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Dietary patterns of French adults: associations with demographic, socio‐economic and behavioural factors
Author(s) -
Bertin M.,
Touvier M.,
Dubuisson C.,
Dufour A.,
Havard S.,
Lafay L.,
Volatier J.L.,
Lioret S.
Publication year - 2016
Publication title -
journal of human nutrition and dietetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.951
H-Index - 70
eISSN - 1365-277X
pISSN - 0952-3871
DOI - 10.1111/jhn.12315
Subject(s) - medicine , demography , logistic regression , body mass index , cross sectional study , gerontology , environmental health , sociology , pathology
Abstract Background Although the French eating model may differ from those of other countries, no studies to date have investigated dietary patterns in a wide age range of adults and at the national level. We aimed to identify dietary patterns ( DP ) of French adults and assess their associations with demographic, socio‐economic and behavioural factors. Methods The present study included 2624 adults (1087 men, 1537 women) aged 18–79 years from the cross‐sectional national French INCA 2 dietary survey. Dietary data were collected using a 7‐day estimated food record. Clusters of DP were derived using principal component analysis and clustering, conjointly. Age‐adjusted logistic regression analyses were used to investigate the association between DP and correlates. Results Five DP were identified, namely ‘traditional’, ‘prudent’, ‘diversified’, ‘processed’ and ‘sandwiches’. Men were more likely to follow a traditional diet and women the ‘prudent’ pattern. Members of the ‘processed’ and ‘sandwiches’ patterns were younger compared to non‐members. Healthier dietary patterns were overall positively associated with a higher socio‐economic position, healthier behaviours (in terms of sedentary behaviours and smoking status) and lower body mass index. Under‐reporting of energy intake, restrictive diet to lose weight and dietary supplement consumption were also related to specific DP , although differentially in men and women. Associations with contextual factors (i.e. household composition, agglomeration size and region) were also observed. Conclusions The identification of adults’ dietary patterns and associated behaviours (all modifiable) is important for the conceptualisation of multi‐behavioural programs. The additional information on social and environmental correlates is also essential for targeting the most vulnerable population groups in the context of such public health interventions.

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