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Introduction: The international physical activity questionnaire (IPAQ) was developed as an instrument for cross-national monitoring of physical activity (PA) and inactivity. The aim of this study was to determine the PA level in a sample of Italian population. Methods: In total 957 adults (56% women) aged 19-65 years were randomly recruited. PA was assessed using the long form of the IPAQ (IPAQ-L). Lifestyle, body weight and height were obtained by questionnaire. Results: The total PA was 1610 MET-min/week: subjects were physically more active in the domestic and garden domain, contrary to transportation and leisure domain. Classifying the activities on the basis of the intensity, significant differences between sexes were detected for moderate and vigorous activities; moreover subjects aged 18-30 years had the lowest levels of PA, while subjects aged >50 had the highest levels. The 86% of the examined population spent at least 30 minutes of moderate PA on 5 days of the week, adhering to the international recommendations. Conclusions: Differences in PA between sexes and among age groups were observed. Strategies for increasing PA should be addressed especially to the young adults.
Keywords: Physical activity assessment; IPAQ; Subjective methods; Community-based research; Physical activity assessment; IPAQ; Subjective methods; Community-based research
Physical activity (PA) has been regarded as one of the most important habitual behaviours, which leads to a healthy life by preventing diseases and increasing health benefits. Regular and adequate levels improve muscular and cardiorespiratory fitness, bone and functional health, reduce the risk of non-communicable diseases and depression and are a key determinant of en- 1-4 ergy expenditure, thus fundamental to energy balance and weight control.1-4 For these reasons,
health : people aged >18 years should accumulate at least 150 minutes of moderate intensity aerobic PA throughout the week or do at least 75 minutes of vigorous intensity aerobic PA
problems of the 21 century. As reported by WHO, insufficient PA has been identified as the
fourth leading risk factor for mortality, as well as the main cause for approximately 21-25% of breast and colon cancers, 27% of diabetes and approximately 30% of ischemic heart disease burden.6 About 3.2 million people die each year because they are 7,8 not active enough7,8 and the levels of physical inactivity increase across the world. In 2012, it was estimated that 31.1% of the adult global population did not meet the physical activity recommendations.9
Notwithstanding physical inactivity is considered a global health concern, as no standardized approaches to measurement exist, international comparisons and global surveillance are difficult.10
In a recent review of adult physical activity levels across Europe is underlined that because of the large variety in the assessment methods used to assess physical activity, the reported outcome variables and the presented physical activity levels per study, absolute physical activity population levels in European adults are currently unknown.11
Several routine instruments are available, all of which having well-known limitations; consequently there is currently no perfect gold-standard criterion.12 Objective methods, as movement sensors, due to their high costs, are not usually practical in large-scale cohort studies while the self-report questionnaire is the most commonly used instrument.
Several questionnaires are been proposed13 and among them the international physical activity questionnaire (IPAQ) is widely used. This questionnaire was developed in the late 1990’s to obtain internationally comparable data on health relat- 10,14 ed PA and several studies have shown its acceptable validity and reliability for population-based studies. In particular, the long form of IPAQ (IPAQ-L) measures frequency, duration, and intensity of PA in four domains of life: work, transport, domestic and garden, leisure-time.
To the best of our knowledge, there has been no population-based study in Italy, which examined all four domains of PA. The aim of this study is to determine PA levels in a sample of adult Italian population using the IPAQ-L.
One-thousand and sixty-two healthy volunteers (482 males and 580 females), aged 18-65 years, were recruited in the North, the Centre and the South of Italy. After being informed about the purpose of the study, they gave their written consent. All the subjects underwent lifestyle questionnaire administration and PA evaluation. From the original sample, after cleaning the data for missing and out-of-range values according to the IPAQ Research Committee,14 957 (422 men and 535 women) subjects represent the final sample of the study.
The study was conducted according to the guidelines laid down in the Declaration of Helsinki and all procedures involving human subjects were approved by the ‘Sapienza’ University of Rome Ethics Committee. Written informed consent was obtained from all the subjects.
The lifestyle questionnaire was administered to each participant by trained personnel and consisting of a package of questions specifically designed to obtain different information about sociodemographic (marital status, education and occupation) and anthropometric characteristics (height and body weight), smoking habits and alcohol consumption. In order to verify the validity of self-reported body anthropometric data, on a subsample of 300 subjects the fasting weight and height were also measured by a trained observer under standardized conditions.16 A calibrated computerized digital scale (K-Tron P1-SR; K-Tron SA, Hansler Division, Colombier, Switzerland; capacity 150 kg, graduation 10 g) and a wall- mounted Holtain stadiometer (Holtain Ltd, Crosswell, Crymych, UK), with height being recorded to the nearest 0.1 cm, were used. Both self-reported and objectivelymeasured weight and height were used to calculate body mass 12 2 index (BMI, kg/m2), and consequently the prevalence of obesity and overweight, using the cut-off points proposed for adult pop- 17 2 ulation17: underweight <18.5 kg/m2; overweight 25.0-29.9 kg/ 2 2 m2 and obesity ≥ 30 kg/m2. The mean difference between selfreported and objectively measured BMI was 0.3 kg/m2 for men 13 2 0.2 kg/m2 for women and can be considered negligible.
For estimating the level of PA, the original English version of 10,15 IPAQ-L was translated into Italian, then back translated into English and the Italian version was administered by trained personnel in a face-to-face interview. The IPAQ-L, designed to assess the levels of habitual PA, consists of 27 questions referred to the previous 7 days covering 4 domains of PA (work-related PA, transport-related PA, domestic and gardening activities, and leisure-time PA). The items in IPAQ are structured to provide separate domain specific scores for walking, moderate-intensity and vigorous-intensity activity within each domain.
The results were presented as the estimation of energy expenditure in metabolic equivalent-minutes per week (METminutes/week), made by using the compendium of physical 18-20 activities, which provides a classification of specific activities in MET. One MET represents the resting energy expenditure during quiet sitting and is commonly defined as 3.5 ml O2•kg−1•min−1 or ≈ 250 mL/min of oxygen consumed, which represents the average value for a standard person (70 kg). Obviously the oxygen consumption increases with activity intensity level, therefore the MET value increases with the intensity of PA (e.g. 1 MET=the rate of energy expenditure while at rest [sitting quietly], 2 MET=walking at 3 km/h would require twice the energy that an average person consumes at rest). According to
IPAQ scoring protocol,14 MET-minutes/week of specific activity (walking or moderate intensity activity or vigorous intensity activity) is computed by multiplying MET value of particular activity (3.3 for walking, 4.0 for moderate intensity activity, and 8.0 for vigorous intensity activity) with hours spent in that particular activity (e.g., walking MET-minutes/week at work=3.3×walking minutes×walking days at work). Computation of the total scores for the long form requires the summation of the duration (in minutes) and frequency (days) for all the types of activities in all domains. Only the activities lasting at least 10 minutes were taken into account. Domain specific scores or activity specific sub-scores may be calculated. Domain specific scores require the summation of the scores for walking, moderate-intensity and vigorous-intensity activities within the specific domain, whereas activity-specific scores require the summation of the scores for the specific type of activity across domains.14
The PA was categorized using the IPAQ scoring protocol. The cut-off levels, reported in Table 1, are based on the current guidelines for PA, which state that every adult should be active on most, preferably all days of the week, at moderate intensity accumulating 30 minutes of PA. In terms of how the IPAQ measures activity, this would be equal to 600 METminutes/week, which is the lowest limit for the moderately active category. The cut-off limit for moderately active category also allows a person to be vigorously active for three days per week for 20 minutes. As the IPAQ measures PA across all domains and the guidelines are based mainly on studies assessing leisure time PA, the cut-off for reaching the moderately active category should be viewed as the absolute minimum of PA for some health benefit. The higher category aims to include persons that are doing intentional PA three days per week or more, accumulating 1500 MET-minutes/week or that are accumulating 3000 MET-minutes/week. Subjects in this category are believed to be sufficiently active for health benefits across all domains.
Low Those individuals who not meet criteria for Categories 2 or 3 are considered to
Moderate The pattern of activity to be classified as ‘moderate’ is either of the following criteria:
High The pattern of activity to
Table 1. Physical activity categories and cut-off levels based on the IPAQ scoring protocol.
Normality of distributions of variables was tested by Shapiro- Wilk test. Median, 95% confidence interval (CI) for median, and interquartile range (IQR) were calculated for each domain of PA separately, as well as for total PA, for sex and for 4 age groups of participants (18-30 years, 31-40 years, 41-50 years, 50 years and older). The student t-test was used to evaluate the differences in physical characteristics between sexes, while differences of PA between age groups and sexes were tested by the non-parametric Kruskal-Wallis test. Differences among prevalence were tested by the chi-square test. Additionally, multiple regression analysis was conducted to identify socio-demographic and anthropometric factors related to PA levels. In the regression model, age, BMI and educational level were used as independent variable, while each of the 4 PA domain scores and total PA score as dependent variable. The level of significance for all analyse was set at p<0.05. Statistical analysis was performed by STATISTICA software (release 8; 135 StatSoft Inc, Vigonza PD, Italy).
The sample included a total of 957 (422 men and 535 women) participants, whose physical characteristics are reported the physical characteristics in Table 2.
There were significant differences for all the variables between men and women (p=0.000). The mean BMI was 26.0±3.8 kg/m2 for men (indicating an overweight status) and 24.5±5.3 kg/m2 for women (p=0.000). There were statistically significant differences between sexes (χ2=63.61, p=0.001) in BMI categories: 60.7% of women was normal weight and 55.8% of men was overweight or obese; moreover, the percentage of obese subjects is similar between men and women (14%) (data not shown).
have a ‘low’ physical activity level.
a) 3 or more days of vigorous-intensity activity of at least 20 minutes per day OR b) 5 or more days of moderate-intensity activity and/or walking of at least 30 minutes per day OR c) 5 or more days of any combination of walking, moderate-intensity or vigorous intensity activities achieving a minimum Total physical activity of at least 600 METminutes/week.
be classified as ‘high’ is either of the following criteria: a) vigorous-intensity activity on at least 3 days achieving a minimum Total physical activity of at least 1500 MET-minutes/week OR b) 7 or more days of any combination of walking, moderate-intensity or vigorousintensity activities achieving a minimum Total physical activity of at least 3000 METminutes/week.
Married/full-time relationship 44.7 Separated/divorced 51.9 Widowed 3.1 Single 0.2
Primary 0.5 Secondary 74 Tertiary 25.5
Unemployed 11.9 Employed 87.4 Retired 0.7 *Statistical analysis: χ2 test; n.s.=not significant.
Table 3. Socio-demographic variables of the sample by gender.
In Table 3 are reported socio-demographic variables of the sample by gender. There were not significant differences in marital status, while regarding educational level, about 70% of the sample (74% of men and 66.6% of women) had a secondary education and, on the whole, there were slight differences (χ2=7,54, p=0,05). The majority of the sample stated to be engaged in some form of work activity; the difference between sexes (χ2=103.27, p=0,001) depends on the high percentage of housewives in the sample, which are included in the “unemployed” category.
The median (95% CI) of PA, expressed as median of MET-minutes/week, is reported in Table 4 for men and women separately and for the total sample and indicated for the 4 domains separately (work, transport, domestic and garden, and leisure-time) and for the specific activities (walking or 155 moderate intensity activity or vigorous intensity activity).
The median (95% CI) of total PA for the whole sample was 1610 MET-min/week, without significant differences between men and women. Regarding the individual domains of PA, subjects were physically more active in the domestic and garden domain (223 MET-min/week), as opposed to transportation and leisure domain (85 MET-min/week each one). Moreover, there were statistical differences between sexes in the median value of MET-min/week in the work (31 MET-min/week for men and 0 MET-min/week for women, p=0.000), in domes-
N° 42 55 Mean SD Mean SD Age 38.6 10.9 35.5 11.2 0.000 Weight (kg) 80.6 13.0 65.3 13.9 0.000 Height (cm) 176.0 7.2 163.4 6.5 0.000 BMI (kg/m ) 26.0 3.8 24.5 5.3 0.000 *Statistical analysis: Student t-test.
Table 2. Physical characteristics of the sample by gender (mean value and SD).
6.97 n.s.
44.7 48.9 4.4 1.9 7.54 0.05 1.5 66.6 31.9 103.27 0.001 42.0 57.9 0.2
tic and garden (69 MET-min/week for men and 617 MET-min/ week for women, p=0.000) and in leisure time (198 MET-min/ week for men vs. 57 MET-min/week for women, p=0.000); no significant differences were observed in the domain of transport. Classifying the activities based on the intensity, significant differences between sexes were detected for moderate (319 METmin/week for men vs. 814 MET-min/week for women, p=0.000) and vigorous activities (103 MET-min/week for men vs. 0 METmin/week for women, p=0.000), while no significant differences were found for walking.
Stratifying the sample by age, all the differences were statistically significant, except for the vigorous activities (Table 5). As a general remark, PA increased with age: subjects aged 18-30 years had the lowest levels of PA (1154 MET-min/week), while subjects aged >50 had the highest levels (3639 MET-min/ week). Moreover, the oldest subjects were highly involved in transport (236 MET-min/week) and domestic and garden (1260 MET-min/week) domains, while in leisure-time the most active group was aged 18-30 years (170 MET-min/week).
The multiple regression analysis between BMI (calculated using self-reported weight and height) and socio-demographic characteristics (age and educational level) as independent variables with PA as the dependent variable is reported in Table 6. Total PA, as well as moderate PA, was positively correlated with age (p=0.000) and negatively with educational
Work 95% CI 5181-5931 2998-3380 4255-4654 0.000
Transport 95% CI 808-925 624-704 724-792 n.s.
Domestic and garden 95% CI 1694-1940 2210-2492 2091-2288 0.000
Leisure-time 95% CI 1107-1268 787-887 970-1061 0.000
Walking 95% CI 1871-2141 1354-1527 1638-1792 n.s.
Moderate activities 95% CI 2763-3163 2725-3073 2804-3067 0.000
Vigorous activities 95% CI 3965-4539 2110-2379 3186-3485 0.000
Total physical activity 95% CI 5979-6845 4014-4527 5089-5567 n.s.
*Interquartile range (IQR) in MET-minutes/week calculated according to the IPAQ protocol. †Statistical analysis: Kruskal-Wallis test; n.s.=not significant. Physical activity expressed in metabolic-equivalent-minutes per week (MET-min/week) by gender (median; 95% CI; IQR*).
Median 0 0 Work 95% CI 2676-3124 4458-5285 4666-5549 4781-6250 4255-4654 0.006 * IQR 226 408 Median 126 42 Transport 95% CI 561-655 636-754 * IQR 363 347 Median 90 309 Domestic and garden 95% CI 1080-1260 2042-2421 2393-2846 2481-3244 2091-2288 0.000 * IQR 449 1449 Median 170 63 Leisure-time 95% CI 1096-1279 767-910 * IQR 656 519 Median 269 170 Walking 95% CI 1249-1458 1741-2064 1747-2078 1506-1968 1638-1792 0.000 * IQR 698 929 Median 274 617 Moderate activities 95% CI 1751-2043 2907-3427 2790-3317 3504-4580 2804-3067 0.000 * IQR 913 1787 Median 0 0 Vigorous activities 95% CI 1846-2155 3105-3682 3851-4579 3534-4619 3186-3485 n.s. * IQR 411 457 Median 1154 1636 Total physical activity 95% CI 3174-3705 5169-6128 5393-6413 6036-7890 5089-5567 0.000 * IQR 2074 3674 *Interquartile range (IQR) in MET-minutes/week calculated according to the IPAQ protocol. †Statistical analysis: Kruskal-Wallis test; n.s.=not significant.
Median 31 0 0
IQR* 1393 137 509 Median 58 113 85
IQR* 453 462 456 Median 69 617 223
IQR* 377 2417 1234 Median 198 57 85
IQR* 728 354 548 Median 283 255 269
IQR* 1110 790 924 Median 319 814 549
IQR* 1251 2314 2059 Median 103 0 0
IQR* 1120 46 411 Median 1573 1657 1610
IQR* 4312 3578 3763
0 0 0
707 1175 509 63 236 85 783-931 878-1148 724-792 0.001 462 767 456 321 1260 223
1844 2734 1234 57 57 85 903-1075 843-1102 970-1061 0.001 426 693 548 285 679 269
999 1443 924 750 1976 549
2359 3471 2059 0 0 0
308 411 411 2113 3639 1610
4559 5596 3763
*
level (p=0.000). PA in work domain was inversely related to educational level and positively to BMI, opposite to leisure-time domain. PA in transport domain was negatively related to BMI and positively to age. Finally, PA in domestic and garden domain was positively related to age and negatively to educational level.
In Table 7 are reported the PA categories of the sample on the basis of the IPAQ scoring protocol. Overall, the 86% of participants reached the levels of at least 30 minutes of moderate PA 5 days a week, which could be considered as the lowest level of PA for achieving health benefits, according to the recommendations.
The aim of the study was to evaluate the PA in a sample of adult Italian population, using the IPAQ-L, which can be considered as an acceptable instrument for monitoring population levels of PA among 18-65 years old adults in different settings.10 Results show that the majority of respondents (86%) reached the levels of at least 30 minutes of moderate PA 5 days a week, which could be considered as the lowest level of PA for achieving health benefits, according to the recommendations. The total PA of the sample is 1610 MET-min/week, without gender differences. This is because women are mainly involved in moderate activities while men do vigorous activities. Additionally, it is important to notice that patterns of PA were also considerably different for men and women. Indeed, men reported more PA at work and leisure-time, while women at domestic and garden. Moreover, there were age differences, with participants aged >51 years having the highest level of PA and youngest participants having the lowest.
Work 0.06 n.s.
Transport 0.16 0.000 Domestic and garden 0.19 0.000 Leisure-time 0.04 n.s.
Walking 0.10 0.005 Moderate activities 0.17 0.000 Vigorous activities 0.06 n.s.
Total physical activities 0.16 0.000 n.s.=not significant
Table 6. Multiple regression analysis between anthropometric and socio-demographic characteristics (independent variables) and physical activity (dependent variable).
Literature studies conducted in Italy and considering all four domains of PA are lacking.11 Similar studies conducted in other European countries considered the short version of IPAQ, more simple to be administered (7 questions in the short version 21,22 compared with 27 questions in the long version) or other ad hoc questionnaires with study-specific items and time references, severely limiting the potential for comparisons across different studies. European Activity Surveillance System (EUPASS) project, designed to contribute to a European health monitoring system, measured PA in 8 European countries, finding a median of 19.6 MET-hour/week (i.e. 1176 MET-min/week) for Italy.19 Eurobarometer published the survey “Sport and physical activity” finding that in Italy 65% did not do any vigorous PA in the previous seven days and 54% did no moderate PA at all.23 In the “Multipurpose survey on households: aspects of daily life” conducted by the Italian National Statistics Institute, the proportion of sedentary people in Italy was 41.2% in 2013 (36.2% of men and 45.8% of women).24 The “Passi study” conducted from 2011 to 2014 reports 31% of sedentary people; this condition increases with age (25.7% of sedentary people aged 18-34 years, 30.8% of 211 sedentary people aged 35-49 years and 35.4% of sedentary people aged 50-69 years) and decreases with higher socio-economic conditions.25
Even if IPAQ-L is less pleasant and more confusing 10,26,27 in comparison with the short form and PA estimated using the long version may be higher because the short version systematically underestimates PA level,22 it has been demonstrated that results obtained by different versions can be compared.10 Moreover, beyond the identification of the total PA, it is also important to study the contribution of the different domains. In most studies recommended levels of PA have been determined
p value p value p value 0.07 0.050 -0.14 0.000 -0.07 0.040 0.03 n.s.
-0.03 n.s. -0.13 0.000 -0.07 0.045 0.09 0.009 -0.04 n.s. -0.06 n.s.
-0.01 n.s. -0.17 0.000 0.06 n.s. -0.06 n.s.
0.02 n.s. -0.15 0.000
3.80 n.s.
Insufficiently active 15.6 12.5 Sufficiently active 30.1 35.3 Active 54.3 52.2 *Statistical analysis: χ2 test; n.s.=not significant
Table 7. Physical activity categories based on the IPAQ score by gender.
in relation to leisure-time PA, while other domains (work, transport, domestic and garden) were not equally considered.21 Most self-reports are unreliable especially for housework and occupational activity; this may be particularly problematic especially in low- and middle-income countries, where transport, occupational, and housework activities often are mixed with daily life.28
Total PA scores alone do not give us a complete understanding of the PA pattern. For example, health studies determining the level of PA only in the domain of leisure, while ignoring the domain of work, could possibly lead to flawed conclusions. This is supported by the studies that found a correlation between PA at work to specific aspects of health. For example, Norfolk prospective population study showed a significantly decreased risk of death and cardiovascular diseases in persons who were physically active at work and other studies showed an inverse correlation between work-related PA and cardiovascular mortal- 30,31 ity. Studies that determine only total PA and do not examine PA throughout domains neglect the fact that PA in the domain of leisure and in the domain of work has a different influence on certain aspects of health. Gutierrez-Fisac and coworkers32 found that PA at work was not related to obesity while Fung et al33 found that there was a relation between PA in leisure time and obesity. Furthermore, in another study34 it was demonstrated that an increased PA at work was not related to the improvement in physical fitness because it does not have adequate intensity and duration to affect positive changes. On the otherhand, other studies35 showed a positive correlation between PA in leisure time and physical fitness.
The multiple regression analysis showed that anthropometric and socio-demographic characteristics were significantly related to PA in different domains. As expected, there was an inverse association between educational level and PA in work domain and positive association in leisure-time domain. People with lower educational level often perform more physically demanding work and probably do not have enough time for leisure-time PA. On the contrary, people having higher educational level have jobs that are more sedentary and have a tendency to be more physically active in leisure time due to greater knowledge about PA health benefits. A positive relationship between educational level and leisure-time PA has been demonstrated by 36,37 other literature studies.
Moreover, BMI was positively related to PA in work domain and negatively in both transport and leisure-time domain even if the multiple regression did not show significant relations between BMI and total PA, as well as with both moderate and vigorous activities. These results differed from other literature studies in which a high PA level especially at work and during leisure time strongly correlate with lower BMI.38 The use of selfreported height and weight to calculate BMI did not influence the results. It has been demonstrated that weight is often underreported (especially by women) and height is generally overestimated, especially by men and older subjects,39 and consequently the prevalence of overweight tends to be lower when self-report-
ed values are used. In our study, the self-reported anthropometric data cannot lead to erroneous estimates of underweight and/or overweight. Indeed, the mean difference between self-reported and objectively measured BMI can be considered negligible.
The main strengths of the study were the size of the sample and the use of the recommended IPAQ-L. IPAQ-L enabled us to assess PA levels in different domains in order to encourage people to be more active not only in their leisure time, but also while performing every-day activities, introduce ‘getmoving’ strategies at work, during transportation and at home to improve their health. Nevertheless, subjective methods of measuring PA are useful with large populations as they are inexpensive and easy to apply but have their limitations such as reliability and validity problems associated with the recall of 28,40 activity. Moreover, the use of self-reported data with the potential for information bias in relation to PA41 could have led to overestimate the time spent in high intensity activity and underestimate the time spent in sedentary activities, probably because 42,43 subjects tend to respond in a socially desirable way, even if it has been demonstrated that data are reproducible and can 33 27 provide reliable estimates of a range of PA domains.27 Whilst subjective methods remain the most feasible and affordable instruments for global surveillance, there is a need for standardization of PA measurements, which would allow the comparison between different studies from different countries. The results of a recent systematic review highlight the need for harmonisation and standardisation of the measurement methods and data processing used to assess physical activity in Europe, and the added value of a cross-European surveillance system including stateof-the-art physical activity measurements.11 Indeed, monitoring population levels of physical (in) activity provides the opportunity to track changes over time, identify and target populations with low physical activity levels, and evaluate public health policies and strategies. Internationally comparable data are especially interesting, since they allow cross-country comparisons and benchmarking.
In conclusion, taking together these findings indicate that 86% of the sample has a sufficient level of PA, with differences between sexes and among age groups. These results can provide useful baseline data in Italian population, but additional studies could be conducted to ascertain population trends over years in order to promote PA and improve public health by using a broad approach which considers the different segments of population.
The authors of the manuscripts have made the following contributions in carrying out the field work and writing of the research paper for publication: AP conceptualized, designed and supervised the study; FI conducted bibliographic research and critically reviewing the paper; DC, LB contributed to the study protocol, conducted the research and contributed to the data analysis; MZ, AT, CF contributed to the collected the data; AP,
FI, DC, LB, MZ, AT, CF drafted the paper and all authors listed reviewed the manuscript and contributed to subsequent drafts. All authors read and approved the final manuscript.
This study was supported by the Italian Ministry of Agricultural, Food and Forestry Policies in the framework of the PALINGEN- IO and TERRAVITA projects.
The authors declare that they have no conflicts of interest.