Association of pasta consumption with body mass index and waist-to-hip ratio: results from Moli-sani and INHES studies

Abstract

Background/objectives: Pasta as a traditional component of Mediterranean diet (MeD) in Italy has not been studied in detail in the management of body weight. This study aimed at evaluating the association of pasta intake with body mass index (BMI) and waist-to-hip ratio, in two large epidemiological datasets.

Subjects/methods: A total of 14 402 participants aged ⩾35 years randomly recruited from the general population of the Molise region (Moli-sani cohort) and 8964 participants aged >18 years from all over Italy (Italian Nutrition & HEalth Survey, INHES) were separately analyzed. The European Prospective Investigation into Cancer and Nutrition (EPIC)-food frequency questionnaire and one 24-h dietary recall were used for dietary assessment. Weight, height, waist and hip circumference were measured in Moli-sani or self-reported in INHES. Residuals methodology corrected for either total energy intake or body weight was used for the analysis of pasta intake.

Results: Higher pasta intake was associated with better adhesion to MeD in both genders (P for both<0.001). In the Moli-sani study, after multivariable analysis, pasta-energy residuals were negatively associated with BMI in women but not in men (β-coef=-0.007, P=0.003 for women and β-coef=-0.001, P=0.58 for men). When pasta intake-body weight residuals were used, pasta intake was significantly and negatively associated with BMI in crude and multi-adjusted models (including adhesion to MeD) in both genders and Moli-sani and INHES studies (for all β-coef<0, P<0.05). In the Moli-sani study, pasta-body weight residuals were significantly and negatively associated with waist and hip circumference and waist-to-hip ratio (for all β-coef<0, P<0.05).

Conclusions: As a traditional component of MeD, pasta consumption was negatively associated with BMI, waist circumference and waist-to-hip ratio and with a lower prevalence of overweight and obesity.

Figure 1

Linear regression analysis evaluating the association of pasta intake as grams per day or pasta-energy residuals or pasta-body weight residuals and BMI.