Abstract

The aim of the present study was to compare the Diet Quality Index-Digital Food Guide (DQI-DFG) to a more widely used measure in the literature: the Brazilian Healthy Eating Index-Revised (BHEI-R). A cross-sectional population-based study was conducted with 822 older adults (≥ 60 years) from the city of Campinas/SP, Brazil. The BHEI-R resulted in a higher overall score compared to DQI-DFG (62.9 vs. 47.7). For the BHEI-R, mean scores increased with age and were worse among smokers and individuals with a higher level of schooling. Regarding the DQI-DFG scores, no significant associations with age, schooling or smoking were detected; however, scores were higher in higher income segments. The components with the worst scores were whole grains, sodium and milk (BHEI-R); fruits, whole grains, roots/tubers, milk, refined cereals and red meat/processed (DQI-DFG). Divergences were found in the global scores and components of the indicators, reflecting important methodological differences. Studies of this nature constitute an opportunity to increase awareness regarding indicators of particular aspects of diet.

Key words:
Aged; Food consumption; Health survey

Introduction

Population aging has been occurring at a rapid rate throughout the world¹1 Miranda GMD, Mendes ACG, Silva ALA. Population aging in Brazil: current and future social challenges and consequences. Rev Bras Geriatr Gerontol 2016; 19(3):507-519.. Healthy eating plays a fundamental role in the aging process as well as the prevention and control of chronic noncommunicable diseases²2 Christ A, Latz E. The Western lifestyle has lasting effects on metaflammation. Nat Rev Immunol 2019; 19:267-268.

3 Afshin A, Sur PJ, Fay KA, Cornaby L, Ferrara G, Salama JS, et al. Health effects of dietary risks in 195 countries, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet 2019; 393(10184):1958-1972.^-44 World Health Organization (WHO). Diet, nutrition and the prevention of chronic diseases. Technical report series 916. Geneva: WHO; 2003.. Therefore, the assessment of eating patterns in older adults is important and can be facilitated with the use of diet quality indicators, which are methods founded on traditional eating patterns or dietary guidelines for the prevention of disease⁵5 Ocke' MC. Evaluation of methodologies for assessing the overall diet: dietary quality scores and dietary pattern analysis. P Nutr Soc 2013, 72:191-199..

Diet quality indicators enable a more comprehensive analysis of eating practices and associations with health, going beyond the reductionism of the assessment of dietary intake based on isolated nutrients and foods⁵5 Ocke' MC. Evaluation of methodologies for assessing the overall diet: dietary quality scores and dietary pattern analysis. P Nutr Soc 2013, 72:191-199.. The most recent edition of the Dietary Guide for the Brazilian Population states that the beneficial effects of a healthy diet are attributed more to the combination of foods that compose eating practices as well as the interaction of nutrients with each other and with other components of the dietary matrix than individual foods and nutrients⁶6 Brasil. Ministério da Saúde (MS). Secretaria de Atenção à Saúde. Departamento de Atenção Básica. Guia Alimentar para a População Brasileira. 2ª ed. Brasília: MS; 2014..

Among the proposed national indicators, the Brazilian Healthy Eating Index-Revised (BHEI-R)⁷7 Previdelli AN, Andrade SC, Pires MM, Ferreira SRG, Fisberg RM, Marchioni DM. Índice de Qualidade da Dieta Revisado para população brasileira. Rev Saude Publica 2011; 45(4):794-798. is composed of 12 components, nine of which are food groups (total fruits; whole fruits; total vegetables; dark green/orange vegetables and legumes; meat, eggs and beans; milk and dairy; total grains; whole grains; oils), two nutrients (sodium and saturated fat) and one that unites solid, saturated and trans fats, alcohol and added sugar. The BHEI-R is derived from the US Healthy Eating Index (HEI-2005)⁸8 Guenther PM, Reedy J, Krebs-Smith SM, Reeve BB, Basiotis PP. Development and evaluation of the Healthy Eating Index-2005: technical report. Washington DC: Center for Nutrition Policy and Promotion, U.S. Department of Agriculture; 2007.. This measure has been adapted for use in Brazil based on the recommendations of the 2006 Dietary Guide for the Brazilian Population, which determined the number of portions and energy value per portion of the food groups in a diet with 2000 kcal/day⁹9 Brasil. Ministério da Saúde (MS). Secretaria de Atenção à Saúde. Coordenação-Geral da Política de Alimentação e Nutrição. Guia alimentar para a população brasileira: promovendo a alimentação saudável. Brasília: MS; 2006. 210 p.. The dietary guidelines are recommended for individuals over than two years of age and were defined based on a revision of the guidelines of the US food pyramid adapted for Brazil¹⁰10 Philippi ST, Latterza AR, Cruz ATR, Ribeiro LC. Pirâmide Alimentar Adaptada: guia para escolha dos alimentos. Rev Nutr 1999; 12(1):65-80.. Regarding nutrients, the definition of the cutoff points was based on the recommendations of the US Institute of Medicine (sodium), the Brazilian Cardiology Society and World Health Organization (saturated fat)⁷7 Previdelli AN, Andrade SC, Pires MM, Ferreira SRG, Fisberg RM, Marchioni DM. Índice de Qualidade da Dieta Revisado para população brasileira. Rev Saude Publica 2011; 45(4):794-798..

Published in 2019, the Diet Quality Index Associated to the Digital Food Guide (DQI-DFG)¹¹11 Caivano S, Colugnati FAB, Domene SMA. Diet Quality Index associated with Digital Food Guide: update and validation. Cad Saude Publica 2019; 35(9):e00043419. has 11 groups, seven of which are denominated “adequacy components” (poultry, seafood and eggs; whole grains, tubers and roots; fruits; vegetables; legumes and nuts; milk and dairy; oils and fats) and four dispensable food groups denominated “moderation components” (sugars and sweets; beef, pork and processed meats; refined grains; and processed fats). The framework of the DQI-DFG is founded on the dietary guidelines proposed by the Department of Nutrition of the Harvard School of Public Health with adjustments made to value foods that are part of the eating habits of the Brazilian population. The energy value of the portions and food intake ranges were determined based on the creation of a reference diet that meets the nutritional requirements of adults established by the US Institute of Medicine (macronutrients, vitamins, minerals, linoleic acid and alpha-linolenic acid) and Brazilian Cardiology Society (saturated, monounsaturated and polyunsaturated fatty acids)¹¹11 Caivano S, Colugnati FAB, Domene SMA. Diet Quality Index associated with Digital Food Guide: update and validation. Cad Saude Publica 2019; 35(9):e00043419..

Considering improvements in the measurement process of diet quality and the fact that instruments of this nature enable a better understanding of the dietary practices of individuals and collectivities, the aim of the present study was to compare the DQI-DFG to a more widely used indicator in the literature (BHEI-R) for the assessment of the diet of older adults.

Methods

A cross-sectional study was conducted using data from the Health Survey and Nutrition Survey, which were population-based studies conducted in the city of Campinas, state of São Paulo, Brazil, between 2014 and 2016. Data were collected from non-institutionalized individuals 60 years of age or older, residents of permanent private homes in urban areas of the city of Campinas.

The Campinas Health Survey defined a minimum sample of 1000 older adults, which would enable estimated a proportion of 0.50 (maximum sample variability), with a 95% confidence level, 4-5% sampling error and a design effect of 2. The sample was obtained through probabilistic cluster sampling in two stages: census sector and household. In the first stage, 70 census sectors were randomly selected with probability proportional to the number of households counted in the 2010 census. The sectors were visited in the field for the establishment of an updated list of households¹²12 Alves MCGP. Plano de Amostragem do ISACAMP-2014/15 [acessado 2020 maio 14]. Disponível em: https://www.fcm.unicamp.br/fcm/sites/default/files/2018/page/plano_de_amostragem_isacamp_2014.15.pdf
https://www.fcm.unicamp.br/fcm/sites/def... .

In the second stage, the number of households necessary to reach the minimum sample size was calculated based on the older adult/household ratio. Thus, 3157 households were selected considering a 20% non-response rate. All older residents (≥ 60 years of age) of the selected homes were asked to participate in the study. Further information on the sampling design of the survey has been published elsewhere¹²12 Alves MCGP. Plano de Amostragem do ISACAMP-2014/15 [acessado 2020 maio 14]. Disponível em: https://www.fcm.unicamp.br/fcm/sites/default/files/2018/page/plano_de_amostragem_isacamp_2014.15.pdf
https://www.fcm.unicamp.br/fcm/sites/def... .

The questionnaire for the Campinas Health Survey addresses broad themes and was organized into blocks to investigate morbidities and disabilities, the use of healthcare services, preventive practices, health-related behaviors, sociodemographic characteristics, etc. The data were obtained at the homes by trained interviewers who administered the questionnaire with the aid of an electronic device (Samsung Galaxy table, model GT-P5200).

The Campinas Nutrition Survey was performed concomitantly to the Campinas Health Survey. The older people who participated in the health survey were asked (upon the second visit to the home) to answer a questionnaire on food intake. Trained interviewers began the interviews with the completion of a 24-hour recall (24HR) using the Multiple-Pass Method¹³13 Moshfegh AJ, Rhodes DG, Baer DJ, Murayi T, Clemens JC, Rumpler WV, Paul DR, Sebastian RS, Kuczynski KJ, Ingwersen LA, Staples RC, Cleveland LE. The US Department of Agriculture Automated Multiple-Pass Method reduces bias in the collection of energy intakes. Am J Clin Nutr 2008; 88(2):324-332.. With this method, the 24HR is applied in five steps with the aim of stimulating the respondent’s memory and improving the quality of the information¹⁴14 Steinfeldt L, Anand J, Murayi T. Food reporting patterns in the USDA Automated Multiple-Pass Method. Procedia Food Sci 2013; 2:145-156.. Only one 24HR was applied per participant. The interviewers visited the field every day of the week and every month of the year. A total of 88.5% of the 24HRs represented food consumption from Monday to Friday. A photographic album was used to assist in the completing of the 24HR¹⁵15 Assumpção D, Barros Filho AA. Manual fotográfico [acessado 2020 maio 14]. Disponível em: https://www.fcm.unicamp.br/fcm/sites/default/files/2016/page/manual_fotografico.pdf
https://www.fcm.unicamp.br/fcm/sites/def... .

Trained nutritionists subsequently performed the revision of the content of the 24HRs to correct possible mistakes as well as to quantify the foods and meals recorded in home measurements¹⁶16 Fisberg RM, Villar BS. Manual de receitas e medidas caseiras para cálculo de inquéritos alimentares: manual elaborado para auxiliar o processamento de inquéritos alimentares. 1ª ed. São Paulo: Signus; 2002.

17 Pinheiro ABV, Lacerda EMA, Benzecry EH, Gomes MCS, Costa VM. Tabela para avaliação de consumo alimentar em medidas caseiras. 5ª ed. São Paulo: Editora Atheneu; 2004.^-1818 Instituto Brasileiro de Geografia e Estatística (IBGE). Pesquisa de Orçamentos Familiares 2008-2009. Tabela de medidas referidas para os alimentos consumidos no Brasil. Rio de Janeiro: IBGE; 2011., on food labels and from consumer services. The data from the 24HRs were entered into the Nutrition Data System for Research (NDS-R) software, version 2015 developed by the Nutrition Coordinating Center of the University of Minnesota, Minneapolis, USA. The NDS-R software is updated annually and has more than 18 thousand foods and 170 nutrients. Meals not in the NDS-R database were developed based on standard recipes and inserted into the User Recipe Module. The data from all 24HRs were checked to ensure the consistency of the information.

Among 1168 older adults identified at the selected domiciles, 986 were interviewed for the Campinas Health Survey (14.0% refusals and 1.5% other losses). Among these 986 individuals, 138 declined to participate in the Campinas Nutrition Survey and 26 declined to answer the 24HR. Thus, the sample was composed of 822 older adults.

Variables of interest

The quality of the diet was assessed using two indicators: Brazilian Healthy Eating Index-Revised (BHEI-R)⁷7 Previdelli AN, Andrade SC, Pires MM, Ferreira SRG, Fisberg RM, Marchioni DM. Índice de Qualidade da Dieta Revisado para população brasileira. Rev Saude Publica 2011; 45(4):794-798. and Diet Quality Index Associated to the Digital Food Guide (DQI-DFG)¹¹11 Caivano S, Colugnati FAB, Domene SMA. Diet Quality Index associated with Digital Food Guide: update and validation. Cad Saude Publica 2019; 35(9):e00043419.. The DQI-DFG is comprised of a set of “adequacy components” (essential for the maintenance of health and the prevention of chronic noncommunicable diseases) and “moderation components” (foods that increase the risk of developing chronic diseases if consumed in excess). Although the BHEI-R was developed based on the HEI-2005⁸8 Guenther PM, Reedy J, Krebs-Smith SM, Reeve BB, Basiotis PP. Development and evaluation of the Healthy Eating Index-2005: technical report. Washington DC: Center for Nutrition Policy and Promotion, U.S. Department of Agriculture; 2007., which classifies adequacy and moderation components, the authors opted not to adopt this denomination⁷7 Previdelli AN, Andrade SC, Pires MM, Ferreira SRG, Fisberg RM, Marchioni DM. Índice de Qualidade da Dieta Revisado para população brasileira. Rev Saude Publica 2011; 45(4):794-798..

The BHEI-R has 12 components, which are presented in Chart 1. For components 1 to 9, the scores ranges from zero (not consumed) to five or ten points (consumption that meets or exceeds the recommended value). Components 10 to 12 receive scores ranging from zero (consumption that surpasses the maximum recommended limit) to ten or twenty points (meets established consumptions levels). Intermediate intake values are calculated proportionally. The total BHEI-R score is the sum of the 12 components and ranges from zero (worst quality) to 100 points (best quality)⁷7 Previdelli AN, Andrade SC, Pires MM, Ferreira SRG, Fisberg RM, Marchioni DM. Índice de Qualidade da Dieta Revisado para população brasileira. Rev Saude Publica 2011; 45(4):794-798..

The DQI-DFG comprises 11 components - seven adequacy components (items 1 to 7) and four moderation components (items 8 to 11). The maximum score (5, 7.5, 10, 12.5 or 15 points) is attributed when consumption reaches the recommended number of portions or when it falls within the range of the established portions. Adequacy components receive an increasing proportional score (consumption below the minimum portion limit), decreasing proportional score (consumption up to twice the maximum limit of portions for items 2, 3 and 6) and no points (null consumption of components 1 to 7 or more than double the maximum limit of portions for items 2, 3 and 6). The other adequacy components (1, 4, 5 and 7) remain at the maximum score if surpassing the determined number of portions, as there is no evidence of health risks. Moderation components are attributed a decreasing proportional score (up to double the upper limit of the range of portions) and no score (more than double the upper limit)¹¹11 Caivano S, Colugnati FAB, Domene SMA. Diet Quality Index associated with Digital Food Guide: update and validation. Cad Saude Publica 2019; 35(9):e00043419.. The total DQI-DFG is the sum of the 11 components and ranges from zero (worst quality) to 100 points (best quality) (Chart 1).

Diet quality was assessed considering the independent variables: sex (male and female), age group (60 to 69, 70 to 79 and 80 or more years of age), schooling (0 to 3, 4 to 8 and 9 or more years of study), family income per capita using the monthly minimum wage (MMW) as reference (< 1, ≥ 1 to < 2, ≥ 2 to < 3 to ≥ 3 times the MMW), smoking (never smoked, ex-smoker and smoker) and self-reported medical diagnosis of arterial hypertension and diabetes mellitus (yes or no). Smoking, hypertension and diabetes were selected to determine whether the indicators discriminate the quality of the diet in these groups, as smokers have a poor quality diet¹⁹19 Assumpção D, Domene SMA, Fisberg RM, Barros MBA. Qualidade da dieta e fatores associados entre idosos: estudo de base populacional em Campinas, São Paulo, Brasil. Cad Saude Publica 2014; 30(8):1680-1694.

20 Andrade SC, Previdelli AN, Cesar CLG, Marchioni DML, Fisberg RM. Trends in diet quality among adolescents, adults and older adults: A population-based study. Prev Med Rep 2016; 4:391-396.^-2121 Raatza SK, Jahns L, Johnson LK, Scheett A, Carriquiry A, Lemieuxd A, Nakajima M, al'Absi M. Smokers report lower intake of key nutrients than nonsmokers, yet both fall short of meeting recommended intakes. Nutr Res 2017; 45:30-37. and the presence of chronic disease requires the search for health care, which increases the opportunity to receive nutritional counseling and make healthy eating choices¹⁹19 Assumpção D, Domene SMA, Fisberg RM, Barros MBA. Qualidade da dieta e fatores associados entre idosos: estudo de base populacional em Campinas, São Paulo, Brasil. Cad Saude Publica 2014; 30(8):1680-1694.^,2222 Malta DC, Bernal RTI, Lima MG, Araújo SSC, Silva MMA, Freitas MIF, Barros MBA. Doenças crônicas não transmissíveis e a utilização de serviços de saúde: análise da Pesquisa Nacional de Saúde no Brasil. Rev Saude Publica 2017; 51(Supl 1):4s..

Data analysis

Means and 95% confidence intervals (CI) were estimated for each component of the BHEI-R and DQI-DFG and transformed into percentages in relation to the maximum score of the component. Next, global means of the BHEI-R and DQI-DFG were estimated according to the categories of the independent variables using simple and multiple (adjusted by sex and age) linear regression models considering a 5% significance level. Means of the components were also calculated according to age group to determine the behavior of the two diet quality instruments with the increase in age. The statistical analyses were performed using the survey module of the Stata 15.1 program, which considers weights and the sampling design of the study.

Ethical considerations

The Campinas Health Survey (certificate number: 37303414.4.0000.5404) and Campinas Nutrition Survey (certificate number: 26068214.8.0000.5404) received approval from the institutional review board of Universidade Estadual de Campinas and the National Research Ethics Committee (CEP/CONEP system). The procedures of the study were only conducted after agreement on the part of the participant through a signed statement of informed consent.

Results

The present study involved the analysis of information on 822 older adults who answered a 24HR. Mean age was 71.0 years (95% CI: 70.2-71.9) and women predominated in the sample (60.5%).

Regarding the BHEI-R components, very low scores (not reaching even 50% of the maximum score) were found for whole grains, milk and dairy (which means less consumption), and sodium (greater intake). For the DQI-DFG, the components with the worst scores were fruits, whole grains, roots and tubers, milk and dairy (low intake), refined grains, and red and processed meats (high consumption) (Table 1).

The total BHEI-R score was higher than the total DQI-DFG score (62.9 versus 47.5). No differences were detected in the mean diet quality scores with regards to sex and arterial hypertension with either measure. Unlike the DQI-DFG, the BHEI-R identified differences per age, schooling and smoking; diet quality was better among long-lived older adults and worse among older adults with less schooling and smokers. BHEI-R scores were lower in the highest income stratum, but this difference lost its statistical significance in the adjusted analysis. In contrast, mean DQI-DFG scores were higher in higher income segments. According to both indicators, diabetics had a diet of better quality (Table 2).

According to the BHEI-R, individuals between 70 and 79 years of age had higher scores for total fruits, whole grains and sodium compared to those 60 to 69 years of age; the mean milk and dairy score increased with the advance in age. According to the DQI-DFG, the mean fruits score was higher among individuals 70 to 79 years of age and the milk and dairy score was higher among individuals 80 years of age or older compared to younger age groups; the processed fat score increased with age, reflecting a reduction in intake (Table 3).

Discussion

The differences found in the global score of the indices used in the present study are partially explained by divergences in the scoring criteria and the definition of the energy value of the portions of foods recommended for a diet of 1000 kcal and intake ranges linked to the maximum score. For instance, the maximum fruit score corresponds to an intake of 70 kcal on the BHEI-R (≥ 1.0 portion of 35 kcal for total fruits and ≥ 0.5 portion of 35 kcal for whole fruits) and between 97.5 and 195 kcal on the DQI-DFG (1.5 to 3.0 portions of 65 kcal); for milk and dairy, the maximum score is equivalent to 180 kcal on BHEI-R (≥ 1.5 portion of 120 kcal) and between 200 and 300 kcal on the DQI-DFG (1.0 to 1.5 portion of 200 kcal). Moreover, the DQI-DFG discriminates the energy value of the milk and dairy component in milk/yogurt (120 kcal) and cheeses (80 kcal), considering the greater concentration of fat and sodium in cheeses.

For grains, the BHEI-R confers the maximum score for intake equal to or greater than 2.0 portions of total grains (including roots and tubers) and 1.0 portion of whole grains (150 kcal each portion). The DQI-DFG takes a different approach by uniting whole grains with roots and tubers (except potato) and classifying refined grains as a moderation component. The number of portions recommended was established to restrict the consumption of refined grains (≤ 1.0 portion of 200 kcal) and prioritize whole grains, roots and tubers (2.0 to 3.0 portions of 260 kcal) in the daily diet.

The indicators also differed in terms of the maximum scores of the components. The DQI-DFG attributes higher scores for foods such as fruits, vegetables, legumes and nuts (15 points) and poultry, seafood and eggs (12.5 points) and lower scores (5 points) for beef, pork and processed meats, sugars and sweets, and processed fats (margarine, mayonnaise, lard and ready-made salad dressings); these 5-point groups are considered moderation components (foods for which consumption is discouraged). On the BHEI-R, the fruits and vegetables components each total 10 points, whereas 10 points is conferred for saturated fat and another 20 points is conferred for SoFAAS (calories from saturated and trans fat, alcohol and added sugars). The adequacy components of the DQI-DFG account for 80% of the total score (100 points), resulting in a refinement in the detection of a diet of better quality.

The DQI-DFG is more discerning regarding the selection of foods that compose some of the components. The BHEI-R allows the inclusion of crackers/cookies, packaged crisps, cakes and sweet breads in the total grains group, sweetened yogurts, milk-based ice creams and soy-based beverages in the milk and dairy group, and processed meats in the meats, eggs and beans group, which is contrary to the current recommendations of the Dietary Guide for the Brazilian Population to avoid the consumption of ultra-processed foods.⁶6 Brasil. Ministério da Saúde (MS). Secretaria de Atenção à Saúde. Departamento de Atenção Básica. Guia Alimentar para a População Brasileira. 2ª ed. Brasília: MS; 2014. The guide offers a change in the paradigm incorporated by the DQI-DFG by classifying the majority of ultra-processed foods as moderation components.

Another important difference between the indicators regards the definition of specific groups for legumes and nuts, poultry, seafood and eggs, and beef, pork and processed meats, as presented in the DQI-DFG. The BHEI-R unites meat, eggs and beans into a single component. If the maximum score for this component were reached (10 points = 1 portion of 190 kcal) and the energy from legumes remains, it is transferred to two other components: total vegetables and dark green/orange vegetables. This method does not consider differences in the nutritional values of proteins²³23 Bohrer BM. Review: Nutrient density and nutritional value of meat products and non-meat foods high in protein. Trends Food Sci Technol 2017; 65:103-112. or the risk of red/processed meats for the development of chronic diseases²⁴24 Pan A, Sun Q, Bernstein AM, Schulze MB, Manson JE, Stampfer MJ, Willett WC, Hu FB. Red Meat Consumption and Mortality: Results from Two Prospective Cohort Studies. Arch Intern Med 2012; 172(7):555-563.^,2525 Micha R, Michas G, Mozaffarian D. Unprocessed Red and Processed Meats and Risk of Coronary Artery Disease and Type 2 Diabetes - An Updated Review of the Evidence. Curr Atheroscler Rep 2012; 14(6):515-524. and overestimates the vegetable scores (raw and cooked vegetables). This difference between the two methods may explain why the percentage of the mean in relation to the maximum score of the meat, eggs and beans component was high on the BHEI-R (87.3%) and low on the DQI-DFG (32.6%) for the beef, pork and processed meats component.

Unlike the BHEI-R, the DQI-DFG did not detect poorer global diet quality among smokers. The association between smoking and poor diet quality has been identified in other studies using the BHEI-R¹⁹19 Assumpção D, Domene SMA, Fisberg RM, Barros MBA. Qualidade da dieta e fatores associados entre idosos: estudo de base populacional em Campinas, São Paulo, Brasil. Cad Saude Publica 2014; 30(8):1680-1694.^,2020 Andrade SC, Previdelli AN, Cesar CLG, Marchioni DML, Fisberg RM. Trends in diet quality among adolescents, adults and older adults: A population-based study. Prev Med Rep 2016; 4:391-396.. Among older residents of Brazilian state capitals and the Federal District, smokers were more likely to have abusive alcohol use (odds ratio = 2.94) and inadequate diet (odds ratio = 1.51) evaluated using an index that reflects the frequency of the consumption of fruits, vegetables, beans, milk, sweets, red meat and sweetened beverages²⁶26 Francisco PMSB, Assumpção D, Borim FSA, Senicato C, Malta DC. Prevalência e coocorrência de fatores de risco modificáveis em adultos e idosos. Rev Saude Publica 2019; 53:86.. A study conducted in the United States using data from 3-day diet records found that smokers had lower intakes of energy, polyunsaturated fatty acids, omega-3, dietary fiber and several micronutrients, such as calcium, iron, magnesium and vitamins A, C and E, in comparison to non-smokers²¹21 Raatza SK, Jahns L, Johnson LK, Scheett A, Carriquiry A, Lemieuxd A, Nakajima M, al'Absi M. Smokers report lower intake of key nutrients than nonsmokers, yet both fall short of meeting recommended intakes. Nutr Res 2017; 45:30-37..

The scoring rules for the DQI-DFG are more rigorous compared to those of the BHEI-R, considering the establishment of consumption ranges that protect the diet from an excess of saturated fat, refined carbohydrates, fructose and sucrose. Seven of the 11 DQI-DFG components receive a decreasing proportional score or no points if intake surpasses the establish range of portions. The maximum DQI-DFG score is linked to portions with higher energy value for milk, fruits and vegetables; the fruits and vegetables score is not split into subgroups and has a higher value; and the classification of foods is more refined, as exemplified by specific groups for red and processed meats, white meats and eggs, legumes, and sugars and sweets. These differences may explain why the DQI-DFG did not identify significant associations with smoking, age or schooling. Moreover, the means of the components are quite distant from each maximum score, as demonstrated in Table 1.

Income and schooling have been associated with better diet quality, as reported in studies conducted in Australia²⁷27 Ribeiro RV, Hirani V, Senior AM, Gosby AK, Cumming RG, Blyth FM, Naganathan V, Waite LM, Handelsman DJ, Kendig H, Seibel MJ, Simpson SJ, Stanaway F, Allman-Farinelli M, Couteur DGL. Diet quality and its implications on the cardio-metabolic, physical and general health of older men: the Concord Health and Ageing in Men Project (CHAMP). Br J Nutr 2017; 118: 130-143., the Unites States²⁸28 Hiza HAB, Casavale KO, Guenther PM, Davis CA. Diet Quality of Americans Differs by Age, Sex, Race/Ethnicity, Income, and Education Level. J Acad Nutr Diet 2013; 113:297-306. and Brasil²⁹29 Souza JPM, Lima MM, Horta PM. Diet Quality among the Brazilian Population and Associated Socioeconomic and Demographic Factors: Analysis from the National Dietary Survey 2008-2009. J Acad Nutr Diet 2019; 119(11):1866-1874. and partially confirmed in the present sample, as older people with greater purchasing power had higher DQI-DFG scores. However, the BHEI-R indicated that poorer diet quality was associated with a higher income and level of schooling, which contrasts findings from other studies and may be due to the particularities of the index mentioned above.

Dietary indices are useful tools for assessing and monitoring food intake on the individual and collective levels, as such measures unite different food groups and/or nutrients, enabling a better understanding of eating practices. Such measures constitute a more appropriate way for assessing diet quality in comparison to studies of a reductionist nature that analyze a single food/nutrient.⁵5 Ocke' MC. Evaluation of methodologies for assessing the overall diet: dietary quality scores and dietary pattern analysis. P Nutr Soc 2013, 72:191-199. The advance of studies in the field of nutrition has demonstrated that the beneficial effects of eating patterns on health are not the result of individual foods, but rather how foods are combined, prepared and consumed⁵5 Ocke' MC. Evaluation of methodologies for assessing the overall diet: dietary quality scores and dietary pattern analysis. P Nutr Soc 2013, 72:191-199.^,66 Brasil. Ministério da Saúde (MS). Secretaria de Atenção à Saúde. Departamento de Atenção Básica. Guia Alimentar para a População Brasileira. 2ª ed. Brasília: MS; 2014.. An example is the Mediterranean diet, which is characterized by high intake of fruits, vegetables, whole grains, nuts and legumes, moderate intake of dairy, fish, poultry and olive oil, and low consumption of red meats³⁰30 Amato M, Bonomi A, Laguzzi F, Veglia F, Tremoli E, Werba JP, Giroli MG. Overall dietary variety and adherence to the Mediterranean diet show additive protective effects against coronary heart disease. Nutr Metab Cardiovas 2020; 30:1315-1321.; several studies have demonstrated the protective role of this traditional eating pattern regarding cardiovascular disease, diabetes and premature death³⁰30 Amato M, Bonomi A, Laguzzi F, Veglia F, Tremoli E, Werba JP, Giroli MG. Overall dietary variety and adherence to the Mediterranean diet show additive protective effects against coronary heart disease. Nutr Metab Cardiovas 2020; 30:1315-1321.

31 Schulze MB, Martínez-González MA, Fung TT, Lichtenstein AH, Forouhi NG. Food based dietary patterns and chronic disease prevention. BMJ 2018; 361:k2396.^-3232 Tong TYN, Wareham NJ, Khaw K-T, Imamura F, Forouhi NG. Prospective association of the Mediterranean diet with cardiovascular disease incidence and mortality and its population impact in a non-Mediterranean population: the EPIC-Norfolk study. BMC Medicine 2016; 14:135..

Studies conducted in Brazil show that older people generally have a healthier, more traditional diet compared to younger groups. A study investigating the most widely consumed foods in Brazil using data from the National Diet Survey, which was part of the 2008-2009 Family Budget Survey, found that only older people cited more than one fruit and raw vegetable and soup/broths among the 20 most prevalent foods and, unlike adolescents and adults, did not report carbonated soft drinks or fried and baked snack foods³³33 Souza AM, Pereira RA, Yokoo EM, Levy RB, Sichieri R. Alimentos mais consumidos no Brasil: Inquérito Nacional de Alimentação 2008-2009. Rev Saude Publica 2013; 47(Supl. 1):190S-199S.. The findings of the 2013 National Health Survey revealed that, compared to adults, older people had higher rates of the recommended intake of fruits and vegetables and fish (≥ 1 day per week)³⁴34 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 Saude 2015; 24(2):267-276. as well as lower frequency of the regular consumption (≥ 5 days per week) of red meat and chicken with excess fat, carbonated soft drinks and sweets³⁵35 Claro RM, Santos MAS, Oliveira TP, Pereira CA, Szwarcwald CL, Malta DC. Consumo de alimentos não saudáveis relacionados a doenças crônicas não transmissíveis no Brasil: Pesquisa Nacional de Saúde 2013. Epidemiol Serv Saude 2015; 24(2): 257-265.. A study involving Brazilian older adults and employing cluster analysis found that the majority had a healthy eating pattern, with the greater consumption of vegetables, chicken, milk, fruits and fruit juices³⁶36 Pereira IFS, Vale D, Bezerra MS, Lima KC, Roncalli AG, Lyra CO. Padrões alimentares de idosos no Brasil: Pesquisa Nacional de Saúde 2013. Cien Saude Colet 2020; 25(3):1091-1102.. However, the diet quality of the older adults in the present study was not considered adequate, revealing that the use of indices offers more robust information on diet as a whole.

In Brazil, 72.6% of deaths in 2013 were caused by chronic noncommunicable diseases, especially cardiovascular disease, cancer, respiratory diseases and diabetes mellitus³⁷37 Malta DC, Andrade SSCA, Oliveira TP, Moura L, Prado RR, Souza MFM. Probabilidade de morte prematura por doenças crônicas não transmissíveis, Brasil e regiões, projeções para 2025. Rev Bras Epidemiol 2019; 22:e190030.. The prevalence and number of chronic diseases increase with age. Among Brazilian older adults, the prevalence of multimorbidity (presence of two or more diseases) was 58.8% among individuals 50 to 59 years of age, increasing to 73.4% (60-69 years), 79.0% (70-79) and 82.4% (≥ 80 years)³⁸38 Nunes BP, Batista SRR, Andrade FB, Souza Junior PRB, Lima-Costa MF, Facchini LA. Multimorbidade em indivíduos com 50 anos ou mais de idade: ELSI-Brasil. Rev Saude Publica 2018; 52(Supl. 2):10s.. Nutritional disorders affect a large portion of older women (18.2% of those underweight and 41.9% of those overweight) and older men (19.9% of those underweight and 31.6% of those overweight)³⁹39 Pereira IFS, Spyrides MHC, Andrade LMB. Estado nutricional de idosos no Brasil: uma abordagem multinível. Cad Saude Publica 2016; 32(5):e00178814.. Moreover, chronic low-grade inflammation (inflamm-aging), which is an inherent condition of aging, increases the risk of chronic diseases⁴⁰40 Franceschi C, Garagnani P, Parini P, Giuliani C, Santoro A. Inflammaging: a new immune-metabolic viewpoint for age-related diseases. Nat Rev Endocrinol 2018; 14:576-590. and an unhealthy diet induces the inflammatory response²2 Christ A, Latz E. The Western lifestyle has lasting effects on metaflammation. Nat Rev Immunol 2019; 19:267-268..

The diet quality of the older adults in the present study was unsatisfactory and the lower DQI-DFG score reflects an assessment that approaches current national recommendations with regards to the classification of foods according to the degree of processing. The indicators analyzed present divergences regarding the scores of the components, which are explained by differences in scoring criteria, the energy value of the portion and the organization of the components. For instance, the total grains group on the BHEI-R includes foods that are classified in other groups on the DQI-DFG (refined grains; sugars and sweets; and whole grains, roots and tubers), as occurs with the meat, eggs and beans group (red and processed meats; poultry, seafood and eggs; and legumes and nuts) and milk and dairy group (sugars and sweets). On the DQI-DFG, the moderation and adequacy (fruits; milk and dairy; and whole grains, tubers and roots) components received decreasing scores if consumed in excess, offering a more thorough method for the assessment of dietary quality.

Considering the methodological differences of the indices and the current epidemiological scenario in Brazil, the DQI-DFG is more aligned with the recommendations of the Dietary Guide for the Brazilian Population,⁶6 Brasil. Ministério da Saúde (MS). Secretaria de Atenção à Saúde. Departamento de Atenção Básica. Guia Alimentar para a População Brasileira. 2ª ed. Brasília: MS; 2014. the aim of which is to protect and promote health. Nevertheless, the results point to the need for further studies that can adapt diet quality indicators to the specificities of what is expected as a quality attribute for this stage in life, considering the absence (to the best of our knowledge) of a specific assessment tool for the diet of older adults.

Among the limitations of the present study, it is necessary to consider possible errors resulting from the methods chosen to estimate food consumption. The application of a single 24-hour recall does not represent habitual consumption due to the variation in foods over the course of several days⁴¹41 Domene SMA. Avaliação do consumo alimentar. In: Taddei JA, Lang RMF, Silva GL, Toloni MHA, organizadores. Nutrição em saúde pública. Rio de Janeiro: Rubio; 2011. p. 41-54.. However, when administered on different days of the week and months of the year, information from a single 24HR is sufficient to estimate the average consumption of a group or differences between groups⁴²42 National Cancer Institute. Dietary Assessment Primer. Describing Dietary Intake Data Capture Recommendations 24-hour Dietary Recalls [acessado 2020 maio 28]. Disponível em: https://dietassessmentprimer.cancer.gov/approach/intake.html
https://dietassessmentprimer.cancer.gov/... . Moreover, the interviewees of the Campinas Nutrition Survey were trained to apply the 24HR using the Multiple-Pass Method, which helps the individual remember the foods and beverages consumed, making the record of information more precise. The interviewers also used a photographic album to assist the individual in defining the quantities of the foods.

The strengths of the present study include the use of a representative sample of the older population and the standardization of the collection procedures as well as the quantification and input of the dietary data. The review of the content of the 24HR and the quantification and input of the data to the NDS-R program were performed by trained nutritionists. To the best of our knowledge, no previous national study has evaluated the results of diet quality indices applied to older adults.

Conclusion

Differences were found between the two diet quality indicators analyzed in the magnitude of the global quality scores as well as associations with sociodemographic variables and smoking. The following are the main characteristics that distinguish the DQI-DFG from the BHEI-R: energy value of the portions, which is high for foods such as milk, fruits and vegetables; the establishment of consumption ranges linked to the maximum score of the components to protect the diet from the excess of nutrients; a decreasing proportional score or no points for situations in which consumption surpasses the established range; maximum scores for components such as fruits, vegetables, legumes and nuts, poultry, seafood and eggs, and lower scores for red and processed meats, sugars and sweets, and processed fats; greater discernment regarding the organization of the components and the selection of foods that integrate the components. These characteristics denote greater refinement in the classification of a diet of better quality. However, the DQI-DFG does not address alcohol intake. Considering evidence in the literature on the use of alcohol and the increase in the risk of chronic diseases and premature death, this aspect can be considered a limitation of the measure, along with the lack of information on the proportion of fatty acids.

The development and improvement of novel diet quality indicators constitutes an opportunity to incorporate scientific advances in nutrition. The complexity of the aging process and implications for the dietary profile require the creation of specific instruments that include aspects such as the consumption of water, coffee, tea, a variety of foods and the use of spices, besides a likely adjustment in the portion criteria, with adequate energy quotas for this stage of life.

Acknowledgments

The authors are grateful to Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) for funding the 2014-2015 Campinas Health Survey (Process nº 2012/23324-3) and 2015-2016 Campinas Nutrition Survey (Process nº 2013/16808-7) and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) for the post-doctoral grant awarded to D. Assumpção.

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