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Research Article
Open Access Peer-reviewed

Sociodemographic and Lifestyle Factors Are Associated with Diet Quality in Cardiometabolic Risk Subjects

Brenda Kelly Souza Silveira, Juliana Farias de Novaes, Nínive de Almeida Reis, Larissa Pereira Lourenço, Ana Helena Moretto Capobiango, Arieta Carla Gualandi Leal, Helen Hermana Miranda Hermsdorff
Journal of Food and Nutrition Research. 2019, 7(2), 141-147. DOI: 10.12691/jfnr-7-2-6
Received December 17, 2018; Revised January 20, 2019; Accepted February 18, 2019

Abstract

We investigated the association of social and lifestyle factors with diet quality in a cardiometabolic risk population. Cross-sectional data was from 265 subjects (aged 42 ± 16 years) attended at the Cardiovascular Health Care Program - PROCARDIO UFV (ReBEC identifier: RBR-5n4y2g). A 24-hour recall was applied and the Revised Healthy Eating Index (R-HEI) was calculated. Socioeconomic and lifestyle data were collected by chart analysis. Women (PR = 1.02, 95% CI: 1.01, 1.04), elderly (PR = 1.05, 95% CI: 1.02, 1.15), and those who eventually drink alcohol (PR = 1.02, 95% CI 1.01, 1.15) presented better diet quality (R-HEI> 70.8 points). Single subjects (PR = 0.89, 95% CI: 0.82, 0.98) and those with higher educational status (PR = 0.90, 95% CI 0.82, 0.98) presented lower score. Women had better scores on milk and dairy products, fruits and sodium. The elderly (> 60 years) presented better scores for total R-HEI, total vegetables and empty calories from solid fats, sugar and alcohol (GORD_AA) (p<0.05). Socioeconomic and lifestyle factors were associated to diet quality in cardiometabolic risk population, indicating the importance of identifying and considering in nutritional education strategies.

1. Introduction

The prevalence of noncommunicable diseases (NCD) has increased worldwide, mainly cardiovascular diseases (CVD) 1. Among risk factor for NCD and CVD development, lifestyle is a relevant modifiable risk factor 2, so that 30% of deaths could be avoided only by dietary habits changes 3. Both inadequate and excessive intakes of certain foods and nutrients are related with increased risk of cardiovascular risk and NCD 2, 4. Currently, the recommendation has been based on in natura foods, such as fruits and vegetables, which are associated with lower risk of CVD and premature mortality 2, 5, while industrialized foods of high caloric density, rich in saturated fats, simple sugars and sodium must be avoided 4, 6.

In this sense, Healthy Eating Index (HEI) was developed based on American Guidelines 7 and adapted by Brazilian researchers 8, 9, 10 in order to evaluate the diet quality and disease association 11, 12, 13. In previous studies, the best HEI score has been associated to a better health profile 14. However, dietary choices are complex and influenced by biological and sociodemographic factors, such as emotional state 15, age 16, sex 16, 17, educational status 18 and social relations 19. Studies indicate that women 17, 20, elderly 20, 21, regular exercise practitioners 22 and better income classes 20, 23 and educational status 22, 23 present better diet quality. However, few studies have investigated these factors as determinants of the diet quality in cardiometabolic risk adults 11, 24.

Since social determinants may influence on food choices 25, 26 and lifestyle is important factor in disease prevention and control, 27, 28 this study investigated the potential association of social and lifestyle factors with diet quality in a cardiometabolic risk population

2. Materials and Methods

2.1. Subjects

In this cross-sectional study, participated 265 subjects (123 male, 172 female), mean age 42 ± 16 years, assisted by the Cardiovascular Health Care Program of the Universidade Federal de Viçosa (UFV) - PROCARDIO-UFV, state of Minas Gerais, Brazil. This program performs continuous nutritional intervention in the academic cardiovascular risk community. Subjects with filled medical records to studied variables between Mach 2012 and July 2017 were included. The data used in this study refer to the information collected during the first appointment, which means before the beginning of the nutritional intervention. The data collection methods have been previously described 29, 30. Briefly, the program adopts as inclusion criteria: age > 20 years old; cardiovascular disease diagnosis or some cardiometabolic risk factor such as overweight (body mass index ≥25 kg/m2), hypertriglyceridemia (≥150 mg/dL), and hypercholesterolemia (≥200 mg/dL), low HDL (men <40 mg/dL and women <50 mg/dL), blood pressure ≥130/≥ 85mmHg or systemic arterial hypertension diagnosis (systolic blood pressure ≥140 and/or diastolic blood pressure ≥90 mmHg), fasting blood glucose ≥100 mg/dL or diagnosis of diabetes mellitus (fasting blood glucose ≥126 mg/dL), and/or medical referral.

PROCARDIO-UFV is registered at Brazilian Clinical Trials Registry (ReBEC), identifier RBR-5n4y2g. This study was approved by the UFV Human Research Ethics Committee (protocol number 066/2012), in accordance to Resolution 466/2012 (National Health Council, Ministry of Health, Brazil). All participants read and signed the written free and informed consent, in accordance to Declaration of Helsinki principles.

2.2. Food Consumption and R-HEI Calculation

The current food intake was estimated based on the 24-hour recall (24HR) information applied at the first visit, considering previous 24 hours of food consumption. All interviewers received four-month-training and were supervised at the first interviews. In order to better estimate food consumption, the "multiple-pass" method was used 31 as well as a photographic album with images of food, preparations and standard utensils for home measurements.

The R-HEI was calculated according to proposed by Previdelli (2011) 10, the only one validated for the Brazilian adults population 32. Foods reported in 24HR were tabulated in an Excel® spreadsheet in established groups according to the Brazilian Food Guide 33. All preparations were dismantled and their ingredients included in the corresponding food group. Nutritional label information was used when some preparation was not contained in the tables. In addition, the salt and oil percentage of the preparations / foods were standardized 34, 35 since these ingredients are reported with imprecision in 24HR.

The R-HEI maximum score is 100 points, which represents the best diet quality, so the higher the score, the better the diet adequacy. This also applies to their twelve components that have been individually punctuated. To R-HEI components considered unhealthy such as calories from solid fats, added sugar and alcohol (GORD_AA) and sodium, higher scores were computed when they were less consumed, and healthy components of index (e.g. fruits, cereals, meats and other food groups) received maximum score when intake reaches the recommendation values. Each R-HEI component score can range from zero to five, zero to ten or zero to twenty. The score was attributed according to consumption adequacy of the food portions ingested per 1000 kcal. For the item GORD_AA, the percentage calories adequacy in relation to the total energy value was evaluated. For sodium, the ingestion was evaluated in mg per 1000 kcal.

In the item GORD_AA, that evaluated the empty calorie intake, were included the calories from solid fats (butter, lard, hydrogenated vegetable fats, "hydrogenated" sauces), sugar and alcohol content (g) from alcoholic beverages, plus added sugar contained in industrialized or home prepared foods. For estimating the simple sugar in each food or preparation, the following tables were used: National Nutrient Database for Standard Reference - USDA release 28 36; Table for Food Consumption Evaluation in Domestic Measures 35 and food labels.

2.3. Sociodemographic and Lifestyle Factors

Sociodemographic and lifestyle variables were collected by interview and analysis of clinical records, such as age, sex, education status, family income (in minimum salaries), marital status (single, married, stable union, divorced or widowed), the UFV membership type (employee, student or relative), smoking (smokers, ex-smokers or non-smokers), sleep hours and regular physical activity practice (yes or no).

2.4. Statistical Analysis

The data normality was evaluated by Kolmogorov-Smirnov test. The R-HEI components were described as mean ± standard deviation. Student's t-test and one-way analysis of variance (ANOVA) with Tukey post hoc was used to compare R-HEI items scores by sex and age. For other analyses, R-HEI was categorized in two groups (lower or higher score), using the median (70.8 points) as the cutoff point. Other studies have already used this strategy 37, 38 based on the premise of creating risk groups in epidemiological studies 39. Associations between R-HEI (dependent variable) and sociodemographic and lifestyle variables were investigated using the Pearson chi-square or linear trend test, and Poisson regression using R-HEI scores as a reference (variable independent). The regression models were performed in the STATA software, version 13.0. The other analyses were performed in the Statistical Package for the Social Science (SPSS® 24.0, Chicago, IL, USA, 2016). A significance level of 5% was considered for all tests.

3. Results

The sample (n=295) was composed mainly by women (58.3%), adults aged between 30 and 60 years (49.5%), who had completed or in progress upper-level course (60.4%), employees or family members (60.0%), never smoked (68.0%), physical activity practitioner (52.9%) and eventually drinking (57.7%) (Table 1). This population had a mean of 69.4 ± 10.5 points (R-HEI) and low scores on total fruits (2.7), whole fruits (2.9), whole grains (0.4), milk and dairy products (5,2), sodium (4,7) and saturated fatty acids (SFA) (6,9) (Figure 1).

Women presented better scores to intake of milk and dairy products, total fruits, whole fruits and sodium, and worse scores on oils and oilseeds (p <0.05). In addition, subjects aged 30-60 years presented better R-HEI scores and the components milk and dairy products, VeVeAL e GORD_AA compared to those aged <30 years. The elderly (> 60 years) presented better scores for total R-HEI, total vegetables and GORD_AA (p <0.05) (Table 2).

When analyzed the association of social and lifestyle factors with better diet quality we notice that female participants, elderly (> 60 years old), married or in stable union, with lower education level, employees and relatives, who drinking eventually had a higher prevalence of higher R-HEI score (> 70, 8 points), independent of confounding factors (Table 3).

4. Discussion

The diet quality was classified as "need to improve" (69.4 ± 10.5 points), according to the criterion of Bowman (1998) 40. Previous studies have identified even lower HEI scores in risk populations (values between 58.7 and 67.8) 41, 42, 43. This is an expected result, since our sample can be considered as high cardiometabolic risk population. Female and older individuals (> 50 years) were more likely to have a higher R-HEI score. Women commonly present better diet quality when compared to men, 17, 20 besides them more likely to engage in healthy eating habits 16. This food behavior is related to greater dissatisfaction with appearance, body weight 44 and greater health concern 17.

Regarding the association between age and diet quality, studies have described that younger people are more likely to have low R-HEI scores 17, 20, 21. The higher meals eaten outside the home and the fast food preference (food consumption with high caloric density and low nutritional value) is commonly in young and adults when compared to elderly 45, 46 This behavior is characteristic of contemporary life and contributing for obesity and cardiometabolic risk factors increase among young adults 47, 48. Thus, nutritional intervention is necessary in order to prevent the early mortality and improve quality of life, since these diseases evolution is silent and the manifestations may occur during life-course 49.

Marital status also influences eating habits, so that married or stable married individuals have better food adequacy compared to single ones 11, 50. In a cardiometabolic risk population living in New York, the married/living with a partner were more likely to have high diet quality (HEI score > 80) 51. In another study, which adopted the Elderly Dietary Index to assess the diet quality of 4.252 older British men, diet quality had been most favorable in married men and those not living alone, showing that marital status and living arrangements can influence eating habits 50. This is because meals made in a social environment motivate for preparing complete and elaborate meals. On the other hand, when this psycho-social engagement is absent, individuals tend to choose monotonous and easy-to-prepare meals 50. In addition, the expense increase and the difficulty in handling the perishable foods purchase in small quantities lead to lower frequency to in natura food intake by those who live alone 19. Among men, the lack of motivation for changing eating habits associated to the lack of familiarity cooking also contributing to worse diet quality 52.

Contradictory to our results, other studies have identified that people with lower educational status are unlikely to have a higher quality diet 18, 20, 53. It is necessary to consider that the majority of the sample has a higher schooling and spend more time away from home due to work, which predisposes the greater ingestion of practical and industrialized foods 45, 46. This context is common in several countries where increasing industrialization and working hours have accompanied the reduction in the time available for preparing food. In this sense, eating at least one meal a day in restaurants is related to a higher chance of having low HEI score 11 and the healthy lifestyle is not commonly prioritized in these populations 54, 55.

Although other studies have identified a positive association between income and HEI score 18, 20, 53, we did not observe any association between income and diet quality. It should be noted that participants reported family income rather than per capita income, which may have contributed to non-association. However, we already know that the increase in years of study is related to better remuneration 56. Data from the Family Budgets Survey - 2002-2003 describe that the Brazilian low-income population consumes more rice, beans, cereals and tubers, while higher-income classes consume more ready-made foods, industrialized mixtures and biscuits 57. Low purchasing power and food access is related to higher food purchases from the basic food basket and lower fruits and vegetables intake 53, 58, but also the lower intake of higher cost processed foods 57.

In relation to alcoholic beverages, those who drinks eventually presented a greater chance of having a better R-HEI score (> 70.8 points), independent of confounding factors. Other authors have observed that moderate alcohol consumption, characterized by the ingestion of few doses in social use, is associated to healthier dietary patterns 59, 60, 61. Although alcohol intake contributes to the cardiometabolic alterations development 48, 62, this association is mediated by the consumption quantity and frequency, factors that were not evaluated in this study.

Regardless of the sociodemographic and lifestyle aspects, the total sample presented low scores in the items whole grains, total fruits, whole fruits, milk and dairy products, SFA and sodium, a common result in cardiometabolic risk populations 13, 42, 63, and the whole grains group is the one that presenting greater inadequacy. For whole grains, the longer preparation time contributes to their low consumption, especially because the women insertion in the job market and less time for preparing food 54. However, whole grains preserve more fiber, B vitamins and trace elements compared to refined grains, and should be associated to death risk reduction due to CVD 64.

The higher intake of fruits and vegetables characterizes healthier eating patterns and lower chronic diseases risk 59, 65, because they provide micronutrients, fibers, anti-antioxidants and anti-inflammatory compounds with cardioprotective effect, leading to reduction of oxidative stress, subclinical inflammation and improving of glycemic and lipemia control 66, 67, 68. Despite this, less than 38% of Brazilians consume fruit five times a week 69, so that the daily fruits [86 g/day) and vegetables (64 g/day) intake of this population 70 is so lower than the recommendation of 400 g/day 4, 71. Since 2.6 million deaths worldwide (30% of cardiovascular causes) could be avoided with adequate fruits and vegetables intake 72, altogether the data indicate the need for stimulating the consumption of these food-groups and providing conditions for accessing them to subsequently improving diet quality and reducing NCD.

As a limitation, only one R24 hour is used, according to Willett (1998), a single R24 hour may be sufficient to adequately estimate the mean intake of food and nutrients. In addition, the food consumption evaluated refers to the current and non-habitual intake. About results, the R-HEI is a useful tool in the diet quality determinants investigation and interventions targeting in risk and has been widely used in nutritional epidemiology 12 and in the investigation about sociodemographic and lifestyle factors 16, 17.

5. Conclusion

The participants had low R-HEI (69.4 ± 10.5) and total fruit, whole fruits, whole grains, milk and dairy products, sodium and SFA scores. The best diet quality was observed among female subjects, older, less educated, married or in stable union, and who reported eventual alcohol consumption, indicating the relevant role of social and lifestyle factors in adopting a healthy diet and controlling NCD.

Acknowledgements

We thank all PROCARDIO-UFV volunteers for their participation and the professionals involved at the program for the excellent assistance in data collection. We also thank the CAPES Foundation for the scholarship granted to B. K. S. Silveira.

Funding

Financial support was provided by the CAPES Foundation (Ministry of Education, Brazil, Financial code 001), National Council for Scientific Technological Development (CNPq/MCT/Brazil), and Foundation for Research Support of the State of Minas Gerais (FAPEMIG, State of Minas Gerais, Brazil). HHM Hermsdorff is a CNPq Research Productivity fellow.

Statement of Competing Interests

The authors have no competing interests to declare.

References

[1]  World Health Organization. Global action plan for the prevention and control of noncommunicable diseases 2013-2020. WHO, Geneva, 2013; 102.
In article      
 
[2]  Sociedade Brasileira de Cardiologia. South American Guidelines on Cardiovascular Prevention and Rehabilitation. Arq Bras Cardiol. 2014; 103(2 Supl.1): 1-31.
In article      
 
[3]  Neumann AICP, Martins IS, Marcopito LF, Araujo EAC. Dietary patterns associated with risk factors for cardiovascular diseases among residents of a Brazilian city. Rev Panam Salud Publica. 2007; 22: 329-39.
In article      View Article  PubMed
 
[4]  World Health Organization. Prevention of cardiovascular disease: guidelines for assessment and management of cardiovascular risk. 2007.
In article      
 
[5]  Aune D, Giovannucci E, Boffetta P, Fadnes LT, Keum N, Norat T, et al. Fruit and vegetable intake and the risk of cardiovascular disease, total cancer and all-cause mortality—a systematic review and dose-response meta-analysis of prospective studies. Int J Epidemiol. 2017; 46: 1029-56.
In article      View Article  PubMed  PubMed
 
[6]  Monteiro CA, Levy RB, Claro RM, de Castro IRR, Cannon G. Increasing consumption of ultra-processed foods and likely impact on human health: evidence from Brazil. Public Health Nutr. 2011; 14: 5-13.
In article      View Article  PubMed
 
[7]  Kennedy E, Ohls J, Carlson S, Fleming K. The Healthy Eating Index: Design and applications. J Am Diet Assoc. 1995; 95: 1103-8.
In article      View Article
 
[8]  Fisberg RM, Slater B, Barros RR, De Lima FD, Cesar CLG, Carandina L, et al. Healthy Eating Index: evaluation of adapted version and its applicability. Rev Nutr. 2004; 17: 301-8.
In article      View Article
 
[9]  Mota JF, Rinaldi AEM, Pereira AF, Maestá N, Scarpin MM, Burini RC. Adaptation of the healthy eating index to the food guide of the Brazilian population. Rev Nutr. 2008; 21: 545-52.
In article      View Article
 
[10]  Previdelli ÁN, Andrade SC de, Pires MM, Ferreira SRG, Fisberg RM, Marchioni DM. A revised version of the Healthy Eating Index for the Brazilian population. Rev Saude Publica. 2011; 45: 794-8.
In article      View Article  PubMed
 
[11]  Deierlein AL, Morland KB, Scanlin K, Wong S, Spark A. Diet Quality of Urban Older Adults Aged 60-99: The Cardiovascular Health of Seniors and Built Environment Study Andrea. J Acad Nutr Diet. 2014; 114: 279-87.
In article      View Article  PubMed  PubMed
 
[12]  Moreira PR, Rocha NP, Milagres LC, Novaes JF De. Critical analysis of the diet quality of the Brazilian population according to the Healthy Eating Index: a systematic review. Cien Saude Colet. 2015; 20: 3907-24.
In article      View Article  PubMed
 
[13]  Petrogianni M, Kanellakis S, Kallianioti K, Argyropoulou D, Pitsavos C, Manios Y. A multicomponent lifestyle intervention produces favourable changes in diet quality and cardiometabolic risk indices in hypercholesterolaemic adults. J Hum Nutr Diet. 2013; 26: 596-605.
In article      View Article  PubMed
 
[14]  Monfort-Pires M, Folchetti LD, Previdelli AN, Siqueira-Catania A, de Barros CR, Ferreira SR. Healthy Eating Index is associated with certain markers of inflammation and insulin resistance but not with lipid profile in individuals at cardiometabolic risk. Appl Physiol Nutr Metab. 2014; 39: 497-502.
In article      View Article  PubMed
 
[15]  Macht M. How emotions affect eating: a five-way model. Appetite. 2008; 50: 1-11.
In article      View Article  PubMed
 
[16]  Hiza H, Casavale K, Guenther P, Davis C. Diet quality of Americans differs by age, sex, race/ethnicity, income, and education level. J Acad Nutr Diet. 2013; 113: 297-306.
In article      View Article  PubMed
 
[17]  Assumpção D de, Domene SMÁ, Fisberg RM, Canesqui AM, Barros MB de A. Differences between men and women in the quality of their diet: a study conducted on a population in Campinas, São Paulo, Brazil. Ciência e Saúde Coletiva. 2017; 22: 347-58.
In article      
 
[18]  Backholer K, Spencer E, Gearon E, Magliano DJ, McNaughton SA, Shaw JE, et al. The association between socio-economic position and diet quality in Australian adults. Public Health Nutr. 2016; 19: 477-85.
In article      View Article  PubMed
 
[19]  Conklin AI, Forouhi NG, Surtees P, Khaw KT, Wareham NJ, Monsivais P. Social relationships and healthful dietary behaviour: Evidence from over-50s in the EPIC cohort, UK. Soc Sci Med. 2014; 100: 167-75.
In article      View Article  PubMed  PubMed
 
[20]  Adjoian TK, Firestone MJ, Eisenhower D, Yi SS. Validation of self-rated overall diet quality by Healthy Eating Index-2010 score among New York City adults, 2013. Prev Med Reports J. 2016; 3: 127-31.
In article      View Article  PubMed  PubMed
 
[21]  Costa D, Reis BZ, Vieira, Diva Aliete dos Santos Costa JO, Teixeira, Pryscila Dryele Souza Raposo, Oscar Felipe Falcão Lima, Flávia Emília Leite Mendes-Netto RS. Healthy eating index of women exercising in the “City Gym Program”, Aracajú, Sergipe, Brazil. Revista de Nutrição Campinas. 2012; 25: 731-41.
In article      View Article
 
[22]  Fisberg RM, Morimoto JM, Slater B, de Azevedo Barros MB, Carandina L, Goldbaum M, et al. Dietary Quality and Associated Factors among Adults Living in the State of São Paulo, Brazil. J Am Diet Assoc. 2006; 106: 2067-72.
In article      View Article  PubMed
 
[23]  Drewnowski A, Aggarwal A, Cook A, Stewart O, Moudon AV. Geographic disparities in Healthy Eating Index scores (HEI-2005 and 2010) by residential property values: Findings from Seattle Obesity Study (SOS). Prev Med (Baltim). 2016; 83: 46-55.
In article      View Article  PubMed  PubMed
 
[24]  Hartman TJ, Haardörfer R, Whitaker LL, Addison A, Zlotorzynska M, Gazmararian JA, et al. Dietary and Behavioral Factors Associated with Diet Quality among Low-income Overweight and Obese African American Women. J Am Coll Nutr. 2015; 34: 416-24.
In article      View Article  PubMed
 
[25]  Hare-Bruun H, Togo P, Andersen LB, Heitmann BL. Adult Food Intake Patterns Are Related to Adult and Childhood Socioeconomic Status. J Nutr. 2011; 141: 928-34.
In article      View Article  PubMed
 
[26]  Bonaccio M, Bonanni AE, Di Castelnuovo A, De Lucia F, Donati MB, de Gaetano G, et al. Low income is associated with poor adherence to a Mediterranean diet and a higher prevalence of obesity: cross-sectional results from the Moli-sani study. BMJ Open. 2012; 2: 1-9.
In article      View Article  PubMed  PubMed
 
[27]  Chomistek AK, Chiuve SE, Eliassen AH, Mukamal KJ, Willett WC, Rimm EB. Healthy Lifestyle in the Primordial Prevention of Cardiovascular Disease Among Young Women. J Am Coll Cardiol. 2015; 65: 43-51.
In article      View Article  PubMed  PubMed
 
[28]  Olinto MTA, Gigante DP, Horta B, Silveira V, Oliveira I, Willett W. Major dietary patterns and cardiovascular risk factors among young Brazilian adults. Eur J Nutr. 2012; 51: 281-91.
In article      View Article  PubMed  PubMed
 
[29]  Rodrigues JS, Almeida AP de, Rosa C de OB, Hermsdorff HHM. Are Body Fat and Uric Acid Associated with Cardiovascular Risk Scores? Cross-Sectional Analysis in the PROCARDIO-UFV Trial. Int J Cardiovasc Sci. 2017; 30: 313-24.
In article      View Article
 
[30]  Almeida AP de, Rocha DMUP, Mendonça LM, Novaes JF de, Hermsdorff HHM. Carotenoid and polyphenol consumption in subjects with cardiometabolic risk. Nutr Clínica y Dietética Hosp. 2016; 36: 138-45.
In article      
 
[31]  Conway JM, Ingwersen LA, Vinyard BT, Moshfegh AJ. Effectiveness of the USDA 5-step Multiple-Pass Method to assess food intake in obese and non-obese women. Am J Clin Nutr. 2003; 77: 71-78.
In article      View Article  PubMed
 
[32]  Andrade SC de, Previdelli AN, Marchioni DML, Fisberg RM. Evaluation of the reliability and validity of the Brazilian Healthy Eating Index Revised. Rev Saude Publica. 2013; 47: 675-83.
In article      
 
[33]  BRASIL. Ministry of Health. Secretariat of Health Care. Department of Basic Attention. Food Guide for the Brazilian Population. Promoting Healthy Eating. 2008. 210p.
In article      
 
[34]  Araújo M, Guerra T. Alimentos “Per capita’’. 3a Ed. Editora da UFRN,. 2007. 324p.
In article      
 
[35]  Pinheiro A, Lacerda E, Benzecry E, Gomes M, Costa V. Table for evaluation of consumption in home measures. In: Ed Atheneu. 2000. p.79.
In article      
 
[36]  USDA. United State Departament of Agriculture, Agricultural Research Service. National Nutrient Database for Standard Reference, Release 28. Nutrient Data Laboratory. 2016.
In article      
 
[37]  Hermsdorff HH, Mansego ML, Campión J, Milagro FI, Zulet MA, Martínez JA. TNF-alpha promoter methylation in peripheral white blood cells: Relationship with circulating TNFα, truncal fat and n-6 PUFA intake in young women. Cytokine. 2013; 64: 265-71.
In article      View Article  PubMed
 
[38]  Carraro JCC, Hermsdorff HHM, Mansego ML, Zulet MÁ, Milagro FI, Bressan J, et al. Higher fruit intake is related to TNF-α hypomethylation and better glucose tolerance in healthy subjects. J Nutrigenet Nutrigenomics. 2016; 9(2-4): 95-105.
In article      View Article  PubMed
 
[39]  Willett W. Nutritional Epidemiology. 1998. 2 ed. New York: Oxford University.
In article      
 
[40]  Bowman S, M L, Gerrior S, Basiotis P. The Healthy Eating Index. US Dep Agric Cent Nutr Policy Promot CNPP-5. 1998; 1-19.
In article      
 
[41]  Santos C, Gouveia L, Portella E, Avila S, Soares E, Lanzillotti H. Healthy Eating Index: evaluation of food consumption by subjects with type 2 diabetes. Nutr rev Soc Bras Alim Nutr = J Brazilian Soc Food Nutr. 2009; 34: 115-29.
In article      
 
[42]  Monfort-pires M, Folchetti LD, Previdelli AN, Siqueira-catania A, Barros CR De, Roberta S, et al. Healthy Eating Index is associated with certain markers of inflammation and insulin resistance but not with lipid profile in individuals at cardiometabolic risk. Appl Physiol Nutr Metab. 2014; 39: 497-502.
In article      View Article  PubMed
 
[43]  Direktör Ş, Özer E. Evaluating dietary quality in diabetes by the Healthy Eating Index. Asia Pac J Clin Nutr. 2013; 22: 620-5.
In article      PubMed
 
[44]  Amaral A, Hernández RN, Basabe BN, Rocandio PA, Arroyo IM. Body satisfaction and diet quality in female university students from the Basque Country. Endocrinol Nutr. 2012; 59: 239-45.
In article      View Article
 
[45]  Carús P, França GVA, Barros AJD. Place and type of meals consumed by adults in medium sized cities. Revista de Saúde Pública. 2014; 48: 68-75.
In article      View Article  PubMed  PubMed
 
[46]  Bezerra IN, Souza ADM, Pereira RA, Sichieri R. Consumption of foods away from home in Brazil. Rev Saúde Pública. 2013; 47(Supl.1): 200-11.
In article      View Article
 
[47]  Rubin JB, Borden WB. Coronary Heart Disease in Young Adults. Curr Atheroscler Rep. 2012; 14: 140-9.
In article      View Article  PubMed
 
[48]  Sociedade Brasileira de Diabetes. Atualização da diretriz brasileira de dislipidemias e prevenção da aterosclerose - 2017. Arq Bras Cardiol. 2017; 109 (Supl.1).
In article      
 
[49]  Leeder S, Raymond S, Greenberg H. A race against time: The challenge of cardiovascular disease in developing economics. New York Columbia Univ. 2004;
In article      
 
[50]  Atkins JL, Ramsay SE, Whincup PH, Morris RW, Lennon LT, Wannamethee SG. Diet quality in older age: the influence of childhood and adult socio-economic circumstances. Br J Nutr. 2015; 113: 1441-52.
In article      View Article  PubMed  PubMed
 
[51]  Deierlein AL, Morland KB, Scanlin K, Wong S, Spark A. Diet Quality of Urban Older Adults Age 60 to 99 Years: The Cardiovascular Health of Seniors and Built Environment Study. J Acad Nutr Diet. 2014 Feb; 114: 279-87.
In article      View Article  PubMed  PubMed
 
[52]  Hughes G, Bennett KM, Hetherington MM. Old and alone: Barriers to healthy eating in older men living on their own. Appetite. 2004; 43: 269-76.
In article      View Article  PubMed
 
[53]  Claro RM, Monteiro CA. Family income, food prices, and household purchases of fruits and vegetables in Brazil Departamento. Revista Saúde Pública. 2010; 44: 1014-20.
In article      View Article  PubMed
 
[54]  Moratoya EE, Carvalhaes GC, Wander AE, Manoel L, Camargo DM. Mudanças no padrão de consumo alimentar no Brasil. Rev Política Agrícola. 2013,22: 72-84.
In article      
 
[55]  ABESO - Associação Brasileira para o estudo da obesidade e da síndrome metabólica. Diretrizes Brasileiras de Obesidade. 4a ed. 2016. 188 p.
In article      
 
[56]  Salvato MA, Ferreira PCG, Duarte AJM. The Impact of Schooling on Income Distribution. Estudos Econômicos (São Paulo). 2010; 40: 753-91.
In article      View Article
 
[57]  BRASIL. Pesquisa de Orçamentos Familiares 2002-2003. IBGE, Instituto Brasileiro de Geografia e Estatística. 2003; 76.
In article      
 
[58]  Aggarwal A, Monsivais P, Cook AJ, Drewnowski A. Does diet cost mediate the relation between socioeconomic position and diet quality? Eur J Clin Nutr. 2011 ; 65: 1059-66.
In article      View Article  PubMed  PubMed
 
[59]  Bressan J, Hermsdorff HHM, Zulet MÁ, Martínez JA. Hormonal and inflammatory impact of different dietetic composition: emphasis on dietary patterns and specific dietary factors. Arq Bras Endocrinol Metabol. 2009; 53: 572-81.
In article      View Article  PubMed
 
[60]  Camelo L do V, Giatti L, Barreto SM. Health related quality of life among elderly living in region of high vulnerability for health in Belo Horizonte, Minas Gerais, Brazil. Rev Bras Epidemiol. 2016; 19: 280-93.
In article      PubMed
 
[61]  Roerecke M, Rehm J. Alcohol consumption, drinking patterns, and ischemic heart disease: a narrative review of meta-analyses and a systematic review and meta-analysis of the impact of heavy drinking occasions on risk for moderate drinkers. BMC Med. 2014; 12: 182.
In article      View Article  PubMed  PubMed
 
[62]  Cepeda MS, Stang P, Blacketer C, Kent JM, Wittenberg GM. Clinical Relevance of Sleep Duration : Results from a Cross-Sectional Analysis Using NHANES. J Clin Sleep Med. 2016; 12: 813-9.
In article      View Article  PubMed  PubMed
 
[63]  Anders S, Schroeter C. Diabetes, diet-health behavior, and obesity. Front Endocrinol. 2015; 6: 1-8.
In article      View Article  PubMed  PubMed
 
[64]  6Aune D, Keum N, Giovannucci E, Fadnes LT, Boffetta P, Greenwood DC, et al. Whole grain consumption and risk of cardiovascular disease, cancer, and all cause and cause specific mortality: systematic review and dose-response meta-analysis of prospective studies. BMJ. 2016; 14: 1-14.
In article      
 
[65]  Hermsdorff HHM, Ángeles Zulet M, Bressan J, Alfredo Martínez J. Effect of diet on the low-grade and chronic inflammation associated with obesity and metabolic syndrome. Endocrinol y Nutr. 2008; 55: 409-19.
In article      View Article
 
[66]  Hermsdorff HHM, Zulet MÁ, Puchau B, Martínez JA. Fruit and vegetable consumption and proinflammatory gene expression from peripheral blood mononuclear cells in young adults: a translational study. Nutr Metab (Lond). 2010; 7: 1-11.
In article      View Article  PubMed  PubMed
 
[67]  Hermsdorff HHM, Zulet MÁ, Abete I, Martínez JA. A legume-based hypocaloric diet reduces proinflammatory status and improves metabolic features in overweight/obese subjects. Eur J Nutr. 2011; 50: 61-9.
In article      View Article  PubMed
 
[68]  Cocate PG, Natali AJ, Oliveira A De, Longo GZ, Alfenas R de CG, Peluzio CG, et al. Fruit and vegetable intake and related nutrients are associated with oxidative stress markers in middle-aged men. Nutrition. 2013; 30: 660-5.
In article      View Article  PubMed
 
[69]  Malta DC, Szwarcwald CL. Lifestyles and chronic non-transmissible diseases of the Brazilian population according to the National Health Survey: balance of the main results. Sao Paulo Med J. 2015; 133: 286-9.
In article      View Article  PubMed
 
[70]  Vargas-Murga L, de Rosso V V., Mercadante AZ, Olmedilla-Alonso B. Fruits and vegetables in the Brazilian Household Budget Survey (2008-2009): carotenoid content and assessment of individual carotenoid intake. J Food Compos Anal. 2016 Jul; 50: 88-96.
In article      View Article
 
[71]  World Health Organization. Diet, nutrition and the prevention of chronic diseases. Vol. Geneva, WHO technical report series. 2003.
In article      
 
[72]  Lock K, Pomerleau J, Causer L, Altmann DR, Mckee M. The global burden of disease attributable to low consumption of fruit and vegetables: implications for the global strategy on diet. Bulletin of the World Health Organization. 2005; 83: 100-8.
In article      PubMed  PubMed
 

Published with license by Science and Education Publishing, Copyright © 2019 Brenda Kelly Souza Silveira, Juliana Farias de Novaes, Nínive de Almeida Reis, Larissa Pereira Lourenço, Ana Helena Moretto Capobiango, Arieta Carla Gualandi Leal and Helen Hermana Miranda Hermsdorff

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Normal Style
Brenda Kelly Souza Silveira, Juliana Farias de Novaes, Nínive de Almeida Reis, Larissa Pereira Lourenço, Ana Helena Moretto Capobiango, Arieta Carla Gualandi Leal, Helen Hermana Miranda Hermsdorff. Sociodemographic and Lifestyle Factors Are Associated with Diet Quality in Cardiometabolic Risk Subjects. Journal of Food and Nutrition Research. Vol. 7, No. 2, 2019, pp 141-147. http://pubs.sciepub.com/jfnr/7/2/6
MLA Style
Silveira, Brenda Kelly Souza, et al. "Sociodemographic and Lifestyle Factors Are Associated with Diet Quality in Cardiometabolic Risk Subjects." Journal of Food and Nutrition Research 7.2 (2019): 141-147.
APA Style
Silveira, B. K. S. , Novaes, J. F. D. , Reis, N. D. A. , Lourenço, L. P. , Capobiango, A. H. M. , Leal, A. C. G. , & Hermsdorff, H. H. M. (2019). Sociodemographic and Lifestyle Factors Are Associated with Diet Quality in Cardiometabolic Risk Subjects. Journal of Food and Nutrition Research, 7(2), 141-147.
Chicago Style
Silveira, Brenda Kelly Souza, Juliana Farias de Novaes, Nínive de Almeida Reis, Larissa Pereira Lourenço, Ana Helena Moretto Capobiango, Arieta Carla Gualandi Leal, and Helen Hermana Miranda Hermsdorff. "Sociodemographic and Lifestyle Factors Are Associated with Diet Quality in Cardiometabolic Risk Subjects." Journal of Food and Nutrition Research 7, no. 2 (2019): 141-147.
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  • Figure 1. Average score obtained on each R-HEI component (in points) in relation to the respective reference values. in a cardiometabolic population. *VeVeAL = Dark green and orange vegetables and beans. GORD_AA = Calories from solid fat. alcohol and added sugar
  • Table 1. Socioeconomic and lifestyle aspects in cardiometabolic risk subjects, according to median Revised Healthy Eating Index (R-HEI) (70.83 points)
  • Table 2. Scores of Revised Healthy Eating Index (R-HEI) components by sex and age in a cardiometabolic risk population
  • Table 3. Prevalence ratio (PR) of higher diet quality (dependent variable)1, according to socioeconomic variables and lifestyle factor in cardiometabolic risk subjects
[1]  World Health Organization. Global action plan for the prevention and control of noncommunicable diseases 2013-2020. WHO, Geneva, 2013; 102.
In article      
 
[2]  Sociedade Brasileira de Cardiologia. South American Guidelines on Cardiovascular Prevention and Rehabilitation. Arq Bras Cardiol. 2014; 103(2 Supl.1): 1-31.
In article      
 
[3]  Neumann AICP, Martins IS, Marcopito LF, Araujo EAC. Dietary patterns associated with risk factors for cardiovascular diseases among residents of a Brazilian city. Rev Panam Salud Publica. 2007; 22: 329-39.
In article      View Article  PubMed
 
[4]  World Health Organization. Prevention of cardiovascular disease: guidelines for assessment and management of cardiovascular risk. 2007.
In article      
 
[5]  Aune D, Giovannucci E, Boffetta P, Fadnes LT, Keum N, Norat T, et al. Fruit and vegetable intake and the risk of cardiovascular disease, total cancer and all-cause mortality—a systematic review and dose-response meta-analysis of prospective studies. Int J Epidemiol. 2017; 46: 1029-56.
In article      View Article  PubMed  PubMed
 
[6]  Monteiro CA, Levy RB, Claro RM, de Castro IRR, Cannon G. Increasing consumption of ultra-processed foods and likely impact on human health: evidence from Brazil. Public Health Nutr. 2011; 14: 5-13.
In article      View Article  PubMed
 
[7]  Kennedy E, Ohls J, Carlson S, Fleming K. The Healthy Eating Index: Design and applications. J Am Diet Assoc. 1995; 95: 1103-8.
In article      View Article
 
[8]  Fisberg RM, Slater B, Barros RR, De Lima FD, Cesar CLG, Carandina L, et al. Healthy Eating Index: evaluation of adapted version and its applicability. Rev Nutr. 2004; 17: 301-8.
In article      View Article
 
[9]  Mota JF, Rinaldi AEM, Pereira AF, Maestá N, Scarpin MM, Burini RC. Adaptation of the healthy eating index to the food guide of the Brazilian population. Rev Nutr. 2008; 21: 545-52.
In article      View Article
 
[10]  Previdelli ÁN, Andrade SC de, Pires MM, Ferreira SRG, Fisberg RM, Marchioni DM. A revised version of the Healthy Eating Index for the Brazilian population. Rev Saude Publica. 2011; 45: 794-8.
In article      View Article  PubMed
 
[11]  Deierlein AL, Morland KB, Scanlin K, Wong S, Spark A. Diet Quality of Urban Older Adults Aged 60-99: The Cardiovascular Health of Seniors and Built Environment Study Andrea. J Acad Nutr Diet. 2014; 114: 279-87.
In article      View Article  PubMed  PubMed
 
[12]  Moreira PR, Rocha NP, Milagres LC, Novaes JF De. Critical analysis of the diet quality of the Brazilian population according to the Healthy Eating Index: a systematic review. Cien Saude Colet. 2015; 20: 3907-24.
In article      View Article  PubMed
 
[13]  Petrogianni M, Kanellakis S, Kallianioti K, Argyropoulou D, Pitsavos C, Manios Y. A multicomponent lifestyle intervention produces favourable changes in diet quality and cardiometabolic risk indices in hypercholesterolaemic adults. J Hum Nutr Diet. 2013; 26: 596-605.
In article      View Article  PubMed
 
[14]  Monfort-Pires M, Folchetti LD, Previdelli AN, Siqueira-Catania A, de Barros CR, Ferreira SR. Healthy Eating Index is associated with certain markers of inflammation and insulin resistance but not with lipid profile in individuals at cardiometabolic risk. Appl Physiol Nutr Metab. 2014; 39: 497-502.
In article      View Article  PubMed
 
[15]  Macht M. How emotions affect eating: a five-way model. Appetite. 2008; 50: 1-11.
In article      View Article  PubMed
 
[16]  Hiza H, Casavale K, Guenther P, Davis C. Diet quality of Americans differs by age, sex, race/ethnicity, income, and education level. J Acad Nutr Diet. 2013; 113: 297-306.
In article      View Article  PubMed
 
[17]  Assumpção D de, Domene SMÁ, Fisberg RM, Canesqui AM, Barros MB de A. Differences between men and women in the quality of their diet: a study conducted on a population in Campinas, São Paulo, Brazil. Ciência e Saúde Coletiva. 2017; 22: 347-58.
In article      
 
[18]  Backholer K, Spencer E, Gearon E, Magliano DJ, McNaughton SA, Shaw JE, et al. The association between socio-economic position and diet quality in Australian adults. Public Health Nutr. 2016; 19: 477-85.
In article      View Article  PubMed
 
[19]  Conklin AI, Forouhi NG, Surtees P, Khaw KT, Wareham NJ, Monsivais P. Social relationships and healthful dietary behaviour: Evidence from over-50s in the EPIC cohort, UK. Soc Sci Med. 2014; 100: 167-75.
In article      View Article  PubMed  PubMed
 
[20]  Adjoian TK, Firestone MJ, Eisenhower D, Yi SS. Validation of self-rated overall diet quality by Healthy Eating Index-2010 score among New York City adults, 2013. Prev Med Reports J. 2016; 3: 127-31.
In article      View Article  PubMed  PubMed
 
[21]  Costa D, Reis BZ, Vieira, Diva Aliete dos Santos Costa JO, Teixeira, Pryscila Dryele Souza Raposo, Oscar Felipe Falcão Lima, Flávia Emília Leite Mendes-Netto RS. Healthy eating index of women exercising in the “City Gym Program”, Aracajú, Sergipe, Brazil. Revista de Nutrição Campinas. 2012; 25: 731-41.
In article      View Article
 
[22]  Fisberg RM, Morimoto JM, Slater B, de Azevedo Barros MB, Carandina L, Goldbaum M, et al. Dietary Quality and Associated Factors among Adults Living in the State of São Paulo, Brazil. J Am Diet Assoc. 2006; 106: 2067-72.
In article      View Article  PubMed
 
[23]  Drewnowski A, Aggarwal A, Cook A, Stewart O, Moudon AV. Geographic disparities in Healthy Eating Index scores (HEI-2005 and 2010) by residential property values: Findings from Seattle Obesity Study (SOS). Prev Med (Baltim). 2016; 83: 46-55.
In article      View Article  PubMed  PubMed
 
[24]  Hartman TJ, Haardörfer R, Whitaker LL, Addison A, Zlotorzynska M, Gazmararian JA, et al. Dietary and Behavioral Factors Associated with Diet Quality among Low-income Overweight and Obese African American Women. J Am Coll Nutr. 2015; 34: 416-24.
In article      View Article  PubMed
 
[25]  Hare-Bruun H, Togo P, Andersen LB, Heitmann BL. Adult Food Intake Patterns Are Related to Adult and Childhood Socioeconomic Status. J Nutr. 2011; 141: 928-34.
In article      View Article  PubMed
 
[26]  Bonaccio M, Bonanni AE, Di Castelnuovo A, De Lucia F, Donati MB, de Gaetano G, et al. Low income is associated with poor adherence to a Mediterranean diet and a higher prevalence of obesity: cross-sectional results from the Moli-sani study. BMJ Open. 2012; 2: 1-9.
In article      View Article  PubMed  PubMed
 
[27]  Chomistek AK, Chiuve SE, Eliassen AH, Mukamal KJ, Willett WC, Rimm EB. Healthy Lifestyle in the Primordial Prevention of Cardiovascular Disease Among Young Women. J Am Coll Cardiol. 2015; 65: 43-51.
In article      View Article  PubMed  PubMed
 
[28]  Olinto MTA, Gigante DP, Horta B, Silveira V, Oliveira I, Willett W. Major dietary patterns and cardiovascular risk factors among young Brazilian adults. Eur J Nutr. 2012; 51: 281-91.
In article      View Article  PubMed  PubMed
 
[29]  Rodrigues JS, Almeida AP de, Rosa C de OB, Hermsdorff HHM. Are Body Fat and Uric Acid Associated with Cardiovascular Risk Scores? Cross-Sectional Analysis in the PROCARDIO-UFV Trial. Int J Cardiovasc Sci. 2017; 30: 313-24.
In article      View Article
 
[30]  Almeida AP de, Rocha DMUP, Mendonça LM, Novaes JF de, Hermsdorff HHM. Carotenoid and polyphenol consumption in subjects with cardiometabolic risk. Nutr Clínica y Dietética Hosp. 2016; 36: 138-45.
In article      
 
[31]  Conway JM, Ingwersen LA, Vinyard BT, Moshfegh AJ. Effectiveness of the USDA 5-step Multiple-Pass Method to assess food intake in obese and non-obese women. Am J Clin Nutr. 2003; 77: 71-78.
In article      View Article  PubMed
 
[32]  Andrade SC de, Previdelli AN, Marchioni DML, Fisberg RM. Evaluation of the reliability and validity of the Brazilian Healthy Eating Index Revised. Rev Saude Publica. 2013; 47: 675-83.
In article      
 
[33]  BRASIL. Ministry of Health. Secretariat of Health Care. Department of Basic Attention. Food Guide for the Brazilian Population. Promoting Healthy Eating. 2008. 210p.
In article      
 
[34]  Araújo M, Guerra T. Alimentos “Per capita’’. 3a Ed. Editora da UFRN,. 2007. 324p.
In article      
 
[35]  Pinheiro A, Lacerda E, Benzecry E, Gomes M, Costa V. Table for evaluation of consumption in home measures. In: Ed Atheneu. 2000. p.79.
In article      
 
[36]  USDA. United State Departament of Agriculture, Agricultural Research Service. National Nutrient Database for Standard Reference, Release 28. Nutrient Data Laboratory. 2016.
In article      
 
[37]  Hermsdorff HH, Mansego ML, Campión J, Milagro FI, Zulet MA, Martínez JA. TNF-alpha promoter methylation in peripheral white blood cells: Relationship with circulating TNFα, truncal fat and n-6 PUFA intake in young women. Cytokine. 2013; 64: 265-71.
In article      View Article  PubMed
 
[38]  Carraro JCC, Hermsdorff HHM, Mansego ML, Zulet MÁ, Milagro FI, Bressan J, et al. Higher fruit intake is related to TNF-α hypomethylation and better glucose tolerance in healthy subjects. J Nutrigenet Nutrigenomics. 2016; 9(2-4): 95-105.
In article      View Article  PubMed
 
[39]  Willett W. Nutritional Epidemiology. 1998. 2 ed. New York: Oxford University.
In article      
 
[40]  Bowman S, M L, Gerrior S, Basiotis P. The Healthy Eating Index. US Dep Agric Cent Nutr Policy Promot CNPP-5. 1998; 1-19.
In article      
 
[41]  Santos C, Gouveia L, Portella E, Avila S, Soares E, Lanzillotti H. Healthy Eating Index: evaluation of food consumption by subjects with type 2 diabetes. Nutr rev Soc Bras Alim Nutr = J Brazilian Soc Food Nutr. 2009; 34: 115-29.
In article      
 
[42]  Monfort-pires M, Folchetti LD, Previdelli AN, Siqueira-catania A, Barros CR De, Roberta S, et al. Healthy Eating Index is associated with certain markers of inflammation and insulin resistance but not with lipid profile in individuals at cardiometabolic risk. Appl Physiol Nutr Metab. 2014; 39: 497-502.
In article      View Article  PubMed
 
[43]  Direktör Ş, Özer E. Evaluating dietary quality in diabetes by the Healthy Eating Index. Asia Pac J Clin Nutr. 2013; 22: 620-5.
In article      PubMed
 
[44]  Amaral A, Hernández RN, Basabe BN, Rocandio PA, Arroyo IM. Body satisfaction and diet quality in female university students from the Basque Country. Endocrinol Nutr. 2012; 59: 239-45.
In article      View Article
 
[45]  Carús P, França GVA, Barros AJD. Place and type of meals consumed by adults in medium sized cities. Revista de Saúde Pública. 2014; 48: 68-75.
In article      View Article  PubMed  PubMed
 
[46]  Bezerra IN, Souza ADM, Pereira RA, Sichieri R. Consumption of foods away from home in Brazil. Rev Saúde Pública. 2013; 47(Supl.1): 200-11.
In article      View Article
 
[47]  Rubin JB, Borden WB. Coronary Heart Disease in Young Adults. Curr Atheroscler Rep. 2012; 14: 140-9.
In article      View Article  PubMed
 
[48]  Sociedade Brasileira de Diabetes. Atualização da diretriz brasileira de dislipidemias e prevenção da aterosclerose - 2017. Arq Bras Cardiol. 2017; 109 (Supl.1).
In article      
 
[49]  Leeder S, Raymond S, Greenberg H. A race against time: The challenge of cardiovascular disease in developing economics. New York Columbia Univ. 2004;
In article      
 
[50]  Atkins JL, Ramsay SE, Whincup PH, Morris RW, Lennon LT, Wannamethee SG. Diet quality in older age: the influence of childhood and adult socio-economic circumstances. Br J Nutr. 2015; 113: 1441-52.
In article      View Article  PubMed  PubMed
 
[51]  Deierlein AL, Morland KB, Scanlin K, Wong S, Spark A. Diet Quality of Urban Older Adults Age 60 to 99 Years: The Cardiovascular Health of Seniors and Built Environment Study. J Acad Nutr Diet. 2014 Feb; 114: 279-87.
In article      View Article  PubMed  PubMed
 
[52]  Hughes G, Bennett KM, Hetherington MM. Old and alone: Barriers to healthy eating in older men living on their own. Appetite. 2004; 43: 269-76.
In article      View Article  PubMed
 
[53]  Claro RM, Monteiro CA. Family income, food prices, and household purchases of fruits and vegetables in Brazil Departamento. Revista Saúde Pública. 2010; 44: 1014-20.
In article      View Article  PubMed
 
[54]  Moratoya EE, Carvalhaes GC, Wander AE, Manoel L, Camargo DM. Mudanças no padrão de consumo alimentar no Brasil. Rev Política Agrícola. 2013,22: 72-84.
In article      
 
[55]  ABESO - Associação Brasileira para o estudo da obesidade e da síndrome metabólica. Diretrizes Brasileiras de Obesidade. 4a ed. 2016. 188 p.
In article      
 
[56]  Salvato MA, Ferreira PCG, Duarte AJM. The Impact of Schooling on Income Distribution. Estudos Econômicos (São Paulo). 2010; 40: 753-91.
In article      View Article
 
[57]  BRASIL. Pesquisa de Orçamentos Familiares 2002-2003. IBGE, Instituto Brasileiro de Geografia e Estatística. 2003; 76.
In article      
 
[58]  Aggarwal A, Monsivais P, Cook AJ, Drewnowski A. Does diet cost mediate the relation between socioeconomic position and diet quality? Eur J Clin Nutr. 2011 ; 65: 1059-66.
In article      View Article  PubMed  PubMed
 
[59]  Bressan J, Hermsdorff HHM, Zulet MÁ, Martínez JA. Hormonal and inflammatory impact of different dietetic composition: emphasis on dietary patterns and specific dietary factors. Arq Bras Endocrinol Metabol. 2009; 53: 572-81.
In article      View Article  PubMed
 
[60]  Camelo L do V, Giatti L, Barreto SM. Health related quality of life among elderly living in region of high vulnerability for health in Belo Horizonte, Minas Gerais, Brazil. Rev Bras Epidemiol. 2016; 19: 280-93.
In article      PubMed
 
[61]  Roerecke M, Rehm J. Alcohol consumption, drinking patterns, and ischemic heart disease: a narrative review of meta-analyses and a systematic review and meta-analysis of the impact of heavy drinking occasions on risk for moderate drinkers. BMC Med. 2014; 12: 182.
In article      View Article  PubMed  PubMed
 
[62]  Cepeda MS, Stang P, Blacketer C, Kent JM, Wittenberg GM. Clinical Relevance of Sleep Duration : Results from a Cross-Sectional Analysis Using NHANES. J Clin Sleep Med. 2016; 12: 813-9.
In article      View Article  PubMed  PubMed
 
[63]  Anders S, Schroeter C. Diabetes, diet-health behavior, and obesity. Front Endocrinol. 2015; 6: 1-8.
In article      View Article  PubMed  PubMed
 
[64]  6Aune D, Keum N, Giovannucci E, Fadnes LT, Boffetta P, Greenwood DC, et al. Whole grain consumption and risk of cardiovascular disease, cancer, and all cause and cause specific mortality: systematic review and dose-response meta-analysis of prospective studies. BMJ. 2016; 14: 1-14.
In article      
 
[65]  Hermsdorff HHM, Ángeles Zulet M, Bressan J, Alfredo Martínez J. Effect of diet on the low-grade and chronic inflammation associated with obesity and metabolic syndrome. Endocrinol y Nutr. 2008; 55: 409-19.
In article      View Article
 
[66]  Hermsdorff HHM, Zulet MÁ, Puchau B, Martínez JA. Fruit and vegetable consumption and proinflammatory gene expression from peripheral blood mononuclear cells in young adults: a translational study. Nutr Metab (Lond). 2010; 7: 1-11.
In article      View Article  PubMed  PubMed
 
[67]  Hermsdorff HHM, Zulet MÁ, Abete I, Martínez JA. A legume-based hypocaloric diet reduces proinflammatory status and improves metabolic features in overweight/obese subjects. Eur J Nutr. 2011; 50: 61-9.
In article      View Article  PubMed
 
[68]  Cocate PG, Natali AJ, Oliveira A De, Longo GZ, Alfenas R de CG, Peluzio CG, et al. Fruit and vegetable intake and related nutrients are associated with oxidative stress markers in middle-aged men. Nutrition. 2013; 30: 660-5.
In article      View Article  PubMed
 
[69]  Malta DC, Szwarcwald CL. Lifestyles and chronic non-transmissible diseases of the Brazilian population according to the National Health Survey: balance of the main results. Sao Paulo Med J. 2015; 133: 286-9.
In article      View Article  PubMed
 
[70]  Vargas-Murga L, de Rosso V V., Mercadante AZ, Olmedilla-Alonso B. Fruits and vegetables in the Brazilian Household Budget Survey (2008-2009): carotenoid content and assessment of individual carotenoid intake. J Food Compos Anal. 2016 Jul; 50: 88-96.
In article      View Article
 
[71]  World Health Organization. Diet, nutrition and the prevention of chronic diseases. Vol. Geneva, WHO technical report series. 2003.
In article      
 
[72]  Lock K, Pomerleau J, Causer L, Altmann DR, Mckee M. The global burden of disease attributable to low consumption of fruit and vegetables: implications for the global strategy on diet. Bulletin of the World Health Organization. 2005; 83: 100-8.
In article      PubMed  PubMed