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Biomedical subjects

A Biggeri

Publications and source records attributed to A Biggeri.

At least 73 records · Page 4Linked to original sources
PubMed1985

A case control study of lung cancer in Florence, Italy. II. Effect of migration from the south.

Risk of lung cancer related to region of birth in Italy was investigated among migrants to Florence, in a case control study of all histologically confirmed incident cases of primary lung cancer in a three year period in that city (n = 376). Controls (n = 892) were patients in the same hospital of similar age, sex, date of admission, and smoking status with discharge diagnoses other than lung cancer or suicide. Information on place of birth and year of migration to Florence was collected directly from each subject, along with a detailed occupational history. Logistic regression models were used to calculate the odds ratio for birth in the south of Italy relative to birth elsewhere. Male migrants from the south have an odds ratio of lung cancer of 0.5 (95% limits 0.3 to 0.7) relative to those born elsewhere. This "protective effect" is not explained by smoking or by any known occupational risk. The risk is lowest among those born on the island of Sicily (odds ratio 0.2 compared to those born in the centre-north).

Age Factors↗
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Non-parametric maximum likelihood estimators for disease mapping.

A Non-Parametric Maximum Likelihood approach to the estimation of relative risks in the context of disease mapping is discussed and a NPML approximation to conditional autoregressive models is proposed. NPML estimates have been compared to other proposed solutions (Maximum Likelihood via Monte Carlo Scoring, Hierarchical Bayesian models) using real examples. Overall, the NPML autoregressive estimates (with weighted term) were closer to the Bayesian estimates. The exchangeable NPML model ranked immediately after, even if it implied a greater shrinkage, while the truncated auto-Poisson showed inadequate for disease mapping. The coefficients of the autoregressive term for the different mixtures have clear interpretations: in the breast cancer example, the larger cities in the region showed high rates and very low correlation with the neighbouring areas, while the less populated rural areas with low rates were strongly positively correlated each other. This pattern is expected since breast cancer is strongly correlated with parity and age at first birth, and the female population of the rural areas experienced a decline in fertility much later than those living in the larger cities. The leukemia example highlighted the failure of the Poisson-Gamma model and other general overdispersion tests to detect high risk areas under specific conditions. The NPML approach in Aitkin is very general, simple and flexible. However the user should be warned against the possibility of local maxima and the difficulty in detecting the optimal number of components. Special software (such as CAMAN or DismapWin) had been developed and should be recommended mainly to not experienced users.

Algorithms↗
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Exploratory tools for disease mapping in geographical epidemiology.

In the present paper a new shrinkage estimator of relative risk, useful in disease mapping, is compared with the empirical and full Bayes estimators, using death certificate data for lung cancer (males and females) and breast cancer (females) 1982-1988 in the Emilia-Romagna region (Italy). The estimates are obtained averaging the relative risks obtained from recursive partitioning of the set of observed values. The number of partitions is fixed in advance and behaves as a smoothing parameter, the lower the number the higher the degree of shrinkage toward the overall mean of the observed values.

Algorithms↗
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Trends in the prevalence of cervical intraepithelial neoplasia grade 3 in the district of Florence, Italy.

AIMS AND BACKGROUND: The objective of this study was to investigate the detection rate of cervical intraepithelial neoplasia grade III (CIN 3) in previously unscreened women, in order to reveal trends over time in the prevalence of CIN 3 in the District of Florence, where a population-based screening for cervical cancer has been going on since 1973. STUDY DESIGN: We considered the women, recorded in the computerized archives of CSPO, who had had no pap test for at least 10 years. Trends of CIN 3 (histologically proven) were analyzed within age groups; the effect of age, cohort and period were considered by means of a Poisson regression model. RESULTS: A total of 648 cases of histologically proven CIN 3 were detected in the study period. The detection rates of CIN 3 increased steadly within age groups over birth cohort and calendar period simultaneously. The Poisson regression analysis showed that only the model with age + time trend was statistically significant. CONCLUSIONS: Although several biases should be taken into account, the analysis seemed to indicate a real increase in CIN 3 prevalence. An increase in frequency of precancerous lesions for cervical cancer in more recent birth cohorts supports the need to keep screening coverage and efficiency as high as possible.

Adult↗
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Analysis of false-negative and underreported smears in the Florence district screening program for cervical carcinoma.

AIMS AND BACKGROUND: To review false-negative or underreported (reactive changes, squamous or glandular atypia) smears performed in women developing histologically proven CIN2 or more severe lesions within 24 months and evaluate error causes. The study setting was the Florence District cervical cancer population-based screening: about 60,000 women age 25-60 years screened per year. METHODS: 118 false-negative or underreported cases were identified at screening files-cancer Registry matching, and the original smears were reviewed by six independent readers to judge smear adequacy and error type. RESULTS: Sampling errors (reported as inadequate, negative or less severe than CIN1 at review) accounted for 74% and screening/interpretation errors (reported as CIN1 or more severe at review) accounted for 26% of studied cases. Screening/interpretation errors were more likely ascribed to misinterpretation and underreporting than to misperception of cellular abnormalities. CONCLUSIONS: Quality control should above all address the problem of sampling adequacy. Due to the rarity of misperceived abnormalities (true screening errors), manual or automated rescreening of negative smears would not be an effective procedure for quality control.

Adult↗
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[Inequalities in mortality in the Italian longitudinal studies].

The article presents some of the most relevant results on inequalities in mortality, obtained by the two Italian longitudinal studies carried out in Turin, and Tuscany (in Leghorn and Florence). The two studies share the same methodology. Each database contains census data, information from population register and from death certificates. The authors approach this issue not in an analytical way (as they did in the works cited in the reference list), but answering some questions, relevant both from a scientific and a political point of view. How big are the health inequalities in Italy? Are the health inequalities in Italy increasing or decreasing? Are the health inequalities due to absolute or to relative deprivation? Does the mortality profile of the Italian population express the presence of old or new health inequalities? Can the health inequalities be reduced? The study's results prove that the health inequalities in Italy are deep and strictly related to individuals' position in the social fabric. Facing the other questions the authors focus only in the Turin data. From the 1970's to the 1990's the health inequalities in Turin have increased, despite of general improvement of population's health condition and the progressive reduction of the size of deprived groups. Turin data support both the hypotheses on the source of health inequalities, using long term unemployment as absolute deprivation's indicator, and status' inconsistency as (a row) indicator of relative deprivation. The growth of drug-related causes of death (AIDS and overdose) shows that in the Turin and--quite reasonably--Italian population old and new health inequalities live together. The essay closes offering evidence on the possibility to reduce health inequalities. For this purpose the authors analyses the Turin trend of avoidable deaths and infant and adolescent mortality.

Adult↗
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[The Tuscany longitudinal study: mortality among selected causes in inner city of Florence and Leghorn].

The analysis of mortality in urban settings for the Cities of Florence (1991-95) and Leghorn (1987-95), based on data from the Tuscany Longitudinal Study, is reported in the present paper. The data came from a census-based cohort study, all residents at the census day 1981 (Leghorn) or 1991 (Florence) being enrolled and followed-up by automated procedures of record-linkage. The cause of death certificate had been eventually collected by the Regional Mortality Register. For each city, internally standardized mortality ratios (SMR) had been calculated by sub-urban areas (city sectors or wards). The analysis was restricted to age groups > 15 years to have interpretable results on socio-economic variables derived from census questionnaires. Bayesian estimates (Besag, York e Mollié) of mortality relative risks had been calculated to overcome extra-variability of SMRs. In the city of Florence two wards showed about 10% excess risk for overall mortality. In the city of Leghorn one sector was at higher risk while one showed a significant lower mortality. For both cities such risk gradients were still present after adjustment for deprivation index at individual level.

Adult↗
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[Deprivation and mortality: a deprivation index suitable for geographical analysis of inequalities].

UNLABELLED: FOREGROUND: A national deprivation index suitable for geographical analysis of inequalities in health is not yet available in Italy, although the link between deprivation and health has been clearly demonstrated in our country in a number of studies. OBJECTIVES: 1) To describe a deprivation index in Italy at municipal level, based on the percentage of selected census variables (simple components) 2) To analyse general mortality according to deprivation categories at municipal level in Italy 3) To measure the size of ecological bias using the Turin Longitudinal Study. SETTING: Italy (1-2), Turin (3). MATERIALS: 1) 1991 census data base at municipal level 2) General mortality in Italy by municipality and age bands in 1990-92. 3) Turin Longitudinal study 1991-1995. METHODS: 1) Percentages of selected indicators of inequalities for all the 8.100 Italian municipalities present at 1991 census were calculated. Factorial analysis were performed in order to help in selecting the most valuable ones. The final choice led to five indicators (low education, unemployment, rented occupier housing, no indoor bathroom, lone parent with childhood). A simple additive index was computed using the method of the sum of normal standard deviates of each component 2) Correlation of indexes with mortality was performed; SMR for each deprivation category were computed; 3) Computation of the index at different levels: individual (one million individuals), census ward (3657 wards), statistic zone (92 statistic zones), two neighborough levels (23 and 10 neighboroughs) was conducted; differential analysis was performed for each level and index category, allowing for comparison among results, adjusting for age. MAIN RESULTS: Increasing deprivation was significantly associated with mortality from all causes: there was up to a 20 percent increase in mortality between the highest and lowest quintile. The relationship was linear with no apparent threshold. The slope of the relationship between deprivation and mortality varied among regions. Differentials in inequalities measured by individual and census tract level resulted to be very small; ecological bias arises when larger areas are taken into account. CONCLUSIONS: An area based measure of deprivation has proved a valuable tool in examining differentials in death and is likely to prove of continuing value to health authorities in planning the delivery of health care.

Adolescent↗
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[Socioeconomic inequalities in health in the Tuscany Longitudinal Study (SLTO): persistence and changes over time in overall mortality and selected causes (lung cancer, liver cirrhosis, AIDS and overdose)].

We evaluate the persistence of social inequalities in overall mortality or mortality by causes (lung cancer, liver cirrhosis; AIDS and overdose) in the Tuscany Longitudinal Study (SLTo), a record linkage-study on the census population identified at the 1981 and 1991 censuses in Leghorn (1981: 175,741 subjects; 1991: 167,512 subjects), and 1991 in Florence (403,294 subjects), Central Italy. The census data allow an evaluation of socio-economic status of each subject, using variables such as education or occupation, or constructing indexes inclusive of deprivation indexes. Follow-up is from the census up to 1995 and for specific causes of death from 1987 (Leghorn) or 1991 (Florence). Estimates of risk are computed comparing rates of mortality among socio-economic groups, by means of poisson regression models, or by means of Standardized Mortality Ratios using the indirect method. The causes of deaths have been selected mainly because explained by known and strong determinants. As far as overall mortality, the results suggest the persistence of gradients by social class, more often negative among males. Mortality from lung cancer has a strong negative social class gradient among males, and a divergent gradient among women in the two towns, which is interpreted as the effect of a different prevalence of smoking by period, social class and sex. High RRs among lower socio-economic groups have been detected for liver cirrhosis mortality. Excess mortality of AIDS and overdose, an expression of the recent drug crisis, concentrates on the lower social strata and in young adults. Whereas mortality from AIDS has been detected among both sexes, deaths from overdose are occurring among males only. Being AIDS and overdose recent diseases, they stress the persistence of social inequalities over time.

Acquired Immunodeficiency Syndrome↗
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[Confounding and causality in epidemiology].

Since the beginning of the discipline epidemiologists developed a specific methodology to assess causal relationships, even opposed to statistics. A special effort to assure unbiasedness explains the importance of the concept of confounding in epidemiology. However, there is an intrinsic conflict in the formal definition of confounding based on association criteria. This conflict is solved in practice by gathering information on the subject specific matter. Causal criteria for confounding generalize with regards to identifiability of causal relationships in observational studies.

Causality↗
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[Trends in mortality from primary pleural tumor and incidence of pleural mesothelioma in Italy: a particularly serious situation].

We present: a) an analysis of the past mortality from Primary Pleural Tumors (PPT) occurred in Italy between 1968 and 1992 by an age-cohort-period model, using a Poisson regression model, estimating the risk of dying by birth cohort, the Lifetime Cumulative risk (25-84 years) by birth cohort, the risk by calendar period and testing the full model (age-cohort-period effects); b) a summary of the incidence of mesothelioma as recorded in Italy by Cancer Registries and Mesothelioma Registries. The highest Lifetime Cumulative Risk of dying from TTP is recorded for the birth cohort 1946-'50 (6.2 per thousand among males, 1.64 among females). Whereas the risk by birth cohort becomes flat among females born after 1936, among males the risk is increasing up to the youngest birth cohorts. By calendar period, the highest risk of dying is observed in the last period (1991-'92). The inclusion in the full model of the calendar period term increases significantly the goodness-of-fit of the model among females, but not among males. The highest incidence of mesothelioma in both genders registered by 150 Cancer Registries all over the world is currently recorded among the population of Genoa and Trieste, where large ship-building plants are located. Even higher incidence mesothelioma rates have been recently recorded in other areas of Italy. The trend in PPT mortality in Italy could have been influenced, but not explained, by the increased awareness over time of the disease, but it fits well with the pattern occurring in most industrialized countries of western Europe, with the unprotected industrial use of asbestos which occurred in Italy, and also with the gender characteristics of the work-force employed in asbestos-exposing activities. A ban of asbestos use has been introduced in Italy in 1992. However, considering that asbestos seems to act as an initiator for mesothelioma, the trend in male mortality for PPT will not peak until two or three decades.

Adult↗
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[Meta-analysis of the Italian studies on short-term effects of air pollution].

BACKGROUND: In recent years, much attention has been given to review reports on the early effects of air pollution on health, measured through daily series of deaths and/or hospital admissions. A number of large planned meta-analyses (in which methods for data retrieval and processing are commonly planned a priori for all participating centers) are on going both in the US and in Europe. The National Mortality, Morbidity and Air Pollution Study included data from 90 US cities, whereas APHEA (Air Pollution and Health, a European Approach) considers data from about 30 european cities. The present paper summarizes methods and findings of MISA, a meta-analysis of data from 8 Italian cities. It belongs to an ad hoc supplement of Epidemiologia & Prevenzione (Epidemiol Prev 2001; 25 (2) Suppl: 1-72), the official Journal of the Italian Association of Epidemiology, which contains a full description of the study. MISA was launched on March 2000, within the project "Statistics, Environment and Health" (GRASPA), funded by the Italian Ministry of Education. Additional support was given by the Authorities of the 8 participating cities (from North to South: Turin, Milan, Verona, Ravenna, Bologna, Florence, Rome and Palermo). DAILY HEALTH DATA: Deaths certificate and hospital admission data have been collected respectively from the Local Health Authority and regional files. The same programme for retrieval of data on selected hospital admissions for acute conditions was used in the 8 cities. Main data are summarized in Table 1. DAILY CONCENTRATION OF POLLUTANTS: Most data were obtained from Regional Environmental Protection Agencies, which are responsible for environmental monitoring since 1993. Verona, Palermo and Milan (1990-94) data were obtained from local sources. Monitors with more than 25% of missing data were excluded. Meteorological data were collected by the same monitors and completed with data from monitors situated in the suburbs or (in Milan and Bologna) in the airport. The monitors were selected by a group of experts to ensure comparability. For SO2 and NO2 daily averages of hourly measurements were used, whereas concentrations of ozone and CO were estimated as the maximum 8 hours moving average. Total suspended particulate or PM10 were measured as 24 hours deposition. All analyses used the whole range of observed values (Table 2). Daily data were considered as missing when more than 25% of hourly data were not available. Missing data in one monitor were imputed as average of data from the remaining monitors weighted by the ratio between the specific monitor's year average and the general year average of all the selected city monitors. Missing data in one day were imputed as average of four days (preceding and following day, the same day of the previous and following weeks). In the city of Florence and Palermo PM10 concentrations were available. For the other cities we applied a conversion factor from PTS to PM10 (0.6 for Turin and 0.8 for all the others) estimated through validation studies. Ozone concentrations were used only where background monitors were available (Turin, Verona, Bologna and Florence) and limited to the warm season (May through September). METHODS: A common protocol for the city-specific analyses was defined on the basis of a structured exploratory analysis. The adopted basic model was a Generalized Additive Model for Poisson data. Effect estimates were age-adjusted (0-64, 65-74, 75+) and formal tests of interaction pollutant-age were conducted. In the first two age groups, indicator variables for seasonality were specified, and cubic splines with fixed number of degree of freedom were specified for the last age group and for all age groups for the morbidity data. Model adequacy was checked by residual analysis and inspection of the partial autocorrelation function. In a sensitivity analysis non linear pollutant effects were considered and overdispersed [table: see text] transitional models were fitted; the analysis was conducted for all lags 0-3 and some distributed lags (0-1, 1-2, 0-3); no multipollutant models were fitted. The same model was fitted to the city data. No model selection was done: Table 3 describes the steps in model building. In the meta-analysis, for each outcome, the estimates for each pollutant and for each city were combined using fixed and random effects models. Heterogeneity of effects was tested according to DerSimonian and Laird. Results were checked using a hierarchical bayesian model, which was used to investigate heterogeneity across cities in a meta-regression phase. Non informative priors were used. Posterior distributions of parameters of interest have been obtained with WinBUGS. 10,000 iterations (excluding [table: see text] the first 2000) were retained, while for the meta-regression 100,000 iterations (excluding the first 4000) were stored. To approximate the marginal posteriors only one sample out of five were used. Achieved convergence was assessed using the Gelman and Rubin approach. In the meta-regression the models specified were the following: [formula: see text] i denotes city, j calendar period (1990-1994; 1995-1999). The first model includes only period as effect modifier, while the second model other potential variables. The ui terms (which do not vary with j) represent city specific random effects. RESULTS: For each pollutant, the meta-analysis detected a statistically significant association with mortality for natural causes. But for ozone, positive associations were commonly found for death and hospital admissions for both cardiovascular and respiratory diseases. Indeed, the only estimates whose lower 95% confidence limit bore a negative sign regarded the association between PM10 and mortality from respiratory diseases. Ozone in the warm season was positively and significantly associated with daily mortality and mortality for cardiovascular diseases whereas other estimates did not reach statistical significance and some were negative (only lag 0-1 for external comparability are reported in Table 4). Risks were highest (up to 4%) for respiratory conditions (Table 4). They were more pronounced at lag 1-2 for mortality, and at lag 0-3 for hospital admissions. Age was an effect modifier for mortality, the elderly being more susceptible. In the random effect meta-analysis, at lag 1-2, excess risks for unit increase of the pollutants at age 75+ and at age 0-64 were respectively: 4.9% and -0.4% for SO2, 1.7% and 0.6% for NO2; 2.3% and 0.2% for CO. Corresponding figures for PM10 at lag 0-1 were 1.1% and 0.2%. The effect of PM10 on mortality [table: see text] was greater during the warm season (2.8% vs 0.8%). A complete analysis is reported in the Italian text. Here we provide some details on the effects of PM10, about which the residual heterogeneity across cities was highest (Table 4). In addition, the epidemiological evidence on the hazards from this fraction of particulate matter is more controversial. Table 5 reports the excess risk estimated through the meta-analysis in 1995-99 for a 10 micrograms/m3 increase of PM10 for some outcomes. Proper prior distributions (overdispersed normal and inverse gamma) were adopted in the final bayesian analyses. The sensitivity of results to the choice of the priors were investigated (we defined proper and improper uniform, student's t), obtaining comparable results. Total natural mortality was significantly heterogeneous across cities (Q = 18.96, 5 df, p < 0.001). City-specific estimates are represented graphically in Fig. 1. As expected, the confidence (credibility) intervals are widest [table: see text] for bayesian estimates, intermediate for those obtained under a random effects model, and narrowest for those found under a fixed effects model. Nevertheless, differences in point estimates are negligible. A North-South gradient in risk is obvious. Table 6 shows, for the cities for which mortality data were available, the improvement in precision and the shrinkage of effect estimates toward the overall mean introduced by the bayesian modelling. In the meta-regression, total mortality and a deprivation score were associated with greater effects. The excess risks on hospital admission were modified by the deprivation score and by the NO2/PM10 ratio. Overall, the risk estimates were greater in the calendar period 1995-99 and there was a North-South gradient, with larger effects in cities located in Central and Southern Italy (Florence, Rome, Palermo). CONCLUSIONS: The meta-analysis of the Italian studies on short-term effects of air pollution in 8 cities, MISA, exhibits the following features: With the exception of Naples, all greatest Italian cities were included; overall a population of 7 million was enrolled. The study protocol was accurate with regard to the selection of hospital admissions for acute conditions. Monitored data of concentration of pollutant were carefully evaluated before their inclusion in the meta-analysis. City specific analyses were carried out according to a common protocol controlling for seasonality, influenza epidemics, age and meterological variables; [table: see text] the protocol derived from a structured exploratory analysis. The meta-analysis was done using fixed and random effects models; a hierarchical bayesian model was fitted in a sensitivity analysis. The heterogeneity of effects across cities was investigated using a hierarchical bayesian model for meta-regression. While mortality data are of good quality, hospital admission data are more problematic. Since the filing criteria for the latter changed around 1995, comparability of results before and after such date is limited. Moreover, hospital admissions rely on availability of beds, the offer of which may be restricted during the warm season. Comparability of pollutant concentration estimates among cities may have been influenced by differences in monitor characteristics. (ABSTRACT TRUNCATED)

Adolescent↗