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Epidemiologia e Serviços de Saúde

Print version ISSN 1679-4974On-line version ISSN 2237-9622

Epidemiol. Serv. Saúde vol.28 no.3 Brasília  2019  Epub Oct 28, 2019 


Positive self-perception of diet: a population-based study in the far south of Brazil*

Karla Pereira Machado1

Juliana dos Santos Vaz2

Raúl Andrés Mendoza-Sassi1

1Universidade Federal do Rio Grande, Programa de Pós-Graduação em Saúde Pública, Rio Grande, RS, Brasil

2Universidade Federal de Pelotas, Programa de Pós-Graduação em Nutrição e Alimentos, Pelotas, RS, Brasil



to analyze prevalence of positive self-perception of diet and association with sociodemographic and behavioral factors, morbidity, self-perception of health and weight, and body weight care, in the city of Rio Grande, RS, Brazil, in 2016.


this was a cross-sectional study conducted with adults and elderly people resident in the city of Rio Grande using 13 indicators of healthy eating and positive self-perception of diet (outcome); Poisson regression was used.


the sample consisted of 1,243 individuals, 72.4% of whom reported positive self-perception of diet; indicators such as weekly consumption of greens or vegetables (PR=133 - 95%CI 1.22;1.45) and fruit (PR=1.35 - 95%CI 1.22;1.48) were positively associated with the outcome; no significant difference was found between sexes.


positive self-perception of diet is associated with healthy eating indicators among adults and the elderly and can be useful in epidemiological surveys.

Keywords: Food Consumption; Self Report; Health Surveys; Cross-Sectional Studies



analisar a prevalência de autopercepção positiva da alimentação e sua associação com fatores sociodemográficos, comportamentais, morbidades, autopercepção da saúde e do peso e cuidados com o peso corporal, no município de Rio Grande, RS, Brasil, em 2016.


estudo transversal realizado com adultos e idosos residentes no município. Foram aplicados 13 indicadores de alimentação saudável e autopercepção de alimentação (desfecho). Empregou-se regressão de Poisson.


a amostra foi de 1.243 indivíduos, dos quais 72,4% referiram autopercepção positiva da alimentação. Indicadores como consumo semanal de verduras ou legumes (RP=1,33 - IC95% 1,22;1,45) e frutas (RP=1,35 - IC95% 1,22;1,48) foram positivamente associados ao desfecho. Não houve diferença significativa entre os sexos.


a autopercepção de alimentação positiva se associa com indicadores de alimentação entre adultos e idosos, podendo ser útil em estudos epidemiológicos.

Palavras-chave: Consumo de Alimentos; Autorrelato; Inquéritos Epidemiológicos; Estudos Transversais



investigar la prevalencia de autopercepción positiva de la alimentación, sus factores sociodemográficos y comportamentales, morbilidades, autopercepción de la salud/peso y cuidados con el peso corporal en el municipio de Rio Grande, RS, Brasil, en 2016.


estudio transversal realizado con adultos y ancianos residentes en el municipio de Rio Grande; se aplicaron 13 indicadores de alimentación saludable y autopercepción de la alimentación; se utilizó la regresión de Poisson.


la muestra fue de 1.243 individuos, 72,4% refirió autopercepción positiva de la alimentación; indicadores como consumo semanal de verduras o legumbres (RP=1,33 - IC95% 1,22;1,45) y frutas (RP=1,35 - IC95% 1,22;1,48) fueron positivamente asociadas al desenlace (p<0,001); no hubo diferencia significativa entre los sexos.


la autopercepción positiva de la alimentación se asocia con indicadores de alimentación entre adultos y ancianos pudiendo ser útil en estudios epidemiológicos.

Palabras-clave: Consumo de Alimentos; Autoinforme; Encuestas Epidemiológicas; Estudios Transversales


The Brazilian People’s Food Guide and the Ten Steps for Healthy Eating - official Ministry of Health document, is dedicated to the approach and recommendation of a adequate and healthy eating, being configured as instruments extremely important to achieve a behavior change in the Brazilian population.1-3 When a person has an adequate level of information about health and nutrition and their individual perception is critical, it is possible for them to keep to a greater number of healthy indicators,4,5 regardless of income. Income, or the cost of food, is one of the main factors influencing health behavior and, consequently, is an aspect to be assessed when choosing what food to buy.6

The relationship between a person’s self-perception of the quality of what they eat and the occurrence of truly health eating habits is, however, little explored in the national and international literature. The studies existing on this theme have evaluated this outcome, mostly among school students and adolescents, and have identified a direct relationship between positive self-perception of diet and more adequate eating habits.1,2,4 In research into food and nutrition, eating habits are evaluated by administering a questionnaire on eating frequency or through standardized surveys that generally require a long time to be conducted.7,8 They are not very practical instruments for situations in which contact between health professionals and their patients is brief. The importance of proposing a question about self-perception, capable of identifying people’s eating habits4,9 and the risk represented by unhealthy eating habits, should be reflected in the indication of target groups for possible interventions.10

The objective of this article was to analyze the prevalence of positive self-perception of diet and its association with sociodemographic and behavioral factors, morbidities, self-perception of health/weight and body weight care in the municipality of Rio Grande, located in Rio Grande do Sul state, Brazil, in 2016.


This is a cross-sectional population-based study conducted in the south of Rio Grande do Sul state. It is part of a larger study entitled ‘Health of the Population of Rio Grande-RS’,11 the purpose of which was to investigate diverse aspects of the health profile of the population of Rio Grande. This municipality iis located in the far south of the state, it had around 200,000 inhabitants and a human development index (HDI) of 0.744 In 2010.13 In 2015, its economy continued to based mainly on its seaport and its gross domestic product (GDP) was close to BRL 35,000 per capita/per annum.

The study’s target audience was comprised of individuals aged 20 years or over who lived in the urban area of Rio Grande. We excluded those who were institutionalized in hospices, hospitals and prisons, or who had physical and/or mental disabilities that prevented them from answering the questionnaire.

Sample size was calculated using as a parameter 51% prevalence for the outcome studied,2,10,14 a 95% confidence level and an acceptable error rate of 3 percentage points. With regard to associated factors, we considered a prevalence ratio (PR)13 of 1.5, a 95% confidence level, 80% power, exposed frequency of between 35% and 50%, as well as a design effect of 1.5, 10% for losses and 15% for control of confounding factors. The final sample size was 1152 individuals. Calculations were performed using Epi Info 7.0 (Centers for Disease Control and Prevention, Atlanta, United States). As this study was part of a larger study that had different outcomes, we decided to use the larger sample size calculated (n=1423) so as to make the study representative for the different independent variables investigated, whereby power of 90% was considered for this number (1423).

In order to ensure sample representativeness, the sampling process occurred in two stages: census tract and household, in accordance with data from the 2010 Demographic Census.12 Initially we identified the 293 census tracts of the urban area of Rio Grande and systematically selected from within them all the urban households (77,835), placed in decreasing order according to the average monthly income of the head of the household. After randomly selecting the first household, we then performed systematic selection, by “skipping” 1,080 households and thus selecting 72 census tracts.

Random selection was then performed to determine which households to be studied. We reached a total of 711 residences, with 32 residences being “skipped” and an expected average of 2.08 individuals per household.12 Census tract and household selection was done based on probability proportional to the population and the number of households per census tract.

Data collection took place between April and June 2016 and was done by nine interviewers trained beforehand. The interviews were conducted in the selected households with all eligible dwellers, following the script of a questionnaire structured, standardized and previously tested comprised of sociodemographic and general health questions, pre-coded.

The study outcome, positive self-perception of diet, was investigated by asking the question “How do you rate your diet?” with the following answer alternatives: ‘very good’, ‘good’, ‘regular’, ‘poor’ or ‘very poor’. For the purposes of analysis, this variable was dichotomized between positive (very good/good) and negative (regular/poor/very poor).

We used 13 indicators of healthy eating, collected over what was a usual week for participants. These indicators were established according to the Brazilian People’s Food Guide recommendations. This publication, which was reformulated in 2014,3 provides guidance as to giving preference to natural food or minimally processed food, rather than ultra-processed food, so as to have a diet comprised of healthy meals.3 The following are the indicators we used:

  • I) having breakfast;

  • II) having lunch;

  • III) having an afternoon snack or coffee;

  • IV) having dinner;

  • V) having a snack or coffee before going to bed at night;

  • VI) habit of eating visible fat on red meat and/or eating chicken skin; and

  • VII) adding more salt.

Indicators I to VII were collected in a dichotomous manner (yes/no); for indicators I to V, appropriate consumption was when the answer was ‘yes’, while for indicators VI to VII is was when the answer was ‘no’.

A further six indicators were collected relating to consumption frequency:

  • VIII) number of days a week you usually eat leguminous plants;

  • IX) number of days a week you usually eat greenery or vegetables;

  • X) number of days a week you usually eat fruit;

  • XI) number of days a week you usually eat fish;

  • XII) number of days a week you usually eat food containing sugar - ice cream, chocolate, cake, biscuits or confectionary -; and

  • XIII) number of days a week you usually drink soda or artificial fruit juice.

These indicators were collected in a polytomous manner: (a) never/hardly ever; (b) 1 to 2 days a week; (c) 3 to 4 days a week; (d) 5 to 6 days a week; (e) every day (including Saturday and Sunday). For the purpose of analysis these indicators were subsequently dichotomized based on adapted Brazilian People’s Food Guide recommendations.3 For indicators VIII to XI, consumption was considered to be adequate when frequency was equal to or greater than 3 times a week; while for indicators XII and XIII, adequate consumption was considered to be ‘never/hardly ever’ and ‘1 to 2 days a week’.

The following independent variables were included:

  • a) Sociodemographic

  • - sex (male; female);

  • - age (in years: 20-29; 30-39; 40-49; 50-59; 60 or more);

  • - self-reported race/skin color (white; black/brown/yellow/indigenous);

  • - marital status (married; single; divorced/separated/widowed);

  • - schooling (in years of study: 0-4; 5-8; 9-11; 12 or more); and

  • - income (in quartiles: 1st quartile [poorest], BRL 293.3 - BRL 520.0; 2nd quartile, BRL 750.0 - BRL 905.5; 3rd quartile, BRL 1,166.7 - BRL 1,500.0; and 4th quartile [wealthiest], BRL 2,200.0 - BRL 4,400.0), whereby the minimum wage in 2016 was BRL 880.00.

  • b) Behavior variables (answer options: ‘yes’ or ‘no’)

  • - tobacco smoking (non-smoker; former smoker/smoker);

  • - alcoholic beverage consumption (does not drink; drinks less than once a week /number of times drinks per week);

  • - physical activity in leisure time, measured as per the ‘Leisure’ section of the International Physical Activity Questionnaire (IPAQ-SHORT), which defines as being active a person who does ≥150 minutes of physical activity a week;15

  • c) Body mass index (BMI) (underweight; normal weight; overweight; obese);

  • d) Self-reported morbidities (presence or absence) - diabetes; - hypertension; - depression - this latter variable being collected as per the Patient Health Questionnaire (PHQ-9), which defines depression as ≥9;16

  • e) Food insecurity, measured by the Brazilian Food Insecurity Scale (EBIA) (food security; mild food insecurity; moderate/severe food insecurity);17

  • f) Self-perception of health (excellent/very good; good; regular/poor)

  • g) Self-perception of body weight (normal; very thin/thin/slightly thin; very fat/fat/slightly fat); and

  • h) Body weight care. This variable was collected by asking “Are you doing anything to lose weight or gain muscle mass?”, with ‘yes’ or ‘no’ as the answer options.

All answered questionnaires were checked and input twice by different typists using EpiData® 3.1 (EpiData Association, Denmark). Quality control was performed by partially repeating 10.5% of the interviews using selected key questions in order to check the reliability of the instrument. The mean value of the Kappa coefficient for agreement between the questions was 0.80 (variation = from 0.27 [number of times a week spent walking in free time] to 0.93 [existence of landline telephone in household]), demonstrating substantial agreement.18

First of all we calculated the absolute and relative frequencies of the five Likert scale categories contained in the outcome (positive self-perception of diet), as well as prevalence and 95% confidence interval (95%CI) of the dichotomized outcome.

We used Poisson regression to study the impact of the independent variables on the outcome, taking into consideration the effect of the study design. We calculated the prevalence ratios (PR) and their 95%CI. We used a four-level hierarchical model. The first level was comprised of the demographic and socio-economic variables, while the second level was comprised of the behavioral variables. The third level contained variables relating to morbidity and food security, while the fourth level contained self-perception of health and self-perception of body weight and body weight care variables. Exposures of interest were adjusted for variables on the same level an on higher levels, so that only variables having p≤0.20 remained in the model. We used the Wald test as the statistical test.

We then estimated the PR and 95%CI of each of the food consumption indicators. Finally, applying the proportion test enabled us to analyze differences between the food consumption indicators and the ‘healthy self-perception’ outcome, stratified by sex.

Data analysis was performed using Stata® version 14.0 (StataCorp/College Station, United States). A significance level of less than 5% was adopted for the two-tailed tests and the sampling design effect was taken into consideration in all the analysis by using the survey (svy) command.

The research protocol was submitted to and approved by the Federal University of Rio Grande (FURG) Health Research Ethics Committee (CEPAS), under number 20/2016. All ethical principles were assured, the Free and Informed Consent form was presented to the respondents and all participants signed it, thus ensuring the right not to take part in the study and ensuring their right to confidentiality.


A total of 1,243 questionnaires were answered (8.9% losses and refusals). The study outcome was answered by 1,240 individuals. More than half were females (56.4%), the majority self-reported having White race/skin color (83.1%) and average age was 47 years (standard deviation [SD]: ±16.6 years). Some 57% had more than 9 years of schooling, and median income was BRL 1,000.00 (P25: BRL 625.00-P75; BRL 1,764.00). The majority did not do physical activities in their leisure time (77.5%) and food insecurity was found in 34.5% of households (Table 1).

Table 1 - Description of the sample of adults and elderly people (n=1,243), Rio Grande, Rio Grande do Sul, 2016 

Variables Overall sample
N %
Male 542 43.6
Female 701 56.4
Age (in years)
20-29 226 18.2
30-39 225 18.1
40-49 240 19.3
50-59 237 19.1
≥60 315 25.3
Race/skin color (n=1,241)
White 1,301 83.1
Black/brown/yellow/indigenous 210 16.9
Marital status
Married 476 38.3
Single 545 43.8
Divorced/separated/widowed 222 17.9
Schooling (in years of study) (n=1,241)
0-4 190 15.3
5-8 343 27.6
9-11 367 29.6
≥12 341 27.5
Income in quartiles (n=1,123)
1st quartile (poorest) 284 25.3
2nd quartile 306 27.2
3rd quartile 255 22.7
4th quartile (wealthiest) 278 24.8
Tobacco smoking
No 1,003 81.5
Yes 230 18.5
Alcoholic beverage consumption (n=1,242)
No 896 72.1
Yes 346 27.9
Physical activity in leisure timea (n=1,233)
Insufficiently active 956 77.5
Sufficiently active 277 22.5
Body mass index (BMI) (n=1,189)
Underweight 14 1.2
Normal weight 431 36.2
Overweight 458 38.5
Obese 286 24.1
Diabetes (self-reported) (n=1,239)
No 1,149 92.7
Yes 90 7.3
Hypertension (self-reported) (n=1,242)
No 879 70.8
Yes 363 29.2
Depressionb (n=1,238)
No 893 72.1
Yes 345 27.9
Self-perception of healthy eating habits (n=1,240)
Negative 342 27.6
Positive 898 72.4
Food insecurityc (n=1,224)
Food security 802 65.5
Mild food insecurity 330 27.0
Moderate/severe food insecurity 92 7.5
Self-perception of health
Excellent/very good 263 21.2
Good 560 45.0
Regular/poor 420 33.8
Self-perception of body weight (n=1,242)
Normal 123 9.9
Very thin/thin/slightly thin 563 45.3
Very fat/fat/slightly fat 556 44.8
Body weight care
No 973 78.3
Yes 270 21.7
Total 1,243 100.0

a) As per the ‘Leisure’ section of the International Physical Activity Questionnaire (IPAQ-SHORT), which defines as being active a person who does ≥150 minutes of physical activity a week.

b) As per the Patient Health Questionnaire (PHQ-9), which defines depression as ≥9.

c) Brazilian Food Insecurity Scale (EBIA).

The frequencies of diet self-perception were: very good - 16.9%; good - 55.5%; regular - 23.2%; poor - 3.4%; and very poor - 1.0%. When this variable was dichotomized, prevalence of positive self-perception of diet was 72.4% (95%CI 69.9;74.9).

The crude PRs and the PRs adjusted for the outcome are shown in Table 2. In the adjusted analysis, outcome prevalence was lower among females when compared to males (PR=0.94 - 95%CI 0.80;1.00). Individuals aged 60 or over had 1.28 times more probability of having the outcome, compared to those in the 20-29 age range, probability was also greater for those in the highest income quartile (PR=1.17 - 95%CI 1.04;1.32), in relation to those in the poorest quartile. On the second level, the outcome increased among those who did physical activity for 150 minutes or more in their leisure time (PR=1.17 - 95%CI 1.08;1.26). On the third level, individuals who reported morbidities such as diabetes (PR=0.98 - 95%CI 0.84;1.14) and depression (PR=0.78 - 95%CI 0.81;0.95) were less likely to have positive self-perception of diet. With regard to food insecurity, the outcome was less likely among those facing mild food insecurity (PR=0.88 - 95%CI 0.81;0.95).

Table 2 - Prevalence and crude and adjusted analysis of factors associated with positive self-perception of diet among adults and elderly people (n=1,240), Rio Grande, Rio Grande do Sul, 2016 

Variables Prevalence of positive self-perception of diet (n=898) N (%) Crude Analysis Adjusted Analysis
PRa (95%CIb) pc PRa (95%CIb) pc
1st level
Sex 0.297 0.071
Male 400 (73.9) 1.00 1.00
Female 498 (71.2) 0.97 (0.90;1.03) 0.94 (0.88;1.00)
Age (in years) <0.001 <0.001
20-29 142 (62.8) 1.00 1.00
30-39 140 (62.2) 0.98 (0.84;1.14) 0.93 (0.80;1.08)
40-49 163 (67.9) 1.08 (0.93;1.25) 1.06 (0.92;1.22)
50-59 190 (80.2) 1.26 (1.12;1.44) 1.23 (1.09;1.39)
≥60 263 (84.3) 1.33 (1.17;1.51) 1.28 (1.13;1.44)
Race/skin color (n=896) 0.594 0.249
White 739 (71.9) 1.00 1.00
Black/brown/yellow/indigenous 157 (74.8) 1.03 (0.93;1.14) 1.05 (0.95;1.16)
Marital status 0.028 0.641
Married 360 (75.8) 1.00 1.00
Single 367 (67.6) 0.90 (0.82;0.98) 0.99 (0.89;1.09)
Divorced/separated/widowed 171 (77.0) 1.01 (0.93;1.11) 0.96 (0.87;1.05)
Schooling (in years of study) (n=897) 0.081d 0.395d
0-4 144 (76.6) 1.00 1.00
5-8 257 (74.9) 0.98 (0.88;1.10) 0.99 (0.88; 1.11)
9-11 260 (71.0) 0.93 (0.82;1.06) 0.96 (0.83;1.11)
≥12 236 (69.2) 0.92 (0.81;1.03) 0.95 (0.82;1.11)
Income in quartiles (median; P25/P75 in BRL )e (n=810) 0.002d 0.017d
1st quartile - poorest (BRL 293.3 to BRL 520.0) 183 (64.4) 1.00 1.00
2nd quartile (BRL 750.0 to BRL 905.5) 219 (72.3) 1.13 (1.01;1.25) 1.09 (0.98;1.22)
3rd quartile (BRL 1,166.7 to BRL 1,500.0) 187 (73.3) 1.14 (1.01;1.28) 1.07 (0.95;1.20)
4th quartile - wealthiest (BRL 2,200.0 to BRL 4,400.0) 221 (79.5) 1.24 (1.10;1.40) 1.17 (1.04;1.32)
2nd level
Current tobacco smoking 0.205 0.398
No 740 (73.2) 1.00 1.00
Yes 158 (69.0) 0.94 (0.86;1.04) 0.95 (0.84;1.07)
Alcoholic beverage consumption (n=897) 0.564 0.927
No 643 (71.0) 1.00 1.00
Yes 254 (73.6) 1.03 (0.95;1.11) 1.00 (0.91;1.09)
Physical activity in leisure timef (n=893) <0.001 <0.001
Insufficiently active 667 (69.8) 1.00 1.00
Sufficiently active 226 (81.6) 0.86 (0.80;0.92) 1.17 (1.08;1.26)
Body mass index (BMI) (n=854) 0.009d 0.015d
Underweight 11 (78.6) 1.00 1.00
Normal weight 325 (75.6) 0.96 (0.74;1.25) 0.90 (0.69;1.17)
Overweight 329 (71.8) 0.91 (0.71;1.17) 0.86 (0.67;1.10)
Obese 189 (66.1) 0.85 (0.65;1.09) 0.80 (0.62;1.05)
3rd level
Diabetes (self-reported) (n=895) 0.972 0.761 0.071
No 829 (72.3) 1.00 1.00
Yes 66 (73.3) 1.00 (0.88;1.14) 0.98 (0.84;1.14)
Hypertension (self-reported) 0.791 0.094 <0.001
No 637 (72.6) 1.00 1.00
Yes 261 (72.1) 0.99 (0.92;1.07) 0.93 (0.85;1.01)
Depressiong (n=896) <0.001 <0.001 0.249
No 697 (78.1) 1.00 1.00
Yes 199 (57.7) 0.74 (0.68;0.81) 0.78 (0.81;0.95)
Food insecurityh (n=884) <0.001 0.006 0.641
Food security 604 (75.5) 1.00 1.00
Mild food insecurity 214 (64.9) 0.86 (0.80;092) 0.88 (0.81;0.95)
Moderate/severe food insecurity 66 (71.7) 0.95 (0.81;1.12) 1.01 (0.85;1.22)
4th level
Self-perception of health <0.001 d 0.001d 0.398
Excellent/very good 210 (79.9) 1.00 1.00
Good 439 (78.4) 0.98 (0.91;1.06) 0.98 (0.89;1.07)
Regular/poor 249 (59.7) 0.74 (0.66;0.83) 0.75 (0.66;0.86)
Body weight care <0.001 0.030 0.927
No 682 (70.3) 1.00 1.00
Yes 216 (80.0) 1.15 (1.07;1.23) 1.10 (1.01;1.21)
Self-perception of body weight (n=897) <0.001 <0.001 <0.001
Normal weight 89 (73.0) 1.00 1.00
Thin (very thin/slightly thin/thin) 452 (80.4) 1.09 (0.97;1.23) 0.99 (0.88;1.14)
Fat (very fat/slightly fat/fat) 356 (64.1) 0.88 (0.77;1.00) 0.80 (0.69;0.95)

a) PR: prevalence ratio.

b) 95%CI: 95% confidence interval.

c) P-value obtained using Wald’s heterogeneity test.

d) P-value obtained using Wald’s linear trend test.

e) Taking the Brazilian minimum wage of BRL 880.00 in 2016.

f) As per the ‘Leisure’ section of the International Physical Activity Questionnaire (IPAQ-SHORT), which defines as being active a person who does ≥150 minutes of physical activity a week.

g) As per the Patient Health Questionnaire (PHQ-9), which defines depression as ≥9.

h) Brazilian Food Insecurity Scale (EBIA).

Note: Sampling design effect taken into consideration.

On the fourth level we found that positive perception of diet was lower among those whose self-perception of their health was regular or poor (PR=0.75 - 95%CI 0.66;0.86) (p=0.001), when compared to those who reported excellent or very good self-perception of their health. Those who reported being careful with their body weight were more likely to perceive their eating habits as being positive (PR=1.10 - 95%CI 1.01;1.21).

Ten of the thirteen indicators of adequate eating habits were significantly associated with the outcome (Table 3). The proportion of individuals with indicators of a healthy diet and positive self-perception of their eating habits was greater than 70.0%. There was no difference in the prevalence rates of healthy diet indicators between males and females (Table 4).

Table 3 Association between positive self-perception of diet and indicators of healthy eating among adults and elderly people (n=1,240), Rio Grande, Rio Grande do Sul, 2016 

Variables Positive self-perception of diet
PRa 95%CIb
Having breakfast
No 1.00 -
Yes 1.46 1.22;1.75
Having lunch
No 1.00 -
Yes 1.77 1.00;3.13
Having an afternoon snack or coffee
No 1.00 -
Yes 1.16 1.05;1.30
Having dinner
No 1.00 -
Yes 0.95 0.84;1.07
Having a snack or coffee before going to bed at night
No 1.00 -
Yes 1.19 1.11;1.27
Leguminous plant consumptionc
Inadequate 1.00 -
Adequate 1.18 1.04;1.32
Greenery or vegetable consumptionc
Inadequate 1.00 -
Adequate 1.33 1.22; 1.45
Fruit consumptionc
Inadequate 1.00 -
Adequate 1.35 1.22;1.48
Fish consumption c (n=1,177)e
Inadequate 1.00 -
Adequate 1.15 1.04;1.26
Soda and artificial fruit juice consumptiond
Inadequate 1.00 -
Adequate 1.15 1.06;1.24
Sweetened food consumption d (n=1,239)e
Inadequate 1.00 -
Adequate 1.01 0.93;1.09
Adding more salt d
No 1.00 -
Yes 0.90 0.76;1.03
Habit of eating visible fat on red meat and/or eating chicken skin
No 1.00 -
Yes 0.85 0.77;0.93

a) PR: prevalence ratio.

b) 95%CI: 95% confidence interval.

c) Adequate = when consumption 3 or more days a week reported.

d) Adequate = when consumption of up to 2 days a week reported.

e) Sample number available for this variable.

Note: Sampling design effect taken into consideration.

Table 4 - Association between positive self-perception of diet and indicators of healthy eating, stratified by sex, in adults and elderly (n=898), Rio Grande, Rio Grande do Sul, 2016 

Variables Occurrence of positive self-perception of diet
Female (n=498) n (%) Male (n=400) n (%) p-valuea
Having breakfast 452 (73.6) 354 (78.7) 0.075
Having lunch 493 (71.8) 398 (74.3) 0.402
Having an afternoon snack or coffee 416 (72.5) 297 (77.8) 0.068
Having dinner 458 (70.7) 366 (73.9) 0.287
Having a snack or coffee before going to bed at night 145 (82.4) 131 (0.4) 0.443
Adequate consumption of leguminous plantsb 387 (73.6) 332 (76.5) 0.319
Adequate consumption of greenery or vegetablesb 360 (79.7) 248 (79.7) 1.000
Adequate consumption of fruitb 358 (79.6) 254 (81.2) 0.549
Adequate consumption of fishb 33 (82.5) 37 (82.2) 0.906
Adequate consumption of soda and artificial fruit juicec 231 (66.0) 225 (69.7) 0.238
Adequate consumption of sweet foodstuffsc 249 (71.5) 189 (73.4) 0.527
Does not add more salt to food 454 (71.2) 362 (75.7) 0.130
Does not eat eating visible fat on red meat and/or chicken skin 182 (63.4) 206 (68.2) 0.133

a) P-value obtained from proportion test.

b) Adequate = when consumption 3 or more days a week reported.

c) Adequate = when consumption of up to 2 days a week reported.


Standing out among the main findings of this study is the prevalence of positive self-perception of diet and its association with ten indicators of adequate food consumption. Greater frequency of positive self-perception of diet was found among people who were older, had higher income and were considered sufficiently physically active, in contrast to those who reported depression and mild food insecurity.

The prevalence of positive self-perception of diet found in this study is similar to that found in other research conducted in Brazil.10,19 In 2016, a study carried out in the country’s southern region revealed 69% prevalence of positive self-perception of diet in a sample of adults and elderly people who used the urban primary health care network.10 In the study conducted by the National Health and Nutrition Examination Survey (NHANES) 2005-2006, however, only 33% of the adult United States population perceived their diet as being excellent or very good (high score) and 42% considered it to be good (medium score).14 The prevalence of positive self-perception of diet found in the United States would have been close to that found in our study if the ‘good’ (medium score) classification in the United States study had been considered positive. Methodological differences, such as the type of instrument used to measure the outcome, can be seen between studies, thus highlighting the importance of defining evaluation criteria in the sense of enabling greater comparability between the literature.

Differences in positive self-perception of diet can also occur for other reasons, in particular cultural differences (different considerations as to what is adequate, according to countries and cultures) and time differences (different periods of time in which studies are conducted). Firstly, it is important to define adequate diet according to Ministry of Health recommendations - such as the Brazilian People’s Food Guide -,3 taking into consideration the variability of the concept over time, according to the reasons mentioned above, and their influence on what each person considers to be adequate in terms of their own diet.

In this study, ten of the thirteen indicators of healthy diet studied were associated with the outcome. Association between self-perception of diet and health and food outcomes has been reported in other noteworthy studies in the literature.14,19-21 Self-perception of diet can therefore be a simple and feasible means of inferring the quality of a person’s diet.4,22

Females had lower positive perception of diet than males. This can possibly be explained by the fact of women paying more attention to aspects relating to taking care with health and diet and therefore identifying better what is healthy and being more judicious in their self-evaluation.10 As males have been historically associated with taking less care of their health, having a diet with more fat and greater intake of alcoholic beverages, they may possibly have less perception of the impact of these habits on maintaining a healthy life.10,19

Age was associated with better self-perception of diet. It is known that older people demonstrate greater variety in food intake.6,8,14,20 The elderly may also restrict intake of some types of food, as a preventive or treatment measure in the face of chronic diseases and, as a consequence of this attitude, may consider their diet to be healthier.8,14 In our study, schooling did not show any statistical difference with perception of diet. Notwithstanding, other studies have found that individuals with less schooling have less perception of diet, less access to information and to health care.23,24

Both income and food security were associated with the outcome. It is known that among poorer individuals, price is a criterion affecting choice of purchasing food products and can influence not only reduced quantity of food but also loss of its nutritional quality and variety,6,23 thus impacting negatively on healthy food consumption behavior.5,6,21

We found that individuals with poor perception of their state of health had reduced positive perception of their diet, on the contrary to individuals considered to be physically active whose perception was better in relation to the physically inactive. It is consensus in the literature that individuals with a better perception of health are more prone to looking after their health as a whole, thus presenting healthier behaviors.10,19,21,25,26

Poorer perception of diet was found among those assessed as having depression. This reinforces the importance of paying attention to diet in this group. Depressed individuals can demonstrate unhealthy behaviors such as, for instance, poor diet, compensatory food intake according to their current mood, sedentariness and sleep alterations.14

This study has some limitations. The first lies in its cross-sectional design, since it is possible that individuals with positive self-perception of diet may have made recent changes to their eating habits and that the healthy diet they reported may have been a more recent habit and not a longstanding one. There may also be other types of bias, such as bias related to food intake and the possibility of people giving answers they think are more adequate or even more socially acceptable, especially when the question is posed by someone else. However, food intake items were significantly associated with questions about positive self-perception, suggesting that the respondents’ answers were consistent. A cross-sectional design is useful for identifying target groups such as, for example, individuals who intend or feel duty-bound to improve their diet, or who already have morbidities - diabetes, hypertension, hypercholesterolemia -, and who need effective and specific actions. Another limitation was related to the use of subjective questions, the answers to which are conditioned by the individual’s interpretation of what is being asked.

Standing out among the study’s strong points is its population-based design and the low number of losses and refusals, thus reducing the likelihood of selection bias, as well as interviewer training and the quality control measures applied.

In conclusion, the findings showed that positive self-perception of diet was related to ten of the thirteen diet indicators evaluated. Negative self-diagnosis of diet can stimulate the need for behavior change, as well as provoking the process of adopting adequate dietary habits. This information can be useful for health professionals directly involved in providing people with health guidance. Nevertheless, further studies on this theme are needed in order to gain better understanding of how self-perception is reflected in dietary practices.


1. Toral N, Slater B, Cintra IP, Fisberg M. Adolescent eating behavior regarding fruit and vegetable intakes. Rev Nutr [Internet]. 2006 May-Jun [cited 2019 Jun 19];19(3):331-40. Available from: Available from: . doi: 10.1590/S1415-52732006000300004 [ Links ]

2. Gregory CA, Smith TA, Wendt M. How Americans rate their diet quality: an increasingly realistic perspective. Econ Inf Bul [Internet]. 2011 Sep [cited 2019 Jun 19];83:1-18. Available from: Available from: ]

3. Ministério da Saúde (BR). Secretaria de Atenção à Saúde. Departamento de Atenção Básica. Coordenação Geral da Política de Alimentação e Nutrição. Guia alimentar para a população brasileira. 2. ed. Brasília: Ministério da Saúde; 2014 [citado 2019 jun 19]. 156 p. Disponível em: Disponível em: ]

4. Rodrigues PRM, Gonçalves-Silva RMV, Ferreira MG, Pereira RA. Viabilidade do uso de uma questão simplificada na avaliação da qualidade da dieta de adolescentes. Ciênc Saúde Coletiva [Internet]. 2017 maio [citado 2019 jun 19];22(5):1565-78. Disponível em: Disponível em: . doi: 10.1590/1413-81232017225.14102015 [ Links ]

5. Strachan S, Brawley L. Healthy-eater identity and self-efficacy predict healthy eating behavior: a prospective view. J Health Psychol [Internet]. 2009 Jul [cited 2019 Jun 19];14(5):684-95. Available from: Available from: . doi: 10.1177/1359105309104915 [ Links ]

6. Defante LR, Nascimento LDO, Lima-Filho DO. Comportamento de consumo de alimentos de famílias de baixa renda de pequenas cidades brasileiras: o caso de Mato Grosso do Sul. Interações (Campo Grande) [Internet]. 2015 jul-dez [citado 2019 jun 19];16(2):265-76. Disponível em: Disponível em: . doi: 10.1590/151870122015203 [ Links ]

7. Cade J, Thompson R, Burley V, Warm D. Development, validation and utilisation of food-frequency questionnaires - a review. Public Health Nutr [Internet]. 2002 Aug [cited 2019 Jun 19];5(4):567-87. Available from: Available from: . doi: 10.1079/PHN2001318 [ Links ]

8. Henn RL, Fuchs SC, Moreira LB, Fuchs FD. Development and validation of a food frequency questionnaire (FFQ-Porto Alegre) for adolescent, adult and elderly populations from Southern Brazil. Cad Saúde Pública [Internet]. 2010 nov [citado 2019 jun 19];26(11):2068-79. Disponível em: Disponível em: . doi: 10.1590/S0102-311X2010001100008 [ Links ]

9. Gomes AA, Pereira RA, Yokoo EM. Characterization of adults food intake based on simplified questionnaire: contribution to food and nutrition surveillance studies. Cad Saúde Colet [Internet]. 2015 Oct-Dec [cited 2019 Jun 19];23(4):368-73. Available from: Available from: . doi: 10.1590/1414-462X201500040055 [ Links ]

10. Lindemann IL, Oliveira RR, Mendoza-Sassi RA. Difficulties in ensuring a healthy diet among primary health care users and associated factors. Ciênc Saúde Coletiva [Internet]. 2016 Feb [cited 2019 Jun 19];21(2):599-610. Available from: Available from: . doi: 10.1590/1413-81232015212.04262015 [ Links ]

11. Dumith SC, Paulitsch RG, Carpena MX, Muraro MFR, Simões MO, Machado KP, et al. Planejamento e execução de um inquérito populacional de saúde por meio de consórcio de pesquisa multidisciplinar. Sci Med [Internet]. 2018 Jul-Sep [cited 2019 Jun 19];28(3):1-8. Available from: Available from: ]

12. Instituto Brasileiro de Geografa e Estatistica. Censo demográfico 2010 [Internet]. Rio de Janeiro: Instituto Brasileiro de Geografa e Estatistica; 2011 [cited 2019 Jun 19]. Available from: Available from: ]

13. Instituto Brasileiro de Geografia e Estatística. Pesquisa nacional por amostras de domicílios 2013 [Internet]. Rio de Janeiro: Instituto Brasileiro de Geografia e Estatística; 2014 [citado 2019 jun 19]. Disponível em: Disponível em: ]

14. Powell-Wiley TM, Miller PE, Agyemang P, Agurs-Collins T, Reedy J. Perceived and objective diet quality in US adults: a cross-sectional analysis of the National Health and Nutrition Examination Survey (NHANES). Public Health Nutr [Internet]. 2014 Dec [cited 2019 Jun 19];17(12):2641-9. Available from: Available from: . doi: 10.1017/S1368980014000196 [ Links ]

15. Matsudo S, Araujo T, Matsudo V, Andrade D, Andrade E, Oliveira LC, et al. Questionário internacional de atividade fisica (IPAQ): estudo de validade e reprodutibilidade no Brasil [Internet]. Rev Bras Ativ Fís Saúde [Internet]. 2001 dez [citado 2019 jun 19];6(2):5-18. Disponível em: Disponível em: . doi: 10.12820/rbafs.v.6n2p5-18 [ Links ]

16. Santos IS, Tavares BF, Munhoz TN, Almeida LSP, Silva NTB, Tams BD, et al. Sensibilidade e especificidade do Patient Health Questionnaire-9 (PHQ-9) entre adultos da população geral. Cad Saúde Pública [Internet]. 2013 Aug [cited 2019 Jun 19];29(8):1533-43. Available from: Available from: . doi: 10.1590/0102-311X00144612 [ Links ]

17. Pérez-Escamilla R, Segall-Corrêa AM, Maranha LK, Sampaio MFA, Marín-León L, Panigassi G. An adapted version of the U.S. Department of Agriculture Food Insecurity Module is a valid tool for assessing household food insecurity in Campinas, Brazil. J Nutr [Internet]. 2004 Aug [cited 2019 Jun 19];134(8):1923-8. Available from: Available from: . doi: 10.1093/jn/134.8.1923 [ Links ]

18. Landis JR, Koch GG. The measurement of observer agrément for categorical data. Biometrics [Internet]. 1977 Mar [cited 2019 Jun 19];33(1):159-74. Available from: Available from: . doi: 10.2307/2529310 [ Links ]

19. Jaime PC, Stopa SR, Oliveira TP, Vieira ML, Szwarcwald CL, Malta DC. Prevalência e distribuição sociodemográfica de marcadores de alimentação saudável, Pesquisa Nacional de Saúde, Brasil 2013. Epidemiol Serv Saúde [Internet]. 2015 abr-jun [citado 2019 jun 19];24(2):267-76. Disponível em: Disponível em: . doi: 10.5123/S1679-49742015000200009 [ Links ]

20. Kye SY, Yun EH, Park KH. Factors related to self-perception of diet quality among South Korean adults. Asian Pac J Cancer Prev [Internet]. 2012 Apr [cited 2019 Jun 19];13(4):1495-504. Available from: Available from: ]

21. Reichert FF, Loch MR, Capilheira MF. Self-reported health status in adolescents, adults and the elderly. Ciên Saúde Colet [Internet]. 2012 Dec [cited 2019 Jun 19];17(12):3353-62. Available from: Available from: . doi: 10.1590/S1413-81232012001200020 [ Links ]

22. Santos JV, Gigante DP, Domingues MR. Prevalence of food insecurity in Pelotas, Rio Grande do Sul State, Brazil, and associated nutritional status. Cad Saúde Pública [Internet]. 2010 Jan [cited 2019 Jun 19];26(1):41-9. Available from: Available from: . doi: 10.1590/S0102-311X2010000100005 [ Links ]

23. Lins APM, Sichieri R, Coutinho WF, Ramos EG, Peixoto MVM, Fonseca VM. Alimentação saudável, escolaridade e excesso de peso entre mulheres de baixa renda. Ciênc Saúde Coletiva [Internet]. 2013 fev [citado 2019 jun 19];18 (2):357-66. Disponível em: Disponível em: . doi: 10.1590/S1413-81232013000200007 [ Links ]

24. DeSalvo KB, Bloser N, Reynolds K, He J, Muntner P. Mortality prediction with a single general self-rated health question a meta-analysis. J Gen Intern Med [Internet]. 2006 Mar [cited 2019 Jun 19];21(3):267-75. Available from: Available from: . doi: 10.1111/j.1525-1497.2005.00291.x [ Links ]

25. Sundquist J, Johansson SE. Self reported poor health and low educational level predictors for mortality: a population based follow up study of 39 156 people in Sweden. J Epidemiol Community Health [Internet]. 1997 Feb [cited 2019 Jun 19];51(1):35-40. Available from: Available from: ]

26. Agostinho MR, Oliveira MC, Pinto MEB, Balardin GU, Harzheim E. Self-perceived health of adults users of Primary Health Care Services in Porto Alegre, RS, Brazil. Rev Bras Med Fam Comunidade [Internet]. 2010 Jan-Dec [cited 2019 Jun 19];5(17):9-15. Avaialble from: Avaialble from: ]

*Article derived from the Master’s Degree thesis entitled ‘Self-perception of healthy eating, associated factors and comparison with eating habits among individuals aged 18 or over in an urban area in the far south of Brazil’, defended by Karla Pereira Machado at the Federal University of Rio Grande Public Health Postgraduate, in 2017.

Received: September 06, 2018; Accepted: May 11, 2019

Correspondence: Karla Pereira Machado - Rua General Osório, S/N, Rio Grande, RS, Brazil. Postcode: 96200-400. E-mail:

Authors’ contributions

Machado KP took part in the study design and field work, analyzed the data collected, interpreted the results and was responsible for writing the manuscript. Vaz JS contributed to data analysis and to writing and revising the manuscript. Mendonza-Sassi RA contributed to supervising the study, right from its conception though to its conclusion, as well as revising the data analysis and participating in interpreting the results and critically reviewing the contents of the manuscript. All the authors approved the final version and are responsible for all aspects of the work, including the guarantee of its accuracy and integrity.

Associate Editor: Doroteia Aparecida Höfelmann -

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