The normal or Gaussean distribution when the expected frequency p has any value between 0,1 and 0,9, and when n is at least superior to ten. b) The Poisson distribution when the expected frequecy p is smaller than 0,1. Tables V to VII show for some special cases that these approximations are very satisfactory. The praticai solution of the following problems, stated in the introduction can now be given: A) What is the minimum number of repititions necessary in order to avoid that any one of a treatments, varieties etc. may be accidentally always the best, on the best and second best, or the first, second, and third best or finally one of the n beat treatments, varieties etc. Using the first term of the binomium, we have the following equation for n: n = log Riim / log (m:) = log Riim / log.m - log a --------------(5) B) What is the minimun number of individuals necessary in 01der that a ceratin type, expected with the frequency p, may appaer at least in one, two, three or a=m+1 individuals. 1) For p between 0,1 and 0,9 and using the Gaussean approximation we have: on - ó. p (1-p) n - a -1.m b= δ. 1-p /p e c = m/p } -------------------(7) n = b + b² + 4 c/ 2 n´ = 1/p n cor = n + n' ---------- (8) We have to use the correction n' when p has a value between 0,25 and 0,75. The greek letters delta represents in the present esse the unilateral limits of the Gaussean distribution for the three conventional limits of precision : 1,64; 2,33; and 3,09 respectively. h we are only interested in having at least one individual, and m becomes equal to zero, the formula reduces to : c= m/p o para a = 1 a = { b + b²}² = b² = δ2 1- p /p }-----------------(9) n = 1/p n (cor) = n + n´ 2) If p is smaller than 0,1 we may use table 1 in order to find the mean m of a Poisson distribution and determine. n = m: p C) Which is the minimun number of individuals necessary for distinguishing two frequencies p1 and p2? 1) When pl and p2 are values between 0,1 and 0,9 we have: n = { δ p1 ( 1-pi) + p2) / p2 (1 - p2) n= 1/p1-p2 }------------ (13) n (cor) We have again to use the unilateral limits of the Gaussean distribution. The correction n' should be used if at least one of the valors pl or p2 has a value between 0,25 and 0,75. A more complicated formula may be used in cases where whe want to increase the precision : n (p1 - p2) δ { p1 (1- p2 ) / n= m δ = δ p1 ( 1 - p1) + p2 ( 1 - p2) c= m / p1 - p2 n = { b2 + 4 4 c }2 }--------- (14) n = 1/ p1 - p2 2) When both pl and p2 are smaller than 0,1 we determine the quocient (pl-r-p2) and procure the corresponding number m2 of a Poisson distribution in table 2. The value n is found by the equation : n = mg /p2 ------------- (15) D) What is the minimun number necessary for distinguishing three or more frequencies, p2 p1 p3. If the frequecies pl p2 p3 are values between 0,1 e 0,9 we have to solve the individual equations and sue the higest value of n thus determined : n 1.2 = {δ p1 (1 - p1) / p1 - p2 }² = Fiim n 1.2 = { δ p1 ( 1 - p1) + p1 ( 1 - p1) }² } -- (16) Delta represents now the bilateral limits of the : Gaussean distrioution : 1,96-2,58-3,29. 2) No table was prepared for the relatively rare cases of a comparison of threes or more frequencies below 0,1 and in such cases extremely high numbers would be required. E) A process is given which serves to solve two problemr of informatory nature : a) if a special type appears in n individuals with a frequency p(obs), what may be the corresponding ideal value of p(esp), or; b) if we study samples of n in diviuals and expect a certain type with a frequency p(esp) what may be the extreme limits of p(obs) in individual farmlies ? I.) If we are dealing with values between 0,1 and 0,9 we may use table 3. To solve the first question we select the respective horizontal line for p(obs) and determine which column corresponds to our value of n and find the respective value of p(esp) by interpolating between columns. In order to solve the second problem we start with the respective column for p(esp) and find the horizontal line for the given value of n either diretly or by approximation and by interpolation. 2) For frequencies smaller than 0,1 we have to use table 4 and transform the fractions p(esp) and p(obs) in numbers of Poisson series by multiplication with n. Tn order to solve the first broblem, we verify in which line the lower Poisson limit is equal to m(obs) and transform the corresponding value of m into frequecy p(esp) by dividing through n. The observed frequency may thus be a chance deviate of any value between 0,0... and the values given by dividing the value of m in the table by n. In the second case we transform first the expectation p(esp) into a value of m and procure in the horizontal line, corresponding to m(esp) the extreme values om m which than must be transformed, by dividing through n into values of p(obs). F) Partial and progressive tests may be recomended in all cases where there is lack of material or where the loss of time is less importent than the cost of large scale experiments since in many cases the minimun number necessary to garantee the results within the limits of precision is rather large. One should not forget that the minimun number really represents at the same time a maximun number, necessary only if one takes into consideration essentially the disfavorable variations, but smaller numbers may frequently already satisfactory results. For instance, by definition, we know that a frequecy of p means that we expect one individual in every total o(f1-p). If there were no chance variations, this number (1- p) will be suficient. and if there were favorable variations a smaller number still may yield one individual of the desired type. r.nus trusting to luck, one may start the experiment with numbers, smaller than the minimun calculated according to the formulas given above, and increase the total untill the desired result is obtained and this may well b ebefore the "minimum number" is reached. Some concrete examples of this partial or progressive procedure are given from our genetical experiments with maize.
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Nest plasticity of Cornitermes silvestrii (Isoptera, Termitidae, Syntermitinae) in response to flood pulse in the Pantanal, Mato Grosso, Brazil. The Pantanal is one of the largest wetlands in the world. Since many areas in Pantanal are flooded during part of the year, it is expected that plants and animals would have mechanisms for their survival during the flooded period. This study investigated the existence of differences in nest shape and inquilines of Cornitermes silvestrii in areas influenced by the flood pulse. We measured the volume, height, width, and height/width ratio of 32 nests in flooded areas and 27 in dry areas, and performed an one-way-Anova with the quasi-Poisson distribution to determine if there were differences in the nest measurements between the points. To analyze the relationship of nest inquilines to flood pulse and nest shape, we performed a regression with a Poisson distribution with the inquiline richness and flood pulse, and the above measurements. The nests of C. silvestrii in flooded areas were significantly higher than nests in dry areas, and had a larger height/width ratio. Colonies in periodically flooded areas would probably make a larger effort to extend their nests vertically, to maintain at least some portion of the structure out of the water and prevent the entire colony from being submerged. Neither the size of the nest nor the flood pulses influenced the assemblage of 11 species found in nests of C. silvestrii.
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The aim of the present study was to establish the extent of in vitro radioresponse of lymphocytes among 62 healthy adults of both genders and to estimate the distribution of baseline micronuclei and radiosensitivity among individuals of the study population using the cytochalasin block micronucleus test. A younger study group consisted of 10 males (mean age, 22.4 years; range, 21-27) and 12 females (mean age, 24.8 years; range, 20-29), whereas an older study group consisted of 18 males (mean age, 35.1 years; range, 30-44) and 22 females (mean age, 38.5 years; range, 30-48). For evaluation of radiosensitivity blood samples were irradiated in vitro using 60Co g-ray source. The radiation dose employed was 2 Gy, the dose rate 0.45 Gy/min. The study revealed a significant gender effect on baseline micronuclei favoring females (Z = 3.25, P < 0.001), while yields of radiation-induced micronuclei did not differ significantly (Z = 0.56, P < 0.56) between genders. The distribution of baseline micronuclei among the individuals tested followed Poisson distribution in both study groups and in both genders, whereas the distribution of radiosensitivity among individuals of the older study group did not fulfill Poisson expectations (Kolmogorov-Smirnof test, P < 0.01). In contrast to a nonsignificant difference in radiosensitivity between males and females of the same age group (Z = 1.97, P < 0.56), a statistically significant difference in radiosensitivity between younger and older group for both genders was found (Z = 3.03, P < 0.03). Since the individuals tested were healthy, the observed variability in radiation response is considered to be an early effect of ageing.
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OBJECTIVE To analyze the temporal evolution of maternal mortality and its spatial distribution.METHODS Ecological study with a sample made up of 845 maternal deaths in women between 10 and 49 years, registered from 1999 to 2008 in the state of Rio Grande do Sul, Southern Brazil. Data were obtained from Information System on Mortality of Ministry of Health. The maternal mortality ratio and the specific maternal mortality ratio were calculated from records, and analyzed by the Poisson regression model. In the spatial distribution, three maps of the state were built with the rates in the geographical macro-regions, in 1999, 2003, and 2008.RESULTS There was an increase of 2.0% in the period of ten years (95%CI 1.00;1.04; p = 0.01), with no significant change in the magnitude of the maternal mortality ratio. The Serra macro-region presented the highest maternal mortality ratio (1.15, 95%CI 1.08;1.21; p < 0.001). Most deaths in Rio Grande do Sul were of white women over 40 years, with a lower level of education. The time of delivery/abortion and postpartum are times of increased maternal risk, with a greater negative impact of direct causes such as hypertension and bleeding.CONCLUSIONS The lack of improvement in maternal mortality ratio indicates that public policies had no impact on women’s reproductive and maternal health. It is needed to qualify the attention to women’s health, especially in the prenatal period, seeking to identify and prevent risk factors, as a strategy of reducing maternal death.
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INTRODUCTION: Malaria is a serious problem in the Brazilian Amazon region, and the detection of possible risk factors could be of great interest for public health authorities. The objective of this article was to investigate the association between environmental variables and the yearly registers of malaria in the Amazon region using Bayesian spatiotemporal methods. METHODS: We used Poisson spatiotemporal regression models to analyze the Brazilian Amazon forest malaria count for the period from 1999 to 2008. In this study, we included some covariates that could be important in the yearly prediction of malaria, such as deforestation rate. We obtained the inferences using a Bayesian approach and Markov Chain Monte Carlo (MCMC) methods to simulate samples for the joint posterior distribution of interest. The discrimination of different models was also discussed. RESULTS: The model proposed here suggests that deforestation rate, the number of inhabitants per km², and the human development index (HDI) are important in the prediction of malaria cases. CONCLUSIONS: It is possible to conclude that human development, population growth, deforestation, and their associated ecological alterations are conducive to increasing malaria risk. We conclude that the use of Poisson regression models that capture the spatial and temporal effects under the Bayesian paradigm is a good strategy for modeling malaria counts.
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Fungal diseases are important factors limiting common bean yield. White mold is one of the main diseases caused by soil pathogens. The objective of this study was to quantify the distribution of a fungicide solution sprayed into the canopy of bean plants by spectrophotometry, using a boom sprayer with and without air assistance. The experiment was arranged in a 2 x 2 x 2 factorial (two types of nozzles, two application rates, and air assistance on and off) randomized block design with four replications. Air assistance influenced the deposition of solution on the bean plant and yield increased significantly with the increased rate of application and air assistance in the boom sprayer.
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OBJECTIVE: To describe the patterns of deliveries in a birth cohort and to compare vaginal and cesarean section deliveries. METHODS: All children born to mothers from the urban area of Pelotas, Brazil, in 2004, were recruited for a birth cohort study. Mothers were contacted and interviewed during their hospital stay when extensive information on the gestation, the birth and the newborn, along with maternal health history and family characteristics was collected. Maternal characteristics and childbirth care financing - either private or public healthcare (SUS) patients - were the main factors investigated along with a description of C-sections distribution according to day of the week and delivery time. Standard descriptive techniques, Χ² tests for comparing proportions and Poisson regression to explore the independent effect of C-section predictors were the methods used. RESULTS: The overall C-section rate was 45%, 36% among SUS and 81% among private patients, where 35% of C-sections were reported elective. C-sections were more frequent on Tuesdays and Wednesdays, reducing by about a third on Sundays, while normal deliveries had a uniform distribution along the week. Delivery time for C-sections was markedly different among public and private patients. Maternal schooling was positively associated with C-section among SUS patients, but not among private patients. CONCLUSIONS: C-sections were almost universal among the wealthier mothers, and strongly related to maternal education among SUS patients. The patterns we describe are compatible with the idea that C-sections are largely done to suit the doctor's schedule. Drastic action is called for to change the current situation.
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OBJECTIVE To estimate the prevalence of depressive symptoms among institutionalized elderly individuals and to analyze factors associated with this condition. METHODS This was a cross-sectional study involving 462 individuals aged 60 or older, residents in long stay institutions in four Brazilian municipalities. The dependent variable was assessed using the 15-item Geriatric Depression Scale. Poisson’s regression was used to evaluate associations with co-variables. We investigated which variables were most relevant in terms of presence of depressive symptoms within the studied context through factor analysis. RESULTS Prevalence of depressive symptoms was 48.7%. The variables associated with depressive symptoms were: regular/bad/very bad self-rated health; comorbidities; hospitalizations; and lack of friends in the institution. Five components accounted for 49.2% of total variance of the sample: functioning, social support, sensory deficiency, institutionalization and health conditions. In the factor analysis, functionality and social support were the components which explained a large part of observed variance. CONCLUSIONS A high prevalence of depressive symptoms, with significant variation in distribution, was observed. Such results emphasize the importance of health conditions and functioning for institutionalized older individuals developing depression. They also point to the importance of providing opportunities for interaction among institutionalized individuals.
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OBJECTIVE To analyze temporal trends and distribution patterns of unsafe abortion in Brazil. METHODS Ecological study based on records of hospital admissions of women due to abortion in Brazil between 1996 and 2012, obtained from the Hospital Information System of the Ministry of Health. We estimated the number of unsafe abortions stratified by place of residence, using indirect estimate techniques. The following indicators were calculated: ratio of unsafe abortions/100 live births and rate of unsafe abortion/1,000 women of childbearing age. We analyzed temporal trends through polynomial regression and spatial distribution using municipalities as the unit of analysis. RESULTS In the study period, a total of 4,007,327 hospital admissions due to abortions were recorded in Brazil. We estimated a total of 16,905,911 unsafe abortions in the country, with an annual mean of 994,465 abortions (mean unsafe abortion rate: 17.0 abortions/1,000 women of childbearing age; ratio of unsafe abortions: 33.2/100 live births). Unsafe abortion presented a declining trend at national level (R2: 94.0%, p < 0.001), with unequal patterns between regions. There was a significant reduction of unsafe abortion in the Northeast (R2: 93.0%, p < 0.001), Southeast (R2: 92.0%, p < 0.001) and Central-West regions (R2: 64.0%, p < 0.001), whereas the North (R2: 39.0%, p = 0.030) presented an increase, and the South (R2: 22.0%, p = 0.340) remained stable. Spatial analysis identified the presence of clusters of municipalities with high values for unsafe abortion, located mainly in states of the North, Northeast and Southeast Regions. CONCLUSIONS Unsafe abortion remains a public health problem in Brazil, with marked regional differences, mainly concentrated in the socioeconomically disadvantaged regions of the country. Qualification of attention to women’s health, especially to reproductive aspects and attention to pre- and post-abortion processes, are necessary and urgent strategies to be implemented in the country.
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OBJECTIVE To analyze the methodology used for assessing the spatial distribution of specialized cardiac care units. METHODS A modeling and simulation method was adopted for the practical application of cardiac care service in the state of Santa Catarina, Southern Brazil, using the p-median model. As the state is divided into 21 health care regions, a methodology which suggests an arrangement of eight intermediate cardiac care units was analyzed, comparing the results obtained using data from 1996 and 2012. RESULTS Results obtained using data from 2012 indicated significant changes in the state, particularly in relation to the increased population density in the coastal regions. The current study provided a satisfactory response, indicated by the homogeneity of the results regarding the location of the intermediate cardiac care units and their respective regional administrations, thereby decreasing the average distance traveled by users to health care units, located in higher population density areas. The validity of the model was corroborated through the analysis of the allocation of the median vertices proposed in 1996 and 2012. CONCLUSIONS The current spatial distribution of specialized cardiac care units is more homogeneous and reflects the demographic changes that have occurred in the state over the last 17 years. The comparison between the two simulations and the current configuration showed the validity of the proposed model as an aid in decision making for system expansion.
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OBJECTIVE To analyze the spatial distribution of risk for tuberculosis and its socioeconomic determinants in the city of Rio de Janeiro, Brazil.METHODS An ecological study on the association between the mean incidence rate of tuberculosis from 2004 to 2006 and socioeconomic indicators of the Censo Demográfico (Demographic Census) of 2000. The unit of analysis was the home district registered in the Sistema de Informação de Agravos de Notificação (Notifiable Diseases Information System) of Rio de Janeiro, Southeastern Brazil. The rates were standardized by sex and age group, and smoothed by the empirical Bayes method. Spatial autocorrelation was evaluated by Moran’s I. Multiple linear regression models were studied and the appropriateness of incorporating the spatial component in modeling was evaluated.RESULTS We observed a higher risk of the disease in some neighborhoods of the port and north regions, as well as a high incidence in the slums of Rocinha and Vidigal, in the south region, and Cidade de Deus, in the west. The final model identified a positive association for the variables: percentage of permanent private households in which the head of the house earns three to five minimum wages; percentage of individual residents in the neighborhood; and percentage of people living in homes with more than two people per bedroom.CONCLUSIONS The spatial analysis identified areas of risk of tuberculosis incidence in the neighborhoods of the city of Rio de Janeiro and also found spatial dependence for the incidence of tuberculosis and some socioeconomic variables. However, the inclusion of the space component in the final model was not required during the modeling process.