OSSERVATORIO PERMANENTE SUI GIOVANI E L’ALCOL Roma, CNR, 9 Luglio 2015

Giovani e alcol:

dati dai progetti

INHES, CONVERGI e MOLI-SANI

Giovanni de Gaetano, MD, PhD Dipartimento di Epidemiologia e Prevenzione IRCCS Istituto

Neurologico Mediterraneo NEUROMED

Pozzilli (Isernia)

The Italian Nutrition & HEalth Survey (INHES) is a program specifically designed to collect

scientifically robust current information on dietary habits of Italians.

The survey, designed on the trace of the NHANES (National Health and Nutrition Examination

Survey), conducted in US, used telephone interviews to collect and analyse a variety of nutrition and

health parameters.

The survey examined a representative national sample of 9.319 persons selected in all Italian regions,

to provide representativeness not only at the national but also at the local level.

2169; 24%

5994; 68%

679; 8%

Tutta la coorte: bevitori 76% Quando si inizia a bere?

MAI BEVITORI

BEVITORI DOPO I 12 ANNI

BEVITORI PRIMA DEI 12ANNI

010203040506070

MAI BEVITORI BEVITORI DOPO I 12ANNI

BEVITORI PRIMA DEI12 ANNI

Età attuale in rapporto all’età di inizio del bere (p<0.0001)

0

20

40

60

80

100

MAI BEVITORI BEVITORI DOPO I 12ANNI

BEVITORI PRIMA DEI12 ANNI

Percento uomini bevitori (p<0.0001)

Confronti corretti per età, sesso e provenienza geografica

An

ni

%

300; 67%

146; 33%

Astemi Bevitori

Distribuzione di bevitori/astemi

nei giovani sotto i 19 anni

reclutati nel progetto INHES:

Astemi: 67%

Bevitori: 33%

0

2

4

6

8

10

12

14

16

18

Astemi Bevitori

Età media (p<0.0001)

0

10

20

30

40

50

donne uomini

Percento dei bevitori by Genere

(p=0.29)

Chi sono i ragazzi sotto i 19 anni che bevono bevande alcoliche? Il percento dei bevitori nei giovani sotto 19 anni del progetto INHES è 33%

Confronti corretti per età, sesso e provenienza geografica

Anni

%

Chi sono i ragazzi sotto i 19 anni che bevono bevande alcoliche? Il percento dei bevitori nei giovani sotto 19 anni del progetto INHES è 33%

0

10

20

30

40

50

North Center South

Percento dei bevitori by regione

(p<0.0001)

0

20

40

60

80

100

Fumo No Fumo Yes

Percento dei bevitori by fumo di sigaretta

(p<0.0001)

0

10

20

30

40

50

Sport No Sport Yes

Percento dei bevitori by sport (p<0.0001)

Confronti corretti per età, sesso e provenienza geografica

%

%

%

Mobile phone short messages service (SMS) related to healthy

lifestyle for high school students:

The CONVERGI Study.

IACOVIELLO Licia1, DE LUCIA Francesca2, DI CASTELNUOVO Augusto1, BONACCIO Marialaura 1, OLIVIERI Marco3, DONATI Maria Benedetta1,

de GAETANO Giovanni1, BONANNI Americo1

1Department of Epidemiology and Prevention IRCCS Istituto Neurologico Mediterraneo Neuromed

Pozzilli (Isernia) 2Associazione Cuore Sano. Campobasso. Italy

3Epicomed Research Srl. Campobasso. Italy

CONVERGI STUDY

N = 371 Mean age 16 ± 1 (min/max: 14 – 19) Boys 37% Randomly recruited in two high schools in Campobasso

CONVERGI STUDY

Bevitori (14-19 anni): 83% A che età ha assaggiato l’alcol per la prima volta? Never 61 17% After 12 yrs 236 65% 9-11 yrs 50 14% Before 11 yrs 24 4%

17%

65%

14% 4%

Never

After 12 yrs

9-11 yrs

Before 11 yrs

CONVERGI STUDY

Quanto alcohol consumi? (gr/day; 12 gr = 1 drink) gr/day N % 0 61 17% 6 91 26% 12 79 22% 24 63 18% mediana di consumo tra i bevitori 42 40 11% 12 gr/day (un drink al giorno) 54 21 6%

L’83% dei ragazzi intervistati consuma bevande alcoliche Il 50% dei consumatori di bevande alcoliche assume più di un drink al giorno

CONVERGI STUDY

Quando consumi le tue bevande alcoliche? (percentuali sul totale dei bevitori, n= 310) N % All’aperitivo 118 38% Dopo cena 97 31% Fuori dai pasti 206 66%

CONVERGI STUDY

Nel weekend consumi…. (percentuali sul totale dei rispondenti, n= 299, tutti bevitori) N % la stessa quantità 126 42% di più 135 45% di meno 38 13%

CONVERGI STUDY

Quali bevande alcoliche consumi? (percentuali sul totale dei bevitori, n= 310) N % Vino 152 49% Vino rosso 141 45% Vino bianco 114 37% Vino rosato 70 23% Birra 240 77% Spumante, champagne (raramente) 246 79% Vini liquorosi (vin santo,cherry, porto) 51 16% Superalcolici 126 41% Liquori leggeri 119 38% Amari 54 17% Aperitivi alcolici 163 53% Cocktail alcolici 194 63% Bevande tipo bacardi breezer 181 58%

CONVERGI STUDY

In cosa differiscono bevitori e non? Bevitori No Si P* (n=61) (N=310) Età (anni, SD) 15.3±1.1 15.5±0.9 0.091 Ragazzi (n, %) 16 (26%) 122 (39%) 0.057 Fumatori (n, %) 1 (2%) 64 (22%) 0.0005 *P corrette per età e sesso Altri parametri antropometrici, indici di stato sociale, attività fisica e abitudini alimentari non differiscono tra le due categorie

Lo studio MOLI-SANI

Lo studio MOLI-SANI

25,000 cittadini della regione Molise

Età > 35 anni

Fase di reclutamento: 2005-2010

Principali end points: eventi

cardiovascolari, tumorali e

neurodegenerativi

Prevalenza di adesione alla dieta mediterranea

negli anni 2005-2010

Bonaccio M et a. Nutr Metab Cardiovasc Dis. 2014;24:853-60

ADHESION TO MEDITERRANEAN DIET IN THE MOLI-SANI COHORT

2005-2006 2007-2010 P value

% of intake above the median

Fruits 57.0 48.7 <.0001

Vegetables 55.9 49.6 <.0001

Fish 54.5 49.3 0.0002

Legumes 67.7 42.6 <.0001

Cereals 53.9 50.7 0.02

Dairy 52.5 50.3 0.14

Meat 49.1 53.3 <.0001

Monounsaturated/saturated fats

P value adjusted for age, sex,

wealth, education, energy

intake.

49.5 48.5 0.0003

ALCOHOL CONSUMPTION IN THE MOLI-SANI COHORT

2005-2006 2007-2010 P value

Alcohol categories % <.0001

Abstainers 24.3 33.9

Light (0-12 donne; 0-24 uomini) 40.0 31.4

Moderate (12-24 donne; 24-48 uomini) 21.8 20.3

Heavy (>24 donne; > 48 uomini) 13.9 14.4

Above median (1.16 gr/day for

women);

63.0 43.4 <.0001

Above median (20.7 gr/day for men) 49.4 50.3 0.031

No abstainers included

Above median (8.0 gr/day for women); 47.3 51.7 <.0001

Above median (26.8 gr/day for men) 47.7 51.2 0.0002

AIM: The aim of our study was to evaluate the efficacy of mobile phone SMS in promoting correct behaviours, compared to more traditional ways of communication.

The widespread use of mobile phone among younger people could provide a new cost-effective tool to disseminate information on healthy lifestyle and to encourage modifications. This study evaluated the efficacy of SMS in promoting correct behaviours and improving metabolic health. Need to explore between boys and girls regarding efficacy of structured SMS texts.

• METHODS: 430 boys and girls, aged 14-17 years, from two high schools in Campobasso (Italy) , were assigned to either intervention or control according to their home school. At baseline, all students received biometric evaluations and answered a questionnaire on lifestyle and a one-week food frequency recall. Conferences and meeting with experts were organized in both schools to enhance knowledge and understanding correct lifestyles. Both groups received nine different SMSs, one every three weeks for one year. SMSs sent to the intervention group contained specific news and messages about healthy behaviour, while those sent to the control group contained scientific news. At the end of the intervention period, a follow up evaluation was carried on. The KIDMED index based on a 16-question test was used to evaluate the Mediterranean quality of the diet

RESULTS: Both groups showed an increase in all anthropometric parameters after one year. The increase in waist circumference was significantly lower in the SMS group as compared to the control one, in both girls and boys (2.58 cm (0.99 to 4.16) in controls vs (0.24 cm (-0.99 to 1.48) in SMS, p<0.001 in girls and 2.14 cm (0.35 to 3.94) vs -0.47 cm (-2.36 to 1.42) in boys, p<0.0002, after adjustment for age and baseline levels). Similar results were observed in girls, but not in boys, for hip circumference (2.77 cm (1.69 to 3.86) vs 0.24 cm (-1.32 to 1.79), p<0.06).

No significant difference was observed neither in physical activity nor in food frequency consumption.

• CONCLUSIONS: Short messages delivered to teenagers through mobile phone may exert a favourable influence on anthropometric parameters. Further research is warranted on the efficacy of this new tool on behaviour and lifestyle. Results suggest interesting hypothesis about gender communication perception. Girls appear to be more likely than boys to receive information with features of paternalism. New studies are necessary to explore gender differences in the type of communication language.