Measures of chronic degenerative disease diffusion, such as incidence and prevalence rates, are a basic need for epidemiologists and others working in many fields of human sciences. Equations relating death probabilities to incidence and survival probabilities for chronic degenerative diseases are derived from a cohort point of view. A maximum likelihood approach is adopted for the estimation of incidence as a function of time related covariates. When time series of mortality data are available, the model can be used to describe and analyse levels and dynamics of morbidity. A trial application to lung and breast cancer is given for the province of Varese, Italy, where incidence data are available from the Lombardy Cancer Register.

International audienceIn this paper we revisit the mortality profiles of France and Italy in 2003 using the multiple-cause-of-death approach. The method leads to a substantial upward reassessment of the role played by certain conditions - e.g. diseases of the blood and diseases of the skin - in overall mortality. Regarding the associations of causes, we distinguish three patterns of pairwise joint occurrence of causes that are common to both countries. The numerous similarities that emerge from the comparison of the two countries are a positive signal of the reliability of the multiple-cause-of-death data

The country-specific disability advantages/disadvantages across educational groups identified here could help to identify determining factors and the efficiency of national policies implemented to tackle social differentials in health.

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Objectives We investigate the reporting of obesity on death certificates in three countries (France, Italy, and the United States) with different levels of prevalence, and we examine which causes are frequently associated with obesity. Methods We use cause-of-death data for all deaths at ages 50–89 in 2010–2011. Since obesity may not be the underlying cause (UC) of death, we compute age- and sex- standardized death rates considering all mentions of obesity (multiple causes or MC). We use cluster analyses to identify patterns of cause-of-death combinations. Results Obesity is selected as UC in no more than 20% of the deaths with a mention of obesity. Mortality levels, whether measured from the UC or the MC, are weakly related to levels of prevalence. Patterns of cause-of-death combinations are similar across the countries. In addition to strong links with cardiovascular diseases and diabetes, we identify several less familiar associations. Conclusions Considering all mentions on the deaths certificates reduces the underestimation of obesity-related mortality based on the UC only. It also enables us to describe the various mortality patterns involving obesity.

Our research highlights several consequences of the conditions under study that could be targeted by public health policy. It also speaks to the existence of differences in diagnosis/certification practices that may explain differences in mortality levels.

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Self-Rated Health (SRH) is becoming one of the most popular indicator of\ud population health. Nevertheless, a limited understanding still remains about the elements to\ud which individuals refer when evaluating their health and how those elements act and\ud interact in the evaluation process. In this study we use a structural equation model with\ud latent variables to identify direct and indirect influences of various health dimensions\ud (chronic morbidity, functional abilities and emotional health) and socio-demographic\ud covariates (age, gender and education) on poor SRH. The sample consists of 25,183 Italian\ud elderly aged 65 years and over, interviewed in the 2005 National Health Interview Survey.\ud The results have pointed out the higher direct effect of psychological and emotional health\ud on SRH, while the higher total effect is caused by chronic morbidity, which influences\ud SRH both directly and altering functional and emotional health. Growing older, being a\ud woman and having a low education negatively impacts on SRH. However, this is almost\ud completely the result of the indirect effect exerted by the covariates, while their direct\ud effect is not significant (gender), negative (age) or very modest (education)