OBJECTIVE -Previous studies have related poor glycemic control and/or some diabetes complications to low socioeconomic status. Some aspects of socioeconomic status have not been assessed in these studies. In the present study, we used an individual index of deprivation, the Evaluation de la Précarité et des Inégalités de santé dans les Centres d'Examens de Santé (Evaluation of Precarity and Inequalities in Health Examination Centers [EPICES]) score, to determine the relationship among glycemic control, diabetes complications, and individual conditions of deprivation.RESEARCH DESIGN AND METHODS -We conducted a cross-sectional prevalence study in 135 consecutive diabetic patients (age 59.41 Ϯ 13.2 years [mean Ϯ SD]) admitted in the hospitalization unit of a French endocrine department. Individual deprivation was assessed by the EPICES score, calculated from 11 socioeconomic questions. Glycemic control, lipid levels, blood pressure, retinopathy, neuropathy, and nephropathy were assessed.RESULTS -HbA 1c level was significantly correlated with the EPICES score (r ϭ 0.366, P Ͻ 0.001). The more deprived patients were more likely than the less deprived patients to have poor glycemic control (␤ ϭ 1.984 [SE 0.477], P Ͻ 0.001), neuropathy (odds ratio 2.39 [95% CI 1.05-5.43], P ϭ 0.037), retinopathy (3.66 [1.39 -9.64], P ϭ 0.009), and being less often admitted for 1-day hospitalization (0.32 [0.14 -0.74], P ϭ 0.008). No significant relationship was observed with either nephropathy or cardiovascular risk factors.CONCLUSIONS -Deprivation status is associated with poor metabolic control and more frequent microvascular complications, i.e., retinopathy and neuropathy. The medical and economic burden of deprived patients is high.

The individual deprivation EPICES score is reliable. Deprivation was related to excess death rate, which clearly indicates that deprivation is a determinant factor that should be considered systematically by health policy makers and health-care providers.

An industry-wide mortality study on the association between lung cancer and occupational exposure to cobalt and tungsten carbide was carried out in the French hard-metal industry. This case-control study was nested in the historical cohort of workers ever employed in this industry's 10 facilities, most of which are located in eastern France. Workers were followed up from 1968 to 1991. Occupational exposure was assessed using a job-exposure matrix that provided semiquantitative scores for 320 job periods. These scores were significantly correlated with the levels of cobalt measured in 744 historical air samples. In this cohort, which comprised 5,777 males and 1,682 females, the death rate from lung cancer was significant (63 deaths, standardized mortality ratio=1.30, 95% confidence interval (CI) 1.00-1.66) when compared with national death rates. Sixty-one cases and 180 controls were included in the study. When the exposures during the last 10 years were ignored, a twofold lung cancer risk was observed among workers simultaneously exposed to cobalt and tungsten carbide (odds ratio (OR)=1.93, 95% CI 1.03-3.62) adjusted for other cobalt exposure (OR=2.21, 95% CI 0.99-4.90). The odds ratios increased with cumulative exposure (first quartile, OR=1.00; second quartile, OR=2.64; third quartile, OR=2.59; fourth quartile, OR=4.13) and, to a lesser degree, with duration of exposure (one decade, OR=1.00; two decades, OR=1.61; three decades, OR=2.77; four decades, OR=2.03). Adjustments for smoking and for exposures to known or suspected carcinogens did not change the results, yet the odds ratio for smoking (3.38) was lower than expected, suggesting the possibility of some misclassification. Occupational risk was highest among smokers. This study supports the hypothesis that workers who manufacture hard metals have an increased mortality from lung cancer due to simultaneous exposure to cobalt and tungsten carbide.

The following articles refer to this text: 2007;33(5): 379-386; 2008;34(6):444-450

and calendar time. The smoking habits of 87% of the whole study population were known. The distribution of welders and controls according to smoking was not statistically different. The overall mortality was slightly higher for welders (SMR = 1P02, 95% confidence interval (95% CI) 0-89-118) than for controls (SMR = 0-91, 95% CI 0 84-0 99). For lung cancer, the SMR was 1-24 (95% CI 0-75-1-94) for welders, whereas the corresponding value was lower for controls (SMR = 0-94, 95% CI 0 68-1-26). The SMR for lung cancer was 159 among non-shipyard mild steel welders (95% CI 0-73-3 02). This contrasted with the results for all stainless steel welders , and for stainless steel welders predominantly exposed to chromium VI (SMR = 1-03, 95% CI 0-12-3-71). Moreover, SMRs for lung cancer for mild steel welders tended to increase with duration of exposure and time since first exposure, leading to significant excesses for duration >20 years and latency 20 years. Such a pattern was not found for stainless steel welders. (British Journal of Industrial Medicine 1993;50:234-243) Welding consists of several processes that result in occupational exposures to various substances. The content ofwelding fumes depends both on the metals welded and on the welding processes involved.'2 In the case of stainless steel welding, unlike mild steel welding, the fumes contain nickel and chromium compounds, particularly chromium VI,." which have carcinogenic effects for humans under certain situations-namely, chromate production, chromate pigment production, chromium plating industries, and the nickel refining industry.'To assess risk of lung cancer due to welding, several epidemiological studies have been carried out over the past 40 years. A recent paper' has reviewed 14 case-control studies taking welding into account and 27 cohort studies."6 Only five of them reported 234