Dietary patterns according to gender and ethnicity associated with metabolic syndrome: a systematic review and meta-analysis

Barbosa, Lídia Bezerra; Gama, Isabelle Rodrigues de Souza; Vasconcelos, Nancy Borges Rodrigues; Santos, Ewerton Amorim dos; Ataide-Silva, Thays; Ferreira, Haroldo da Silva

doi:10.1590/1413-812320242910.03662023

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ARTICLES REVIEWS • Ciênc. saúde coletiva 29 (10) • Oct 2024 • https://doi.org/10.1590/1413-812320242910.03662023 copy

Dietary patterns according to gender and ethnicity associated with metabolic syndrome: a systematic review and meta-analysis

Padrões alimentares segundo gênero e etnia associados com a síndrome metabólica: uma revisão sistemática e meta-análise

Authorship SCIMAGO INSTITUTIONS RANKINGS

Abstract

The objective of this systematic review (SR) with meta-analysis (MA) was to identify the dietary patterns of the population, regarding ethnicity and gender, and their association with the metabolic syndrome and its risk factors (MetS-RF). The literature search was performed using Medline, Scopus, Ebsco, SciELO, and BVS databases. Studies with adult participants that identified dietary patterns associated with MetS-RF were included. Pooled odds ratio (OR) and 95%CI were calculated using a random-effect, generic inverse variance method. Statistical heterogeneity and publication bias were explored. The dietary patterns were classified as healthy or unhealthy. Studies were categorized into three groups: Women (all ethnicities), Afro-descendant (men and women), and General Population (both genders and ethnicity). Among the articles found (n=8,496), 22 integrated the SR and 11 the MA. The adherence to the healthy dietary pattern was negatively associated (protective factor) with MetS-RF only in the General Population (OR=0.77; 95%CI: 0.61-0.98). Nevertheless, the unhealthy dietary pattern was associated with the higher prevalence of MetS-RF in all analyzed groups. It was concluded that an unhealthy eating pattern increases the chances of SM-RF in adults, regardless of gender and ethnicity.

Key words:
Metabolic syndrome; Feeding behavior; Western diet

Author, year of publication and country	Perio- dical	Data collection year	Study design	Target-public	Sample size; age range	% Women/ % afro-descendant	Assessed outcome	Assessed risk factors for MetS	Methodo- logical quality
Frank et al., 2014⁴⁷47 Frank LK, Kröger J, Schulze MB, Bedu-Addo G, Mockenhaupt FP, Danquah I. Dietary patterns in urban Ghana and risk of type 2 diabetes. Br J Nutr 2014; 112(1):89-98. Ghana	Br J Nutr	Between August 2007 and June 2008	Case-control	Men and women	1,221 participants: 679 controls and 542 cases; Average age of 50.4 years	76.0/100	T2DM	WC, WHR, fasting glycemia	Strong
Nettleton et al., 2009⁴⁸48 Nettleton JA, Polak JF, Tracy R, Burke GL, Jacobs DR. Dietary patterns and incident cardiovascular disease in the Multi-Ethnic Study of Atherosclerosis. Am J Clin Nutr 2009; 90(3):647-654. USA	Am J Clin Nutr	2002-2003	Cohort	Men and women	5,316 participants; 45-84 years	53.0/24.28	CVD	WC, HDL cholesterol, blood pressure	Strong
Lara et al., 2019⁴⁹49 Lara KM, Levitan EB, Gutierrez OM, Shikany JM, Safford MM, Judd SE, Rosenson RS. Dietary Patterns and Incident Heart Failure in U.S. Adults Without Known Coronary Disease. J Am Coll Cardiol 2019; 73(16):2036-2045. USA	J Am Coll Cardiol	2003-2007	Cohort	Men and women	16,068 participants; ≥45 years	59.0/33.6	CI	WC, HDL cholesterol, blood pressure, SAH, LDL cholesterol, high fasting glucose, T2DM	Strong
Nettleton et al., 2008³⁶36 Nettleton JA, Steffen LM, Ni H, Liu K, Jacobs DR. Dietary Patterns and Risk of Incident Type 2 Diabetes in the Multi-Ethnic Study of Atherosclerosis (MESA). Diabetes Care 2008; 31(9):1777-1782. USA	Diabetes Care	2002-2003, 2004-2005 and 2005-2007	Cohort	Men and women	5,011 participants; 45-84 years	47.0/24.04	T2DM	CC, HDL cholesterol, blood pressure, triglyceride, LDL cholesterol, fasting glucose	Strong
Liu et al., 2009¹²12 Liu L, Nettleton JA, Bertoni AG, Bluemke DA, Lima JA, Szklo M. Dietary pattern, the metabolic syndrome, and left ventricular mass and systolic function: the Multi-Ethnic Study of Atherosclerosis123. Am J Clin Nutr 2009; 90(2):362-368. USA	Am J Clin Nutr	Between July 2000 and August 2002	Cross-sectional	Men and women	4,601 participants; 45-84 years	53.0/24	MetS	WC, HDL cholesterol, blood pressure, triglyceride, LDL cholesterol, high fasting glucose	Strong
Liu et al., 2013³⁸38 Liu J, Hickson DA, Musani SK, Talegawkar SA, Carithers TC, Tucker KL, Fox CS, Taylor HA. Dietary patterns, abdominal visceral adipose tissue, and cardiometabolic risk factors in African Americans: the Jackson heart study. Obesity 2013; 21(3):644-651. USA	Obesity	September 2000 and March 2004	Cross-sectional	Men and women	1,775 participants; 21-94 years	>50.0/100	MetS	WC, HDL cholesterol, blood pressure, triglyceride, LDL cholesterol, high fasting glucose	Strong
Deshmukh-Taskar et al., 2009⁶6 Deshmukh-Taskar PR, O'Neil CE, Nicklas TA, Yang SJ, Liu Y, Gustat J, Berenson GS. Dietary patterns associated with metabolic syndrome, sociodemographic and lifestyle factors in young adults: the Bogalusa Heart Study. Public Health Nutr 2009; 12(12):2493-2503. USA	Public Health Nutr	1995-1996	Cross-sectional	Men and women	995 participants; 19-39 years	61.0/20	MetS	WC, blood pressure arterial, T2DM (insulin and glucose), HDL cholesterol, triglyceride	Strong
Nettleton et al., 2006⁴⁰40 Nettleton JA, Steffen LM, Mayer-Davis EJ, Jenny NS, Jiang R, Herrington DM, Jacobs DR. Dietary patterns are associated with biochemical markers of inflammation and endothelial activation in the Multi-Ethnic Study of Atherosclerosis (MESA). Am J Clin Nutr 2006; 83(6):1369-1379. USA	Am J Clin Nutr	-	Cross-sectional	Men and women	5,089 participants; 45-84 years	53.0/24	Endothelial inflammation	WC, blood pressure, high serum insulin and glucose, HDL cholesterol, LDL cholesterol	Strong
Davis et al., 2013⁴⁴44 Davis NJ, Schechter CB, Ortega F, Rosen R, Wylie-Rosett J, Walker EA. Dietary patterns in blacks and Hispanics with diagnosed diabetes in New York City's South Bronx. Am J Clin Nutr 2013; 97(4):878-885. USA	Am J Clin Nutr	-	Cross-sectional	Men and women	235 participants; Average age of 56.5 years	71.0/27.2	T2DM	T2DM	Moderate
Delisle et al., 2009⁴¹41 Delisle HF, Vioque J, Gil A. Dietary patterns and quality in West-African immigrants in Madrid. Nutr J 2009; 8:3. Spain	Nutr J	2001	Cross-sectional	Men and women	213 participants; Average age of 36.5 years	61.0/100	Conditions of self-reported CVD	T2DM, SAH, cholesterol, obesity	Moderate
Keding et al., 2011⁴⁶46 Keding GB, Msuya JM, Maass BL, Krawinkel MB. Dietary patterns and nutritional health of women: the nutrition transition in rural Tanzania. Food Nutr Bull 2011; 32(3):218-226. Tanzanian	Food Nutr Bull	2006-2007	Cohort	Women	252 participants; 16-45 years	100.0/100	Obesity and anemia	Overweight (BMI)	Moderate
Boggs et al., 2015³²32 Boggs DA, Ban Y, Palmer JR, Rosenberg L. Higher Diet Quality Is Inversely Associated with Mortality in African-American Women. J Nutr 2015; 145(3):547-554. USA	J Nutr	1995 and 2011	Cohort	Women	37,001 participants; 21-69 years	100.0/100	Mortality by all causes according to BMI	Overweight (BMI)	Strong
Holmes et al., 2018³¹31 Holmes MD, Dalal S, Sewram V, Diamond MB, Adebamowo SN, Ajayi IO, Adebamowo C, Chiwanga FS, Njelekela M, Laurence C, Volmink J, Bajunirwe F, Nankya-Mutyoba J, Guwatudde D, Reid TG, Willett WC, Adami HO, Fung TT. Consumption of processed food dietary patterns in four African populations. Public Health Nutr 2018; 21(8):1529-1537. Nigerian, Tanzanian, South Africa and Uganda	Public Health Nutr	2011	Cross-sectional	Men and women	738 participants; Average age of 38.8 years	60.0/100	Obesity/ overweight	Overweight [BMI)	Weak
Becquey et al., 2010⁴³43 Becquey E, Savy M, Danel P, Dabiré HB, Tapsoba S, Martin-Prével Y. Dietary patterns of adults living in Ouagadougou and their association with overweight. Nutr J 2010; 9:13. Burkina Faso	Nutr J	April/May 2005	Cross-sectional	Men and women	1,072 participants; 15-65 years	52.0/100	Overweight	Overweight (BMI)	Strong
Boggs et al., 2011⁴⁵45 Boggs DA, Palmer JR, Spiegelman D, Stampfer MJ, Adams-Campbell LL, Rosenberg L. Dietary patterns and 14-y weight gain in African American women. Am J Clin Nutr 2011; 94(1):86-94. USA	Am J Clin Nutr	1995 and 2001	Cohort	Women	41,351 participants; 21-54 years	100.0/100	Weight gain	Overweight (BMI)	Strong
Liese et al., 2004²⁹29 Liese AD, Schulz M, Moore CG, Mayer-Davis EJ. Dietary patterns, insulin sensitivity and adiposity in the multi-ethnic Insulin Resistance Atherosclerosis Study population. Br J Nutr 2004; 96(2):973-984. USA	Br J Nutr	1992 and 1994	Cross-sectional	Men and women	980 participants; 40-69 years	55.0/26	Sensitivity to insulin and adiposity	BMI, WC, high glucose and insulin	Strong
Fröhlich et al., 2019³⁰30 Fröhlich C, Garcez A, Canuto R, Paniz VMV, Pattussi MP, Olinto MTA. Obesidade abdominal e padrões alimentares em mulheres trabalhadoras de turnos. Cien Saude Colet 2019; 24(9):3283-3292. Brazil	Ciência & Saúde Coletiva	Between January and April, 2011	Case-control	Women	541 participants: 215 cases and 326 Controls; 18 to 53 years	100/ not white 10.7 (cases) and 13.2 (controls)	Abdominal obesity	WC	Moderate
Silva et al., 2014⁴²42 Silva BDP, Neutzling MB, Camey S, Olinto MT. Dietary patterns and hypertension: a population-based study with women from Southern Brazil. Cad Saude Publica 2014; 30(5):961-971. Brazil	Cad Saúde Pública	2003	Cross-sectional	Women	1,026 participants; 20-60 years	100/ 16.2	SAH	BMI, Blood pressure	Strong
Perozzo et al., 2008³⁹39 Perozzo G, Olinto MT, Dias-da-Costa JS, Henn RL, Sarriera J, Pattussi MP. Associação dos padrões alimentares com obesidade geral e abdominal em mulheres residentes no Sul do Brasil. Cad Saude Publica 2008; 24(10):2427-2439. Brazil	Cad Saúde Pública	2003	Cross-sectional	Women	1,026 participants; 20-60 years	100/ 16,2	Abdominal obesity	BMI, WC	Moderate
Gower et al., 2021³⁷37 Gower BA, Pearson K, Bush N, Shikany JM, Howard VJ, Cohen CW, Tison SE, Howard G, Judd S. Diet pattern may affect fasting insulin in a large sample of black and white adults. Eur J Clin Nutr 2021; 75(4):628-635. USA	Eur J Clin Nutr	Between 2003 and 2007	Cohort	Men and women	13,528 participants; ≥45 years.	57/ 30	High fasting insulin	High fasting insulin, BMI	Strong
Sarfo et al., 2021³³33 Sarfo J, Pawelzik E, Keding GB. Dietary Patterns as Characterized by Food Processing Levels and Their Association with the Health Outcomes of Rural Women in East Africa. Nutrients 2021; 13(8):2866. East Africa	Nutrients	2019	Cross-sectional	Women	1,152 participants; 15-49 years	100/100	Overweight/ obesity	BMI	Moderate
Mukoma et al., 2022³⁵35 Mukoma G, Wrottesley S V, Kagura J, Oni T, Micklesfield L, Norris SA. The relationships between socioeconomic status, dietary knowledge and patterns, and physical activity with adiposity in urban South African women. South African J Clin Nutr 2022; 36(2):56-62. South Africa	SAJCN	2019	Cross-sectional	Women	160 participants; Between 8 and 24 years	100/100	Body adiposity	BMI	Weak

Source	Assessment method of food consump tion	Statistical method to identify dietary patterns	Dietary patterns and characteristics	Category/ pattern scoring	HR/ OR/RR⁶	CI95%⁷	p for the trend
Nettleton et al., 2009⁴⁸	FFQ¹	PCA² (with varimax orthogonal rotation)	1-Dietary pattern fat and processed meat: added fat, processed meat, French fries, and desserts;	Quintile 1 Quintile 5	1.00 1.82	Reference 0.99-3.35	0.100
			2-Dietary pattern vegetables and fish: vegetables, fish, soup, Chinese food, red meat, poultry, and soya;	Quintile 1 Quintile 5	1.00 0.98	Reference 0.54-1.79	0.380
			3-Dietary pattern beans, tomatoes and refined grains: Beans, tomato, refined grains, high-fat dairy products, avocado/guacamole and red meat;	Quintile 1 Quintile 5	1.00 0.8	Reference 0.45-1.42	0.790
			4-Dietary pattern whole grains and fruit: whole grains, fruit, nuts and seeds, green leafy vegetables, and low-fat dairy products.	Quintile 1 Quintile 5	1.00 0.54	Reference 0.33-0.91	0.007
Nettleton et al., 2008³⁶	FFQ	PCA (with varimax orthogonal rotation)	1-Dietary pattern fat and processed meat: added fat, processed meat, French fries and desserts;
			2-Dietary pattern vegetables and fish: vegetables, fish, soup, Chinese food, red meat, poultry and soya;
			3-Dietary pattern beans, tomatoes and refined grains: Beans, tomato, refined grains, high-fat dairy products, avocado / guacamole and red meat;	Quintile 1 Quintile 5	1.00 1.23	Reference 0.85-1.78	0.004
			4-Dietary pattern whole grains and fruit: whole grains, fruit, nuts and seeds, green leafy vegetables and low-fat dairy products.	Quintile 1 Quintile 5	1.00 0.66	Reference 0.47-0.93	0.005
Liu et al., 2009¹²	FFQ	Reduced classification regression	RRR³ dietary pattern: food with high glycemic index (bread / refined grain noodles, white potato and sweet bread), meat with high content of fat, cheese and processed food (French fries, snack food, pizza, ice cream).				<0.001
Liu et al., 2013³⁸	FFQ	PCA	1-“South” pattern: beans and legumes, corn products, fried fish and chicken, margarine and butter, rice and noodles;	Tertile 1 Tertile 3	1.00 2.16	Reference 1.30-3.60	0.004
			2-“Fast food” pattern: sugars and sweetened juices, fast food and snack food;	Tertile 1 Tertile 3	1,00 2.40	Reference 1.40-4.20	0.002
			3-“Prudent” pattern: fruit and vegetables, cold and hot cereals, nuts and seeds.	Tertile 1 Tertile 3	1.00 0.75	Reference 0.50-1.10	0.120
Lara et al., 2019⁴⁹	FFQ	PCA and Factor analysis	1-Convenience pattern: meat, pasta, Mexican dishes, pizza, French fries, Chinese dishes and fast food;	Quartile 1 Quartile 4	1.00 1.21	Reference 0.83-1.77	0.17
			2-Plant-based pattern: cruciferous vegetables and other vegetables, fruit, beans and fish;	Quartile 1 Quartile 4	1.00 0.59	Reference 0.41-0.86	0.004
			3-Sweets/Fat pattern: desserts, bread for breakfast, chocolate, sweets, solid fats and oils and diverse sugar;	Quartile 1 Quartile 4	1.00 0.76	Reference 0.51-1.11	0.240
			4-South pattern: fried food, organ meat, processed meat, eggs, added fat and sugar-sweetened drinks;	Quartile 1 Quartile 4	1.00 1.32	Reference 0.90-1.93	0.240
			5-Alcohol/ salad pattern: wine, liqueur, bear, vegetables and salad dressing.	Quartile 1 Quartile 4	1.00 0.83	Reference 0.59-1.16	0.450
Keding et al., 2011⁴⁶	24HR⁴ (applied for 3 non-consecutive days)	PCA	1-“Traditional coast” pattern: fruit, nuts, starchy plants and fish;
			2-“Purchase ” pattern: bread or cakes, sugar and tea;				0.005
			3-“Traditional-countryside” pattern: cereals, vegetables and the food group oil or fat;
			4-“Pulses” pattern: dried and cooked common red beans, chickpeas, cowpeas, green beans, green peas (dried), pigeon peas and soya;
			5-“Animal products” pattern: products of animal origin, excluding fish.				0.003
Desh-mukh-Taskar et al., 2009⁶	YFQ⁵	PCA and Factor analysis	1-Western dietary pattern: refined grains, French fries, dairy products rich in fat, dishes with cheese, red meat, processed meat, eggs, snack food, sweets and desserts, sugar-sweetened drinks and condiments;		0.93	0.80-1.07	0.070
Desh-mukh-Taskar et al., 2009⁶	YFQ⁵	PCA and Factor analysis	2-Prudent dietary pattern: whole grains, legumes, vegetables, tomatoes, 100%-fruit juice, low-fat dairy products, poultry, soups and salad dressing with low-fat content.		0.93	0.80-1.07	0,350
Davis et al., 2013⁴⁴	FFQ	Factor analysis through PCA	1-Pizza and sweets pattern: pizza, sweets, bread, pasta and fried chicken;
			2-Meat pattern: eggs, processed meat and cultural meat (for instance, goat and oxtail);
			3-Fried food pattern: French fries and fried chicken;
			4-Fruit and vegetable pattern: fresh fruit, non-aquatic vegetables and fish; 5-Caribbean starch pattern: vegetables rich in starch, rice and beans.
Boggs et al., 2015³²	FFQ	Factor analysis	1-Prudent dietary pattern: vegetables and fruit;
Boggs et al., 2015³²	FFQ	Factor analysis	2-Western pattern: red and processed meat, fried food8.	Quintile 1 Quintile 5	1.00 1.10	Reference 0.82-1.46	0.74
Holmes et al., 2018³¹	FFQ	PCA	1-Mixed-diet pattern: non-processed food, such as legumes, fresh fish, cereals, fruit and beans, and, processed food, such as cold meat, salad dressing and canned fish;	Tertile 1 Tertile 3	1.00 0.81	Reference 0.46-1.44	0.950
Holmes et al., 2018³¹	FFQ	PCA	2-Processed diet pattern: salad dressing, margarine, French fries, coffee, canned fish, butter, sweets and refined grains.	Tertile 1 Tertile 3	1.00 3.00	Reference 1.66-5.45	<0.0001
Nettleton et al., 2006⁴⁰	FFQ	PCA	-Fat and processed meat pattern: fats and oils, meat with high content of fat and processed meat, French fries, snack food and desserts;
			2-Vegetables and fish pattern: vegetables, fish and soup;
			3-Beans, tomato and refined grains pattern: legumes, tomato, refined bread, rice, noodles, cheese with high content of fat, cheese and cream sauce, avocado and guacamole;
			4-Whole grains and fruit pattern: whole-grain bread, rice and noodles, fruit, seeds, nuts and peanut butter
Becquey et al., 2010⁴³	Qualitative FFQ	PCA	1-Snack food pattern: food usually consumed between the main meals (déguè, milk, sugar-sweetened drinks, yogurt, bread, fruit…);		1.04	0.95-1.13	0.424
Becquey et al., 2010⁴³	Qualitative FFQ	PCA	2-Modernity pattern: opposite to traditional dishes and sauces (sauces of tô, okra and Sumaúma) and local snack food (peanut, cakes and local drinks) to more modern-type food or preparations (scrambled eggs, chicken, tomato sauce, pasta, cheese, meat, soft drinks, soup, French sauce, hamburger).		1.19	1.03-1.36	0.018
Boggs et al., 2011⁴⁵	FFQ	PCA and Factor Analysis	1-Vegetables/fruit pattern: vegetables, fruit, legumes, fish and whole grain;				0.820
Boggs et al., 2011⁴⁵	FFQ	PCA and Factor Analysis	2-Meat/fried food pattern: red meat, processed meat, French fries, fried chicken and added fat.				0.080
Frank et al., 2014⁴⁷	FFQ and 24HR	Factor analysis through PCA.	1-Shopping dietary pattern sweets and sugar-sweetened drinks, rice, food rich in protein (red meat, poultry, eggs and milk), vegetable oils (vegetable oil and margarine) fruit and vegetables (carrot, lettuce and cucumber);	Quintile 1 Quintile 5	1.00 0.11	Reference 0.06-0.21	<0.001
Frank et al., 2014⁴⁷	FFQ and 24HR	Factor analysis through PCA.	2-Traditional dietary pattern: banana, green leafy vegetables, beans, Garden egg, fish, corn (banku), palm oil, okra and fruit.	Quintile 1 Quintile 5	1.00 3.2	Reference 1.96-5.22	<0.001
Liese et al., 2004²⁹	FFQ	Cluster grouping	1-French fries pattern: whole milk, soft drinks, pastry, cakes, sweets;				0.161
			2-White bread pattern: White bread, tomato, cheese, dried beans, eggs, fats and oils and beer;				0.000
			3-Low-frequency eater pattern: distinguished by the lower daily average intake of food of several groups, which reflected in lesser intake of general energy;				0.003
			4-Fruit and poultry pattern: fruit and fruit juice, poultry, in addition to ice cream and meal substitutes;
			5-Wine pattern: denoted the intake of food groups of mean levels, except wine and mixed drinks, of which a total of 2,3 portions per day were consumed;
			6-Brown bread pattern: brown bread and cereals or rich in fibers, rice, noodles, legumes and also cooked or baked potatoes, low-fat dairy products, fish diet soft drinks and tofu.
Delisle et al., 2009¹	FFQ	Cluster analysis	1-Western pattern: sweet food and drinks, animal fat and diverse/mixed dishes (this food group includes composed dishes as croquettes, soups and sauces);
Delisle et al., 2009¹	FFQ	Cluster analysis	2-Healthier dietary pattern: consumption of milk and dairy products, fish, legumes, fruit and bread.		1.51	0.56-3.48	0.480
Fröhlich et al., 2019³⁰	FFQ	Factor analysis through PCA	1-Animal fat/calorie pattern: consumption of animal fat, jam, bread, potatoes/manioc, coffee, eggs, red meat and sweets;	Quartile 1 Quartile 4	1.00 0.86	Reference 0.49-1.51
			2-Snack food/fast food pattern: consumption of salty and sweet biscuits, cold meats, snack food, soft drinks, fast food, vegetable oil and dairy products;	Quartile 1 Quartile 4	1.00 0.61	Reference 0.36-1.01
			3-Fruit/vegetable pattern: consumption of green vegetables, yellow vegetables, banana, citric fruit, whole cereals, other vegetables, other fruit.	Quartile 1 Quartile 4	1.00 2.26	Reference 1.30-3.93
Silva et al., 2014⁴²	FFQ	RRR	1-Factor 1: cheese, cream, processed meat;	Tertile 1 Tertile 2 Tertile 3	1.30 1.23 1.00	0.89-1.90 0.83-1.81 Reference	0.376
			2-Factor 2: condensed milk, papaya, apple, banana, Orange, pumpkin, leafy vegetables, other vegetables and in natura fruit juice and lesser consumption of processed meat;	Tertile 1 Tertile 2 Tertile 3	0.83 0.62 1.00	0.59-1.19 0.42-0.90 Reference	0.046
			3-Factor 3: whole milk, creams, red meat, industrial mayonnaise and lesser consumption of processed meat.	Tertile 1 Tertile 2 Tertile 3	0.95 0.94 1.00	0.66-1.37 0.66-1.35 Reference	0.940
Perozzo et al., 2008³⁹	FFQ	Factor analysis through PCA	1-Vegetables food pattern: cabbage, kale, cauliflower, Brussel sprout, pumpkin, carrot, orange, broccoli, beets, tomatoes, pods, bananas, papayas, apples, bergamots, and others. green vegetables and biscuits;	HC⁸ LC⁹
			2-Fruit dietary pattern: melon, watermelon, mango, pear, peach, persimmon, grape, lemon, passion fruit, pineapple, ice cream, avocado, guava, kiwi, natural juice and fish;	HC⁸ LC⁹	1.00 1.05	Reference 0.99-1.11	0.070
			3-Nuts/oleaginous dietary pattern: almond, hazelnut, walnut, chestnut, prune, raisin, whole grain pasta, oatmeal, wheat bran, brown sugar, honey, rye bread, whole grain bread, soy, red wine and whole rice);	HC⁸ LC⁹	1.00 0.93	Reference 0.89-0.98	0.088
			4-Bread/cassava/sweet potato dietary pattern: homemade bread, cassava, sweet potatoes, corn, beans, lentils, sugar, lard, whole milk, potatoes, cream, pasta and pork;	HC⁸ LC⁹	1.00 0.98	Reference 0.92-1.03	0.460
			5-Chocolate/sweets dietary pattern: chocolate, candies, desserts, sweets, sour cream, ham, mortadella, salami, pantry, mayonnaise, processed cheese, fried foods, fast food, sweet biscuit, cuca and cake.	HC⁸ LC⁹	1.00 1.03	Reference 0.97-1.09	0.323
Gower et al., 2021³⁷	FFQ	PCA	1-Convenience pattern: ready-made food/fast food;	Quintile 1 Quintile 5	1.00 0.99	Reference 0.82-1.19	0.810
			2-Plant-based pattern: poor in processed and prepared and sugar-sweetened food, and rich in fruit, legumes and cereals;	Quintile 1 Quintile 5	1.00 0.59	Reference 0.49-0.71	<0.0001
			3-Sweets/fat pattern: pastries and other sweets, fat snack food and fried food;	Quintile 1 Quintile 5	1.00 1.36	Reference 1.12-1.65	0.002
			4-Southern pattern: fried food, processed meat and sugar-sweetened drinks;	Quintile 1 Quintile 5	1.00 1.59	Reference 1.32-1.92	<0.0001
			5-Alcohol/salad pattern: alcohol (all types), green salad, and salad dressing.	Quintile 1 Quintile 5	1.00 0.74	Reference 0.62-0.87	<0.0001
Sarfo et al., 2021³³	24HR	PCA	1-Vegetable-based pattern: intake of starchy plants, as cereals, roots and tubercles, as well as legumes and nuts, oils and fats;
			2-Shopping pattern: Highly-processed food;
			3-Mixed pattern: cereals, roots, tubercles, fruit, milk, sugar, sugar-sweetened drinks, legumes;
			4-Vegetarian pattern: based on greenery (lettuce, tomato, cabbage, carrot, cassava leaves, black-eyed bean leaves, cucumber, eggplant, etc.);
Mukoma et al., 2022³⁵	Quanti tative FFQ	PCA	1-Western pattern: sugar, tea and coffee, cooking fats, whole milk, breakfast cereals, red meat, vegetables, soup powder, condiments and sauces, processed meat, whole grain bread and fruit juice;
Mukoma et al., 2022³⁵	Quanti tative FFQ	PCA	2-Mixed pattern: processed meat, red meat, fruits, vegetables, yogurt, rice and noodles, cakes and biscuits, soup powder, condiments and sauces and fruit juice.

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Maria Cecília de Souza Minayo, Romeu Gomes, Antônio Augusto Moura da Silva