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Alcohol ; 14(1): 9-19, 1997.
Article in English | MEDLINE | ID: mdl-9014018

ABSTRACT

Four hundred and ninety-two (232 males and 260 females) randomly selected inhabitants older than 15 years of La Esperanza, a rural village of Tenerife, have been inquired about their daily alcohol intake, analyzing the relationship between this parameter and sex, age, marital status, educational level, job and smoking habit, physical signs, and biological markers of excessive ethanol consumption. One hundred and seventy-four out of them (35.4%) were teetotalers, while 318 (64.6%) consumed alcoholic beverages; 18.2% (34.1% of the males and 4.2% of the females) referred excessive ethanol consumption (more than 80 g/day and 40 g/day, respectively). Men consumed 62.3 +/- 4 g/day ethanol and women, 8 +/- 1 g/day. The distribution of the population according to the amount of ethanol consumed fits into Lederman's curve, most of the individuals being consumers of small amounts of ethanol. Male sex, middle age, married or separated status, unskilled job, sometimes unemployed, low educational level, daily drinking (mainly wine), and smoking, were all related to a higher ethanol consumption. When assessed by logistic regression, only liver enlargement, parotid swelling, retches and tremor in the morning, and hoarseness, out of the physical signs, showed independent predictive value as indicators of excessive consumption as well as serum GGT, ASAT, MCV, and urate levels out the biological markers. When all those physical and analytical signs that had previously shown predictive independent value are analyzed together, all the five physical signs (liver enlargement, parotid swelling, retches and tremor in the morning, and hoarseness) but only urate, out of the biochemical markers, showed independent predictive value.


Subject(s)
Alcohol Drinking/adverse effects , Adult , Aged , Alcohol Drinking/blood , Alcohol Drinking/epidemiology , Biomarkers , Blood Pressure/drug effects , Body Height/physiology , Body Weight/physiology , Enzymes/blood , Female , Humans , Male , Middle Aged , Multivariate Analysis , Predictive Value of Tests , Rural Population , Socioeconomic Factors , Spain/epidemiology
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