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The assessment of food consumption data using harmonized methodologies at the European level is fundamental to support the development of public policies. Portugal is one of the countries with the most outdated information on individual food consumption.
The objective of this study was to describe the design and methodology of the National Food, Nutrition and Physical Activity Survey, 2015-2016, developed to collect national and regional data on dietary habits, physical activity (PA), and nutritional status, in a representative sample of the Portuguese general population (3 months-84 years).
Participants were selected by multistage sampling, using the National Heath Registry as the sampling frame. Data collection, during 12 months, was harmonized according to European guidelines (EU-MENU, European Food Safety Authority [EFSA]). Computer-assisted personal interviewing (CAPI) was performed on a specific electronic platform synchronized with nutritional composition data and considering the FoodEx2 classification system. Dietary assessment was performed using 24-hour recalls (two nonconsecutive, 8-15 days apart) or food diaries in the case of children aged <10 years, complemented with a food propensity questionnaire; PA data (International Physical Activity Questionnaire [IPAQ], the Activity Choice Index [ACI], and 4-days PA diaries); sociodemographic data, and other health-related data were also collected.
A sample of 6553 individuals completed the first interview, and 5811 participants completed two dietary assessments. The participation rate among eligible individuals was 33.38% (6553/19,635), considering the first interview, and 29.60% (5811/19,635) for the participants with two completed interviews (about 40% in children and adolescents and 20% in elderly individuals). Results of the survey will be disseminated in national and international scientific journals during 2018-2019.
The survey will assist policy planning and management of national and European health programs on the improvement of nutritional status and risk assessment related to food hazards, and the enhancement of PA. The infrastructures and data driven from this Survey are a solid basis to the development of a future national surveillance system on diet, PA, and other health behaviors reproducible over time.
Monitoring food consumption at the national level is imperative to assist health policy making, to provide a solid basis for the development of nutritional and food security policies, and to plan future research. According to the European Report on Food Consumption Survey Methods (EFCOSUM) [
The European Food Safety Authority (EFSA) has conducted the Pan-European Survey “What's in European menu?” (EU-Menu), promoting the development and testing of harmonized instruments and protocols for evaluating food consumption across Europe [
This paper aims to describe the design and data collection methodologies used in the IAN-AF 2015-2016. The survey aimed to collect nationwide data (from 3 months to 84 years of age) on dietary habits (foods, nutrients, dietary supplements, food safety, and insecurity), physical activity (PA) (sedentary behaviors, sports, and active choices in daily living) and their relation with health determinants, namely, socioeconomic factors.
A probabilistic sample of the Portuguese general population aged between 3 months and 84 years was selected by multistage sampling, using the National Health Registry (RNU coding) as the sampling frame. Participation was independent of the regular attendance to the National Health System.
The first step of sampling was based on the random selection of primary health care units, stratified by the 7 Statistical Geographic Units of Portugal (NUTS II), weighted by the number of individuals registered in each health unit. The second step of sampling was based on the random selection of registered individuals in each health unit, according to sex and age groups.
The sample selection was performed in consecutive recruitment waves to use the most updated versions of the National Health Registry lists (4 recruitment waves for infants and toddlers and 2 recruitment waves for the remaining age groups). Individuals with the following criteria were excluded: (1) living in collective residences or institutions (eg, elderly in retirement homes or individuals in hospitals, at prisons, or military barracks); (2) living in Portugal for less than 1 year (nonapplicable to infants); (3) non-Portuguese speakers; (4) with diminished physical and/or cognitive abilities that hamper participation (eg, blind, deaf, with diagnosed dementias); and (5) deceased.
Individuals with no established contact after all planned attempts were considered with unknown eligibility. Eligible participants without availability for the 2 interviews during the evaluation period or who missed appointments were classified as eligible nonparticipants. In addition, for eligible participants aged 65 years or more, a screening of cognitive impairment was performed by using the Mini-Mental State Examination test [
The sample size was estimated by assuming a mean population energy intake of 2000 kcal/day (standard deviation, SD=500) and an effect size of 8%, with a confidence level of 95%. The sample size for each geographical region was estimated in 603 individuals (a total of 4221 individuals in the 7 regions).
To estimate the study design effect, the following information was taken into consideration: (1) a coefficient of variation of cluster sizes defined as 0.4; (2) data from cluster-based studies with primary health care setting in Portugal, measuring the dependency effect of exposures such as body mass index or energy intake (mean intracluster correlation coefficient of 58%); and (3) a mean number of participants reachable in each primary health care unit, depending on the field work management (30 individuals were estimated to be evaluated during 4 weeks). Considering these data, a design effect of 1.20 (an increase of 20% of the sample size) was estimated.
As a result of the settled design effect, the number of individuals to be assessed in each region was estimated as 724, resulting in a total sample of 5068 individuals in the 7 regions. Thus, taking into consideration the distribution of the Portuguese population according to the Census 2011 [
An additional sample of pregnant women was also estimated (n=200) using the same sampling frame, resulting in 2 to 3 pregnant women by each health unit. A potential participation rate of 70% in the first interview and in the second interview was defined, resulting in 50% (70%×70%=49%) of nonresponse, unreachable individuals, incomplete questionnaires, and drop-offs expected. Thereby, the number of participants to be selected and contacted was estimated to be 10,204 (5102 x 2). After a pilot study, a more conservative participation rate of 20% (5102 x 5=25,510) was assumed.
Assuming a one-month period for data collection in each health unit, and an estimation of approximately 30 participants by unit, the number of health units needed to be selected was 21 by region. This number was applied to the North, Centre, and Lisbon regions, but due to logistic constraints related to field work efficiency and the low number of health units in the other regions, 12 health units were selected in Alentejo and Algarve, and 6 health units were selected in Madeira and Azores.
The field work management team included a national coordinator, a subnational coordinator, and 5 regional coordinators. The field work team included 40 interviewers with nutrition or dietetics background and one statistician.
All the procedures related to the management of the field work and participants’ recruitment were performed through an electronic platform (“You eAT&Move”) based on a client-server software architecture, which was specially developed for the survey purposes.
Participants were contacted by telephone to check their willingness to participate. At maximum, 6 contact attempts in different daytimes and day hours were performed. If participants did not answer after 4 attempts, a short message was sent, followed by more 2 contacts attempts, before they were classified as unknown eligibility. If an oral acceptance was provided by individuals, an invitation letter with participation details was sent by post. If individuals refused to participate, some questions included in a short refusal questionnaire were collected. The examination location was selected according to participant’s preference. One of the following two options was provided: the participant’s home or the health units they belong to.
Overall, the survey includes the evaluation of the following dimensions: (1) dietary and nutritional intake, (2) eating habits and behaviors, (3) dietary and nutritional supplements use, (4) food insecurity, (5) PA and sedentary behaviors, (6) sociodemographics, (7) general health data, (8) anthropometrics, and (9) biochemical indicators of nutritional intake (subsample).
Spatial distribution of the primary health care units, weighted by the number of registered individuals: the IAN-AF 2015-2016 survey (NUT: Statistical Geographic Units of Portugal).
Most of the procedures of data collection were adapted from the EFSA Guidance in view of the EU Menu methodology [
Dietary intake was obtained by 2 nonconsecutive one-day food diaries for children aged less than 10 years and 2 nonconsecutive 24-hour recalls for the remaining age groups. The time between interviews was set at 8 to 15 days. The days of reporting were randomly selected, but participants were able to change them according to their own availability for the interview. For Saturdays, a 24-hour recall was performed on Mondays. For adolescents from 10 to 14 years, the 24-hour recall was administered with the presence of one of the parents or other main caregiver; for adolescents from 15 to 17 years, the 24-hour recall was administered without the need of parents’ help. For children aged less than 10 years, the 2 nonconsecutive one-day food diaries were followed by a face-to-face interview, allowing the parent or other main caregiver to add details related to food description and quantification.
To validate nutritional intake in participants aged 18 years or more, data from the 24-hour recall were compared against urinary biomarkers. In a subsample of adults (n=94), 24-hour urinary samples were collected during the day before the second interview. The urinary concentration of sodium, potassium, iodine, and total nitrogen were assessed.
Dietary intake data were collected using the “eAT24” module (electronic assessment tool for 24-hour recall), which allows the assessment of dietary data by an automated multiple-pass method for 24-hour (5 steps) [
The eAT24 methodology requires the description of consumed foods during the dietary interview through several facets and respective descriptors, using the FoodEx2 classification system [
The software allows subsequent conversion of foods into nutrients, using by default the Portuguese food composition table [
Different methods are available for use for food and recipe quantification: (1) weight or volume method, (2) standard unit method, (3) photo method (food picture book including 186 food photo series [with 6 portions each food/recipe], and 11 household measures photo series), (4) household measure method, and (5) default portion method.
A FPQ was also used for usual intake modeling purposes [
Overview of data dimensions collected in the National Food, Nutrition and Physical Activity Survey, 2015-2016, (IAN-AF) by age groups (plus pregnant women).
Modules and dimensions | Age groups (years) | Pregnant women | ||||||||
3 months-2 | 3-5 | 6-9 | 10-14 | 15-17 | 18-64 | 65-84 | ||||
Sociodemographics (SD)a | SD1 | SD1 | SD1 | SD2 | SD2 | SD3 | SD3 | SD3 | ||
General health (G)b | G1 | G2 | G2 | G3 | G3 | G4 | G4 | G5 | ||
Eating behaviors (EB)c | EB1 | EB2 | EB2 | EB2 | EB2 | EB3 | EB3 | EB3 | ||
Anthropometrics (A)d | A1 | A2 | A2 | A2 | A2 | A2 | A2 | A3 | ||
Household food security (HFS) | - | - | - | - | - | HFS | HFS | HFS | ||
Food Propensity Questionnaire (FPQ)e | - | FPQ1 | FPQ1 | FPQ2 | FPQ2 | FPQ2 | FPQ2 | FPQ3 | ||
Food diaries 1 (FD1)f and 2 (FD2) | FD1 | FD2 | FD2 | - | - | - | - | - | ||
24-h recall 1 (24R) | - | - | - | 24R | 24R | 24R | 24R | 24R | ||
24-h recall 2 (24R) | - | - | - | 24R | 24R | 24R | 24R | 24R | ||
Physical activity diaries (PAD) | - | - | PAD | PAD | - | - | - | - | ||
International Physical Activity Questionnaire (IPAQ) | - | - | - | - | IPAQ | IPAQ | IPAQ | IPAQ | ||
Activity Choice Index (ACI) | ACI | ACI | ACI | ACI | ||||||
Sedentary behaviors (SB)g | - | SB1 | SB2 | SB3 | SB4 | SB5 | SB5 | SB6 |
aSD1 and SD2 differ from SD3 by including also questions on country of origin, nationality, professional activity, education of parents, and the current school year (in SD2 only). These versions do not have questions on marital status and household income (only included in SD3).
bG1 assesses previous diseases with need of regular medical care (predefined list of diseases) and identifies the health professional assistant. G2 only assesses previous diseases with need of regular medical care. G3 assesses previous diseases with need of regular medical care, and also the general health condition and current and past smoking habits. G4 evaluates previous diseases with need of regular medical care, and also diseases previously diagnosed by a physician, the general health condition, current and past smoking habits, and gynecological history in women. G5 assesses the general health condition before and during pregnancy, smoking habits before and during pregnancy, gynecological history, and data on current pregnancy (gestational weeks, health problems, etc).
cEA1 include questions relating to breastfeeding, consumption of different milk options, food diversification, and a brief food frequency questionnaire (FFQ) of interest items. EA2 only includes a fruit and vegetables FFQ. EA3 include besides a fruit and vegetables FFQ, questions about organic foods consumption, food safety, and a salt consumption scale.
dA1 includes weight and length driven from the child health booklet and measured weight and height. A2 includes self-reported weight and height and measured weight, height, and waist and hip circumferences. A3 does not include waist and hip circumference measurements, and evaluates self-reported height and weight before pregnancy.
eFPQ1 assesses the consumption of 45 food items in the last month. FPQ2 assesses the consumption of 49 food items (including alcoholic beverages) in the last 12 months, and an option for seasonal consumption is available. FPQ3 is similar to FPQ2, but the reference period is the last 3 months.
fFD1 differs from FD2 because it has a specific structure for registering breastfeeding and formula feeding.
gAll SB include information about sleep habits on weekdays and weekend days and questions about regular and programmed PA. SB1 differs from SB2 and SB3 on the type of sedentary behaviors asked. SB4 and SB5 include also a question about physical or sedentary choices.
The use of dietary supplements was retrieved by 2 methods. The first method used the 24-hour recall, in which dietary supplements and foods consumed during a 24-hour period were recorded per consumption occasion and quantified and described as consumed. Supplements were described according to 6 facets (supplement source, target group, place of acquisition, packaging material, brand, and physical state). This interview-based dietary assessment instrument allows a very detailed description of supplements consumed in the course of the preceding day.
The second method asked the frequency of use, in the last 12 months, of a predefined list of 16 different dietary supplement types (eg, supplements of vitamins, such as C, D, and folate; supplements of minerals, such as calcium and iron; supplements of multivitamins; supplements of fatty acids, herbs, plants, and probiotics).
Food insecurity [
For children (6-9 years) and adolescents (10-14 years), PA was assessed by diaries (2 consecutive days during the week and 2 of the weekend), and for the other age groups (≥15 years), the assessment methods included the International Physical Activity Questionnaire (IPAQ) short version [
The PA diaries were an adaptation of a model proposed by Bouchard et al [
Additional questions on sedentary behaviors were also asked in all age groups (including children aged 3-6 years). From the age of 15, self-reported activities representative of “opportunistic” active choices in daily routine during the last month (eg, taking the stairs, parking further away from an entrance, or choosing to stand instead of sitting) were assessed with 6 item response options on a 5-point Likert scale (ie, 1=never, 5=always), by using the ACI scale [
The collection of PA data was performed using the e-module “Move,” including the IPAQ questionnaire and PA diaries, synchronized with metabolic equivalents data associated with each type of PA. For all types of activity, daily energy expenditure was computed using the energy cost of each activity as estimated from reference values for participants aged 15 years or more [
In children, energy expenditure was estimated by multiplying the related MET by the self-reported time spent in each activity (min/day) recorded in the diary. Individual daily energy expenditure was computed as the mean expenditure of the 4-day diaries. To validate the information from PA diaries, PA was objectively measured by accelerometry in a subsample of 35 participants from 6 to 14 years. Participants were asked in the first interview to wear an accelerometer (ActiGraph GT3X models; Pensacola, FL) during 4 days, including 2 consecutive weekdays and 2 consecutive weekend days, the same registered in the PA diary.
Adolescents and adults were asked to self-report their actual height and weight before the performance of objective measurements. In children, this information was retrieved from their health booklets, the last registry was considered. In pregnant women, weight and height was reported before pregnancy.
Anthropometric measurements, including length/height, weight, and body circumferences, were performed in both children and adults according to standard procedures [
Body weight was measured in the same conditions to the nearest tenth of a kilogram using a digital scale (SECA 813, Hamburg, Germany). For children under 2 years, a specific pediatric digital weight scale was used (SECA 354, Hamburg, Germany), and measurements were conducted with participants naked and without diaper, to the nearest 0.01 cm.
Arm, waist, and hip circumferences were measured, using an anthropometric tape, in all age groups except in children under 3 years and in pregnant women. Arm circumference was measured at the marked level of the mid-acromiale-radiale. Waist circumference was measured at the level of the narrowest point between the lower costal border and the iliac crest. Hip circumference was measured at the level of greatest posterior protuberance of the buttocks. All these circumferences were performed to the nearest 0.1 cm.
As part of quality control procedures, a bubble level was used to check the best position for the equipment in the room; a small platform was used to allow the direct observation of values from the stadiometer and the calibration of scales using standard weights of 5000 g and 500 g and their combinations was performed.
Several quality control actions were undertaken before, during, and after the fieldwork process, including the following: (1) testing the e-platform in several pilot studies performed across the different geographical regions, (2) recruitment of interviewers with thorough knowledge of the available foods on the market and traditional recipes, (3) on-going training of those interviewers (distance electronic devices were used to assist interviews, when needed), and (4) control of individual energy and macronutrient intake at the end of interview, and definition of a maximum food weight to easily identify information biases. This control is directly integrated in the software. For example, for the total energy intake, a minimum of 122 Kcal or 500 Kcal and a maximum of 2816 Kcal or 4000 Kcal were considered according to the age groups 3 months to 9 years or 10 years to 84 years, respectively. An outlier is signalized with an alert message allowing the interviewer to perform the corrections during the interview. Few other quality control actions that were undertaken are as follows: (1) preliminary statistical analysis during fieldwork to check possible information bias, the distribution of interviews by days of the week and seasons, (2) registry of doubts in an editor book to be solved by the research team, (3) calibration of anthropometric devices each 3 months, (4) application of a refusal questionnaire to nonresponders to check the representativeness of the final sample, (5) identification of under- and over-reporters of energy intake [
Ethical approval was obtained from the National Commission for Data Protection, the Ethical Committee of the Institute of Public Health of the University of Porto, and the Ethical Commissions of each one of the Regional Administrations of Health.
All participants were asked to provide their written informed consent according to the Ethical Principles for Medical Research involving human subjects expressed in the Declaration of Helsinki and the national legislation. Written agreements from the parents were required for children and adolescents below 18 years. Adolescents (10-17 years) were also asked to sign the consent form together with their legal representative.
All documents with identification data were treated separately and stored in a different dataset.
A total of 5819 participants completed 2 interviews (5811 with two complete dietary assessments) and 6553 completed only the first interview (
Final sample size by sex and age groups—the National Food, Nutrition and Physical Activity Survey, 2015-2016, (IAN-AF).
Age groups | Children (<10 years) | Adolescents (10-17 years) | Adults (18-64 years) | Elderly (≥65 years) | Total | |||||||||
Male | Female | Male | Female | Male | Female | Male | Female | |||||||
Selected participants, n | 1923 | 1965 | 952 | 988 | 8336 | 9384 | 3094 | 2541 | 29,183 | |||||
Unknown eligibility, n | 388 | 404 | 197 | 163 | 1677 | 1960 | 458 | 369 | 5616 | |||||
Known eligibility, n | 1535 | 1561 | 755 | 825 | 6659 | 7424 | 2636 | 2172 | 23,567 | |||||
Eligible, n | 1410 | 1422 | 658 | 719 | 5725 | 5971 | 2037 | 1693 | 19,635 | |||||
Noneligible, n | 125 | 139 | 97 | 106 | 934 | 1453 | 599 | 479 | 3932 | |||||
Contact rate, n (%)a | 1410 |
1422 |
658 |
719 |
5725 |
5971 |
2037 |
1693 |
19,635 |
|||||
Cooperation rate, |
769 |
745 |
351 |
349 |
1881 |
1563 |
429 |
466 |
6553 |
|||||
Participation rate, |
769 |
745 |
351 |
349 |
1881 |
1563 |
429 |
466 |
6553 |
|||||
Cooperation rate, |
667 |
660 |
319 |
313 |
1674 |
1428 |
358 |
392 |
5811 |
|||||
Participation rate, |
667 |
660 |
319 |
313 |
1674 |
1428 |
358 |
392 |
5811 |
aContact rate: eligible/(eligible + unknown eligible individuals).
bCooperation rate: participants/eligible individuals.
cParticipation rate: participants/(eligible + unknown eligible individuals).
The contact rate was 77.76%. The cooperation rate among eligible individuals was 33.37%, considering the first interview, and 29.60% for the participants with 2 completed dietary assessments. Similarly, the participation rate was 25.95% and 23.01%, respectively. The participation rates were higher in children and adolescents (approximately 40%) and much lower in the elderly (approximately 20%) (
The characteristics of participants were compared with characteristics of individuals who refused to participate and who accepted to fill out a small refusal questionnaire by phone.
Information on some important indicators, such as sex, age, and region of residence; frequency of consumption of fruit and vegetables; regular practice of leisure-time PA; and self-reported weight and height; were available. Individuals who refused to participate were older (over 65 years: 22% vs 13%) and less educated (over 12 years: 19% vs 27%), although for variables representing the main areas of the survey—fruit and vegetables consumption (≥5 portions/day: 18.6% vs 18.1%), practice of regular leisure-time PA (33% vs 39%), and obesity (12.4% vs 12.7%)—the differences are of a small magnitude.
All statistics that will be used to calculate future estimates driven from this survey, both at national or regional levels, will include the weighting of the sample data. The weighted sample represents the number of individuals from the national general population that are represented by each individual in the study sample. The sample weighting includes the following: (1) initial weights to overcome the different probability of sampling units selection; (2) a second weight to overcome the different probability of individuals selection in each unit, by sex and age (considering the total population, by sex and age groups in the closest recruitment wave); and (3) correction of these initial weights for nonresponse bias.
The distribution of the interviews by week days and seasons was also analyzed. The distribution of interviews by day of the week was 18.3%, 20.5%, 18.5%, 16.9%, 8.2%, 5.1%, and 12.6% from Monday to Sunday, respectively. The distribution of the interviews by season showed that spring was the season where most interviews were performed (35.9%), followed by winter (28.3%), summer (24.7%), and finally by autumn (11.1%).
Final databases were already checked and ready for analysis. Specific statistical analysis for identification of outliers and removal of intra-individual variability preceded the final analysis. Results of the survey will be disseminated in national and international scientific journals during 2018-2019.
The response rates were lower than expected, particularly among adults and elderly individuals, despite several dissemination activities (eg, through regional media) that were undertaken to promote the survey close to the population. However, results were similar to other national European dietary surveys using the same sampling approach [
The used sampling frame covers the entire population resident with a national identification card, which means that illegal residents such as refuges or irregular immigrants are not included. However, most of these individuals, even if included in the survey by the sampling strategy, would be noneligible, since they are non-Portuguese speakers (considered as an exclusion criteria). Moreover, the proportion of legal foreign residents is only 3.7% [
The distribution of interview week days and seasonality was checked and, although not exactly as planned, it follows the minimum requisites of having a considerable number of registries in all the week days and seasons. Fewer registries on Saturdays result from the fact that no interviews were scheduled on Sundays, as the report of both Saturdays and Sundays was conducted on Mondays. Friday also had fewer registries than other weekdays because not all health care units were opened on Saturdays, despite the continuous efforts of the fieldwork team to have alternative spaces for the interviews on Saturdays. Additionally, autumn was the season with the lowest proportion of interviews, because it coincided with the beginning and the end of the field work, when there are less concentrated interviews.
Following the European standards of dietary assessment is a major strength of this project as it will allow the comparison of important indicators in Europe in several different domains of food and nutrient intake, eating behaviors, nutritional status, food safety, and food insecurity. Information of the major contributors for sugar, sodium, or fat intake will orient new community interventions. The information could also give support to the assessment of the impact of current legislative measures, such as those related to the reduction of sugar in soft drinks or reduction of salt in bread. Furthermore, accurate and detailed food consumption data are important for the assessment of risk exposure to potentially hazardous substances. The use of the Foodex2 food classification system, proposed by EFSA [
For PA, the harmonization of procedures in Europe is still under discussion, but having information on different domains such as overall activity level, structured leisure-time physical exercise, and sedentary behaviors could be useful for supporting the estimation of indicators and to better develop new population interventions.
Findings from this survey will allow having national updated knowledge on the distribution of diet, PA, and other health-related risks according to sex, age, education, and geographical region. It also serves as an important descriptive starting point for future follow-up surveys in specific target groups. It expects to contribute to the development of national and European evidence-based policies that translate research into effective nutrition and health strategies, sustainable over time. A comprehensive analysis according to socioeconomic dimensions will also contribute to the development of policies with impact in equity and human well-being.
It is expected that the structure and information driven from this survey could also contribute to develop and consolidate solid infrastructures for epidemiological and public health research by building a future national functioning surveillance system on diet, PA, and other health behaviors, reproducible over time.
Activity Choice Index
computer-assisted personal interviewing
electronic assessment tool for 24-hour recall
eating behaviors
European Food Safety Authority
food diary
Food Propensity Questionnaire
general health
household food security
The National Food, Nutrition and Physical Activity Survey, 2015-2016 (Portuguese acronym)
International Physical Activity Questionnaire
physical activity
physical activity diaries
sedentary behaviors
sociodemographics
24-h recall
The IAN-AF 2015-2016 Survey was conducted by a Consortium, coordinated by CL. All authors are members of the Consortium and were involved in the design of the study and contributed for the writing of the manuscript. All authors critically revised and approved the manuscript.
None declared.