Author
|
Year
|
Continent
|
Country
|
Study Design
|
n
|
Main
|
Age range (years)
|
Score/
Methodological quality
|
Survey
|
Variables
|
BMI cut-off points
|
Nº Records
|
Sichieri R. et al[22]
|
2015
|
Americas
|
Brazil
|
Cross-sectional
|
34,003*
(26,862 adults/
elderly)
|
To identify major food group contributors of energy intake.
|
> 10
|
9 (high)
|
Brazilian Household Budget Survey (2008–2009)
|
BMI > 25 kg/m²
Food consumption
|
WHO, 1998
|
2-day Food Record
|
Ferreira R.; Benício M[26]
|
2015
|
Americas
|
Brazil
|
Cross-sectional
|
11,961
|
To determine the influence of reproductive history on the prevalence of
obesity in Brazilian women and effect of socioeconomic variables on the association between parity and excess weight.
|
20–49
|
6 (moderate)
|
PNDS (2006)
|
BMI
|
WHO, 2000
|
-
|
Velasquez-Melendez G.; Mendes M.[36]
|
2015
|
Americas
|
Brazil
|
Cross-sectional
|
34,362
|
To evaluate the prevalence of cardiovascular
health in the Brazilian population.
|
> 18
|
9 (high)
|
PNS (2013)
|
BMI
Food consumption
|
WHO, 1998
|
Markers of food consumption questionnaire
|
Pereira R. et al[23]
|
2014
|
Americas
|
Brazil
|
Cross-sectional
|
34,003*
(26,522 adults/
The elderly)
|
To examine the patterns of consumption of foods high in solid fats and added sugars in the first Brazilian nationally representative individual dietary survey.
|
> 10
|
6 (moderate)
|
Brazilian Household Budget Survey (2008–2009)
|
Consumption of saturated and trans fats
Consumption of added sugar
|
-
|
2-day Food Record
|
Meller F. et al[25]
|
2014
|
Americas
|
Brazil
|
Cross-sectional
|
14,101
|
To evaluate the association between waist circumference
and body mass index of Brazilian
women of childbearing age studied in the National Demographic and Health Survey, in 2006.
|
18–49
|
6 (moderate)
|
PNDS (2006)
|
BMI/CC
|
WHO, 1998
|
-
|
Pavão A. et al[24]
|
2013
|
Americas
|
Brazil
|
Cross-sectional
|
12,324
|
To investigate the association between self-rated health and social and demographic factors, health behavior, and morbidity.
|
> 20
|
7 (moderate)
|
PDSD (2008)
|
BMI
|
WHO, 1998
|
-
|
Bezerra I; Schieri R[21]
|
2011
|
Americas
|
Brazil
|
Cross-sectional
|
33,393
|
To evaluate whether a diversity of healthy foods in a household would
decrease the availability of unhealthy foods and to evaluate the association between a healthy dietary diversity
score and nutritional status among adults.
|
20–65
|
8 (high)
|
Brazilian Household Budget Survey (2002–2003)
|
BMI
Food consumption
|
WHO, 1998
|
7-day Food Record
|
Barr S. et al[31]
|
2016
|
Americas
|
Canada
|
Cross-sectional
|
12,337
|
To examine the association of breakfast consumption, and the type of breakfast consumed, with body mass index and prevalence rates and odds ratios of overweight/obesity among Canadian adults.
|
> 18
|
7 (moderate)
|
Canadian Community Health Survey Cycle 2.2 (2004)
|
Dietary intake
BMI
|
BMI > 25.0 for definition of overweight/obesity in all age groups
|
R24h 1 day
|
Gray-Donald K. et al[34]
|
2000
|
Americas
|
Canada
|
Cross-sectional
|
1,722*
(1,544 adults/elderly)
|
To monitor whether changes in dietary intake have occurred since the last Canadian dietary survey, conducted a generation ago (1970).
|
13–17 and 18–65
|
7 (moderate)
|
Food Habit of Canadians survey (1997–1998)
|
Food consumption
|
-
|
R24h − 1 day (repeated in 30% of the sample)
with the use of models of food portions.
|
Acosta K.[29]
|
2013
|
Americas
|
Colombia
|
Cross-sectional
|
150,733
|
To calculate obesity concentration indices among adults in Colombia.
|
18–64
|
7 (moderate)
|
ENDS (2005) and ENSIN (2010)
|
BMI
|
WHO, 1995
|
-
|
Kordas K. et al[30]
|
2013
|
Americas
|
Colombia
|
Cross-sectional
|
3,267*
(2,612 adults)
|
To investigate the association among iron deficiency (ID), anemia, and weight status among nonpregnant Colombian females aged 13–49 y.
|
13–17 and 18–49
|
7 (moderate)
|
ENSIN (2005)
|
BMI
|
WHO, 1998
|
|
Acosta S. et al[37]
|
2005
|
Americas
|
Cuba
|
Cross-sectional
|
19,519
|
To evaluate the nutritional status of the resident population in the urban area of Cuba and compare evolutionarily the changes experienced in relation to the previous survey.
|
> 20
|
6 (moderate)
|
Segunda Encuesta Nacional sobre Factores de Riesgo y Afecciones Crónicas no Transmisibles de la Población Cubana (2000–2001)
|
BMI
CC
CQ
|
FAO, 1994
WHO, 1998
|
-
|
Ponce X. et al[27]
|
2013
|
Americas
|
Mexico
|
Cross-sectional
|
15,675
|
To characterize the health and nutritional status of the Mexican population in all age
groups.
|
19–59
|
8 (high)
|
ENSANUT (2006)
|
BMI
Food consumption
|
WHO, 1998
|
Semi-quantitative 7-day FFQ
|
Barquera S. et al[28]
|
2010
|
Americas
|
Mexico
|
Cross-sectional
|
14,630
|
To describe the prevalence of hypertension among Mexican adults, and to compare to that observed among Mexican-Americans living in the US.
|
> 20
|
8 (high)
|
ENSANUT (2006)
|
BMI
|
WHO, 1998
|
-
|
Barquera S. et al[35]
|
2009
|
Americas
|
Mexico
|
Cross-sectional
|
33,023
|
To estimate the prevalence of overweight, obesity and central adiposity in Mexico, and to explore trends compared to the previous Mexican National Health Survey and to Mexican-Americans.
|
> 20
|
8 (high)
|
Mexican National Health and Nutrition Survey (2006)
|
BMI
CC
|
WHO, 1998
|
-
|
Melano-Carranza E.[32]
|
2008
|
Americas
|
Mexico
|
Cross-sectional
|
2,029
|
To determine factors associated with failure to adhere to treatment for diagnosed hypertension among a representative sample of older Mexican adults living
in the community.
|
> 65
|
7 (moderate)
|
ENASEM
(2001)
|
BMI
|
Mean BMI
|
-
|
Pisabarro R. et al[33]
|
2009
|
Americas
|
Uruguay
|
Cross-sectional
|
900
|
To evaluate prevalence of obesity, its comorbilities and predisposing factors through the Second
National Survey on Overweight and Obesity in Uruguay
in people between 18 and 65 years, or older, carried out in 2006.
|
18–65 and > 65
|
6 (moderate)
|
ENSO 2
(2006)
|
BMI
|
International Obesity Task Force
|
-
|
Cifelli C. et al[62]
|
2016
|
Americas
|
USA
|
Cross-sectional
|
17,387*
|
To use national survey data to model different dietary scenarios to assess the potential effects of increasing plant-based foods (and concomitantly decreasing animal foods) or dairy foods on macronutrient intake and nutrient adequacy.
|
2–18 and > 19
|
7 (moderate)
|
NHANES
(2007–2010)
|
Food and dietary consumption
|
-
|
R24h 2 days (in person + telephone contact)
|
Kant A. et a[18]
|
2015
|
Americas
|
USA
|
Cross-sectional
|
62,298
|
To examine time trends in the distribution of day’s intake into individual
meal and snack behaviors and related attributes in the United States adult population.
|
20–74
|
9 (high)
|
NHANES
(1971–74, 1976–1980, 1988–1994, 1999–2000, 2001–2002, 2003–2004, 2005–2006, 2007–2008, and 2009–2010)
|
Food consumption of meals and snacks
BMI
|
WHO, 1998
|
R24h 1 day (in paper form, interview by telephone, computer)
|
Guendelman S. et al[20]
|
2013
|
Americas
|
USA
|
Cross-sectional
|
979
|
To examine actual and perceived weight in national cohorts of Mexican-origin adult men in Mexico and the United States (US).
|
20–59
|
7 (moderate)
|
NHANES (2001/2006) and ENSANUT (2006)
|
Calculated BMI and self-perceived BMI
|
WHO, 1998
|
-
|
Tande D. et al[19]
|
2009
|
Americas
|
USA
|
Cross-sectional
|
15,658
|
To describe
relationships between the Health Eating Index and abdominal obesity among adults.
|
> 20
|
7 (moderate)
|
NHANES III (1988–1994)
|
CC
Index of healthy eating
|
-
|
R24h 1 day
|
Bays H. et al[38]
|
2007
|
Americas
|
USA
|
Cross-sectional
|
215,354
|
To explore the relation between body mass index and prevalence of diabetes mellitus, hypertension and dyslipidaemia; examine BMI distributions among patients with these conditions; and compare results from two national surveys.
|
> 18
|
7 (moderate)
|
SHIELD (2004)
NHANES (1999–2002)
|
BMI
|
Adaptation of the 1998 National Heart, Lung and Blood Institute - National Institutes of Health Clinical Guidelines.
|
-
|
Pot G. et al[42]
|
2015
|
Europe
|
England
|
Cohort
|
989
|
To describe changes in food consumption patterns and food availability in an ageing population.
|
36, 43, 53,
60–64
|
8 (high)
|
NSHD
(cohort 1946)
|
Food consumption
|
-
|
Pre-structured 5-day food record
|
Pot G. et al[43]
|
2014
|
Europe
|
England
|
Cross-sectional
|
1,768
|
To study associations
between irregular consumption of energy intake in meals and cardio-metabolic risk factors.
|
53
|
8 (high)
|
NSHD (cohort of 1946 - the year 1999 was used for this study).
|
BMI
Dietary Intake
|
Mean BMI
|
5-day food record
|
Cooper R. et al[45]
|
2014
|
Europe
|
England
|
Cross-sectional
|
2,229*
(1,511 adults/ elderly)
|
To examine the associations of body mass index from age 15 years onwards with low muscle mass, strength, and quality in early old age.
|
15, 20, 26, 36, 43, 53, 60–64
|
6 (moderate)
|
NSHD (data from 1946 cohort)
|
BMI
|
Mean BMI
|
-
|
Whitton C. et al[49]
|
2011
|
Europe
|
England
|
Cross-sectional
|
4,321*
(2,158 adults and elderly)
|
To report dietary intakes and main food sources of fat and fatty acids from the first year of the National Diet and Nutrition Survey rolling programme in the UK.
|
4–64
|
7 (moderate)
|
NDNS 2008–2009
|
Food and dietary consumption
|
-
|
4-day food record
|
Prynne C. et al[44]
|
2009
|
Europe
|
England
|
Cohort
|
4,028
|
To quantify more precisely the meat intake of a cohort of adults in the UK by disaggregating composite meat dishes.
|
43 and 53
|
8 (high)
|
NSHD (cohort of 1946)
|
Ingestion of meat
|
-
|
Pre-structured 5-day food record
|
Tressou J. et al[46]
|
2016
|
Europe
|
France
|
Cross-sectional
|
2,624
|
To explore in details the fatty acids intakes in French adults using the most recent available data.
|
Adults
|
7 (moderate)
|
INCA 2
(2006–2007)
|
Consumption of fish or margarine
|
-
|
7-day Food Record
|
Gazan R. et al[47]
|
2016
|
Europe
|
France
|
Cross-sectional
|
1,918
|
To examine the association between drinking water intake and diet quality, and to analyse the adherence of French men and women to the European Food Safety Authority 2010 Adequate Intake.
|
> 18
|
7 (moderate)
|
INCA 2
(2005–2007)
|
Consumption of food, drinks, and water
|
-
|
7-day Food Record
|
Vernay M. et al[53]
|
2009
|
Europe
|
France
|
Cross-sectional
|
3,115
|
To describe disparities in the prevalence of overweight and obesity across socioeconomic status groups in 18–74 year-old French adults.
|
18–74
|
7 (moderate)
|
ENNS (2006–2007)
|
Food consumption
BMI
Cardiovascular risk
|
WHO, 1998
|
R24h 3 days
|
Gose M. et al[55]
|
2016
|
Europe
|
Germany
|
Cohort
|
1,840*
|
To assess changes in food consumption and nutrient intake in Germany.
|
14–65 and > 65
|
8 (high)
|
NVS II (2005/2007)
NEMONIT (2008–2012/ 2013)
|
Dietary consumption
|
-
|
R24h 2 days
|
Sette S. et al[64]
|
2011
|
Europe
|
Italy
|
Cross-sectional
|
2,830
|
To describe energy and nutrient intakes in Italy.
|
> 18
|
7 (moderate)
|
INRAN-SCAI (2005–2006)
|
Energy, macro, and micronutrients
Alcohol intake
MI
|
Mean BMI
|
self-administered 3-day food record
|
Leclercq C. et al[63]
|
2009
|
Europe
|
Italy
|
Cross-sectional
|
2,831
|
To present the main results of the Italian National Food Consumption Survey INRAN-SCAI 2005–06.
|
> 18
|
8 (high)
|
INRAN-SCAI (2005–2006)
|
Food consumption
BMI
|
Mean BMI
|
self-administered 3-day food record
|
Alkerwi A. et al[50]
|
2015
|
Europe
|
Luxembourg
|
Cross-sectional
|
1,352
|
To examine the association between nutritional awareness and diet quality, as indicated by energy density, dietary diversity and adequacy to achieve dietary recommendations, while considering the potentially important role of socioeconomic status
|
18–69
|
7 (moderate)
|
ORISCAV-LUX
(2007–2008)
|
Food consumption
|
-
|
Semi-quantitative FFQ
|
Alkerwi A. et al[51]
|
2015
|
Europe
|
Luxembourg
|
Cross-sectional
|
1,351
|
To compare the ability of five diet quality indices, namely the Recommendation Compliance Index, Diet Quality Index-International, Dietary Approaches to Stop Hypertension, Mediterranean Diet Score, and Dietary Inflammatory Index, to detect changes in chronic disease risk biomarkers.
|
18–69
|
7 (moderate)
|
ORISCAV-LUX (2007–2009)
|
Food consumption
|
-
|
QFC
|
Sluik D. et al[65]
|
2014
|
Europe
|
Netherlands
|
Cross-sectional
|
2100
|
To investigate associations between alcoholic beverage preference and dietary intake in The Netherlands.
|
19–69
|
7 (moderate)
|
DNFCS
|
Energy intake
Frequency and absolute consumption of alcohol
BMI
|
Mean BMI
|
R24h 2 non-consecutive days
|
Kruizenga H. et al[54]
|
2003
|
Europe
|
Netherlands
|
Cross-sectional
|
7,606
|
To determine the prevalence of disease-related malnutrition in The Netherlands in all ¢elds of medical care and to investigate the involvement of the dietitian in the treatment of malnutrition.
|
> 18
|
8 (high)
|
National Screening on Malnutrition (2001)
|
BMI
|
WHO, 1998
|
-
|
Nissensohn M. et al[41]
|
2017
|
Europe
|
Spain
|
Cross-sectional
|
99,111
|
To compare the average daily consumption of foods and beverages in adults of selective samples of the European Union population to understand the
contribution of these to the total water intake, evaluate if the EU adult population consumes adequate amounts of total water according to the current guidelines, and to illustrate the real water intake in Europe.
|
18–75
|
6 (moderate)
|
ANIBES (Spain − 2013); INRAN-SCAI Dataset (Italy – 2005–2006); NutriNet-Santé Dataset (France – 2009–2010)
|
BMI
CC
Consumption of foods and beverages
|
Mean BMI
|
Italy - semi-structured 3-day diary
France − 3-day food record
Spain − 3-day food record
|
Nissensohn M. et al[39]
|
2016
|
Europe
|
Spain
|
Cross-sectional
|
2,007*
(1,784 adults/ elderly)
|
To quantify the total water and beverage intake, and to explore associations between the types of beverage consumed and energy intake.
|
9–75
|
8 (high)
|
ANIBES (2013)
|
Consumption of foods and beverages
|
-
|
3-days
Food Record (food diary)
(using a digital camera, tablet, interview by phone, or form)
|
Ruiz E. et al[40]
|
2016
|
Europe
|
Spain
|
Cross-sectional
|
2,009*
(1,861 adults/elderly)
|
To analyze dietary macronutrient intake and its main sources according to sex and age.
|
9–75
|
6 (moderate)
|
ANIBES (2013)
|
Consumption of foods and beverages
Dietary Intake
|
-
|
3-day Food Record
|
Ruiz E et al[61]
|
2015
|
Europe
|
Spain
|
Cross-sectional
|
2,009*
(1,861 adults/elderly)
|
To contribute to updating data of dietary energy intake
and its main sources from food and beverages, according to gender and age.
|
9–75
|
6 (moderate)
|
ANIBES (2013)
|
Consumption of energy and nutrients
Food consumption
|
-
|
3-day food record (A three-day dietary record) (with the use of digital camera, tablet, interview by phone, or form)
|
Beltrán-de-Miguel B. et al[52]
|
2015
|
Europe
|
Spain
|
Cross-sectional
|
3,000
|
To assess the intake of the individual components of vitamin A and major dietary sources in the Spaniards using data on food consumption from Spanish National Dietary Intake Survey (2009–2010).
|
18–64
|
6 (moderate)
|
ENIDE
(2009–2010)
|
Consumption of vitamin A
|
|
R24h 1 day
3-day Food Diary
|
Bjermo H. et al[56]
|
2013
|
Europe
|
Sweden
|
Cross-sectional
|
273
|
To examine the body burden of lead, mercury, and cadmium in blood among Swedish adults and the association between blood levels, diet and other lifestyle factors.
|
18–80
|
8 (high)
|
The National Survey Riksmaten (2010–2011)
|
Food and dietary consumption
|
-
|
4-day food record
FFQ foods not widely consumed
|
Meier M. et al[57]
|
2010
|
Europe
|
Switzerland
|
Cross-sectional
|
1,786
|
To assess whether Swiss residents aged 15–24 years follow current nutritional guidelines and whether differences exist according to gender and weight status.
|
15–24
|
9 (high)
|
The Swiss Health Survey (2007)
|
BMI
Food consumption
|
WHO, 1998
|
FFQ
|
Marcenes W. et al[48]
|
2003
|
Europe
|
UK
|
Cross-sectional
|
949
|
To review the major
findings from a large representative and comprehensive national survey in Great Britain to which the numbers of teeth and dentures affected older people’s ease of eating, nutrient intake, nutritional status, and body mass index.
|
> 65
|
6 (moderate)
|
NDNS (1998)
|
BMI
Food and dietary consumption
|
WHO, 1998
|
4-day Heavy food record
|
Lei L. et al[60]
|
2016
|
Oceania
|
Australia
|
Cross-sectional
|
8,202*
(6,326 adults and elderly)
|
To examine the AS and free sugar intakes and the main food sources of AS among Australians.
|
> 02
|
8 (high)
|
NNPAS (2011–2012)
|
BMI
Food consumption
|
WHO, 1998
|
R24h 2 days (in person + telephone contact)
|
Bell L. et al[58]
|
2015
|
Oceania
|
Australia
|
Cross-sectional
|
2,415
|
To identify dietary patterns in Australian
adults, and to determine whether these dietary patterns are associated with metabolic phenotype and obesity.
|
> 45
|
6 (moderate)
|
Australian Health Survey (2011–2013)
|
BMI
CC
Food consumption
|
WHO, 1998
|
R24h 2 days
|
Mohr P. et al[59]
|
2007
|
Oceania
|
Australia
|
Cross-sectional
|
20,527*
|
To identify key predictors of fast-food consumption from a range of demographic, attitudinal, personality and lifestyle variables.
|
> 14
|
6 (moderate)
|
Nielsen Media Research (2004–2005)
|
Food consumption
|
-
|
FFQ fast food
|