Dietary and nutritional patterns in an elderly rural population in Northern and Southern Italy: (I). A cluster analysis of food consumption.
OBJECTIVE
To describe the food consumption patterns of Italian elderly subjects and the factors associated with different dietary habits.


METHODS
Cross-sectional study.


METHODS
Population-based study.


METHODS
A total of 847 men and 1465 women aged 65 y or older, living in rural areas in the province of Pavia (Northern Italy) and near Cosenza (Southern Italy) in 1992-1993.


METHODS
The dietary information was collected by means of a quantitative food-frequency questionnaire, with cluster analysis being used to segregate the subjects on the basis of similarities in their food consumption. A generalised logistic regression model including residence, age, living status, education, physical activity and degree of disability was fitted to assess the factors associated with different food consumption habits.


RESULTS
Six dietary clusters were selected for men and seven for women. The largest cluster for both genders was "small eaters" (46% of men and 51% of women); "big eaters", "light diet" and "alcohol" clusters were also identified for both genders. The men were also grouped into "balanced diet" and "cheese" clusters, and the women into "sweet", "greens" and "butter" clusters.


CONCLUSIONS
In addition to the influence of the area of residence--residents in Northern Italy consume greater amounts of animal fats, sugar and alcoholic beverages, and those living in Southern Italy have a greater intake of fruit, vegetables, fish and olive oil--all of the other studied variables predicted the probabilities of falling into a specific dietary cluster.


BACKGROUND
National Research Council (Italy)--Invecchiamento Project No. 95.01048. PF40.
Corrêa Leite
M L
ML
Department of Epidemiology and Medical Informatics, Institute of Biomedical Technologies, National Research Council, Via Fratelli Cervi, 20090 Segrate, Milan, Italy.
Nicolosi
A
A
Cristina
S
S
Hauser
W A
WA
Pugliese
P
P
Nappi
G
G
D000368:Aged; D000369:Aged, 80 and over; D000375:Aging; D000428:Alcohol Drinking; D016000:Cluster Analysis; D003430:Cross-Sectional Studies; D004032:Diet / Q000706:statistics & numerical data*; D004034:Diet Surveys; D004041:Dietary Fats / Q000008:administration & dosage; D019422:Dietary Sucrose / Q000008:administration & dosage; D004522:Educational Status; D015444:Exercise; D005247:Feeding Behavior; D005260:Female; D005638:Fruit; D006801:Humans; D007558:Italy; D016015:Logistic Models; D008297:Male; D017533:Marital Status; D000069463:Olive Oil; D010938:Plant Oils / Q000008:administration & dosage; D012424:Rural Population / Q000706:statistics & numerical data*; D017747:Seafood; D011795:Surveys and Questionnaires; D014675:Vegetables
D004041:Dietary Fats; D019422:Dietary Sucrose; D000069463:Olive Oil; D010938:Plant Oils