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2.
Rev Mal Respir ; 36(6): 679-687, 2019 Jun.
Article in French | MEDLINE | ID: mdl-31235336

ABSTRACT

The objective of this article is to describe the changes in lung cancer mortality among employed men over the period 1976-2005, according to their activity sector and socio-professional categories. This work was done as part of the Cosmop monitoring program. The socio-professional data come from the DADS panel constituted by INSEE. For each person of the panel, the vital status was searched until 2005 by matching the national file of medical causes of death managed by Inserm's CépiDC (Epidemiological Center for Mortality by Medical Causes). The results show large disparities in mortality among male employees by activity sector. Over the period 1976-2005, the rates vary twofold between the sector with the highest rate (Construction, 98 p.100,000 person-years) and the sector with the lowest rate (Education, 43 p.100,000 person-years). For most of the activity sectors, mortality rates increased between the periods 1976-1985 and 1986-1995 before decreasing over the period 1996-2005. Some activity sectors stand out by an increase in mortality over the study period. This is the case for construction, education and public administration. It is essential to continue the surveillance of cancers by social category and activity sector. This will permit us to identify sectors in which specific preventive actions should be carried out, particularly on smoking for lung cancer.


Subject(s)
Lung Neoplasms/mortality , Occupations , Adult , Aged , Humans , Male , Middle Aged , Time Factors
3.
Rev Epidemiol Sante Publique ; 56(4): 245-52, 2008 Aug.
Article in French | MEDLINE | ID: mdl-18684576

ABSTRACT

BACKGROUND: For many years in France, premature mortality (i.e., deaths before 65 years old) and avoidable deaths have generally been used to monitor health of the population and help to elaborate policies in this area. This paper aims to examine the utility of another indicator of premature mortality, which makes it possible to take into account the impact of deaths, the expected years of life lost (EYLL). METHODS: Mortality data for France in the years 2000 to 2002 were obtained from the Centre for Epidemiology of the Medical Causes of Death. Premature mortality was defined as death before 65 years of age. For the calculation of EYLL, the mortality norm chosen was French-life expectancy for the years 2001 to 2003. In order to study the spatial distribution of the indicators above defined, standardized ratios were calculated for each administrative area, taking France as the reference population. RESULTS: Irrespective of the gender and indicator considered, ranking of the causes emphasized three major groups of pathological conditions, which are strongly distinguished from the others: cardiovascular diseases, malignant neoplasm and injuries. The ranking of causes varied considerably according to the indicator used. The spatial representation of standardized ratios of expected years of life lost and deaths before 65 showed a strong North-South trend. CONCLUSION: The concept of premature mortality is difficult to define and discussions persist on the age limit to use for its quantification. The choice of an indicator strongly depends on the use which one wishes to make. The simple analysis of deaths before 65 years currently used to describe premature mortality in France makes it possible to describe its frequency. The use of a summary measure as EYLL allows to quantify the impact of premature mortality by giving different weights to deaths depending on the age of occurrence. EYLL, thus, seems to be an indicator, which is particularly adapted to decision-making in public health, depending on choices and values one wishes to give preference to.


Subject(s)
Life Expectancy , Mortality/trends , Adolescent , Adult , Age Distribution , Age Factors , Aged , Aged, 80 and over , Algorithms , Cause of Death/trends , Child , Child, Preschool , Female , France/epidemiology , Health Status Indicators , Humans , Infant , Infant, Newborn , Life Expectancy/trends , Male , Middle Aged , Odds Ratio , Sex Distribution , Young Adult
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