[The supply of long-term care services for the elderly in Italian regions]. / L'offerta di servizi di Long-Term Care per gli ultrasessantacinquenni nelle regioni italiane.

In Italy, as in other European Countries, ageing population drives policymakers to redesign the Long Term Care (LTC) system for the elderly. This study analyses the LTC supply for elderly considering the distribution of different components: formal care (institutional and alternative), and informal one in Italian regions. An observational, cross-sectional, ecological study was carried out using statistical data drawn from the Italian National Institute of Statistics and Ministry of Health referred to 2004. Factorial analysis selected the most important components of LTC phenomenon. These components were used for the application of cluster analysis. Cluster Analysis was performed on main components of Factorial Analysis. Then, the ratio of mean value in each cluster on national mean value was calculated for each indicator. Factorial analysis showed three factors characterized by autovalue > 1 that accounted for 61% of the total variance. Cluster analysis highlighted four groups of regions with different way of supply. High level of home care (141,9) and social network (121,3) emerged in group 1. High level of family who received help and family paying a caregiver (108,3 e 121,1) resulted in group 2. High level of no profit LTC (168) supply was reported in group 3. High level of public residential care (451,4) was found in group 4. These remarkable differences in the way of service supply, highlight the need of improvement of the information system on LTC. Thus LTC policy and practice might be better supported both in planning and organizational targets.

Cause-specific mortality in classic Kaposi's sarcoma: a population-based study in Italy (1995-2002).

BACKGROUND: Little information is available on the causes of death among persons with classic Kaposi's sarcoma (CKS). METHODS: We conducted a population-based study in Italy to identify deceased persons with CKS and the underlying causes of death among them, by reviewing multiple-causes-of-death records. Standardised mortality ratios (SMRs) and 95% confidence intervals were calculated to compare the distribution of causes to that among the same-age general population of deceased persons. The geographical distribution was also evaluated. RESULTS: Of the 946 deaths among persons with CKS, 65.9% were attributable to non-neoplastic conditions and 21.9% to malignancies. For 12.2%, no lethal pathology was identified and CKS was considered as the underlying cause. In 90% of these cases, there was visceral/nodal involvement, therapy-related complications, or neoplastic cachexia. Among persons with CKS who died of other causes, an excess for lymphoid malignancies emerged (SMR=4.40) (chronic lymphocytic leukaemia (11.03), non-Hodgkin's lymphoma (4.22), Hodgkin's lymphoma (11.80), and multiple myeloma (2.3)), balanced by a deficit for all solid cancers (0.56), with a marked deficit for lung cancer (0.41). We found an excess for respiratory diseases (chronic obstructive pulmonary disease (1.86)) and genitourinary diseases (chronic renal failure (6.47)). There was marked geographical heterogeneity in the distribution of deaths. CONCLUSIONS: Though referring specifically to Italy, the results are informative for other countries and populations and all cases of CKS in general.

Persistent variations in average height between countries and between socio-economic groups: an overview of 10 European countries.

PRIMARY OBJECTIVES: This paper aims to provide an overview of variations in average height between 10 European countries, and between socio-economic groups within these countries. DATA AND METHODS: Data on self-reported height of men and women aged 20-74 years were obtained from national health, level of living or multipurpose surveys for 1987-1994. Regression analyses were used to estimate height differences between educational groups and to evaluate whether the differences in average height between countries and between educational groups were smaller among younger than among older birth cohorts. RESULTS: Men and women were on average tallest in Norway, Sweden, Denmark and the Netherlands and shortest in France, Italy and Spain (range for men: 170-179 cm; range for women: 160-167 cm). The differences in average height between northern and southern European countries were not smaller among younger than among older birth cohorts. In most countries average height increased linearly with increasing birth-year (approximately 0.7-0.8 cm/5 years for men and approximately 0.4 cm/5 years for women). In all countries, lower educated men and women on average were shorter than higher educated men (range of differences: 1.6-3.0 cm) and women (range of differences: 1.2-2.2 cm). In most countries, education-related height differences were not smaller among younger than among older birth cohorts. CONCLUSIONS: The persistence of international differences in average height into the youngest birth cohorts indicates a high degree of continuity of differences between countries in childhood living conditions. Similarly, the persistence of education-related height differences indicates continuity of socio-economic differences in childhood living conditions, and also suggests that socio-economic differences in childhood living conditions will continue to contribute to socio-economic differences in health at adult ages.

Educational differences in smoking: international comparison.

OBJECTIVE: To investigate international variations in smoking associated with educational level. DESIGN: International comparison of national health, or similar, surveys. SUBJECTS: Men and women aged 20 to 44 years and 45 to 74 years. SETTING: 12 European countries, around 1990. MAIN OUTCOME MEASURES: Relative differences (odds ratios) and absolute differences in the prevalence of ever smoking and current smoking for men and women in each age group by educational level. RESULTS: In the 45 to 74 year age group, higher rates of current and ever smoking among lower educated subjects were found in some countries only. Among women this was found in Great Britain, Norway, and Sweden, whereas an opposite pattern, with higher educated women smoking more, was found in southern Europe. Among men a similar north-south pattern was found but it was less noticeable than among women. In the 20 to 44 year age group, educational differences in smoking were generally greater than in the older age group, and smoking rates were higher among lower educated people in most countries. Among younger women, a similar north-south pattern was found as among older women. Among younger men, large educational differences in smoking were found for northern European as well as for southern European countries, except for Portugal. CONCLUSIONS: These international variations in social gradients in smoking, which are likely to be related to differences between countries in their stage of the smoking epidemic, may have contributed to the socioeconomic differences in mortality from ischaemic heart disease being greater in northern European countries. The observed age patterns suggest that socioeconomic differences in diseases related to smoking will increase in the coming decades in many European countries.

Differences in self reported morbidity by educational level: a comparison of 11 western European countries.

STUDY OBJECTIVE: To assess whether there are variations between 11 Western European countries with respect to the size of differences in self reported morbidity between people with high and low educational levels. DESIGN AND METHODS: National representative data on morbidity by educational level were obtained from health interview surveys, level of living surveys or other similar surveys carried out between 1985 and 1993. Four morbidity indicators were included and a considerable effort was made to maximise the comparability of these indicators. A standardised scheme of educational levels was applied to each survey. The study included men and women aged 25 to 69 years. The size of morbidity differences was measured by means of the regression based Relative Index of Inequality. MAIN RESULTS: The size of inequalities in health was found to vary between countries. In general, there was a tendency for inequalities to be relatively large in Sweden, Norway, and Denmark and to be relatively small in Spain, Switzerland, and West Germany. Intermediate positions were observed for Finland, Great Britain, France, and Italy. The position of the Netherlands strongly varied according to sex: relatively large inequalities were found for men whereas relatively small inequalities were found for women. The relative position of some countries, for example, West Germany, varied according to the morbidity indicator. CONCLUSIONS: Because of a number of unresolved problems with the precision and the international comparability of the data, the margins of uncertainty for the inequality estimates are somewhat wide. However, these problems are unlikely to explain the overall pattern. It is remarkable that health inequalities are not necessarily smaller in countries with more egalitarian policies such as the Netherlands and the Scandinavian countries. Possible explanations are discussed.