Nutrition Label Use Is Related to Chronic Conditions among Mexicans: Data from the Mexican National Health and Nutrition Survey 2016

RESEARCH

Original Research

Nutrition Label Use Is Related to Chronic Conditions among Mexicans: Data from the Mexican National Health and Nutrition Survey 2016 Claudia Nieto, MPH, MSc; Lizbeth Tolentino-Mayo, PhD; Eric Monterrubio-Flores, PhD; Catalina Medina, PhD; Sofia Rincón-Gallardo Patiño, MSc; Rebeca Aguirre-Hernández, PhD; Simón Barquera, PhD ARTICLE INFORMATION Article history: Submitted 9 January 2019 Accepted 22 July 2019

Keywords: Nutrition label Front of package labeling Chronic diseases Nutrients of concern 2212-2672/Copyright ª 2019 by the Academy of Nutrition and Dietetics. https://doi.org/10.1016/j.jand.2019.07.016

ABSTRACT Background Non-communicable diseases, such as obesity, diabetes, and hypertension, can be prevented and treated through a balanced nutrient-rich diet. Nutrition labels have been recognized as crucial to preventing obesity and non-communicable diseases through a healthier diet. Objective Our aim was to examine the association between nutrition label use and chronic conditions (overweight, obesity, previously diagnosed diabetes, and hypertension) among an adult Mexican population. Design This was a cross-sectional study that used data from the Mexican National Health and Nutrition Survey of 2016 (ENSANUT MC 2016). Participants/setting The participants were 5,013 adults aged 20 to 70 years old. Older adults (>70 years), illiterate participants, pregnant women, and participants with implausible blood pressure data were excluded from the sample. The survey was conducted from May to August 2016 in the participants’ households. Main outcome measures We measured chronic conditions (overweight, obesity, previously diagnosed diabetes, and hypertension). Statistical analyses performed Pearson c2 test was used to examine the associations among the use of nutrition labels and sociodemographic characteristics and chronic conditions. Multiple logistic regression was used to determine the association between nutrition label use and chronic conditions adjusting for the effect of confounding variables like sex, age, body mass index, education level, marital status, ethnicity, residence area, region, and socioeconomic status. Results From the total sample, 40.9% (95% CI 38.4% to 43.8%) reported using nutrition labeling. Respondents with overweight or obesity were less likely to use nutrition labels (odds ratio 0.74; P<0.05). Participants who self-reported diabetes had significantly lower odds of nutrition label use than participants who did not report to have diabetes (odds ratio 0.66; P<0.05). Participants having 3 chronic conditions had lower odds of nutrition label use (odds ratio 0.34; P<0.01) relative to having zero chronic conditions. Conclusions This study suggests an association between nutrition label use and chronic conditions (obesity and diabetes). These findings demonstrate that people with obesity, diabetes, and a combination of chronic conditions were less likely to use nutrition labels than people without these conditions. J Acad Nutr Diet. 2019;-(-):---.

I

N MEXICO, 72.5% OF THE POPULATION HAS OVERweight or obesity, 9.4% has diabetes, and 25.5% has hypertension.1-3 In November 2016, the Mexican government called attention to the epidemic of obesity and diabetes among the adult population.4,5 Because there are several nutrition-related diseases that can be prevented and treated with an appropriate diet,6 strong strategies are needed to fight this public health emergency. People with nutrition-related diseases, such as overweight, obesity,

ª 2019 by the Academy of Nutrition and Dietetics.

diabetes, and hypertension, are considered vulnerable groups because they need an individualized diet that does not exceed the limits of nutrients of concern.7,8 Energy, sugar, saturated fat, and sodium have been linked to noncommunicable diseases.9 Since the nutritional transition, the population’s diet has been modified, traditional meals have been replaced with processed and ultra-processed foods high in energy and nutrients of concern.10 A cross-sectional study performed in Mexico found that ultra-processed

JOURNAL OF THE ACADEMY OF NUTRITION AND DIETETICS

1

RESEARCH foods have one of the highest dietary energy contributions (29.8%).11 Another study demonstrated that the sales of ultraprocessed foods are increasing in Latin America.12 Processed and ultra-processed foods mandatorily display at least one type of nutrition labeling; the nutrition labeling can be displayed in the front or the back of the packages to facilitate food choices.13 The nutrition labeling, especially the front of package labeling, has been widely recognized as an effective tool that guides consumers toward healthy food choices.14,15 Nutrition labels assist the population to make healthier food decisions that can positively affect their health outcomes, such as lower energy intake, lower glucose, and lower cholesterol levels.16-18 Some other studies have documented the association between the use of nutrition labeling and improved health behaviors.19-21 Because consumers with chronic diseases usually look for dietary information on the package,19 the nutrition labeling strategy has the potential to modify a population’s food choices. In 2010, the Mexican government mandated nutritional labeling on packaged foods through the Mexican National Act, NOM-051 (Figure).22 At the national level, 40.6% of the Mexicans reported reading nutrition labels displayed on packaged foods and beverages.23 On the other hand, data from the National Health and Nutrition Examination Survey in the United States showed that 61.6% of Americans use labels,24 with a slightly lower percentage among US Latinos (60%).25 Currently, in Mexico and Latin America, it is unknown how people with chronic conditions, such as overweight, obesity, diabetes, and hypertension, use the nutrition labeling displayed on food packaging. Identifying this relationship between use of labels and chronic conditions could lead to better understanding of the impact of food labels among the Mexican population with diverse health conditions. The objective of the present study was to examine the association between nutrition label use and chronic conditions (overweight, obesity, diabetes, and hypertension) among the adult population, using the Mexican National Health and Nutrition Survey of 2016 (ENSANUT MC 2016, by its acronym in Spanish). Our rationale is oriented by the framework of consumer decision making proposed by Grunert and colleagues26 in which awareness is a necessary precursor to understanding food labels. Once labeling is seen and understood, it can influence food choices.

MATERIALS AND METHODS Study Design This was a cross-sectional study that used the information from Mexican adults aged 20 to 70 years that participated in the ENSANUT MC 2016. Data are available on the ENSANUT’s website.27 The ENSANUT is a probabilistic population-based survey with a complex multistage and stratified sampling design, representative of the Mexican population. It is also representative at the national level and for rural and urban areas. The survey was conducted from May to August 2016 to monitor and assess the health and nutrition status of the Mexican population. Informed consent was obtained before interviewing the participants, and all participants provided written informed consent. The ethics committee of the Mexican National Institute of Public Health evaluated and approved the study. 2

JOURNAL OF THE ACADEMY OF NUTRITION AND DIETETICS

RESEARCH SNAPSHOT Research Question: Is nutrition label use associated with chronic conditions (overweight, obesity, previously diagnosed diabetes, and hypertension) among a Mexican population? Key Findings: In this cross-sectional study that included 5,013 adult participants of the Mexican National Health and Nutrition Survey of 2016, the use of the nutrition label was inversely associated with chronic conditions. Participants having three chronic conditions had lower odds of nutrition label use (odds ratio 0.34; P<0.01). Additional descriptions and methods of the ENSANUT MC 2016 are presented elsewhere.3,28

Participants In total, 8,667 participants completed the nutrition labeling questionnaire. People older than 70 years (n¼934), illiterate participants (n¼951), pregnant women (n¼110), and participants with implausible blood pressure data (n¼188) were excluded from the analysis. We excluded older adults (older than 70 years) because it has been reported that this population faces several barriers to shopping and feeding themselves, such as poor vision and dementia.29 Illiterate participants were also excluded because the labeling use requires reading and mathematical skills. Pregnant women were excluded from the analysis because they frequently receive nutritional advice during their pregnancy.30 Of the remaining respondents, only 5,013 had complete information for all relevant sociodemographic variables. These participants represented 50,898,114 Mexicans at the national level.

Nutrition Labeling Questionnaire To assess the nutrition label use and understanding, study participants answered a semi-structured questionnaire with 16 items that explored their perception about the usage and comprehension of nutrition labels displayed on packaged foods and beverages. The questionnaire was adapted and validated from previous studies31 (and Carriedo A, unpublished data, 2014). ENSANUT MC 2016 asked detailed questions about the use of nutrition labeling; however, for the present study, we used the following single question to assess the nutrition label use: “Do you read the nutrition label on packaged foods and beverages when you shop?” with response options: “yes” or “no.” The term read was used interchangeably with use because in the pilot study that validated the tool, we found that if the participant read the label it meant that they used it when shopping for food. In addition, field workers showed a picture of the current nutrition labeling system (Figure), including the Daily Food Guidelines and the Nutrition Facts label displayed in the back of the package.

Anthropometric Measurements Anthropometric measures were obtained by trained staff using the Lohman technique.32 Weight was measured using a Tanita scale with precision of 100 g. Height was measured with a stadiometer of 1-mm precision. Height and weight --

2019 Volume

-

Number

-

RESEARCH

Figure. Mandatory nutrition labeling system implemented in Mexico. (A) Daily Food Guidelines displayed on the front of the package. (B) Nutrition Facts label displayed on the back of the package of food and beverages. measurements (kg/m2) were used to determine body mass index (BMI). To assess nutrition status, we used the World Health Organization criteria to classify adults as normal weight (BMI 18.5 to 24.9), overweight (BMI 25.0 to 29.9), or obese (BMI 30).33

Self-Report of Previously Diagnosed Diabetes Previously diagnosed diabetes was self-reported within ENSANUT MC 2016 using the following question: “Has your doctor ever said you had diabetes or high blood sugar?” Those who responded “yes” were defined as self-reported type 2 diabetes.

Survey Findings of Hypertension and Self-Report of Previously Diagnosed Hypertension Hypertension was defined as having systolic blood pressure >140 mm Hg and/or diastolic blood pressure >90 mm Hg. Blood pressure was measured twice using a digital sphygmomanometer Omron HEM-907 and then averaged. Trained personnel followed American Heart Association procedures.34 Blood pressure was only measured in a subsample. Self-reported hypertension was defined as those that answered “yes” to the question: “Has your doctor ever said you had hypertension or high blood pressure?” Participants were classified as having hypertension if it was measured or self-reported.

Combination of Chronic Conditions Respondents were classified according to the number of conditions: one condition (having overweight, obesity, diabetes, or hypertension), two conditions (overweight and diabetes, obesity and diabetes, overweight and hypertension, obesity and hypertension, or diabetes and hypertension), and three conditions (overweight, diabetes, and hypertension or obesity, diabetes, and hypertension). --

2019 Volume

-

Number

-

Other Covariates Covariates included sociodemographic characteristics and other variables relevant to the use of nutrition labeling. Trained field workers of ENSANUT MC 2016 collected the variables sex, age, education level, marital status, ethnicity, residence area, region, socioeconomic status (SES), and occupation. Age groups were classified as follows: 20 to 39 years old, 40 to 59 years old, and 60 to 70 years old. Educational level was classified according to the maximum degree of studies as elementary education or lower (6 years or less), middle school education (more than 6 years and 9 years or less), and high school education or higher (10 years of education or more). Marital status was collapsed into two categories: married or having a partner and divorced, widowed, or single. Ethnicity was defined as belonging to an ethnic group if the participant spoke an indigenous language. Residence area was defined as rural (locations with <2,500 inhabitants) and urban (locations with 2,500 inhabitants). The country was divided into four regions: North (states of Baja California, Baja California Sur, Coahuila, Chihuahua, Durango, Nuevo León, Sonora, Sinaloa, San Luis Potosí, Tamaulipas, and Zacatecas); Center (states of Aguascalientes, Colima, Guanajuato, Hidalgo, Jalisco, Michoacán, Morelos, Nayarit, Querétaro, and Estado de México); South (states of Campeche, Chiapas, Guerrero, Oaxaca, Puebla, Tlaxcala, Quintana Roo, Tabasco, Veracruz, Yucatán); and Mexico City. An SES index was previously constructed and validated by the Center of Survey Research at the Mexican National Institute of Public Health35 by combining eight variables that assessed the household properties and available services, including construction materials of the floor, ceiling, and walls; sleeping rooms; water accessibility; vehicle ownership; household goods (refrigerator, washing machine, microwave, stove, and boiler); and electrical goods (television, radio, telephone, and computer). The index was divided into tertiles and used as a proxy for low, medium, and high SES. JOURNAL OF THE ACADEMY OF NUTRITION AND DIETETICS

3

RESEARCH Occupation was classified as employee or worker, housewife, and other activities. The term housewife refers to women who manage the household and perform domestic chores.

Data Analysis Descriptive statistics were used to characterize the sample. Pearson c2 test was used to examine the associations among the use of nutrition labels and sociodemographic characteristics, chronic conditions, and the combination of chronic conditions. Logistic regression models were used to test differences between categories of sociodemographic and chronic conditions variables. Simple logistic regression (unadjusted models) was used to evaluate the association between the use of nutrition labels and chronic conditions, the combination of chronic conditions, and sociodemographic characteristics. Model 1 determined the association between nutrition label use and overweight/obesity. Model 2 determined the association between nutrition label use and selfreported diabetes. Model 3 determined the association between nutrition label use and hypertension. Model 4 determined the association between nutrition label use and the combination of chronic conditions. Models 1 to 4 were adjusted by the effect of confounding variables like sex, age, education level, marital status, ethnicity, residence area, region, and socioeconomic status. Models 2 and 3 also controlled for the effect of BMI. A P value <0.05 was considered statistically significant. Some participants had missing values in some chronic conditions so sample weights were adjusted for non-response. The svy command was used to take into account the survey sample weights and the sample design of the ENSANUT MC 2016. Models diagnostics were tested using goodness of fit. All statistical analyses were performed using Stata, version 14.1.36

compared to participants with self-reported diabetes (30.9%; 95% CI 23.5% to 39.5%) (P<0.05). Participants without hypertension also reported higher use of nutrition labels at 42.8% (95% CI 39.8% to 45.8%), while participants with hypertension reported 34.7% (95% CI 27.9% to 42.2%) (P<0.05). When assessing the presence of several chronic conditions, we found that the percentage of people that use nutrition labels decreases as the number of chronic conditions increases; 47.3% (95% CI 41.7% to 53.1%) of adults without chronic conditions use nutrition labels, while only 21.6% (95% CI 12.5% to 34.7%) of individuals with 3 chronic conditions use them (P¼0.01). The unadjusted model indicated that the odds of nutrition label use were lower for people with diabetes compared to non-diabetes (odds ratio [OR] 0.63; 95% CI 0.42 to 0.93). Also, the OR for obesity and hypertension were lower compared to their counterpart (OR 0.73 and OR 0.71, respectively) (Table 2). Model 1 indicated that respondents with overweight or obesity were less likely to use nutrition labels (OR 0.74; P¼0.03) compared to respondents with normal weight. In model 2, participants who self-reported diabetes had significantly lower odds of nutrition label use than participants who did not report to have diabetes (OR 0.66; P¼0.04). In model 3, similar results were found, hypertension was associated with a lower nutrition label use (OR 0.77; P¼0.12), but the association was not statistically significant. In model 4, a tendency was observed for the combination of chronic conditions. The more chronic conditions the lower the probability of using nutrition labels. Participants with three chronic conditions had lower odds of nutrition label use (OR 0.34; P¼0.01) relative to having zero chronic conditions. All models were adjusted by covariates (Table 2).

RESULTS

DISCUSSION

From the total sample (n¼5,013), 40.9% (95% CI 38.4% to 43.8%) reported to use the nutrition labeling. Table 1 shows frequencies of the nutrition label use by sociodemographic characteristics and chronic conditions. Participants who had higher education level (high school or higher) reported more use of the nutrition labeling (47.9%; 95% CI 43.7% to 52.1%) compared to those with lower education level: 34.7% (95% CI 29.4% to 40.3%) for elementary school or lower and 35.5% (95% CI 31.8% to 39.5%) for middle school (P<0.05). Participants who were divorced, widowed, or single reported higher levels of labeling use (46.4%; 95% CI 41.5% to 51.4%) compared to those who were married or had a partner (38.1%; 95% CI 34.8% to 41.5%) (P¼0.01). In addition, 44.5% (95% CI 40.7% to 48.4%) of participants from the highest tertile for SES reported using the labels compared to 33.8% (95% CI 29.1% to 38.9%) from the medium SES (P<0.05). The use of nutrition labels was not significantly different across different categories of ethnicity, residence area, region, and occupation (P>0.05). When assessing nutrition label use across chronic conditions (overweight/obesity, self-reported diabetes, and hypertension), we found significant differences (P0.05). Participants with normal weight had a use of 46.9% (95% CI 41.5% to 52.3%), while participants with overweight or obesity reported a lower usage of 36.2% (95% CI 31.6% to 41.1%) (P<0.05). Participants without diabetes also reported a higher use of nutrition labels (41.5%; 95% CI 38.7% to 44.4%)

The present population-based study is the first one to examine the associations between nutrition label use and chronic conditions among the Mexican population. These findings indicate that a large percentage (59%) of the population do not read the nutrition labels. Participants who were healthy were more likely to use the nutrition labels, while those who had obesity, diabetes, or a combination of chronic conditions were less likely to use nutrition labels, except for participants with hypertension. The use of nutrition labels varies across population subgroups. Literature reports that women and young adults have a higher use of nutrition labels compared to men and older adults (>60 years old).21,37,38 These results are consistent with ours; nevertheless, the differences among categories were not significantly different in our study. Older adults (60 to 70 years) read nutrition labels less. This relation is relevant to explore because the older population is at greater health risk and they have a higher probability of having noncommunicable diseases.39 The present study shows that those participants who are married or live with a partner use the nutrition label less than those who are divorced, widowed, or single. This might be explained by the fact that one partner usually makes the food decisions and the household food shopping. Previous studies have inconclusive findings on nutrition label use in relation to marital status, ethnicity, residence area, and occupation.40,41 Individuals with less

4

JOURNAL OF THE ACADEMY OF NUTRITION AND DIETETICS

--

2019 Volume

-

Number

-

RESEARCH Table 1. Frequency of nutrition label use by sociodemographic characteristics and chronic conditions in participants of the Mexican National Health and Nutrition Survey of 2016 (ENSANUT MC 2016) (n¼5,013)a

Variable

Total

Yes

Nutrition label use, % (95% CI)b

P value

0.17

Sociodemographic characteristics Sex Female

3,313

631

42.96 (38.39-47.66)

Male

1,700

1,245

39.13 (36.17-42.17)

60-70 y

475

158

36.50 (29.38-44.26)

40-59 y

1,825

663

40.36 (35.26-45.68)

20-39 y

2,713

1,055

42.01 (38.01-46.09)

Elementary school or lower

1,427

437

34.65 (29.41-40.29)y

Middle school

1,932

677

35.54 (31.76-39.51)y

High school or higher

1,654

726

47.90 (43.69-52.14)w

3,499

1,268

Age group 0.53

Education <0.001

Marital status Married/partner Divorced/widowed/single

1,514

608

38.07 (34.76-41.50) 46.40 (41.49-51.37)

0.01 w

Ethnicity Indigenous

346

157

49.32 (38.18-60.53)

4,667

1,719

40.63 (37.80-43.54)

Urban

2,796

1,055

41.98 (36.34-45.65)

Rural

2,217

822

40.91 (36.34-45.65)

North

1,161

328

35.52 (30.16-41.27)

Center

1,728

729

45.56 (40.41-50.81)

Non-indigenous

0.15

Residence area 0.98

Region

Mexico City South

699

250

39.42 (32.12-46.08)

1,425

570

40.51 (36.08-45.10)

1,317

501

41.08 (36.44-45.89)

0.06

Socioeconomic status Low

0.01 y

Medium

1,701

588

33.82 (29.08-38.91)

High

1,995

787

44.52 (40.73-48.38)x

Employee/worker

2,695

1,022

Housewife

1,905

696

36.37 (32.52-40.40)

413

158

45.84 (35.53-56.51)

Normal weight

1,208

467

46.90 (41.53-52.34)y

Overweight

1,803

702

41.93 (36.48-47.57)

Obesity

1,750

616

36.19 (31.55-41.11)w (continued on next page)

Occupation

Other activities

41.84 (38.22-45.65)

0.17

Chronic conditions BMIc (n¼4,761)

--

2019 Volume

-

Number

-

0.04

JOURNAL OF THE ACADEMY OF NUTRITION AND DIETETICS

5

RESEARCH Table 1. Frequency of nutrition label use by sociodemographic characteristics and chronic conditions in participants of the Mexican National Health and Nutrition Survey of 2016 (ENSANUT MC 2016) (n¼5,013)a (continued)

Total

Yes

Nutrition label use, % (95% CI)b

P value

No

4,510

1714

41.51 (38.72-44.35)

0.02

Yes

404

119

30.89 (23.45-39.49)w

3,684

1,424

952

305

34.69 (27.90-42.16)w

1,015

392

47.33 (41.66-53.07)yz

Variable Self-reported diabetes (n¼4,914)

Hypertension (n¼4,636) No Yesd

42.78 (39.82-45.80)

0.05

Combinations of chronic conditions (n¼4,608) Zero chronic conditions One chronic condition

41.26 (37.66-44.95)

0.01

z

2,583

1,010

Two chronic conditionse

837

272

37.44 (30.47-44.97)wz

Three chronic conditionsf

173

49

21.57 (12.48-34.65)wxy

a Pearson c2 tests were calculated to determine differences by demographic and health characteristics variables. Logistic regression models were used to test differences between categories. Missing data for BMI, self-reported diabetes, and hypertension variables was due to subsampling. b Data adjusted by survey design. c BMI¼body mass index; calculated as kg/m2. BMI classification: normal weight (18.5 to 24.9), overweight (25.0 to 29.9), and obesity (30).27 d Participants were classified as having hypertension if it was measured (survey finding) or self-reported. e The combinations of two chronic conditions was determined as follows: overweight or obesityþdiabetes, overweight or obesityþhypertension, diabetesþhypertension. f The combination of three chronic conditions was determined as follows: overweight or obesityþdiabetesþhypertension. wxyz Different superscript letters represent statistically significant differences between categories (P<0.05).

educational attainment also report a lower usage of nutrition labels.20,42e45 Literature reports that less educated individuals prefer simple formats that indicate the overall healthiness of food products.46,47 The complex format and lack of understanding of the nutrition label implemented in Mexico, the Daily Food Guidelines, might be one of the reasons why this stratum of the population reported lower usage in the present study. The Daily Food Guidelines provides numeric information about the nutrients of concern referent to cutoff points. This specific format was proven difficult to understand.48,49 Simple formats like the warning labels or the traffic light are reported to be easier to understand and more accurate for making comparisons between products to choose the healthiest.50,51 In the present study, high SES populations had a higher probability of using the nutrition labeling compared to low SES populations, although our results were not statistically significant. These results are consistent with previous investigations undertaken in Hispanics.23,49 Studies have shown that individuals from low SES face barriers for comprehending complex labeling schemes and they also report a lower probability of using them.42,44 The warning labels had proved to be a simple effective format in studies performed in the Latin-American region. Warning labels are displayed on the front of packages for each nutrient that is considered to be present in unhealthy levels. Those labels are understandable by different subgroups, similar to the Mexican population.51-53 Chile has implemented warning labels as a strategy to improve food choices among their population.54 Other countries like Peru and Uruguay have approved the warning label/front of package labeling strategy and are awaiting implementation. 6

JOURNAL OF THE ACADEMY OF NUTRITION AND DIETETICS

Our results are worrisome, given the poor health was associated with a lower likelihood of nutrition label use. Participants within normal weight reported higher use of the nutrition labeling. This may mean that those who are managing their weight are interested in food labels. Another hypothesis is that healthy people may have healthier lifestyles and thus may have higher use of nutrition labels compared to those participants diagnosed with obesity or diabetes. One study that used the National Health and Nutrition Examination Survey data reported similar results regarding obesity. Those who use nutrition labels have lower BMI than those who do not.55 However, when exploring chronic diseases, the majority of studies found that people already diagnosed with chronic diseases tend to check and use more the nutrition label compared to those who are healthy,19,38,45,46 probably because they have been advised by health professionals to follow dietary guidelines.19,56 These results are contradictory to ours, one of the reasons might be that they evaluated the Nutrition Facts label and the present study evaluated the nutrition labeling system, including the Daily Food Guidelines displayed on the front of the package. Regarding hypertension, we did not find statistically significant results, but the study that mentioned that hypertension was associated with frequent label use assessed the Nutrition Facts label.57 Furthermore, the few studies that have examined this relationship were performed in countries like the United States and France.19,38,45,46 We did not find any research performed in Latin America or in low-income countries that explored this association. Mexico is a country with health and economic disparities among the population. Most of the individuals are not exposed to health or nutrition knowledge,58 and not all the population has access to the health care --

2019 Volume

-

Number

-

--

2019 Volume

Table 2. Associations among nutrition label use, chronic conditions (overweight/obesity, diabetes, and hypertension), and the combination of chronic conditions in participants of the Mexican National Health and Nutrition Survey of 2016a Unadjusted Models (n[5,013)

-

b

Model 1 (n[4,762)

Number

P value OR (95% CI)

Model 2 (n[4,916)

P value OR (95% CI)

Model 4 (n[4,610)

-

P value OR (95% CI)

P value OR (95% CI)

P value

—

—

—

—

—

—

—

—

—

0.77 (0.526-1.07) 0.12

—

—

Variable

OR (95% CI)

Overweight or obesity

0.73 (0.55-0.95) 0.02

0.74 (0.57-0.98) 0.03

—

Self-reported diabetes (refc nondiabetic)

0.63 (0.42-0.93) 0.02

—

0.66 (0.45-0.98) 0.04

—

Model 3 (n[4,638)

Hypertension (ref non-hypertensive) 0.71 (0.51-1.00) 0.05

—

—

—

—

Combination of chronic conditions (ref zero chronic conditions)

—

—

—

—

One chronic condition

0.78 (0.59-1.02) 0.07

—

—

—

—

—

—

0.79 (0.60-1.04) 0.09

Two chronic conditions

0.67 (0.45-0.99) 0.04

—

—

—

—

—

—

0.65 (0.44-0.96) 0.03

Three chronic conditions

0.31 (0.15-0.63) 0.002

—

—

—

—

—

—

0.34 (0.16-0.73) 0.01

Age

0.99 (0.99-1.00) 0.50

1.07 (1.01-1.13) 0.03

1.01 (0.99-1.01) 0.26

1.01 (0.99-1.01)

0.25

1.06 (1.00-1.13) 0.06

Male

1.17 (0.94-1.47) 0.17

0.85 (0.68-1.07) 0.18

0.87 (0.69-1.09) 0.23

0.85 (0.67-1.07)

0.18

0.84 (0.66-1.07) 0.15

Body mass index

—

—

0.97 (0.95-0.99) 0.03

0.97 (0.95-1.00)

0.05

—

Sex (ref female) —

—

—

Middle school

1.04 (0.78-1.39) 0.79

1.08 (0.79-1.49) 0.63

1.10 (0.81-1.50) 0.54

1.11 (0.80-1.54)

0.51

1.06 (0.77-1.45) 0.74

High school or higher

1.73 (1.30-2.30) <0.001 1.74 (1.26-2.40) 0.00

1.72 (1.26-2.35) 0.00

1.66 (1.20-2.31)

0.00

1.62 (1.17-2.24) 0.00

1.41 (1.09-1.83) 0.01

1.30 (1.02-1.66) 0.04

1.19 (0.93-1.51) 0.15

1.22 (0.96-1.56)

0.09

1.32 (1.04-1.69) 0.02

0.70 (0.44-1.14) 0.15

0.66 (0.41-1.05) 0.08

0.63 (0.39-1.05) 0.08

0.64 (0.39-1.01)

0.06

0.63 (0.39-1.01) 0.06

0.99 (0.79-1.26) 0.98

0.93 (0.72-1.20) 0.60

0.95 (0.73-1.23) 0.71

0.97 (0.75-1.25)

0.81

0.97 (0.75-1.26) 0.84

Marital status (ref married/partner) Divorced/widowed/single Ethnicity (ref non-indigenous) Indigenous Residence area (ref urban) Rural Region (ref north) Center

1.52 (1.10-2.09) 0.01

1.62 (1.19-2.19) 0.00

1.58 (1.16-2.15) 0.01

1.62 (1.17-2.23)

0.00

1.65 (1.21-2.26) 0.00

Mexico City

1.18 (0.82-1.70) 0.40

1.25 (0.88-1.78) 0.21

1.21 (0.85-1.72) 0.28

1.24 (0.86-1.79)

0.24

1.25 (0.88-1.79) 0.22

South

1.23 (0.90-1.68) 0.20

1.25 (0.91-1.72) 0.16

1.25 (0.92-1.71) 0.15

1.27 (0.92-1.76)

0.14

1.29 (0.93-1.79) 0.12 (continued on next page)

7

RESEARCH

JOURNAL OF THE ACADEMY OF NUTRITION AND DIETETICS

Education (ref elementary school or lower)

8

Data adjusted by survey design. Simple logistic regression (unadjusted models) was used to assess the associations among use of nutrition labels, chronic conditions, and the combination of chronic conditions and sociodemographic characteristics. Logistic models (model 1 to 4) differed in the predictor used (overweight/obesity, self-reported diabetes, hypertension, and the combination of chronic conditions) and were adjusted by the same covariates (age, sex, education, marital status, ethnicity, residence area, region, and socioeconomic status). Models 2 and 3 were also adjusted by body mass index. b OR¼odds ratio. c ref¼reference category.

a

0.75 (0.56-0.99) 0.04

1.03 (0.77-1.37) 0.86 0.77 1.04 (0.78-1.39)

0.03 0.74 (0.55-0.98)

1.05 (0.79-1.39) 0.72 1.03 (0.78-1.36) 0.83 1.15 (0.91-1.46) 0.25

0.74 (0.56-0.97) 0.03 0.72 (0.55-0.95) 0.02 0.74 (0.55-0.98) 0.04 Medium

Socioeconomic status (ref low)

High

P value P value OR (95% CI) P value OR (95% CI) P value OR (95% CI)

Model 4 (n[4,610) Model 3 (n[4,638) Model 2 (n[4,916) Model 1 (n[4,762)

P value OR (95% CI) OR (95% CI) Variable

b

Unadjusted Models (n[5,013)

Table 2. Associations among nutrition label use, chronic conditions (overweight/obesity, diabetes, and hypertension), and the combination of chronic conditions in participants of the Mexican National Health and Nutrition Survey of 2016a (continued)

RESEARCH

JOURNAL OF THE ACADEMY OF NUTRITION AND DIETETICS

system that includes nutritional advice.59 Considering the importance of dietary habits in the management of chronic diseases, the use of nutrition labels among these patients necessitates great accessibility. They should be using nutrition labels to aid in chronic disease prevention; nevertheless, not all of the population is using the current nutrition labeling strategy. Furthermore, the stratum of the population who have chronic conditions have lower education level, which also might have influenced the use of the nutrition label. This is the reason why all models were adjusted by education level. In addition, this scenario is common in a country under economic development, such as Mexico. International evidence points out that consumers tend to look at brands, quality, prices, family influence, and marketing strategies in addition to checking the nutrition label.49,60,61 Evidence has shown that the Mexican population has a high proportion of poverty; therefore, consumers make some decisions based on price.62 Other factors that can explain our results are that people frequently choose foods based on price because socioeconomic characteristics are strong determinants of unhealthy dietary patterns.63,64

Strengths and Limitations of the Study Data for the present study were taken from ENSANUT MC 2016, which is a population-based survey designed to be representative of the Mexican population. The complex survey design permits the results to be generalized to the national level. The food labeling questionnaire was validated31,65; therefore, the results are a reliable estimation as well. The present cross-sectional study was performed in the respondents’ homes according to the ENSANUT MC 2016 methodology.28 Fieldworkers showed pictures of the current nutrition label implemented in the country and asked whether they use the labels. We did not assess what happens in real life when packaged foods are purchased at a selling point or when shopping on a budget. As it was a self-report of the use of nutrition labels, it should be noted that over-reporting might have existed,42,66 however, results are consistent with other studies performed in the same population.23,49 This study did not test comprehension of the labeling; therefore, the self-reported use does not mean that the respondent fully comprehends the nutrition labeling. Selfreported data can potentially incur reporting bias.26 Another limitation for the present study is that a single question was used to assess nutrition label use and that the terms read and use were interchangeably used because in the pilot study participants seem to be using it by reading it. Others studies must be performed with more extensive measures for the use of labels, for example, recent studies used the eye-tracking technique, which measures the use in real time and within real-world settings.67,68 Another aspect to consider in the causal pathway is that consumers have many drivers when purchasing foods, especially deprived groups. The present cross-sectional study is not looking for causality. This is the first step to characterizing the nutrition problem, it cannot explain the causal relationship between nutrition label use and chronic conditions.

Future Considerations and Research Recently, a national non-bias expert committee launched a scientific statement about the front of package labeling in --

2019 Volume

-

Number

-

RESEARCH Mexico.69 The document recommends a labeling system aligned with international recommendations, free of conflict of interest, that is simple and easier to comprehend, such as the warning labels system. This posture may help stakeholders and policy makers create and implement better front of package labeling for Mexico. The present study explores the nutrition labeling that is placed mostly on ultraprocessed and processed foods. Studies have found that such food products are unhealthy, therefore, their intake should not be recommended on a daily basis.70-72 In the future, effective nutrition policies should focus on awareness, understanding, and use of nutrition labeling, along with the promotion of fresh foods and traditional meals.73 Finally, experimental studies that assess purchasing behavior with regard to front of package labeling in developing countries like Mexico are needed.

13.

Ducrot P, Julia C, Méjean C, et al. Impact of different front-of-pack nutrition labels on consumer purchasing intentions. Am J Prev Med. 2016;50(5):627-636.

14.

World Health Organization. Global Action Plan for the Prevention and Control of Noncommunicable Diseases 2013-2020. Geneva: World Health Organization; 2013.

15.

Cecchini M, Warin L. Impact of food labelling systems on food choices and eating behaviours: A systematic review and metaanalysis of randomized studies. Obes Rev. 2016;17(3):201-210.

16.

Crockett RA, Hollands GJ, Jebb SA, Marteau TM. Nutritional labelling for promoting healthier food purchasing and consumption. Cochrane Database Syst Rev. 2011;9.

17.

Hersey JC, Wohlgenant KC, Arsenault JE, Kosa KM, Muth MK. Effects of front-of-package and shelf nutrition labeling systems on consumers. Nutr Rev. 2013;71(1):1-14.

18.

Vyth EL, Hendriksen MA, Roodenburg JC, et al. Consuming a diet complying with front-of-pack label criteria may reduce cholesterol levels: A modeling study. Eur J Clin Nutr. 2012;66(4):510-516.

19.

Lewis JE, Arheart KL, LeBlanc WG, et al. Food label use and awareness of nutritional information and recommendations among persons with chronic disease. Am J Clin Nutr. 2009;90(5): 1351-1357.

20.

Borgmeier I, Westenhoefer J. Impact of different food label formats on healthiness evaluation and food choice of consumers: A randomized-controlled study. BMC Public Health. 2009;9(1):184.

21.

Haidar A, Carey FR, Ranjit N, Archer N, Hoelscher D. Self-reported use of nutrition labels to make food choices is associated with healthier dietary behaviours in adolescents. Public Health Nutr. 2017;20(13): 2329-2339.

22.

NORMA Oficial Mexicana NOM-051-SCFI/SSA1-2010, Especificaciones generales de etiquetado para alimentos y bebidas no alcohólicas preenvasados-Información comercial y sanitaria. 2010:1-31. http://www.economia-noms.gob.mx/normas/noms/2010/051scfissa1 mod.pdf. Accessed September 2, 2019.

23.

Tolentino-Mayo L, Patiño SR, Bahena-Espina L, Ríos V, Barquera S. Conocimiento y uso del etiquetado nutrimental de alimentos y bebidas industrializados en México. Salud Publica Mex. 2018; 60(3).

CONCLUSIONS This study suggests an association between nutrition label use and chronic conditions (obesity and diabetes). Participants who were healthy were more likely to use the nutrition labels, while those who had overweight, obesity, diabetes, or a combination of chronic diseases were less likely to use nutrition labels. Further experimental studies are needed to confirm these results and to evaluate the understanding of nutrition labels in relation to diet-related diseases.

References 1.

Rtveladze K, Marsh T, Barquera S, et al. Obesity prevalence in Mexico: Impact on health and economic burden. Public Health Nutr. 2014;17(1):233-239.

2.

Hernández-Ávila M, Gutiérrez JP, Reynoso-Noverón N. Diabetes mellitus en México. El estado de la epidemia. Salud Publica Mex. 2013;55(1):129-136.

24.

3.

Hernández M, Rivera J, Shamah T, et al. Encuesta Nacional de Salud y Nutrición de Medio Camino. Mexico City, Mexico: Government of Mexico; 2016:1-154.

Ollberding NJ, Wolf RL, Contento I. Food label use and its relation to dietary intake among US adults. J Am Diet Assoc. 2010;110(8):12331237.

25.

Sharif MZ, Rizzo S, Prelip ML, et al. The association between Nutrition Facts label utilization and comprehension among Latinos in two East Los Angeles neighborhoods. J Acad Nutr Diet. 2014;114(12): 1915-1922.

4.

de Salud Secretaría. Declaratoria de Emergencia Epidemiologica EE-32016. Mexico City, Mexico: Secretaría de Salud; 2016.

5.

Secretaría de Salud. Declaratoria de Emergencia Epidemiológica EE4-2016. Mexico City, Mexico: Secretaría de Salud; 2016:1-3.

26.

6.

Popkin BM. Global nutrition dynamics: The world is shifting rapidly toward a diet linked with noncommunicable diseases. Am J Clin Nutr. 2006;84(2). 289-29.

Grunert KG, Wills JM, Fernández-Celemín L. Nutrition knowledge, and use and understanding of nutrition information on food labels among consumers in the UK. Appetite. 2010;55(2):177-189.

27.

Hernández M, Rivera J, Shamah T, et al. Datos de la Encuesta Nacional de Salud y Nutrición 2016, Instituto Nacional de Salud Pública; 2016. https://www.gob.mx/cms/uploads/attachment/file/ 209093/ENSANUT.pdf. 2016. Accessed September 2, 2019. Romero-Martínez M, Shamah-Levy T, Cuevas-Nasu L, et al. Diseño metodológico de la Encuesta Nacional de Salud y Nutrición de Medio Camino 2016. Salud Publica Mex. 2017;59(3):299-305.

7.

World Health Organization. Globalization, Diets and Noncommunicable Diseases. Geneva, Switzerland: World Health Organization; 2003:1-185.

28.

8.

Swinburn BA, Sacks G, Sing K Lo, et al. Estimating the changes in energy flux that characterize the rise in obesity prevalence. Am J Clin Nutr. 2009;89(6):1723-1728.

29.

9.

US Department of Agriculture. Scientific Report of the 2015 Dietary Guidelines Advisory Committee. Advisory Report to the Secretary of Health and Human Services and the Secretary of Agriculture. Washington, DC: US Department of Agriculture; 2015. https://health. gov/dietaryguidelines/2015/guidelines/. Accessed September 2, 2019.

Quigley KK, Warde WD. Factors associated with Oklahoma Older Americans Act nutrition program participants ability to shop, cook, and feed themselves. J Nutr Elder. 2006;25(2):69-82. https://doi.org/ 10.1300/j052v25n02_05. Accessed September 2, 2019.

30.

Farrar D, Butterfield G, Palethorpe R, Jones V, Syson J. Nutrition advice in pregnancy. Pract Midwife. 2013;16(9):13-20. Rincón-Gallardo Patiño S, Carriedo A, Tolentino-Mayo L, Allemandi L, et al. Review of Current Labelling Regulations and Practices for Food and Beverage Targeting Children and Adolescents in Latin America Countries (Mexico, Chile, Costa Rica and Argentina) and Recommendations for Facilitating Consumer. United Nations Children’s Fund. 2016:655. Lohman TG, Roche AF, Martorell R. Anthropometric Standarization Reference Manual. Champlaign, IL: Human Kinetics; 1988.

10.

Rivera J, Barquera S, Campirano F, Campos I, Safdie M, Tovar V. Epidemiological and nutritional transition in Mexico: Rapid increase of non-communicable chronic diseases and obesity. Public Health Nutr. 2002;5(1A):113-122.

11.

Marrón-Ponce JA, Sánchez-Pimienta TG, Louzada ML da C, Batis C. Energy contribution of NOVA food groups and sociodemographic determinants of ultra-processed food consumption in the Mexican population. Public Health Nutr. 2017;21(1):87-93.

12.

--

Moubarac J-C. Ultra-Processed Food and Drink Products in Latin America: Trends, Impact on Obesity, Policy Implications. Washington, DC: Pan American Health Organization; 2015.

2019 Volume

-

Number

-

31.

32. 33.

World Health Organization. Physical Status: The Use and Interpretation of Anthropometry. Report of a WHO Expert Committee. WHO Technical Report Series 854. Geneva, Switzerland: World Health Organization; 1995.

JOURNAL OF THE ACADEMY OF NUTRITION AND DIETETICS

9

RESEARCH 34.

Pickering TG, Hall JE, Appel LJ, et al. Recommendations for blood pressure measurement in humans and experimental animals. Hypertension. 2005;45(1):142-161.

54.

Corvalán C, Reyes M, Garmendia ML, Uauy R. Structural responses to the obesity and non-communicable diseases epidemic: The Chilean Law of Food Labeling and Advertising. Obes Rev. 2013;14:79-87.

35.

Gutiérrez JP. Clasificación socioeconómica de los hogares en la ensanut 2012. Salud Publica Mex. 2013;55(suppl 2):341-346.

55.

Loureiro ML, Yen ST, Nayga RM. The effects of nutritional labels on obesity. Agric Econ. 2012;43(3):333-342.

36.

STATA [computer program]. Version 14.1. College Station, TX: Stata Corp; 2015.

56.

37.

Campos S, Doxey J, Hammond D. Nutrition labels on pre-packaged foods: A systematic review. Public Health Nutr. 2011;14(8):14961506.

Post RE, Mainous AG, Diaz VA, Matheson EM, Everett CJ. Use of the Nutrition Facts label in chronic disease management: Results from the National Health and Nutrition Examination Survey. J Am Diet Assoc. 2010;110(4):628-632.

57.

38.

Su D, Zhou J, Jackson HL, Soliman GA, Huang TT-K, Yaroch AL. A sexspecific analysis of nutrition label use and health, Douglas County, Nebraska, 2013. Prev Chronic Dis. 2015;12:150167.

Elfassy T, Yi S, Eisenhower D, Lederer A, Curtis CJ. Use of sodium information on the Nutrition Facts label in New York City adults with hypertension. J Acad Nutr Diet. 2015;115(2):278-283.

58.

39.

Kennedy BK, Berger SL, Brunet A, et al. Aging: A common driver of chronic diseases and a target for novel interventions. Cell. 2014;159(4):709-713.

Cuevas-Nasu L, Levy TS, Gaona-Pineda E, Rodrguez-Ramrez S, GmezAcosta L. Obesity and lack of nutrition knowledge in Mexico urban areas. FASEB J. 2014;28(1).

59.

40.

Graham DJ, Jeffery RW. Predictors of nutrition label viewing during food purchase decision making: An eye tracking investigation. Public Health Nutr. 2012;15(2):189-197.

Gutiérrez JP, García-Saisó S, Dolci GF, Ávila MH. Effective access to health care in Mexico. BMC Health Serv Res. 2014;14(1):186.

60.

Christoph MJ, An R, Ellison B. Correlates of nutrition label use among college students and young adults: A review. Public Health Nutr. 2015;19(12):1-14.

Katz DL, Doughty K, Njike V, et al. A cost comparison of more and less nutritious food choices in US supermarkets. Public Health Nutr. 2011;14(9):1693-1699.

61.

Dixon H, Scully M, Niven P, et al. Effects of nutrient content claims, sports celebrity endorsements and premium offers on preadolescent children’s food preferences: Experimental research. Pediatr Obes. 2014;9(2):e47-e57.

62.

Alcalde-Rabanal JE, Orozco-Núñez E, Espinosa-Henao OE, Arredondo-López A, Alcayde-Barranco L. The complex scenario of obesity, diabetes and hypertension in the area of influence of primary healthcare facilities in Mexico. PLoS One. 2018;13(1):1-17.  o M, Brug J, Kunst AE. A systematic review of Giskes K, Avendan studies on socioeconomic inequalities in dietary intakes associated with weight gain and overweight/obesity conducted among European adults. Obes Rev. 2010;11(6):413-429.

41.

42.

Grunert KG, Wills JM. A review of European research on consumer response to nutrition information on food labels. J Public Health (Bangkok). 2007;15(5):385-399.

43.

Hawley KL, Roberto CA, Bragg MA, Liu PJ, Schwartz MB, Brownell KD. The science on front-of-package food labels. Public Health Nutr. 2013;16(3):430-439.

44.

Gorton D, Ni Mhurchu C, Chen MH, Dixon R. Nutrition labels: A survey of use, understanding and preferences among ethnically diverse shoppers in New Zealand. Public Health Nutr. 2009;12(9): 1359-1365.

63.

45.

Méjean C, Macouillard P, Péneau S, Hercberg S, Castetbon K. Perception of front-of-pack labels according to social characteristics, nutritional knowledge and food purchasing habits. Public Health Nutr. 2013;16(3):392-402.

64.

Mayen A-L, Marques-Vidal P, Paccaud F, Bovet P, Stringhini S. Socioeconomic determinants of dietary patterns in low- and middleincome countries: A systematic review. Am J Clin Nutr. 2014;100(6):1520-1531.

46.

Mejean C, Macouillard P, Péneau S, Hercberg S, Castetbon K. Consumer acceptability and understanding of front-of-pack nutrition labels. J Hum Nutr Diet. 2013;26(5):494-503.

65.

Steptoe A, Pollard TM, Wardle J. Development of a measure of the motives underlying the selection of food: The Food Choice Questionnaire School, London. Appetite. 1995;25(3):267-284.

47.

Méjean C, Macouillard P, Péneau S, Lassale C, Hercberg S, Castetbon K. Association of perception of front-of-pack labels with dietary, lifestyle and health characteristics. PLoS One. 2014;9(3).

66.

Cowburn G, Stockley L. Consumer understanding and use of nutrition labeling: A systematic review. Public Heal Nutr. 2005;8(1):21-28.

67.

Ares G, Giménez A, Bruzzone F, Vidal L, Antúnez L, Maiche A. consumer visual processing of food labels: Results from an eye-tracking study. J Sens Stud. 2013;28(2):138-153.

68.

Tanner SA, McCarthy MB, O’Reilly SJ. Exploring the roles of motivation and cognition in label-usage using a combined eye-tracking and retrospective think aloud approach. Appetite. 2019;135:146-158.

48.

Stern D, Tolentino L, Barquera S. Revisión del etiquetado frontal: Análisis de las Guías Diarias de Alimentación (GDA) y su comprensión por estudiantes de nutrición en México. Inst Nac Salud Publica. 2013;53:37.

49.

De la Cruz-Góngora V, Torres P, Contreras-Manzano A, et al. Understanding and acceptability by Hispanic consumers of four front-of-pack food labels. Int J Behav Nutr Phys Act. 2017;14(1):28.

69.

Kaufer-Horwitz M, Tolentino-Mayo L, Jáuregui A, et al. Postura sobre un Sistema de Etiquetado Frontal de Alimentos y Bebidas para México: Una Estrategia para la Toma de Decisiones Saludables. Salud Publica Mex. 2018;4:479-486.

50.

Freire WB, Waters WF, Rivas-Mariño G, et al. A qualitative study of consumer perceptions and use of traffic light food labelling in Ecuador. Public Health Nutr. 2016;387:1-9.

70.

Fiolet T, Srour B, Sellem L, et al. Consumption of ultra-processed foods and cancer risk: Results from NutriNet-Sante prospective cohort. BMJ. 2018;360:322.

51.

Arrúa A, MacHín L, Curutchet MR, et al. Warnings as a directive front-of-pack nutrition labelling scheme: Comparison with the Guideline Daily Amount and traffic-light systems. Public Health Nutr. 2017;20(13):2308-2317.

71.

Rauber F, Louzada ML da C, Steele EM, Millett C, Monteiro CA, Levy RB. Ultra-processed food consumption and chronic noncommunicable diseases-related dietary nutrient profile in the UK (2008e2014). Nutrients. 2018;10(5).

52.

Kanter R, Reyes M, Corvalan C. Implementation of the advertising and labelling law in Chile: Early results of impact on food reformulation. Ann Nutr Metab. 2017;71:223.

72.

53.

Khandpur N, de Morais Sato P, Mais LA, et al. Are front-of-package warning labels more effective at communicating nutrition information than traffic-light labels? A randomized controlled experiment in a Brazilian sample. Nutrients. 2018;10(6):1-15.

Martínez Steele E, Baraldi LG, Louzada ML da C, Moubarac J-C, Mozaffarian D, Monteiro CA. Ultra-processed foods and added sugars in the US diet: Evidence from a nationally representative crosssectional study. BMJ Open. 2016;6(3):e009892.

73.

Monteiro C, Cannon G, Moubarac J, Levy RB. Science and politics of nutrition food for thought we should eat freshly cooked meals. BMJ; 2018:361.

10

JOURNAL OF THE ACADEMY OF NUTRITION AND DIETETICS

--

2019 Volume

-

Number

-

RESEARCH AUTHOR INFORMATION C. Nieto, L. Tolentino-Mayo, E. Monterrubio-Flores, and C. Medina are researchers, and S. Barquera is director, Research Center of Nutrition and Health, Mexican National Institute of Public Health, Cuernavaca, Morelos, México. S. Rincón-Gallardo Patiño is a researcher, Human Nutrition, Foods, and Exercise, Virginia Tech, Blacksburg. R. Aguirre-Hernández is a professor, Facultad de Medicina, Universidad Nacional Autónoma de México, Ciudad de México, México. Address correspondence to: Simón Barquera, PhD, Research Center of Nutrition and Health, Mexican National Institute of Public Health, Ave Universidad 655, Col Santa María Ahuacatitlán, Cuernavaca CP 62100, Morelos, Mexico. E-mail: [email protected]

STATEMENT OF POTENTIAL CONFLICT OF INTEREST No potential conflict of interest was reported by the authors.

FUNDING/SUPPORT Mexican National Health and Nutrition Survey of 2016 (ENSANUT MC 2016) was funded by the Ministry of Health. This project was made possible by the generosity of Bloomberg Philanthropies, which funded grant 43003.

ACKNOWLEDGEMENTS The authors would like to thank Martin Romero, PhD, for his help to adjust the sample weights. We also would like to thank Angela Carriedo, PhD, for the long conversations about the comprehension of the nutrition labeling among the Mexican population. We would also like to acknowledge Benjamin Aceves, MPH, MA, for his English editing.

AUTHOR CONTRIBUTIONS C. Nieto drafted the manuscript and performed the statistical analysis, L. Tolentino-Mayo design the questionnaire and provided the methods, E. Monterrubio-Flores and R. Aguirre-Hernández provided statistical support, C. Medina participated in the analysis of data, S. Rincón-Gallardo Patiño gave input for introduction and discussion, and S. Barquera provided the research idea, guided the manuscript, and gave input for discussion.

--

2019 Volume

-

Number

-

JOURNAL OF THE ACADEMY OF NUTRITION AND DIETETICS

11