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. 2018 Apr 15;7(4):58. doi: 10.3390/antiox7040058

Macronutrient and Major Food Group Intake in a Cohort of Southern Italian Adults

Serena Mulè 1, Mariagiovanna Falla 1, Alessandra Conti 1, Dora Castiglione 1, Isabella Blanco 1, Armando Platania 1, Maurizio D’Urso 2, Marina Marranzano 1,*
PMCID: PMC5946124  PMID: 29662045

Abstract

Background: Dietary intake of macronutrient and foods is considered crucial to decrease the risk of diet-related non-communicable diseases. Methods: The aim of this study was to describe the intake of major food groups and macronutrients in a random sample of 1838 southern Italian adults. Results: No significant differences of macronutrient consumption between sexes were found. By contrast, younger individuals had significantly higher intake of animal protein than older ones. Men reported consuming significantly more total processed meats and less eggs than women; egg consumption significantly increased by age groups. Significantly lower intake of fruit in the younger age group compared to older ones was found. Various patterns of correlation between food groups were described. More than half of individuals reached the suggested recommendations for carbohydrate and fiber intake, and about two-thirds met the recommendations for total protein and cholesterol intake, while only a minority met for total fat intake. Total and plant protein, monounsaturated and omega-6 fatty acids, were significantly inversely related with BMI (body mass index), while trans fatty acids and cholesterol were directly correlated. A direct association with unprocessed meats and an inverse association with processed meats was also found. Conclusions: The overall findings suggest that relatively healthy dietary habits are common in southern Italy.

Keywords: macronutrients, food intake, body mass index, dietary recommendations, cohort

1. Introduction

Over the last decades, great efforts have been done to identify a nutritionally balanced diet that might help reduce the risk of chronic non-communicable diseases. There is convincing evidence that dietary factors, alongside with physical activity and abstinence from unhealthy lifestyle behaviors (such as smoking habits), play a crucial role in prolonging the lifespan and ameliorating human health [1,2]. Adequate nutritional requirements represent, nowadays, a key element of public health effort [3]; thus, assessment and knowledge of current populations’ nutritional status is needed to design national recommendations [4]. Previous guidelines were mainly interested in macronutrient intake, but more recent dietary advice focused on food groups, in order to improve the understanding of the general population and facilitate public health educators and policymakers to better identify crucial priorities in the field [5,6].

Research in nutritional epidemiology produced over the last years investigated the association between macronutrients/major food groups, and the most common chronic non-communicable diseases [7]. As prevalence of metabolic disorders has increased in the last decades, major attention has been appointed to the risk of obesity, considered the potential lead mediating factor for many other conditions [8]. In contrast with the individual role of obesity as determinant of diet-related diseases, there is general agreement that calorie source matters, and that diet quality, intended as a proper ratio between macronutrients and individual food groups, constitutes an independent risk factor for negative outcomes [9]. As carbohydrates are generally the most common source of dietary energy, it is therefore intuitive to ascribe to them the major responsibility for higher risk of obesity. However, numerous studies failed in assessing such a relationship, making evidence on this matter difficult to understand [10]. In fact, whether carbohydrates come in the form of whole or refined grains, has been suggested to be relevant in the explanation for the uncertainty of the findings from the studies exploring the association between total carbohydrate intake and weight status [10]. Similar concerns regard dietary guidelines involving protein intake. In fact, there is adequate evidence (from randomized controlled trials, RCTs) showing that substitution of protein for carbohydrate may favorably affect weight management and improve cardiometabolic biomarkers [11,12]. However, the type of protein may have specific effects, and other studies reported that differences between animal and plant protein occur when exploring long-term association with metabolic disorders [13] and overall mortality risk [14,15]. Final important different effects have been recently associated with various dietary fats. The failure of “low-fat diets” in prolonging the lifespan [16] and the discovery of the beneficial effects of (relatively) “high-fat diets”, such as the Mediterranean dietary pattern [17,18], underlined the need to better distinguish between dietary fats and their effects on health. There is evidence that mono- and polyunsaturated fatty acids (MUFA and PUFA, respectively), including omega-3 PUFA from fish and vegetable, may exert a number of beneficial effects compared to saturated or, even worse, trans-fatty acids [19,20]. However, evidence on unhealthy effects of saturated fatty acids, per se, is still controversial, and further research is needed, overall, to better distinguish between subgroups of macronutrients, as aforementioned.

National and international organizations are dealing with current evidence on the association between diet and health. Experts boards continuously draft and update dietary guidelines and recommendations in order to prevent, on a large population scale, common non-communicable diseases. However, data on actual food consumption in cohort studies is often underrated and scarcely described. The aim of the present study was to describe the intake of major food groups and macronutrients in a sample of southern Italian adults, and to analyze the differences in consumption between sexes and age groups. Additionally, the study aimed to explore the correlation between the variables investigated and the association with weight status of participants.

2. Materials and Methods

2.1. Study Population

A sample of 2044 men and women aged 18 or more was collected between 2014 and 2016 in the main districts of the city of Catania, southern Italy, to build the Mediterranean healthy eating, ageing, and lifestyle (MEAL) cohort. A detailed description of the study protocol is published elsewhere [21]. Briefly, the theoretical sample size was set at 1500 individuals to provide a specific relative precision of 5% (type I error, 0.05; type II error, 0.10), taking into account an anticipated 70% participation rate. The sampling technique included stratification by municipality area, age, and sex of inhabitants, and randomization into subgroups, with randomly selected general practitioners being the sampling units, and individuals registered to them comprising the final sample units. Out of 2405 individuals invited, the final sample size was 2044 participants (response rate of 85%). All participants were informed about the aims of the study and provided a written informed consent. All the study procedures were carried out in accordance with the Declaration of Helsinki (1989) of the World Medical Association. The study protocol has been approved by the concerning ethical committee (protocol number: 802/23 December 2014).

2.2. Data Collection

Data was collected by a face-to-face computer-assisted personal interview using tablet computers. In order to visualize the response options, participants were provided of a paper copy of the questionnaire, however, final answers were filled in by the interviewer directly on the digital device (tablet computer). The demographic and anthropometric data were collected according to standard procedures [22]. Regarding anthropometric measurements, height was measured to the nearest 0.5 cm without shoes, with the back square against the wall tape, eyes looking straight ahead, with a right-angle triangle resting on the scalp and against the wall. Weight was measured with a lever balance to the nearest 100 g without shoes and with light undergarments. Body mass index (BMI) was finally calculated [23].

2.3. Dietary Assessment

A food frequency questionnaire (FFQ) previously validated for the Sicilian population was administered to collect information on food consumption [24,25]. The long version of the FFQ used to retrieve the dietary estimates presented in this study consisted of 110 food items; intake of seasonal foods referred to consumption during the period in which the food was available, and then adjusted by its proportional intake in one year. Following the identification of the food frequency consumption, the estimated intakes were converted into daily intake (g/day) and were used to calculate energy and macronutrient content based on online food composition databases (such as the Research Center for Foods and Nutrition CREA—Consiglio per la ricerca in agricoltura e l’analisi dell’economia agraria) [26]. Nutrient intake was finally adjusted for total energy intake (kcal/day) using the residual method [27]. FFQs with unreliable intakes (we arbitrarily considered <1000 or >6000 kcal/day as realistically unreliable energy intake; n = 107) as well as missing items for the purposes of this study (n = 99) were excluded from the analyses, leaving a total of 1838 individuals included in the analysis.

2.4. Dietary Recommendations

To investigate agreement with dietary recommendations, we used the European proposed values for macronutrient intake of the European Food Safety Agency (EFSA) [28] and those proposed by the Italian Society of Human Nutrition “Livelli di Assunzione di Riferimento di Nutrienti” (LARN) [29], while for major food groups we used the World Health Organization (WHO) recommendations [30].

2.5. Statistical Analysis

Frequencies are presented as absolute numbers and percentages; continuous variables are presented as means and standard errors, medians and ranges. Differences between groups for continuous variables were compared with Student’s t test and ANOVA for continuous variables distributed normally, and Mann–Whitney U test and Kruskal–Wallis test for variables not normally distributed. Correlations among major food groups were tested through calculation of Pearson’s or Spearman’s correlation coefficients, depending on the distribution of the variable. Linear association between variables of interest and BMI levels were tested through linear regression analyses. All reported P values were based on two-sided tests and compared to a significance level of 5%. SPSS 17 (SPSS Inc., Chicago, IL, USA) software was used for all the statistical calculations.

3. Results

Table 1 shows the distribution of total energy, macronutrient and fiber intake in the study cohort, by sex and age groups. No significant differences of mean consumption of macronutrients between sexes were found. All macronutrients were mostly equally distributed, and even though men had slightly higher intake of cholesterol and total protein, the difference was not significant compared to women. In contrast, younger individuals consumed significantly more animal protein than older ones.

Table 1.

Total, sex, and age group-specific consumption of macronutrients and fiber in the study participants of the Mediterranean healthy eating, ageing, and lifestyle (MEAL) study (n = 1838). * denotes p < 0.05.

Total <20 years 20 < years < 50 50 < years < 70 >70 years
n Mean (SE) Median (Range) n Mean (SE) Median (Range) n Mean (SE) Median (Range) n Mean (SE) Median (Range) n Mean (SE) Median (Range)
Total Energy
Total 1838 2022.80 (15.30) 1927.63 (1000.80, 4974.01) 53 2037.36 (79.24) 1986.05 (1025.75, 3728.68) 963 2027.51 (21.91) 1930.64 (1000.80, 4865.38) 597 2038.93 (27.00) 1920.70 (1015.33, 4974.01) 225 1956.43 (36.66) 1923.88 (1010.31, 3379.32)
Men 772 2054.16 (25.38) 1939.18 (1012.84, 4974.01) 30 2101.73 (111.24) 2048.38 (1025.75, 3728.68) 384 2047.09 (37.99) 1907.56 (1012.84, 4865.38) 265 2076.45 (43.57) 1938.57 (1015.33, 4974.01) 93 2004.48 (56.27) 2025.94 (1019.88, 3334.93)
Women 1066 2000.09 (18.90) 1915.60 (1000.80, 3915.46) 23 1953.41 (111.15) 1873.20 (1133.85, 3547.77) 579 2014.52 (26.35) 1942.98 (1000.80, 3915,46) 332 2008.99 (33.84) 1902.58 (1016.84, 3911.26) 132 1922.58 (48.27) 1887.88 (1010.31, 3379.32)
Saturated fat
Total 1838 23.58 (0.23) 22.17 (6.49, 80.45) 53 25.55 (1.29) 26.51 (11.85, 55.77) 963 23.71 (0.33) 22.11 (6.49, 80.45) 597 23.52 (0.41) 21.88 (6.91, 74.26) 225 22.69 (0.55) 22.87 (6.60, 45.05)
Men 772 23.86 (0.38) 22.09 (6.60, 80.45) 30 27.89 (1.80) 26.80 (14.82, 55.77) 384 23.45 (0.55) 20.88 (8.61, 80.45) 265 24.04 (0.64) 22.20 (9.47, 74.26) 93 23.75 (0.88) 24.47 (6.60, 44.82)
Women 1066 23.37 (0.29) 22.33 (6.49, 62.82) 23 22.50 (1.64) 21.09 (11.85, 34.77) 579 23.88 (0.40) 23.00 (6.49, 62.82) 332 23.11 (0.52) 21.46 (6.91, 61.79) 132 21.94 (0.69) 21.65 (6.97, 45.05)
Monounsaturated fat
Total 1838 25.30 (0.21) 24.13 (7.29, 93.85) 53 27.41 (1.23) 25.73 (13.19, 63.32) 963 25.39 (0.29) 24.04 (7.29, 80.32) 597 25.28 (0.38) 23.99 (11.01, 93.85) 225 24.48 (0.49) 24.07 (7.61, 47.14)
Men 772 25.62 (0.36) 23.94 (7.61, 93.85) 30 29.12 (1.83) 26.56 (15.20, 63.32) 384 25.12 (0.51) 23.19 (11.71, 80.32) 265 25.98 (0.66) 24.26 (11.77, 93.85) 93 25.56 (0.80) 26.43 (7.61, 47.14)
Women 1066 25.07 (0.25) 24.19 (7.29, 62.38) 23 25.18 (1.45) 24.10 (13.19, 41.50) 579 25.57 (0.35) 24.74 (7.29, 62.38) 332 24.72 (0.43) 23.67 (11.01, 55.05) 132 23.71 (0.60) 23.04 (11.03, 44.77)
Total omega-6 fatty acids
Total 1838 9.92 (0.10) 9.21 (3.08, 55.51) 53 10.33 (0.61) 8.94 (3.36, 27.60) 963 9.97 (0.14) 9.21 (3.08, 30.64) 597 10.03 (0.19) 9.22 (3.29, 55.51) 225 9.29 (0.21) 9.13 (3.64, 20.44)
Men 772 9.99 (0.16) 9.09 (3.08, 55.51) 30 10.49 (0.86) 9.43 (3.36, 27.60) 384 9.93 (0.23) 8.96 (3.08, 29.06) 265 10.19 (0.31) 9.18 (3.29, 55.51) 93 9.54 (0.30) 9.43 (4.01, 16.09)
Women 1066 9.87 (0.12) 9.27 (3.61, 32.07) 23 10.11 (0.89) 8.92 (4.89, 23.60) 579 10.00 (0.17) 9.37 (3.61, 30.64) 332 9.91 (0.23) 9.24 (3.69, 32.07) 132 9.12 (0.29) 9.03 (3.64, 20.44)
Seafood omega-3 fat
Total 1838 0.53 (0.01) 0.38 (0.00, 5.24) 53 0.55 (0.05) 0.42 (0.00, 1.56) 963 0.52 (0.02) 0.36 (0.00, 5.24) 597 0.56 (0.02) 0.41 (0.01, 5.06) 225 0.53 (0.03) 0.43 (0.03, 3.26)
Men 772 0.53 (0.02) 0.38 (0.00, 5.24) 30 0.49 (0.07) 0.36 (0.00, 1.34) 384 0.50 (0.03) 0.34 (0.00, 5.24) 265 0.58 (0.04) 0.44 (0.05, 5.06) 93 0.56 (0.06) 0.42 (0.05, 3.26)
Women 1066 0.53 (0.02) 0.39 (0.00, 3.97) 23 0.63 (0.08) 0.56 (0.17, 1.56) 579 0.53 (0.02) 0.38 (0.00, 3.97) 332 0.54 (0.03) 0.38 (0.01, 3.05) 132 0.51 (0.04) 0.43 (0.03, 2.98)
Plant omega-3 fat
Total 1838 1.17 (0.01) 1.06 (0.39, 5.66) 53 1.23 (0.08) 1.08 (0.51, 3.78) 963 1.17 (0.02) 1.06 (0.41, 5.51) 597 1.20 (0.02) 1.06 (0.42, 5.66) 225 1.10 (0.03) 1.05 (0.39, 2.79)
Men 772 1.17 (0.02) 1.06 (0.41, 4.48) 30 1.25 (0.11) 1.09 (0.60, 3.78) 384 1.17 (0.03) 1.02 (0.41, 3.93) 265 1.18 (0.03) 1.07 (0.46, 4.48) 93 1.14 (0.04) 1.13 (0.46, 2.32)
Women 1066 1.18 (0.02) 1.06 (0.39, 5.66) 23 1.20 (0.12) 0.90 (0.51, 2.82) 579 1.18 (0.02) 1.09 (0.42, 5.51) 332 1.21 (0.03) 1.05 (0.42, 5.66) 132 1.08 (0.04) 1.02 (0.39, 2.79)
Trans fatty acid
Total 1838 32.31 (0.28) 30.83 (10.30, 135.12) 53 34.60 (1.69) 31.68 (16.68, 84.81) 963 32.38 (0.39) 30.82 (10.30, 100.42) 597 32.46 (0.50) 31.02 (12.26, 135.12) 225 31.09 (0.62) 30.07 (10.99, 59.82)
Men 772 32.63 (0.47) 30.63 (10.99, 135.12) 30 36.18 (2.50) 32.79 (17.03, 84.81) 384 32.05 (0.66) 29.66 (11.97, 100.42) 265 33.19 (0.88) 31.42 (12.26, 135.12) 93 32.26 (1.00) 32.83 (10.99, 59.82)
Women 1066 32.08 (0.33) 30.87 (10.30, 84.75) 23 32.55 (2.12) 30.14 (16.68, 59.93) 579 32.60 (0.47) 31.38 (10.30, 84.75) 332 31.88 (0.58) 30.35 (14.88, 68.99) 132 30.28 (0.78) 29.62 (13.84, 55.51)
Dietary cholesterol
Total 1838 187.55 (1.93) 175.00 (17.29, 921.07) 53 198.15 (9.17) 191.00 (87.71, 371.79) 963 187.15 (2.74) 173.89 (17.29, 921.07) 597 188.24 (3.44) 172.62 (59.94, 876.81) 225 184.84 (4.92) 180.36 (42.92, 521.31)
Men 772 191.35 (3.22) 174.09 (42.92, 921.07) 30 206.26 (12.70) 206.42 (102.85, 371.79) 384 186.61 (4.64) 164.24 (56.99, 921.07) 265 195.15 (5.78) 176.70 (63.53, 876.81) 93 195.29 (7.83) 189.94 (42.92, 521.31)
Women 1066 184.80 (2.37) 176.30 (17.29, 594.94) 23 187.57 (13.09) 177.00 (87.71, 333.42) 579 187.51 (3.35) 181.67 (17.29, 594.94) 332 182.73 (4.10) 164.69 (59.94, 487.38) 132 177.65 (6.26) 169.40 (56.35, 475.25)
Total protein
Total 1838 83.98 (0.66) 80.02 (29.27, 332.66) 53 86.24 (3.14) 83.52 (33.65, 138.33) 963 84.27 (0.96) 79.31 (29.27, 332.66) 597 83.89 (1.14) 80.18 (29.35, 303.04) 225 82.41 (1.63) 80.23 (29.35, 185.58)
Men 772 85.22 (1.11) 79.67 (33.65, 332.66) 30 88.27 (4.03) 89.30 (33.65, 137.17) 384 85.01 (1.63) 79.21 (43.56, 332.66) 265 85.59 (1.96) 79.54 (37.92, 303.04) 93 84.07 (2.56) 80.73 (39.51, 185.58)
Women 1066 83.07 (0.81) 80.23 (29.27, 215.96) 23 83.59 (5.01) 78.86 (50.69, 138.33) 579 83.78 (1.17) 80.38 (29.27, 215.96) 332 82.53 (1.32) 80.24 (29.35, 185.93) 132 81.25 (2.12) 79.47 (29.35, 156.18)
Animal protein
Total 1838 25.65 (0.44) 22.75 (0.00, 449.25) 53 30.68 (1.83) 30.97 (6.63, 68.99) 963 26.03 (0.68) 23.08 (0.00, 449.25) 597 25.73 (0.74) 22.63 (0.00, 238.85) 225 22.67 (0.77) * 18.98 (3.05, 61.61)
Men 772 26.46 (0.67) 23.07 (0.00, 238.85) 30 31.26 (2.85) 29.70 (6.63, 68.99) 384 26.88 (0.91) 23.55 (0.00, 161.09) 265 26.46 (1.32) 23.20 (0.00, 238.85) 93 23.13 (1.09) 20.69 (6.23, 54.31)
Women 1066 25.07 (0.59) 22.38 (0.00, 449.25) 23 29.93 (2.08) 31.34 (7.14, 47.55) 579 25.46 (0.95) 22.91 (0.00, 449.25) 332 25.15 (0.81) 22.19 (5.25, 148.42) 132 22.35 (1.07) 18.71 (3.05, 61.61)
Dairy protein
Total 1838 14.01 (0.21) 12.24 (0.00, 67.63) 53 14.84 (1.02) 12.69 (0.00, 28.48) 963 14.19 (0.30) 11.78 (0.00, 67.63) 597 13.75 (0.34) 12.85 (0.00, 52.81) 225 13.69 (0.53) 13.09 (0.00, 50.39)
Men 772 13.59 (0.32) 11.60 (0.00, 67.63) 30 13.69 (1.55) 11.91 (0.00, 28.48) 384 13.70 (0.52) 10.76 (0.00, 67.63) 265 13.17 (0.48) 13.08 (0.00, 44.02) 93 14.28 (0.78) 15.25 (0.00, 42.42)
Women 1066 14.31 (0.27) 12.71 (0.00, 54.33) 23 16.35 (1.17) 15.53 (8.52, 27.50) 579 14.52 (0.37) 12.77 (0.00, 54.33) 332 14.21 (0.47) 12.39 (0.00, 52.81) 132 13.27 (0.72) 12.04 (0.00, 50.39)
Plant protein
Total 1838 44.71 (0.41,) 41.90 (6.90, 178.86) 53 44.13 (1.89) 43.91 (6.90, 86.56) 963 45.11 (0.61) 41.92 (13.67, 178.86) 597 44.69 (0.70) 41.88 (11.96, 140.10) 225 43.16 (0.99) 40.57 (15.11, 83.01)
Men 772 45.35 (0.67) 42.14 (6.90, 178.86) 30 44.75 (2.53) 45.04 (6.90, 70.78) 384 45.93 (1.02) 42.46 (13.67, 178.86) 265 45.19 (1.11) 41.79 (16.35, 140.10) 93 43.64 (1.55) 40.55 (17.71, 82.61)
Women 1066 44.24 (0.52) 41.80 (11.96, 117.03) 23 43.32 (2.91) 40.89 (25.91, 86.56) 579 44.57 (0.74) 41.69 (16.36, 117.03) 332 44.29 (0.89) 42.31 (11.96, 100.77) 132 42.82 (1.30) 40.62 (15.11, 83.01)
Total carbohydrates
Total 1838 296.02 (2.56) 274.18 (100.18, 897.76) 53 289.04 (13.47) 275.29 (119.11, 590.50) 963 296.17 (3.69) 271.23 (109.87, 897.76) 597 300.52 (4.44) 278.50 (100.18, 673.97) 225 285.14 (6.31) 268.17 (114.52, 560.82)
Men 772 300.69 (4.13) 278.62 (109.87, 897.76) 30 290.46 (17.43) 275.52 (119.11, 482.17) 384 302.36 (6.33) 276.32 (109.87, 897.76) 265 303.96 (6.78) 286.63 (126.94, 673.97) 93 287.83 (9.23) 269.57 (132.74, 504.86)
Women 1066 292.64 (3.25) 270.39 (100.18, 670.72) 23 287.19 (21.57) 270.44 (137.86, 590.50) 579 292.06 (4.47) 270.50 (112.30, 670.72) 332 297.77 (5.86) 272.22 (100.18, 608.56) 132 283.24 (8.60) 265.18 (114.52, 560.82)
Fiber
Total 1838 31.69 (0.33) 29.30 (2.81, 150.50) 53 29.77 (1.55) 27.98 (2.81, 57.65) 963 31.81 (0.50) 29.11 (6.63, 150.50) 597 32.09 (0.54) 30.43 (5.46, 100.03) 225 30.53 (0.79) 29.26 (8.31, 81.77)
Men 772 32.25 (0.54) 29.52 (2.81, 150.50) 30 30.87 (2.18) 28.23 (2.81, 57.65) 384 32.23 (0.86) 28.34 (9.48, 150.50) 265 32.65 (0.86) 30.39 (8.83, 100.03) 93 31.65 (1.14) 30.36 (11.01, 57.97)
Women 1066 31.28 (0.42) 29.23 (5.46, 85.11) 23 28.34 (2.17) 26.42 (12.77, 56.68) 579 31.54 (0.60) 29.28 (6.63, 85.11) 332 31.63 (0.68) 30.46 (5.46, 78.36) 132 29.73 (1.08) 27.75 (8.31, 81.77)

The description of consumption of major food group from animal source is shown in Table 2. Regarding differences between sex, men reported consuming significantly more total processed meats and less eggs than women (18.00 g/day vs. 14.54 g/day and 2.04 g/day vs. 2.62 g/day, respectively). Difference in egg consumption was also found between age groups, as intake significantly increased with age. Table 3 describes distribution of intake of plant food groups between sex and age groups. No significant differences were evident between sexes, but a significantly lower intake of fruit in the younger age group compared to older ones was found.

Table 2.

Total, sex, and age group-specific consumption of animal food groups in the study participants of the MEAL study (n = 1838). * denotes p < 0.05, ** denotes p < 0.001.

Total <20 years 20 < years < 50 50 < years < 70 >70 years
n Mean (SE) Median (Range) n Mean (SE) Median (Range) n Mean (SE) Median (Range) n Mean (SE) Median (Range) n Mean (SE) Median (Range)
Total processed meats
Total 1838 15.99 (0.43) ** 11.50 (0.00, 168.00) 53 16.82 (1.92) 17.05 (0.00, 53.00) 963 17.57 (0.58) 11.50 (0.00, 129.50) 597 14.54 (0.82) 7.00 (0.00, 168.00) 225 12.85 (0.99) 7.00 (0.00, 157.00)
Men 772 18.00 (0.75) 11.50 (0.00, 168.00) 30 18.68 (2.67) 18.00 (0.00, 53.00) 384 19.12 (1.02) 11.50 (0.00, 129.50) 265 17.63 (1.49) 11.50 (0.00, 168.00) 93 14.24 (1.36) 7.85 (0.00, 50.00)
Women 1066 14.52 (0.49) 7.42 (0.00, 157.00) 23 14.40 (2.73) 7.00 (1.50, 53.00) 579 16.54 (0.68) 11.50 (0.00, 99.35) 332 12.08 (0.84) 7.00 (0.00, 129.50) 132 11.87 (1.39) 7.00 (0.00, 157.00)
Unprocessed meats
Total 1838 33.78 (0.59) 28.00 (0.00, 286.00) 53 38.01 (4.06) 28.00 (0.00, 114.00) 963 33.58 (0.76) 28.00 (0.00, 136.00) 597 33.78 (1.10) 28.00 (0.00, 286.00) 225 33.67 (1.85) 28.00 (0.00, 164.00)
Men 772 34.65 (0.65) 28.00 (0.00, 286.00) 30 35.06 (5.18) 28.00 (0.00, 100.00) 384 33.58 (1.19) 28.00 (0.00, 128.00) 265 36.23 (1.80) 28.00 (0.00, 286.00) 93 34.40 (2.96) 28.00 (3.00, 164.00)
Women 1066 33.16 (0.75) 28.00 (0.00, 164.00) 23 41.86 (6.51) 28.00 (0.00, 114.00) 579 33.58 (0.99) 28.00 (0.00, 136.00) 332 31.82 (1.34) 28.00 (0.00, 136.00) 132 33.16 (2.36) 28.00 (0.00, 164.00)
Total seafood
Total 1838 60.81 (1.28) 47.40 (0.00, 784.70) 53 60.35 (5.30) 54.70 (0.00, 145.00) 963 59.17 (1.85) 45.00 (0.00, 784.70) 597 63.71 (2.19) 50.40 (0.00, 442.00) 225 60.26 (3.45) 48.10 (0.00, 448.00)
Men 772 61.07 (2.18) 46.80 (0.00, 784.70) 30 56.56 (7.47) 46.50 (0.00, 142.00) 384 58.41 (3.28) 43.30 (0.00, 784.70) 265 65.84 (3.55) 54.10 (3.00, 442.00) 93 59.91 (6.03) 45.00 (6.00, 448.00)
Women 1066 60.62 (1.55) 48.00 (0.00, 408.00) 23 65.29 (7.40) 58.40 (12.70, 145.00) 579 59.68 (2.18) 47.40 (0.00, 408.00) 332 62.01 (2.72) 47.70 (0.00, 373.70) 132 60.50 (4.09) 50.45 (0.00, 250.00)
Eggs
Total 1838 2.38 (0.11) * 0.77 (0.00, 24.75) 53 1.84 (0.38) 0.77 (0.00, 13.75) 963 1.92 (0.12) 0.77 (0.00, 24,75) 597 2.80 (0.22) 0.77 (0.00, 24.75) 225 3.30 (0.38) ** 0.77 (0.00, 24.75)
Men 772 2.04 (0.14) 0.77 (0.00, 24.75) 30 1.72 (0.48) 0.77 (0.00, 13.75) 384 1.42 (0.11) 0.77 (0.00, 24.75) 265 2.27 (0.27) 0.77 (0.00, 24.75) 93 4.08 (0.67) 1.98 (0.00, 24.75)
Women 1066 2.62 (0.16) 0.77 (0.00, 24.75) 23 2.00 (0.61) 0.77 (0.16, 13.75) 579 2.26 (0.19) 0.77 (0.00, 24.75) 332 3.23 (0.32) 0.77 (0.00, 24.75) 132 2.75 (0.44) 0.77 (0.00, 24.75)
Cheese
Total 1838 53.45 (0.80) 46.70 (0.00, 328.01) 53 56.29 (4.27) 50.20 (15.51, 147.47) 963 53.68 (1.13) 46.82 (0.00, 310.01) 597 53.49 (1.43) 46.08 (0.00, 328.01) 225 51.74 (2.02) 46.33 (0.00, 231.88)
Men 772 55.16 (1.30) 47.53 (0.00, 328.01) 30 64.43 (5.02) 52.67 (26.48, 147.47) 384 53.49 (1.86) 44.85 (1.50, 310.01) 265 56.61 (2.35) 48.63 (0.00, 328.01) 93 54.98 (3.13) 52.08 (0.00, 123.20)
Women 1066 52.22 (1.01) 45.82 (0.00, 296.01) 23 45.69 (6.84) 31.43 (15.51, 138.88) 579 53.80 (1.42) 47.50 (0.00, 296.01) 332 51.00 (1.74) 43.82 (0.00, 213.71) 132 49.46 (2.64) 45.72 (0.00, 231.88)
Yoghurt
Total 1838 28.79 (1.07) 8.38 (0.00, 312.50) 53 37.23 (9.20) 8.38 (0.00, 312.50) 963 26.83 (1.36) 8.38 (0.00, 312.50) 597 29.71 (1.88) 8.38 (0.00, 312.50) 225 32.77 (3.57) 8.38 (0.00, 312.50)
Men 772 28.27 (1.66) 8.38 (0.00, 312.50) 30 50.05 (14.85) 17.50 (0.00, 312.50) 384 26.31 (2.09) 8.38 (0.00, 312.50) 265 27.70 (2.79) 8.38 (0.00, 312.50) 93 30.96 (5.28) 8.38 (0.00, 312.50)
Women 1066 29.17 (1.40) 8.38 (0.00, 312.50) 23 20.51 (7.72) 0.00 (0.00, 125.00) 579 27.18 (1.79) 8.38 (0.00, 312.50) 332 31.32 (2.55) 8.38 (0.00, 312.50) 132 34.04 (4.83) 8.38 (0.00, 312.50)
Reduced fat milk
Total 1838 124.71 (3.68) 90.00 (0.00, 1125.00) 53 129.83 (19.42) 90.00 (0.00, 625.00) 963 127.22 (5.16) 90.00 (0.00, 1125,00) 597 118.01 (6.28) 90.00 (0.00, 1125.00) 225 130.56 (10.82) 90.00 (0.00, 625.00)
Men 772 121.70 (5.48) 90.00 (0.00, 1125.00) 30 125.20 (20.49) 90.00 (0.00, 250.00) 384 130.70 (8.31) 90.00 (0.00, 1125.00) 265 107.36 (8.60) 35.00 (0.00, 625.00) 93 124.31 (15.55) 90.00 (0.00, 625.00)
Women 1066 126.89 (4.95) 90.00 (0.00, 1125.00) 23 135.87 (36.48) 90.00 (0.00, 625.00) 579 124.91 (6.59) 90.00 (0.00, 625.00) 332 126.52 (8.94) 90.00 (0.00, 1125.00) 132 134.96 (14.88) 90.00 (0.00, 625.00)

Table 3.

Total, sex, and age group-specific consumption of plant food groups in the study participants of the MEAL study (n = 1838). * denotes p < 0.05.

Total <20 years 20 < years < 50 50 < years < 70 >70 years
n Mean (SE) Median (Range) n Mean (SE) Median (Range) n Mean (SE) Median (Range) n Mean (SE) Median (Range) n Mean (SE) Median (Range)
Fruits
Total 1838 395.92 (7.43) 295.13 (0.00, 2801.47) 53 335.51 (28.08) 303.58 (0.00, 951.57) 963 402.02 (11.09) 295.09 (0.00, 2801.47) 597 412.67 (12.52) 318.32 (0.00, 1822.92) 225 339.64 (16.42) 268.78 (0.00, 1545.11)
Men 772 410.55 (11.81) 305.19 (0.00, 2801.47) 30 375.82 (44.50) 326.02 (0.00, 951.57) 384 408.13 (18.20) 302.11 (0.00, 2801.47) 265 430.97 (19.18) 308.70 (0.60, 1822.92) 93 373.56 (27.59) 289.75 (18.08, 1207.35)
Women 1066 385.33 (9.54) 285.57 (0.00, 2305.08) 23 282.93 (25.86) 257.78 (72,56, 541.09) 579 397.96 (13.95) 291.35 (0.00, 2305.08) 332 398.06 (16.50) 320.91 (0.00, 1791.90) 132 315.74 (19.98) 253.81 (0.00, 1545.11)
Non-starchy vegetables
Total 1838 219.48 (3.22) 195.86 (0.00, 1506.75) 53 250.47 (28.28) 192.78 (1.13, 1236.37) 963 214.51 (4.54) 189.54 (0.00, 1506.75) 597 222.71 (5.29) 199.63 (0.00, 1254.12) 225 224.87 (8.58) 217.68 (0.00, 1268.28)
Men 772 221.43 (5.04) 195.80 (0.00, 1506.75) 30 254.14 (31.47) 204.14 (1.13, 799.94) 384 211.29 (7.58) 182.75 (0.00, 1506.75) 265 227.06 (7.88) 203.94 (1.50, 709.37) 93 236.69 (12.51) 235.67 (36.69, 567.68)
Women 1066 218.07 (4.19) 195.86 (0.00, 1268.28) 23 245.68 (51.48) 183.20 (33.78, 1236.37) 579 216.65 (5.63) 192.75 (0.00, 1146.28) 332 219.23 (7.15) 197.86 (0.00, 1254.12) 132 216.54 (11.56) 208.32 (0.0, 1268.28)
Other starchy vegetables
Total 1838 16.33 (0.44) 14.00 (0.00, 450.90) 53 15.88 (2.06) 14.00 (0.00, 66.00) 963 17.24 (0.72) 14.00 (0.00, 450.90) 597 15.22 (0.57) 14.00 (0.00, 130.00) 225 15.46 (0.87) 14.00 (0.00, 66.00)
Men 772 17.07 (0.80) 14.00 (0.00, 450.90) 30 17.08 (2.94) 14.45 (0.00, 66.00) 384 18.04 (1.43) 14.00 (0.00, 450.90) 265 16.03 (0.93) 14.00 (0.00, 130.00) 93 16.00 (1.34) 14.00 (0.00, 66.00)
Women 1066 15.80 (0.48) 14.00 (0.00, 130.00) 23 14.31 (2.85) 8.71 (0.00, 46.80) 579 16.72 (0.73) 14.00 (0.00, 130.00) 332 14.57 (0.72) 14.00 (0.00, 74.80) 132 15.08 (1.14) 14.00 (0.00, 66.00)
Beans and legumes
Total 1838 35.61 (0.88) 23.70 (0.00, 655.33) 53 35.35 (4.78) 23.10 (0.00, 130.23) 963 36.69 (1.32) 24.00 (0.00, 655.33) 597 33.69 (1.33) 23.70 (0.00, 325.33) 225 36.15 (2.48) 22.33 (0.00, 184.00)
Men 772 36.33 (1.48) 23.85 (0.00, 655.33) 30 36.18 (6.39) 27.17 (0.00, 129.00) 384 37.19 (2.33) 24.10 (0.00, 655.33) 265 34.65 (2.15) 24.70 (0.00, 325.33) 93 37.58 (4.09) 22.33 (3.00, 179.00)
Women 1066 35.09 (1.08) 23.40 (0.00, 210.70) 23 34.27 (7.35) 22.33 (5.23, 130.23) 579 36.36 (1.56) 23.70 (0.00, 210.70) 332 32.91 (1.67) 23.40 (0.00, 210.70) 132 35.14 (3.10) 22.28 (0.00, 184.00)
Nuts and seeds
Total 1838 20.30 (0.73) 11.52 (0.00, 408.40) 53 19.77 (4.48) 9.05 (0.00, 190.00) 963 19.87 (0.98) 10.35 (0.00, 408.40) 597 21.89 (1.42) 12.75 (0.00, 408.40) 225 18.10 (1.60) 10.05 (0.00, 153.40)
Men 772 20.91 (1.21) 10.40 (0.00, 408.40) 30 23.29 (7.54) 7.71 (0.00, 190.00) 384 19.42 (1.92) 7.94 (0.00, 408.40) 265 22.69 (1.70) 13.40 (0.00, 190.00) 93 21.20 (3.05) 10.35 (0.00, 153.40)
Women 1066 19.87 (0.90) 11.70 (0.00, 408.40) 23 15.17 (3.16) 11.70 (0.00, 68.80) 579 20.16 (1.02) 12.73 (0.00, 190.00) 332 21.26 (2.17) 11.52 (0.00, 408.40) 132 15.91 (1.66) 9.92 (0.00, 101.48)
Potatoes
Total 1838 25.52 (0.58) 17.75 (0.00, 450.75) 53 31.09 (5.13) 24.20 (0.00, 253.00) 963 25.86 (0.85) 17.75 (0.00, 450.75) 597 24.98 (0.95) 17.00 (0.00, 169.20) 225 24.21 (1.30) 17.00 (0.00, 106.70)
Men 772 26.48 (0.87) 17.75 (0.00, 180.00) 30 30.72 (4.27) 24.20 (0.00, 100.00) 384 26.17 (1.22) 17.50 (0.00, 180.00) 265 26.56 (1.61) 17.00 (0.00, 169.20) 93 26.23 (2.06) 20.70 (0.00, 103.00)
Women 1066 24.82 (0.78) 17.50 (0.00, 450.75) 23 31.56 (10.58) 20.70 (0.00, 253.00) 579 25.65 (1.16) 18.68 (0.00, 450.75) 332 23.73 (1.12) 17.00 (0.00, 136.00) 132 22.78 (1.68) 16.34 (0.00, 106.70)
Whole grains
Total 1838 27.38 (1.19) 3.00 (0.00, 330.00) 53 26.21 (5.42) 1.01 (0.00, 151.20) 963 29.34 (1.74) 3.00 (0.00, 330.00) 597 25.90 (1.99) 3.00 (0.00, 298.70) 225 23.21 (3.01) 2.10 (0.00, 270.36)
Men 772 26.56 (1.77) 3.00 (0.00, 330.00) 30 37.73 (8.69) 9.00 (0.00, 151.20) 384 30.52 (2.78) 5.40 (0.00, 330.00) 265 20.54 (2.58) 3.00 (0.00, 298.70) 93 23.75 (4.59) 3.00 (0.00, 252.85)
Women 1066 27.97 (1.59) 2.10 (0.00, 330.00) 23 11.20 3.50 0.45 (0.00, 46.80) 579 28.55 (2.23) 3.00 (0.00, 330.00) 332 30.17 (2.91) 3.00 (0.00, 298.70) 132 22.84 (4.00) 0.73 (0.00, 270.36)
Refined grains
Total 1838 214.10 (3.04) 184.15 (3.00, 909.26) 53 197.89 (17.80) 174.05 (3.00, 576.71) 963 210.54 (4.15) 180.89 (4.50, 909.26) 597 220.89 (5.51) 189.00 (6.70, 909.26) 225 215.19 (8.41) 185.05 (11.28, 630.03)
Men 772 217.24 (4.60) 187.39 (3.00, 909.26) 30 169.00 (20.22) 173.83 (3.00, 420.10) 384 217.19 (6.47) 186.51 (12.60, 589.85) 265 226.87 (8.25) 196.70 (11.28, 909.26) 93 205.57 (11.86) 180.31 (25.20, 541.06)
Women 1066 211.83 (4.06) 182.40 (4.50, 909.26) 23 235.58 (30.14) 173.83 (3.00, 420.10) 579 206.12 (5.41) 179.66 (4.50, 909.26) 332 216.12 (7.41) 182.60 (6.70, 696.60) 132 221.98 (11.65) 187.62 (11.28, 630.03)

The correlation between intake of all major food groups is shown in Table 4. A correlation between fruit, vegetables, legumes, and seafood was found; however, the latter were also correlated with all other animal products, including cheese, eggs, and processed and unprocessed red meats. Whole and refined grain intake was correlated with yoghurt, while nuts and seeds were correlated with both meat and vegetable product intake. However, most of the significant associations were very weak and arguably negligible.

Table 4.

Pearson/Spearman correlation coefficients between major food groups intake. * denotes p < 0.05, ** denotes p < 0.001.

Total Processed Meats Unprocessed Red Meats Total Seafood Eggs Cheese Yoghurt Fruits Non-Starchy Vegetables Potatoes Other Starchy Vegetables Beans and Legumes Nuts and Seeds Refined Grains Whole Grains
Total processed meats 1 - - - - - - - - - - - - -
Unprocessed red meats 0.217 ** 1 - - - - - - - - - - - -
Total seafood 0.162 ** 0.072 ** 1 - - - - - - - - - - -
Eggs 0.003 0.179 ** 0.093 ** 1 - - - - - - - - - -
Cheese 0.251 ** 0.200 ** 0.189 ** 0.094 ** 1 - - - - - - - - -
Yoghurt −0.010 −0.032 0.145 ** 0.034 0.0123 ** 1 - - - - - - - -
Fruits 0.004 −0.004 0.121 ** −0.010 0.074 ** 0.113 ** 1 - - - - - -
Non-starchy vegetables −0.002 −0.037 0.209 ** 0.016 0.167 ** 0.138 ** 0.297 ** 1 - - - - - -
Potatoes 0.316 ** 0.085 ** 0.151 ** 0.084 ** 0.305 ** 0.063 ** 0.073 ** 0.075 ** 1 - - - - -
Other starchy vegetables 0.075 ** −0.029 0.203 ** 0.018 0.138 ** 0.073 ** 0.258 ** 0.399 ** 0.144 ** 1 - - - -
Beans and legumes 0.044 0.000 0.268 ** 0.041 0.108 ** 0.114 ** 0.203 ** 0.370 ** 0.052 * 0.211 ** 1 - - -
Nuts and seeds 0.098 ** 0.069 ** 0.048 * 0.036 0.084 ** 0.005 −0.037 0.060 ** 0.080 ** −0.002 0.071 ** 1 - -
Refined grains 0.052 * 0.189 ** −0.055 * 0.154 ** 0.197 ** −0.152 ** 0.034 −0.029 0.055 * −0.032 −0.017 −0.021 1 -
Whole grains 0.058 * −0.057 * 0.109 ** −0.065 ** 0.079 ** 0.190 ** 0.151 ** 0.196 ** 0.008 0.070 ** 0.090 ** −0.042 −0.119 ** 1

Table 5 describes the percentage of individuals meeting recommendations from LARN, EFSA, and WHO on macronutrients and food group intake. Generally, more than half of individuals reached the suggested recommendations for carbohydrate and fiber intake, while the proportion of adherent individuals was even higher for total protein and cholesterol intake recommendations. By contrast, only a minority met the recommendations for total fat intake.

Table 5.

Percentage of study population meeting various recommendations for macronutrients (EFSA, LARN) and selected food groups (WHO).

Total (n = 1839) Men (n = 772) Women (n = 1066)
Yes, % (n) No, % (n) Yes, % (n) No, % (n) Yes, % (n) No, % (n)
EFSA
Total carbohydrate (45–60%E) 56.3 (1035) 43.7 (804) 56.6 (437) 43.4 (335) 56.0 (597) 44.0 (469)
Total protein (>0.83 g/kg/day) 89.7 (1649) 10.3 (190) 85.5 (660) 14.5 (112) 92.8 (989) 7.2 (77)
Total fat (20–35%E) 17.1 (315) 82.9 (1524) 17.6 (136) 82.4 (636) 16.8 (179) 83.2 (887)
Fiber (>25 g/day) 62.8 (1154) 37.2 (685) 62.7 (484) 37.3 (288) 62.9 (670) 37.1 (396)
LARN
Total carbohydrates (40–60%E) 59.4 (1092) 40.6 (747) 59.5 (459) 40.5 (313) 59.3 (632) 40.7 (434)
Total protein (>0.90 g/kg/day) 83.9 (1543) 16.1 (296) 78.6 (607) 21.4 (165) 87.8 (936) 12.2 (130)
Total fat (20–35%E) 17.1 (315) 82.9 (1524) 17.6 (136) 82.4 (636) 16.8 (179) 83.2 (887)
Cholesterol (<300 mg/day) 91.8 (1688) 8.2 (151) 91.3 (705) 8.7 (67) 92.1 (982) 7.9 (84)
Fiber (12.6–16.7 g/1000 kcal/day) 53.5 (983) 46.5 (856) 54.3 (419) 45.7 (353) 52.9 (564) 47.1 (502)
WHO
Fruit and vegetable (>400 g/day) 74.6 (1371) 25.4 (468) 76.4 (590) 23.6 (182) 73.2 (780) 26.8 (286)
Pulses and nuts (>30 g/day) 81.7 (1503) 18.3 (336) 82.5 (637) 17.5 (135) 81.2 (866) 18.8 (200)
Total meat (<70 g/day) 77.0 (1416) 23.0 (423) 75.4 (582) 24.6 (190) 78.1 (833) 21.9 (233)

Table 6 and Table 7 describe the association between macronutrient and major food group intake and BMI levels in the investigated population, total and by sex. Total protein, and specifically plant protein, monounsaturated fatty acids and omega-6 fatty acids were significantly inversely related with BMI, while trans fatty acids and cholesterol were directly correlated (Table 6). However, no significant results were found for major food groups, with the exception of a direct association with unprocessed meats and an inverse association with processed meats (Table 7). It was noteworthy that the magnitude of the latter associations and of proteins, in general, were very small compared to those of dietary fats.

Table 6.

Linear association between macronutrient intake and BMI levels in the study participants of the MEAL study (n = 1838). * denotes p < 0.05, ** denotes p < 0.001.

Total Men Women
Total carbohydrates 0.000 (0.006) −0.002 (0.008) −0.001 (0.008)
Total protein −0.035 (0.016) * −0.022 (0.025) −0.046 (0.022) *
Animal protein 0.000 (0.006) −0.002 (0.010) 0.002 (0.008)
Dairy protein −0.013 (0.013) 0.002 (0.020) −0.023 (0.018)
Plant protein −0.049 (0.022) * 0.010 (0.033) −0.081 (0.031) **
Saturated fat −0.023 (0.041) −0.108 (0.064) 0.028 (0.053)
Monounsaturated fat −0.707 (0.138) ** −0.594 (0.212) ** −0.838 (0.184) **
Total omega-6 fatty acids −0.657 (0.173) ** −0.722 (0.251) ** −0.647 (0.242) **
Seafood omega-3 fat 0.024 (0.356) 0.272 (0.548) −0.204 (0.471)
Plant omega-3 fat 0.654 (0.522) 2.178 (0.879) * −0.213 (0.748)
Trans fatty acid 0.666 (0.135) ** 0.520 (0.202) * 0.807 (0.184) **
Dietary cholesterol 0.021 (0.004) ** 0.015 (0.007) * 0.026 (0.006) **
Fiber −0.013 (0.016) −0.054 (0.024) * 0.014 (0.021)

Table 7.

Linear association between major food group intake and BMI levels in the study participants of the MEAL study (n = 1838). * denotes p < 0.05, ** denotes p < 0.001.

Total Men Women
Total processed meats −0.023 (0.007) ** −0.031 (0.010) ** −0.015 (0.010)
Unprocessed meats 0.017 (0.005) ** 0.014 (0.007) * 0.019 (0.006) **
Total seafood 0.004 (0.002) 0.007 (0.003) * 0.002 (0.003)
Eggs 0.039 (0.024) 0.037 (0.043) 0.042 (0.031)
Cheese 0.004 (0.004) −0.001 (0.007) 0.008 (0.006)
Yoghurt −0.002 (0.003) −0.010 (0.004) * 0.003 (0.003)
Fruits −0.001 (0.000) −0.001 (0.001) −0.001 (0.001)
Non-starchy vegetables 0.001 (0.001) 0.002 (0.002) 0.001 (0.001)
Potatoes −0.005 (0.005) −0.003 (0.009) −0.007 (0.006)
Other starchy vegetables 0.002 (0.007) 0.004 (0.009) −0.005 (0.011)
Beans and legumes 0.001 (0.003) −0.008 (0.005) 0.007 (0.005)
Nuts and seeds 0.002 (0.004) 0.002 (0.006) 0.000 (0.006)
Refined grains 0.002 (0.002) 0.001 (0.002) 0.002 (0.002)
Whole grains −0.004 (0.003) −0.004 (0.004) −0.003 (0.003)

4. Discussion

The present study provided updated information on intake of major food groups and macronutrients and their association with weight status in a sample of southern Italian adults. We found that a large proportion of individuals had adequate intake of protein, fiber, fats, fruit and vegetable, meat, and pulses according to national and international recommendations. These results suggest that the investigated population has generally healthy dietary choices; however, investigating major food group consumption and comparison with other reports is crucial to better understand dietary priorities for future strategies to improve dietary habits and overall health.

Despite the importance of monitoring dietary intakes at population level, previous studies investigating macronutrient and food consumption are scarce. A recent report of Global Burden of Diseases Nutrition and Chronic Diseases Expert Group aimed to describe consumption of major food groups worldwide and at national level [31]. Despite that the report showed standardized intake to the same isocaloric diet (2000 kcal/day), our data are comparable, due to similar average total energy intake in both men and women. In 2010, mean global fruit consumption in adults has been reported to be 81.3 g/day, with the highest intake in Greece, and no clear pattern of variation of consumption worldwide. In this study, we reported a much higher fruit intake (about 400 g/day) only comparable with reports from Jamaica and Malaysia. However, two Italian surveys [32,33] showed an average national consumption of fruit closer to those reported in the present study (about 200–300 g/day); our estimates might be higher, due to the higher availability of fruit and lower prices in the regional territory [34] (taking into account that none of the previous reports included the municipality of Catania for sampling), or represent an overestimation, due to potential limitation of this type of recall studies (i.e., higher number of food items coding for “fruit” compared to other FFQs). Mean vegetable and legume consumption in our study was more in line with worldwide average intake (about 250 g/day versus 208.8 g/day, respectively) and those reported in the other Italian studies [32,33]. Moreover, fruit and vegetable consumption were strongly intercorrelated, reflecting a global trend. Consumption of nuts, seeds, and wholegrain is relatively low worldwide (around 10 g/day and 40 g/day), with the highest consumption in Southeast Asian nations and the lowest in Central European nations. Our reports were similar to worldwide average regarding whole-grain consumption, but much higher concerning nut intake (about 20 g/day); again, this can be the result of increased intake due to local production of certain nut subtypes (i.e., pistachios), which might be easier available and at lower price, or an overestimation due to various questions on nut-subtypes in our FFQs. Regarding animal products, in our cohort we found a higher consumption of seafood (about 60 g/day versus 28 g/day), similar of processed meat (about 16 g/day versus 14 g/day), and slightly lower of unprocessed meat (about 34 g/day versus 42 g/day) compared to worldwide reports. However, the higher seafood intake was evident in Pacific Island nations, the Mediterranean Basin, South Korea, and Japan, consistently with historical cultures and local availability. Also, the other Italian report showed similar intake of processed and unprocessed meat products than those reported in the present study, while consumption of fish was lower [32,33]. According to the Italian National Institute of Statistics (ISTAT), the mean expenditure for major food groups in the Italian islands (including Sicily) does not substantially differ from the national average, with the exception of higher purchase of seafood, thus reflecting a regional preference in consuming such products. Interestingly, we have found that seafood intake was weakly correlated with most of the other food groups investigated, suggesting that preference for fish might be common, and related with either healthy or unhealthy food groups.

Global and national reports on macronutrient intake have underlined dramatic diversity across nations and the need for inform policies to improve global health. Our estimates for dietary fats are slightly “healthier” than those previously reported in the Italian population (i.e., lower cholesterol and saturated fatty acid intake) [35]; however, no previous data on specific subgroup of fats (i.e., omega-6, omega-3, etc.) or protein (plant protein, animal protein) has been reported for the Italian population. When comparing our data to global consumption of fat, we reported lower intake of dietary cholesterol (187 mg/day vs. 228 mg/day), higher of seafood omega-3 (0.53 g/day vs. 0.16 g/day) and similar of plant omega-3 (1.17 g/day vs. 1.37 g/day) [36]. Comparative data on type of protein is harder to retrieve. By roughly converting our estimates as percentage of total energy (%E), we may consider that the population investigated in this study consumed an average 5%E of animal protein (not including dairy protein) and about 9%E of plant protein: cohort studies conducted in the United States reported animal and plant protein intake of about 14% and 6%, respectively [15]; another Australian cohort reported slightly lower median intake of animal protein (about 10% of total energy) and similar of plant protein (about 6.5%) [37,38]. Thus, despite that studies to compare our reports to are scarce, we found a pattern of protein source intake healthier than in the aforementioned countries. These data on macronutrients, together with the aforementioned findings on major food groups, reflects the other findings on adherence to dietary recommendations. Various studies across the globe have reported an overall poor adherence to dietary guidelines of adult populations. Recent reports showed that diet quality of Americans, measured as agreement with dietary recommendations listed in the Healthy Eating Index (HEI), were far from optimal, regardless of socioeconomic status and race. Similarly, comparable trends have been observed in European countries. In Spain, there is a general low adherence to dietary guidelines, and these trends are particularly evident in individuals with overweight and obesity [39]. Nutrition surveys from France [40] and Germany [41] reported that consumption of fruit and vegetable does not meet dietary recommendations: similar findings were showed in other studies, where only about 30% of people living in United Kingdom [42] and 10% in Italy [43] reported eating the recommended five portions of fruits and vegetables per day. A report from Eastern European countries showed that roughly half individuals met WHO criteria for fruit and vegetable consumption, but only a minority met those for pulses and nut consumption [44]. By contrast, we found that half to two-thirds of the participants in our cohort met dietary guidelines on macronutrient and food group consumption, with the exception for total fats. However, despite that most of the individuals were under or, most likely, over the recommended intake, the results are not necessarily alarming, as we reported a higher intake of healthy rather than unhealthy fats. It has been shown that food sources of fat, such as olive oil, fish, and nuts, are associated with positive outcomes for health and a general recommendation in limiting total dietary fats may not entirely reflect a proper advice [45,46,47].

In this study, we found a correlation between certain macronutrients and food groups with BMI levels of the participants. Mostly in line with expectations, among dietary proteins, only plant protein intake was inversely correlated with BMI, while among dietary fats, monounsaturated and omega-6 fatty acids were inversely correlated, whereas trans fatty acids and cholesterol were directly correlated. However, these results did not entirely fit with correlations obtained with major food groups, as processed and unprocessed meats were indirectly and directly correlated with BMI levels, respectively. A possible reason for such unexpected findings may be the relative good quality of processed meat in southern Italy, which according the results of individual questions of the FFQ, we found it mostly referred to cured meat rather than fast foods (data not shown). Another explanation is the relatively low magnitude of the correlation for protein and meat products, which in fact might be spurious. Regarding the findings on dietary fats, we hypothesize that a major contributor to monounsaturated fatty acid intake was olive oil, highly consumed in this cohort as reported in previous studies [48]. General high levels of adherence to the Mediterranean diet has been previously shown in this cohort, as well as the association with lower likelihood of being obese and other metabolic conditions for those participants highly adherent to this dietary pattern; however, the association was not driven by olive oil or any other of the components of the score [49,50,51]. These findings corroborate the results of several other studies and suggest that the overall dietary pattern was more descriptive for a healthy nutritional alternative associated with better metabolic health [52,53,54]. Possible mediating factors have been hypothesized to be dietary polyphenols, which have been reported to exert potential beneficial effects on health [55,56]. With special regards to metabolic outcomes, dietary polyphenols have been shown to mediate, at least in part, the observed association with better metabolic health in this cohort [57,58,59]. Further studies are needed to investigate whether such compounds may explain, from a mechanistic point of view, the beneficial effects of healthy dietary pattern rich in fruit and vegetable, and other features typical of the Mediterranean diet.

The results presented in this study should be considered in light of methodological limitations. The use of FFQs is a widely-consolidated methodology, but they are also known to only provide estimates and not true intake, as they are subject to recall bias and over- and underestimation, depending on the number of food items included and social desirability bias, respectively. However, comparative reports used similar methodology and results are generally in line with literature and expected findings.

5. Conclusions

In conclusion, the present study provided updated information on macronutrient and major food group intake in a southern Italian adult population, taking into account specific subgroup of macronutrients rarely reported in current literature. The overall findings suggest that relatively healthy dietary habits are common in southern Italy, in up to two-thirds of the sample investigated. Further in-depth studies are needed to better understand whether findings related to foods may translate in equally adequate micronutrient intake in this cohort. However, further efforts should be made to improve diet quality of the remaining population in order to prevent non-communicable diseases.

Author Contributions

M.M. conceived and designed the experiments; A.P. performed the experiments; M.F., A.C., D.C. and I.B. analyzed the data; S.M. and M.M. and M.D’U. wrote the paper.

Conflicts of Interest

The authors declare no conflict of interest.

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