Erythrocytes parameters due to aging, smoking, alcohol consumption and occupational activity in a working population of petrochemical industry. The Pavia Study.
The main purpose of the study was to assess the red blood cell disorders in works employed in the petrochemical industry in the Lombardia region (ENI). In the analysis of the data the confounding factors such as age, smoking habit, alcohol consumption, nutritional status based on body mass index have also been taken into consideration. In total, material consisted of 1175 male workers in whom red blood cell examination of the peripheral fasting blood was carried out. The results of the study showed that clinical anemia has been found in 1.7% of subjects examined. The distribution of anemia cases was not related to job category or physical occupational activity, neither to age, smoking or alcohol consumption. However, the results of the study suggest that aging processes are associated with weakening of hemopoietic system which affect in a great extent hemoglobin production. The effect of smoking on hemopoietic system appeared to have different features from that attributed to aging. Smoking increased hemoglobin level and hematocrit significantly in comparison to nonsmokers, but had no effect on the number of erythrocytes. It was concluded that adaptation to carbon monoxide inhaled with cigarette smoke is reflected by an increased red cell mass and hemoglobin. Occupational factors measured by the type of job (manual vs nonmanual) appeared to have no harmful effect on the hemopoietic system, however, respondents who reported working physically in an intensive way, showed significantly lower mean corpuscular concentration hemoglobin level than those having a sedentary job or engaged in very small physical activity at work.
Pollini
G
G
Dipartimento di Medicina Preventiva, Occupazionale e di Comunità, Università di Pavia.
Maugeri
U
U
Bernardo
A
A
Bianchi
I
I
Flak
E
E
Jedrychowski
W
W
D000328:Adult; D000375:Aging / Q000097:blood*; D000428:Alcohol Drinking / Q000097:blood*; D002617:Chemical Industry / Q000706:statistics & numerical data; D003430:Cross-Sectional Studies; D004909:Erythrocyte Indices; D006402:Hematologic Diseases / Q000097:blood / Q000453:epidemiology; D006801:Humans; D007558:Italy / Q000453:epidemiology; D008297:Male; D008875:Middle Aged; D009784:Occupational Diseases / Q000097:blood / Q000453:epidemiology; D016273:Occupational Exposure / Q000009:adverse effects* / Q000032:analysis / Q000706:statistics & numerical data; D010578:Petroleum / Q000706:statistics & numerical data; D012044:Regression Analysis; D012907:Smoking / Q000097:blood*
D010578:Petroleum