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OBJECTIVE To analyze lifestyle risk factors related to direct healthcare costs and the indirect costs due to sick leave among workers of an airline company in Brazil. METHODS In this longitudinal 12-month study of 2,201 employees of a Brazilian airline company, the costs of sick leave and healthcare were the primary outcomes of interest. Information on the independent variables, such as gender, age, educational level, type of work, stress, and lifestyle-related factors (body mass index, physical activity, and smoking), was collected using a questionnaire on enrolment in the study. Data on sick leave days were available from the company register, and data on healthcare costs were obtained from insurance records. Multivariate linear regression analysis was used to investigate the association between direct and indirect healthcare costs with sociodemographic, work, and lifestyle-related factors. RESULTS Over the 12-month study period, the average direct healthcare expenditure per worker was US$505.00 and the average indirect cost because of sick leave was US$249.00 per worker. Direct costs were more than twice the indirect costs and both were higher in women. Body mass index was a determinant of direct costs and smoking was a determinant of indirect costs. CONCLUSIONS Obesity and smoking among workers in a Brazilian airline company were associated with increased health costs. Therefore, promoting a healthy diet, physical activity, and anti-tobacco campaigns are important targets for health promotion in this study population.

Objective: To describe an index to identify inequities in living conditions and health and its relationship with health planning., Methods: Variables and indicators that would reflect demographic, economic, environment and education processes as well as supply and production of health services were applied for nondimensional scaling and clustering of 5,507 Brazilian municipalities. Data sources were the 2000 Census and the Brazilian Ministry of Health information systems. Z-score test statistic and cluster analysis were performed allowing to defining 4 groups of municipalities by living conditions., Results: There was seen a polarization between the group with the best living conditions and health (Group 1) and the group with the worst living conditions (Group 4). Group 1 consisted of municipalities with larger populations while Group 4 comprised mainly the smallest municipalities. As for Brazilian macroregions, municipalities in Group 1 are clustered in the south and southeast and those in Group 4 are in the Northeast., Conclusions: The living conditions and health index comprises reality dimensions such as housing, environment and health which allows to identifying the most vulnerable municipalities and can provide input for setting priorities, and developing criteria for more equitable financing and resource allocation.

Objective: To assess the lag structure between air pollution exposure and elderly cardiovascular diseases hospital admissions, by gender., Methods: Health data of people aged 64 years or older was stratified by gender in São Paulo city, Southeastern Brazil, from 1996 to 2001. Daily levels of air pollutants (CO, PM10, O3, NO2, and SO2) , minimum temperature, and relative humidity were also analyzed. It were fitted generalized additive Poisson regressions and used constrained distributed lag models adjusted for long time trend, weekdays, weather and holidays to assess the lagged effects of air pollutants on hospital admissions up to 20 days after exposure., Results: Interquartile range increases in PM10 (26.21 microg/m(3)) and SO2 (10.73 microg/m(3)) were associated with 3.17% (95% CI: 2.09-4.25) increase in congestive heart failure and 0.89% (95% CI: 0.18-1.61) increase in total cardiovascular diseases at lag 0, respectively. Effects were higher among female group for most of the analyzed outcomes. Effects of air pollutants for different outcomes and gender groups were predominately acute and some "harvesting" were found., Conclusions: The results show that cardiovascular diseases in São Paulo are strongly affected by air pollution.