Association between the diagnosis of diet-related non-communicable diseases and the use of nutritional labeling among Mexican, Mexican American, and non-Mexican American adults: a cross-sectional study from the International Food Policy Study 2021– 2022

Association between the diagnosis of diet-related non-communicable diseases and the use of nutritional labeling among Mexican, Mexican American, and non-Mexican American adults: a cross-sectional study from the International Food Policy Study 2021– 2022 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Association between the diagnosis of diet-related non-communicable diseases and the use of nutritional labeling among Mexican, Mexican American, and non-Mexican American adults: a cross-sectional study from the International Food Policy Study 2021– 2022 Isabel García-Perfecto, Alejandra Contreras-Manzano, Kathia Larissa Quevedo, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7521567/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 06 Dec, 2025 Read the published version in BMC Public Health → Version 1 posted 21 You are reading this latest preprint version Abstract Background Diet-related non-communicable diseases (NCDs) are a leading cause of morbidity and mortality worldwide. Front-of-package warning labels (WLs) and nutrition facts labels (NFLs) have been implemented to help consumers make healthier choices, yet little is known about their use among individuals with NCDs or across different population groups. Understanding these patterns is essential to evaluate labeling policies and their potential to support healthier diets. This study aimed to examine the association between NCD diagnosis and WL use among Mexican adults, and to compare NFL use across Mexican, Mexican American, and non-Mexican American adults. Methods This study used cross-sectional data from the 2021 and 2022 International Food Policy Study. We analyzed self-reported WL and NFL use and NCD diagnoses (diabetes, hypertension, heart disease, high cholesterol, cancer) among adults in Mexico, Mexican Americans, and non-Mexican Americans. Multivariate logistic regression models assessed associations between label use and NCD status, adjusting for sociodemographic and health-related confounders. Results Among 23,951 adults, NFL use was highest among non-Mexican Americans (80.1%) and lowest among Mexicans (69.8%, p < 0.01). NFL use was significantly associated with diabetes and multiple NCDs in non-Mexican Americans. In Mexico, WL use (77.4%) exceeded NFL use. Mexicans with diabetes and high cholesterol reported that “Excess Sugar” and “Excess Sodium” labels were particularly helpful. Conclusions Labeling use varied across populations and NCD status. Findings highlight the importance of promoting interpretive front-of-package labels, especially among individuals with NCDs, to encourage healthier food choices and reduce diet-related disease burden. non-communicable diseases nutrition label front of pack labeling warning labels critical nutrients 1. Background Non-communicable diseases (NCDs) are the leading cause of global mortality, responsible for approximately 15 million deaths annually among adults aged 30–60 years ( 1 ). Mexico and the United States have some of the highest adult obesity prevalences globally (32.2% and 41.6% respectively) ( 2 ), diabetes (12.4% and 14.7%) ( 3 , 4 ), hypertension (29.9% and 47.3%) ( 5 , 6 ) and other diet-relation conditions ( 7 ). The excessive consumption of foods high in critical nutrients (e.g., sugars, fats, sodium) has emerged as a major dietary driver of NCD risk ( 1 ). Interpretive nutrition labels, such as front-of-package warning labels (WLs), aim to reduce unhealthy food consumption and support NCD management by providing simple, prominent information on excessive nutrients ( 8 , 9 ). Nutrition facts labels (NFLs), mandatory in both Mexico and the U.S. ( 10 , 11 ), offer detailed quantitative information but require greater nutritional literacy. U.S. data show NFL usage rates of 61.6% among non-Mexican Americans and 60.0% among Mexican Americans ( 12 ). The 2017 International Food Policy Study (IFPS) survey found that NFL use among US Latinos (57%) was lower than among non-Latino Whites (70%) but higher than among Mexicans (38%) ( 13 ). Recent label policy changes include Mexico's 2020 implementation of octagonal WLs and U.S. NFL updates in 2021 ( 10 , 11 ). Some studies have found lower usage of the NFLs among Mexican Americans compared to non-Latino U.S. residents; a discrepancy that has been attributed to language barriers that hinder interpretation in these subpopulations ( 13 , 14 ). To address the challenges of interpreting and using the NFL, front-of-package labeling systems aim to clearly and concisely communicate nutrition information about packaged foods at the point of product selection and consumption. In 2020, Mexico introduced black octagonal warning labels on the front of the packages that clearly identify foods with "excessive" levels of calories, sugars, sodium, saturated fat, or trans-fat, as well as warnings for products containing non-nutritive sweeteners ( 10 ). Mexican consumers have shown a high level of understanding and acceptance of this labeling system ( 14 ). Some subpopulations may be more prone to using food labels, particularly those who have diet-related illnesses that require closer monitoring of nutritional practices. Previous reports from the United States and Korea have shown that NFL use is associated with healthier food decision-making among individuals with NCDs ( 15 , 16 ). These studies, primarily cross-sectional, suggest that individuals with NCDs are more likely to use NFLs than those without NCDs, suggesting a positive association between NFL use and food decision-making among people with NCDs. In contrast, in Mexico, individuals with three or more NCDs were less likely to use the GDA label (OR: 0.34, p < 0.01) compared with 0, 1, 2 or 3 NCDs ( 17 ). This finding highlights a potential gap in the effectiveness of labeling systems for individuals with multiple NCDs. Different NCDs may require specific types of nutritional information; for example, people with diabetes may seek nutrition information to identify products high in sugar, while people with hypertension may be more concerned about sodium content of foods. Understanding these nuances can help tailor labeling policies to better meet the needs of groups with different diet-related NCDs. This study aimed to assess the association between the diagnosis of diet-related NCDs and the use of WL among Mexican adults, as well as the perceived usefulness of each WL for making healthy food choices. A secondary objective was to compare the association between having NCDs and using NFLs among three groups: non-Mexican American, Mexican American, and Mexican adults. 2. Methods 2.1 Study Design Data was collected through the International Food Policy Study (IFPS), an online survey conducted annually among adults in five countries during November and December. Secondary data analyses were performed using 2021 and 2022 data from adults in the Mexico and United States arms of the IFPS. 2.2 Participants Participants were recruited through the Nielsen Global Consumer Panel and Qualtrics online panels with their partners using non-probability sampling methods with age and sex quotas to obtain a diverse sample that better represented each country's demographic proportions. Eligibility criteria included being 18 years or older and residing in one of the selected countries. Oversampling strategies were implemented differently by country: in Mexico, participants with the lowest education levels were oversampled to improve representation of this group, while in the United States, there was specific oversampling of Mexican American participants. For this study, surveyed adults were categorized into three subpopulations: 1) "Mexicans" (adults residing in Mexico), 2) "Mexican Americans" (US adults of Mexican heritage), and 3) "non-Mexican Americans" (other US ethnic groups including White, Black/African American, Asian/Pacific Islander, Native American, and Hispanic/Latino individuals not of Mexican origin). Participants provided informed consent before the survey and received compensation according to their panel's standard incentive structure (28). Complete IFPS study methods are detailed in the Technical Reports ( 18 ). 2.3 Measures Use of nutrition labels NFL use was assessed with the question, "How often do you use this type of food label when deciding to buy a food product?" accompanied by an image of the country-specific NFL. Response options were categorized as "not used" (never, rarely) and "used" (sometimes, often, all the time). Mexican participants were also asked a similar question regarding the use of WL, accompanied by an image of the ‘excess calories’ WL, with response options identical to those for the NFL. Use of WLs was only assessed in Mexico, and not in USA, because Mexico was the only country with a government endorsed front of package labeling scheme. Perceived usefulness of warning labels Additionally, in 2021, Mexican participants were shown images of all five WLs and asked to evaluate the usefulness of each WL with the question, “Which of these stamps, if any, has been most useful to choose healthier foods: excess calories, excess sugars, excess saturated fats, excess trans fats, excess sodium, none of the stamps have been useful, or all the stamps have been equally useful. Type and number of diagnoses of diet-related non-communicable diseases (NCDs) Participants reported diagnoses for six diet-related NCDs (“Has a doctor, nurse, or other health professional ever told you that you have or had…”), including the following: 1) hypertension or high blood pressure, 2) heart attack (myocardial infarction), 3) angina or coronary disease, 4) diabetes or high blood sugar, 5) high cholesterol, and 6) cancer (excluding skin cancer). Responses for each condition were categorized as “yes” or “no.” The total number of self-reported NCDs was calculated by summing the number of conditions reported by each participant out of 6. This was then classified into three categories: “none,” “1 to 2” and “3 or more.” Covariates Covariates included sociodemographic characteristics and other relevant variables that may affect food choice, food intake, and NCD management. Sociodemographic characteristics included sex at birth, age group (18 to 30, 30, 30 to 39, 40 to 49, 50 to 59, 60 to 69, 70 to 100), and highest educational attainment using country-specific response options, recoded as: “low” (none, preschool, elementary school, middle school, high school, or basic normal education for Mexicans; none, 8th grade or lower, 9th grade, 10th grade, 11th grade, 12th grade or high school for Mexican Americans and non-Mexican Americans); “medium” (career and technical studies for Mexicans; associate degree for Mexican Americans and non-Mexican Americans); and “high” (bachelor's degree or higher for both all respondents). Additionally, participants' subjective income adequacy was assessed with the question, “Thinking about your total monthly income, how difficult or easy is it for you to make ends meet?” (Recoded as easy/very easy or neither easy nor difficult/difficult/very difficult. Body Mass Index (BMI) was calculated from self-reported weight and height, with participants classified into categories of BMI < 24.9 kg/m², 25-29.9 kg/m², ≥ 30 kg/m², or missing. Nutrition knowledge was assessed using the question, “How would you rate your nutrition knowledge?” Responses were categorized as “none” (not at all knowledgeable), “low” (a little knowledgeable, somewhat knowledgeable), or “high” (very knowledgeable, extremely knowledgeable). Several characteristics associated with the use of nutrition labels were also included as covariates and assessed through the following questions: Do you have children (under 18 years old) living in your household? (“yes” or “no”); This question was included because research has shown that the WL system is beneficial for parents when selecting healthy foods for their children ( 14 ). To assess the role in household food shopping, participants were asked, “How much of the food shopping do you do in your household?” Responses were recategorized as "primary shopper” (most) and "non primary shopper” (share equally with other(s); some, but less than other(s), none). Participants who either declined to respond or answered 'don’t know’ questions regarding the use of nutrition labeling (WL and NFL), diagnosis of NCDs, or adjustment covariates were excluded from the analytic sample ( Supplementary Fig. 1 ). 2.4 Statistical Analysis Descriptive statistics characterized the sample based on sociodemographic variables, dietary behaviors, and NCDs by analytic subpopulation of interest (i.e., Mexican, Mexican American, non-Mexican American). To estimate associations between diagnosis of specific NCDs and nutrition label use, adjusted logistic regression models were estimated separately for each subpopulation. These models independently estimated the associations between NFL or WL usage among Mexicans and each NCD diagnosis. Subsequently, a multivariate logistic regression model incorporating the entire analytic sample of non-Mexican Americans, Mexicans, and Mexican Americans was developed to evaluate the association between NFL usage and NCD diagnosis stratified by these subpopulations. Separate models were also developed based on the number of NCDs in each subpopulation. Furthermore, models treating the NCD variable as a continuous variable were run to assess how label usage and the perceived usefulness of warning labels varied with the increasing number of diseases. All models were adjusted for survey year, age, sex at birth, income adequacy, educational level, nutrition knowledge, presence of children under 18 years in the household, household shopping role, and BMI categories to control for potential confounding factors. Post-stratification weights were applied in all analyses. These were constructed using a raking algorithm with census population estimates for each country based on age group, sex, region, education, and ethnicity. Data analyses were performed using STATA version 16.0. Statistical significance was established with a p-value < 0.01 and a 99% confidence interval. 3. Results The final analytic sample across 2021 and 2022 included 23,951 participants; of these 46.5% were non-Mexican Americans (n = 6,710), 25.5% were Mexican Americans (n = 6,101), and 28.0% were Mexicans (n = 11,140) ( Supplementary Fig. 1 ). Table 1 displays the sociodemographic characteristics, nutrition labeling use, and prevalence of NCDs across analytic subpopulations. Table 1 Sociodemographic characteristics, nutrition labeling use, and diagnosis of NCDs by subpopulation. International Food Policy Study 2021 and 2022 (n = 23,951) Mexicans (Mx) (n = 11,140) Mexican Americans (Ma) (n = 6,101) Non-Mexican American (n-Ma) (n = 6,710) p- value Mx vs Ma p- value Mx vs n-Ma p- value Ma vs n-Ma % (99% CI) % (99% CI) % (99% CI) Sociodemographic characteristics Year 2021 48.56 (46.81–50.33) 49.74 (47.85–51.64) 50.99 (49.19–52.79) 0.240 0.013 0.220 2022 51.44 (49.67–53.19) 50.26 (48.36–52.15) 49.01 (41.21–50.81) Sex at birth Male 47.24 (45.49–48.99) 47.18 (45.29–49.08) 48.81 (47.01–50.61) 0.955 0.107 0.109 Female 52.76 (51.01–54.51) 52.82 (50.92–54.71) 51.19 (49.39–52.99) Age group (years) 18 to 30 27.40 (25.97–28.88) 29.16 (27.50-30.88) 15.53 (14.21–16.94) < 0.01 < 0.01 < 0.01 30 to 39 23.68 (22.27–25.15) 27.70 (26.02–29.44) 14.79 (13.55–16.12) 40 to 49 17.90 (16.72–19.14) 20.32 (18.82–21.89) 15.72 (14.46–17.06) 50 to 59 18.94 (17.45–20.53) 13.48 (12.24–14.81) 17.85 (16.52–19.25) 60 to 69 9.47 (8.28–10.80) 7.04 (6.07–8.16) 21.82 (20.37–23.35) 70 to 100 2.61 (1.97–3.44) 2.30 (1.78–2.97) 14.30 (13.12–15.57) Educational level Low 74.88 (73.53–76.19) 65.29 (63.63–66.91) 50.84 (49.04–52.63) < 0.01 < 0.01 < 0.01 Medium 9.70 (8.66–10.86) 10.50 (9.74–11.30) 10.14 (9.40-10.93) High 15.41 (14.58–16.28) 24.22 (22.77–25.72) 39.02 (37.34–40.74) Perceived income adequacy Easy or very easy 10.38 (9.45–11.39) 25.84 (24.25–27.49) 42.45 (40.70-44.22) < 0.01 < 0.01 < 0.01 Neither easy nor difficult 40.22 (38.51–41.95) 38.32 (36.50-40.18) 30.35 (28.69–32.07) Difficult or very difficult 49.40 (47.64–51.17) 35.84 (34.02–37.71) 27.20 (25.60-28.85) Presence of children (under 18) in the household 50.72 (48.96–52.48) 45.26 (43.38–47.15) 25.65 (24.14–27.23) < 0.01 < 0.01 < 0.01 Primary shopping role for household 68.62 (66.98–70.22) 67.25 (65.45–69.01) 70.58 (68.88–72.22) 0.143 0.031 < 0.01 Nutrition knowledge Not at all/ a little knowledgeable 44.21 (42.47–45.98) 33.56 (31.78–35.39) 34.41 (32.70-36.15) < 0.01 < 0.01 0.026 Somewhat knowledgeable 46.19 (44.44–47.95) 42.37 (40.51–44.26) 39.81 (38.06–41.59) Very/extremely knowledgeable 9.60 (8.65–10.63) 24.07 (22.51–25.69) 25.78 (24.25–27.37) BMI (kg/m 2 ) < 24.9 32.31 (30.72–33.95) 30.81 (29.11–32.57) 37.49 (35.76–39.26) < 0.01 < 0.01 < 0.01 25.0 to 29.9 29.43 (27.84–31.07) 28.53 (26.85–30.27) 28.49 (26.91–30.12) ≥ 30 16.73 (15.42–18.12) 28.68 (26.99–30.43) 24.26 (22.74–25.84) Missing 21.53 (20.11–23.03) 11.98 (10.76–13.31) 9.76 (8.72–10.91) Nutrition labeling use Nutrition facts table (NFL) use < 0.01 < 0.01 0.003 Used 69.81 (68.16–71.41) 77.61 (75.99–79.16) 80.13 (78.62–81.56) Not used 30.19 (28.59–31.84) 22.39 (20.84–24.01) 19.87 (18.44–21.38) Front-of-pack warning label (WL) use Used 77.46 (75.96–78.88) - - - - - Not used 22.54 (21.12–24.04) - - Non-Communicable Diseases (NCDs) NCD diagnosis Hypertension 23.50 (21.96–25.11) 25.22 (23.60-26.91) 37.33 (35.60-39.09) 0.051 < 0.01 < 0.01 Heart attack 2.62 (2.10–3.27) 3.08 (2.49–3.81) 5.16 (4.42–6.01) 0.172 < 0.01 < 0.01 Angina 2.66 (2.14–3.29) 3.60 (2.90–4.46) 5.36 (4.62–6.20) 0.010 < 0.01 < 0.01 Diabetes 13.00 (11.74–14.37) 15.17 (13.83–16.60) 16.10 (14.84–17.45) 0.003 < 0.01 0.207 High cholesterol 24.34 (22.78–25.97) 21.16 (19.67–22.74) 32.45 (30.80-34.15) < 0.01 < 0.01 < 0.01 Cancer (excluding skin cancer) 2.03 (1.59–2.59) 4.20 (3.49–5.05) 7.12 (6.25–8.09) < 0.01 < 0.01 < 0.01 Number of NCD diagnoses (categorical) None 58.77 (56.99–60.53) 60.26 (58.38–62.10) 46.96 (45.17–48.77) < 0.01 < 0.01 < 0.01 1 or 2 35.16 (33.45–36.91) 30.69 (28.97–32.46) 39.78 (38.04–41.55) 3 or more 6.07 (5.20–7.07) 9.06 (7.99–10.25) 13.25 (12.08–14.52) The p-value was calculated using Pearson's chi-squared test. In the adjusted independent logistic regression models for each NCD (Table 2 ) it was observed that non-Mexican Americans were 68% more likely to use the NFL when diagnosed with diabetes (AOR 1.68, 99% CI: 1.26–2.24) compared to those without an NCD diagnosis. Furthermore, non-Mexican Americans were 48% more likely to use the NFL when they had 3 or more NCD diagnoses (AOR 1.48, 99% CI: 1.07–2.06) compared to those without any NCD diagnosis. When analyzing the NCD variable as a continuous measure, it was found that for each diagnosed NCD among non-Mexican Americans, the likelihood of using the NFL increased by 16% (AOR 1.16, 99% CI: 1.02–1.32). Table 2 Association between the diagnosis of NCDs and the use of nutritional labeling in Mexican, Mexican American and non-Mexican American adults. IFPS 2021 and 2022 Use of NFL Use of WL Mexican Mexican American Non-Mexican American Mexican n 11,140 6,101 6,710 11,140 AOR (99% CI) AOR (99% CI) AOR (99% CI) AOR (99% CI) Diagnosis of NCDs a None ref ref ref ref Hypertension 1.01 (0.82–1.24) 1.09 (0.86–1.38) 1.09 (0.88–1.35) 1.02 (0.82–1.27) Heart attack 1.18 (0.66–2.08) 1.09 (0.61–1.97) 1.57 (0.96–2.57) 1.11 (0.61–2.02) Angina 1.05 (0.63–1.76) 1.85 (0.94–3.63) 1.57 (0.97–2.53) 1.33 (0.73–2.43) Diabetes 1.02 (0.78–1.34) 1.17 (0.87–1.56) 1.68 (1.26–2.24) 1.13 (0.84–1.52) High cholesterol 0.94 (0.76–1.15) 1.21 (0.95–1.56) 1.06 (0.85–1.31) 0.90 (0.72–1.11) Cancer 1.40 (0.77–2.56) 1.19 (0.71–1.99) 1.14 (0.78–1.69) 1.37 (0.74–2.57) Number of NCD diagnoses (categorical) b None ref ref ref ref 1 to 2 0.92 (0.77–1.11) 1.08 (0.86–1.35) 1.14 (0.91–1.42) 1.00 (0.82–1.22) 3 or more 1.07 (0.72–1.59) 1.37 (0.93–2.02) 1.48 (1.07–2.06) 1.06 (0.69–1.63) Number of NCD diagnoses (continuous) c 1.00 (0.87–1.14) 1.05 (0.91–1.22) 1.16 (1.02–1.32) 1.01 (0.92–1.12) a Independent logistic regression models for each type of NCD and each subpopulation, adjusted for: survey year, sex, age group, educational level, income adequacy, children under 18 in the household, shopping role for household, nutrition knowledge, and BMI categories. b Independent logistic regression models for each subpopulation, adjusted for: survey year, sex, age group, educational level, income adequacy, children under 18 in the household, shopping role for household, nutrition knowledge, and BMI categories. c A logistic regression model was conducted using the NCD variable as a continuous measure. Bold numbers indicate statistical significance (p < 0.01). IFPS = International Food Policy Study (waves 2021 and 2022); NCDs = Non-Communicable Diseases; NFL = Nutrition Facts Label; WL = Warning Label; AOR = Adjusted Odds Ratio; CI = Confidence Interval. Table 3 presents the results of the association between NCD diagnosis and the perceived usefulness of WLs for selecting healthier foods among Mexican adults from the 2021 survey. Adults diagnosed with diabetes were more likely to perceive the "Excess Sugars" WL as the most useful when choosing healthier foods (AOR 1.65, 99% CI: 1.07–2.54) compared to those without any NCD diagnosis. Adults diagnosed with high cholesterol were more likely to perceive the "Excess Sodium" WL as the most useful for choosing healthier foods (AOR 1.89, 99% CI: 1.15–3.12) compared to those without any NCD diagnosis. Regarding the number of diagnosed NCDs among Mexican adults (Table 3 ), those with 1 or 2 diagnoses were more likely to perceive the "Excess Sodium" WL as the most useful for choosing healthier foods (AOR 1.72, 99% CI: 1.08–2.73) compared to those without any NCD diagnoses. Furthermore, adults with 3 or more NCDs were more likely to perceive the "Excess Sugars" WL as the most useful for selecting healthier options (AOR 1.96, 99% CI: 1.04–3.71) compared to individuals without any diagnoses. In the regression model examining the number of NCDs as a continuous variable, it was observed that for each diagnosed NCD among Mexican adults, the likelihood of perceiving the "Excess Sodium" WL (AOR 1.21, 99% CI: 1.02–1.44) and the "Excess Sugars" WL (AOR 1.21, 99% CI: 1.05–1.39) as the most useful when choosing healthier foods increased. Table 3 Association between the type and number of diagnosed NCDs and the perceived usefulness of warning labels for selecting healthier foods among Mexican adults. IFPS 2021 (n = 5,430) Excess calories Excess sodium Excess trans fats Excess sugars Excess saturated fats None of the stamps have been useful All of the stamps have been equally useful AOR (99% CI) AOR (99% CI) AOR (99% CI) AOR (99% CI) AOR (99% CI) AOR (99% CI) AOR (99% CI) Diagnosis of NCDs a None ref ref ref ref ref ref ref Hypertension 0.85 (0.53–1.38) 1.59 (0.97–2.61) 1.14 (0.65–2.03) 1.39 (0.99–1.95) 0.88 (0.58–1.32) 0.90 (0.62–1.31) 0.81 (0.60–1.08) Heart attack 0.86 (0.35–2.15) 0.63 (0.19–2.06) 1.11 (0.71–1.74) 1.22 (0.49–3.05) 0.62 (0.21–1.87) 1.38 (0.62–3.10) 1.00 (0.48–2.07) Angina 0.58 (0.20–1.67) 0.31 (0.09–1.04) 0.82 (0.23–2.92) 1.51 (0.67–3.39) 1.20 (0.49–2.91) 1.00 (0.33–3.01) 1.04 (0.48–2.25) Diabetes 0.81 (0.41–1.62) 1.44 (0.75–2.77) 0.55 (0.23–1.29) 1.65 (1.07–2.54) 0.53 (0.27–1.04) 0.97 (0.59–1.60) 1.01 (0.69–1.47) High cholesterol 0.64 (0.39–1.06) 1.89 (1.15–3.12) 1.17 (0.68–2.01) 1.34 (0.96–1.87) 0.79 (0.51–1.22) 0.80 (0.54–1.17) 0.98 (0.74–1.30) Cancer 1.10 (0.26–4.66) 0.32 (0.07–1.40) 1.15 (0.37–3.56) 1.16 (0.45-3.00) 0.57 (0.15–2.10) 1.45 (0.48–4.40) 1.01 (0.43–2.38) Number of NCD diagnoses (categorical) b None ref ref ref ref ref ref ref 1 or 2 0.72 (0.48–1.10) 1.72 (1.08–2.73) 1.50 (0.93–2.43) 1.25 (0.93–1.67) 0.83 (0.57–1.20) 0.93 (0.66–1.30) 0.87 (0.67–1.11) 3 or more 0.88 (0.34–2.31) 1.59 (0.64–3.39) 0.70 (0.24–2.06) 1.96 (1.04–3.71) 0.65 (0.26–1.62) 0.80 (0.37–1.74) 0.82 (0.46–1.46) Number of NCD diagnoses (continuous) c 0.85 (0.66–1.09) 1.21 (1.02–1.44) 1.00 (0.82–1.21) 1.21 (1.05–1.39) 0.85 (0.69–1.04) 0.95 (0.80–1.14) 0.96 (0.84–1.09) a Independent logistic regression models for each type of NCD and each warning label, adjusted for: survey year, sex, age group, educational level, income adequacy, children under 18 in the household, shopping role for household, nutrition knowledge, and BMI categories. b Independent logistic regression model for each warning label, adjusted for: survey year, sex, age group, educational level, income adequacy, children under 18 in the household, shopping role for household, nutrition knowledge, and BMI categories. c A logistic regression model was conducted using the NCD variable as a continuous measure. IFPS = International Food Policy Study (waves 2021 and 2022); NCDs = Non-Communicable Diseases, AOR = Adjusted Odds Ratio, CI = Confidence Interval Bold numbers indicate statistical significance at a p-value < 0.01. 4. Discussion This study explored the use of the NFL and WLs across Mexicans, Mexican Americans, and non-Mexican Americans, with a focus on differences by NCD diagnosis. While a general trend of increased NFL use with more NCDs was observed, statistically significant differences were found only among non-Mexican Americans, particularly those with diabetes or three or more NCDs. This supports previous evidence suggesting that individuals with chronic conditions have greater nutrition awareness due to more frequent healthcare interactions, including dietary counseling ( 15 , 19 – 21 ). One study from the ENSANUT 2016 found that Mexican adults with hypertension, diabetes, or three or more NCDs tended to use the GDA front-of-package labeling system less than those without diagnoses ( 17 ). Additionally, ENSANUT 2018 data showed that individuals with NCDs were more likely to read the NFL than the GDA ( 22 ). This trend may be explained by the complexity of the GDA labeling system, which required nutritional knowledge, time, and mathematical calculations for proper use, making it difficult for most consumers to understand ( 22 – 25 ). In contrast, our findings showed that WL use (77.5%) exceeded NFL use (69.8%) among Mexicans, and no significant differences were found in WL use by NCD status. This suggests that WLs are widely adopted regardless of diagnosis ( 14 ) regardless of NCD status. Supporting this, a prior Mexican study found no significant variation in WL use among those with diabetes or hypertension ( 26 ). Previous studies in adult populations have reported that WLs encourage the selection of foods with lower amounts of critical nutrients ( 9 ). While our findings did not support the hypothesis that individuals with NCDs generally use WLs more frequently due to a heightened interest in avoiding excessive levels of critical nutrients to better manage their conditions ( 8 ), we observed a notableassociation when analyzing the perceived usefulness of WLs related to the critical nutrient to the diagnosed NCD. For instance, individuals with diabetes were more likely to consider the "Excess sugars" label to be most useful when choosing healthy foods, and those with high cholesterol were more likely to find the "Excess sodium" label as most useful. Additionally, as the number of diagnosed NCDs increased, so did the likelihood of considering these two labels as the most useful for making informed food choices. This suggests a heightened awareness among individuals with NCDs regarding the importance of certain critical nutrients in the onset and progression of these diseases. Similarly, our study found that among the Mexican population, the likelihood of considering the "Excess sodium," "Excess trans-fat," and "Excess sugars" WLs as useful doubled with an increasing number of NCDs. These findings align with evidence that warning label-type systems provide interpretative elements that quickly convey the nutritional quality of products, helping consumers choose those considered more beneficial for their health ( 27 ). Experimental studies conducted in various countries have shown that WLs enhance consumers' ability to understand nutrition information and discourage the selection of products high in nutrients linked to NCDs ( 28 – 30 ). Consistent with our findings, previous research based on 2017 IFPS data has shown that the overall U.S. population reports higher use of NFLs (70.00% vs 80.13% in our study) compared to the Mexican population (38.00% vs 69.81% in our study) and the U.S. Latino population (57.00% vs 77.61% in our study) ( 13 ). The greater use of NFLs among Americans could be attributed to the fact that NFLs is the primary tool available for obtaining nutrition information on packaged products, as there is no mandatory front-of-package labeling system in the United States ( 31 ). Conversely, Mexico’s recently implemented WL system might partly explain the lower use of NFLs in this population compared to subpopulations residing in the United States. However, an increase in NFL use has been observed in Mexico in recent years compared to the pre-implementation stage of the WL system ( 32 ). Despite these trends, further data are needed to determine why NFL use remains higher in the United States compared to Mexico. One of the study's main strengths is the large sample size, including NFL use data collected over two years, which allowed for rigorous statistical analyses. However, certain limitations should be acknowledged. Firstly, although oversampling of low education populations in Mexico and weighting techniques was applied to enhance representativeness, participant recruitment relied on non-probabilistic sampling, limiting generalizability to the national level. Additionally, the cross-sectional design of our study prevents causal inferences between nutrition labels use and NCD presence. Furthermore, data on years since diagnosis and adherence to medical or nutritional treatment were not collected. These factors should be considered when interpreting our results, as they may influence both nutritional label use and NCD management. Conclusions In conclusion, our findings highlight the potential of food labeling as an essential tool for individuals with health conditions. This underscores the need to promote the use of interpretive labels, such as the WLs, among populations with NCDs to support informed food choices that can contribute to both prevention and effective management of these conditions. Abbreviations AOR: Adjusted odds ratio BMI: Body mass index CI: Confidence interval ENSANUT: Encuesta Nacional de Salud y Nutrición GDA: Guideline daily amounts IFPS: International Food Policy Study NFL: Nutrition facts label NCD: Non-communicable disease NCDs: Non-communicable diseases NIH: National Institutes of Health OR: Odds ratio U.S.: United States WL: Warning label WLs: Warning labels Declarations Ethics approval and consent to participate The study received ethical approval from the Research Ethics Committee at the University of Waterloo (REB #30829), the Institutional Review Board at the University of South Carolina, and the Research Ethics Committee at the National Institute of Public Health in Mexico. All participants provided informed consent prior to participation. Availability of data and materials The datasets analyzed during the current study are not publicly available. Data are available from the International Food Policy Study (contact: Dr. Christine White, University of Waterloo) upon reasonable request and with permission from the study team. Competing interests The authors declare that they have no competing interests. Funding Funding for the International Food Policy Study was provided by a Canadian Institutes of Health Research (CIHR) Project Grant (PJT162167), with additional support from the National Institute of Diabetes and Digestive and Kidney Disorders of the National Institutes of Health (NIH) (R01 DK128967). The content is solely the responsibility of the authors and does not necessarily represent the official views of the CIHR or NIH. Authors' contributions Isabel García-Perfecto: Formal analysis, Investigation, Methodology, Writing – original draft. Alejandra Contreras-Manzano: Resources, Formal analysis, Methodology, Supervision, Writing – review & editing. Kathia Larissa Quevedo: Methodology, Supervision, Writing – review & editing. Christine M. White: Funding acquisition, Writing – review & editing. Lana Vanderlee: Writing – review & editing. Rachel E. Davis: Supervision, Writing – review & editing. Cecilia I. Oviedo-Solís: Supervision, Writing – review & editing. James F. Thrasher: Supervision, Writing – review & editing. Simón Barquera: Writing – review & editing. David Hammond: Writing – review & editing. Claudia Nieto: Writing – review & editing. Dai Fang: Writing – review & editing. Alejandra Jáuregui: Supervision, Writing – review & editing. Declaration of generative AI and AI-assisted technologies in the writing process During the preparation of this work, the author(s) used DeepL (OpenAI) to improve the readability and language of the manuscript, including translation into English. After using this tool, the author(s) carefully reviewed and edited the content as needed and take(s) full responsibility for the content of the published article. Data Availability The datasets analyzed during the current study are not publicly available. Data are available from the International Food Policy Study (contact: Dr. Christine White, University of Waterloo) upon reasonable request and with permission from the study team. References Organización Mundial de la Salud. Enfermedades no transmisibles [Internet]. 2022 [cited 2023 Oct 2]. Available from: https://www.who.int/es/news-room/fact-sheets/detail/noncommunicable-diseases#:~:text=Cada%20a%C3%B1o%2C%2017%20millones%20de,de%20ingresos%20bajos%20y%20medianos Global Obesity Observatory. Ranking (% obesity by country) [Internet]. 2024 [cited 2024 Sep 19]. Available from: https://data.worldobesity.org/rankings/ Basto-Abreu A, Reyes-Garcia A, Stern D, Torres-Ibarra L, Rojas-Martínez R, Aguilar-Salinas CA, et al. Cascadas de tamizaje y atención de la diabetes tipo 2 en México. Salud Publica Mex. 2024;66(4):528–36. U.S. Centers for Disease Control and Prevention. National Diabetes Statistics Report [Internet]. 2024 [cited 2024 Sep 19]. Available from: https://www.cdc.gov/diabetes/php/data-research/index.html Campos-Nonato I, Oviedo-Solís C, Hernández-Barrera L, Márquez-Murillo M, Gómez-Álvarez E, Alcocer-Díaz L, et al. Detección, atención y control de hipertensión arterial. Salud Publica Mex. 2024;66(4):537–46. U.S. Centers for Disease Control and Prevention. High Blood Pressure Facts [Internet]. 2022 [cited 2024 Sep 19]. Available from: https://www.cdc.gov/high-blood-pressure/data-research/facts-stats/index.html Elder JP. Mexico and the USA: the world’s leaders in the obesity epidemic. Salud Publica Mex. 2013;55:355. Organización Panamericana de la Salud. El etiquetado frontal como instrumento de política para prevenir enfermedades no transmisibles en la Región de las Américas [Internet]. 2020 [cited 2023 Aug 9]. Available from: https://iris.paho.org/bitstream/handle/10665.2/53013/OPSNMHRF200033_spa.pdf?sequence=5&isAllowed=y Kaufer-Horwitz M, Tolentino-Mayo L, Jáuregui A, Sánchez-Bazán K, Bourges H, Martínez S et al. Sistema de etiquetado frontal de alimentos y bebidas para México: una estrategia para la toma de decisiones saludables. salud publica mex. 2018;60(4). Diario Oficial de la Federación. MODIFICACIÓN a la Norma Oficial Mexicana NOM-051-SCFI/SSA1-2010, Especificaciones generales de etiquetado para alimentos y bebidas no alcohólicas preenvasados-Información comercial y sanitaria, publicada el 5 de abril de 2010. [Internet]. 2020 [cited 2023 Sep 20]. Available from: https://www.dof.gob.mx/normasOficiales/8150/seeco11_C/seeco11_C.html U.S. Food and Drug administration. What’s on the Nutrition Facts Label [Internet]. 2024 [cited 2024 Apr 4]. Available from: https://www.fda.gov/food/nutrition-facts-label/whats-nutrition-facts-label 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):1233–7. Nieto C, Jáuregui A, Contreras-Manzano A, Arillo-Santillan E, Barquera S, White CM, et al. Understanding and use of food labeling systems among Whites and Latinos in the United States and among Mexicans: Results from the International Food Policy Study, 2017. Int J Behav Nutr Phys Activity. 2019;16(1):87. Instituto Nacional de Salud Pública. Encuesta Nacional de Salud y Nutrición 2021 sobre COVID-19. Resultados Nacionales [Internet]. 2022 [cited 2022 Dec 26]. Available from: https://ensanut.insp.mx/encuestas/ensanutcontinua2021/doctos/informes/220804_Ensa21_digital_4ago.pdf 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):628–32. Park SG, Kim HJ, Kwon YM, Kong MH. Nutrition Label Use and Its Relation to Dietary Intake among Chronic Disease Patients in Korea: Results from the 2008–2009 Fourth Korean National Health and Nutrition Examination Survey (KNHANES-IV). Korean J Health Promotion. 2014;14(4):131. Nieto C, Tolentino-Mayo L, Monterrubio-Flores E, Medina C, Patiño SRG, Aguirre-Hernández R et al. Nutrition Label Use Is Related to Chronic Conditions among Mexicans: Data from the Mexican National Health and Nutrition Survey 2016. J Acad Nutr Diet [Internet]. 2020 May [cited 2023 Mar 11];120(5):804–14. Available from: https://pubmed.ncbi.nlm.nih.gov/31585829/ International Food Policy Study. International Food Policy Study. Methods [Internet]. 2023 [cited 2023 Oct 25]. Available from: https://foodpolicystudy.com/methods/ Limbu YB, McKinley C, Gautam RK, Ahirwar AK, Dubey P, Jayachandran C. Nutritional knowledge, attitude, and use of food labels among Indian adults with multiple chronic conditions. Br Food J. 2019;121(7):1480–94. Hong Swoo, Oh SW, Lee C, Kwon H, Hyeon Jhyeon, Gwak Jseop. Association between Nutrition Label Use and Chronic Disease in Korean Adults: The Fourth Korea National Health and Nutrition Examination Survey 2008–2009. J Korean Med Sci. 2014;29(11):1457. Lewis JE, Arheart KL, LeBlanc WG, Fleming LE, Lee DJ, Davila EP, et al. Food label use and awareness of nutritional information and recommendations among persons with chronic disease. Am J Clin Nutr. 2009;90(5):1351–7. Tolentino-Mayo L, Sagaceta-Mejía J, Cruz-Casarrubias C, Ríos-Cortázar V, Jauregui A, Barquera S. Comprensión y uso del etiquetado frontal nutrimental Guías Diarias de Alimentación de alimentos y bebidas industrializados en México. Salud Publica Mex. 2020;62(6):786–97. Organización P, de la Salud. Organización Mundial de la Salud. Estudio de políticas sobre el etiquetado nutricional frontal en las Américas: Evolución y resultados [Internet]. 2022 [cited 2024 Mar 22]. Available from: https://www.paho.org/es/documentos/estudio-politicas-sobre-etiquetado-nutricional-frontal-americas-evolucion-resultados Dalia S, Lizbeth T. Barquera Simón. Revisión del etiquetado frontal: análisis de las Guías Diarias de Alimentación (GDA) y su comprensión por estudiantes de nutrición en México. 2011 [cited 2023 Aug 10]; Available from: https://elpoderdelconsumidor.org/wp-content/uploads/2015/07/Etiquetado-Evaluaci%C3%B3n-GDA-por-Barquera-y-col.pdf Vargas-Meza J, Jáuregui A, Contreras-Manzano A, Nieto C, Barquera S. Acceptability and understanding of front-of-pack nutritional labels: an experimental study in Mexican consumers. BMC Public Health. 2019;19(1):1751. Montes de Oca-Juárez O, Fernández-Villa JM, González-Lara M, García-Peña C. Uso y comprensión del etiquetado nutricional en personas mayores mexicanas: un estudio secundario de la Encuesta Nacional de Salud y Nutrición (ENSANUT 2021). Gac Med Mex. 2024;160(3). Ares G, Antúnez L, Curutchet MR, Giménez A. Warning labels as a policy tool to encourage healthier eating habits. Curr Opin Food Sci. 2023;51:101011. Cabrera M, Machín L, Arrúa A, Antúnez L, Curutchet MR, Giménez A, et al. Nutrition warnings as front-of-pack labels: influence of design features on healthfulness perception and attentional capture. Public Health Nutr. 2017;20(18):3360–71. Song J, Brown MK, Tan M, MacGregor GA, Webster J, Campbell NRC, et al. Impact of color-coded and warning nutrition labelling schemes: A systematic review and network meta-analysis. PLoS Med. 2021;18(10):e1003765. Taillie LS, Hall MG, Popkin BM, Ng SW, Murukutla N. Experimental Studies of Front-of-Package Nutrient Warning Labels on Sugar-Sweetened Beverages and Ultra-Processed Foods: A Scoping Review. Nutrients. 2020;12(2):569. The Food Industry Association. Facts up front. GMA-FMI Voluntary Front-of-Pack Nutrition Labeling System [Internet]. 2012 [cited 2024 Apr 3]. Available from: https://www.fmi.org/docs/health-and-wellness/nk_style_guide_for_implementers-2012.pdf?sfvrsn=2 Acton RB, Rynard VL, Adams J, Bhawra J, Cameron AJ, Contreras-Manzano A, et al. Awareness, use and understanding of nutrition labels among adults from five countries: Findings from the 2018–2020 International Food Policy Study. Appetite. 2023;180:106311. Additional Declarations No competing interests reported. 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16:14:05","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1668001,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7521567/v1/ef6b048f-73ca-43bf-83ab-a650d9c95db4.pdf"},{"id":92025891,"identity":"5dbabda1-0b2f-4c88-9a5f-849cdb8c1ccd","added_by":"auto","created_at":"2025-09-23 18:55:04","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":22778,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-7521567/v1/80c19b954f3d90eff1755305.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association between the diagnosis of diet-related non-communicable diseases and the use of nutritional labeling among Mexican, Mexican American, and non-Mexican American adults: a cross-sectional study from the International Food Policy Study 2021– 2022","fulltext":[{"header":"1. Background","content":"\u003cp\u003eNon-communicable diseases (NCDs) are the leading cause of global mortality, responsible for approximately 15\u0026nbsp;million deaths annually among adults aged 30\u0026ndash;60 years (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Mexico and the United States have some of the highest adult obesity prevalences globally (32.2% and 41.6% respectively) (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e), diabetes (12.4% and 14.7%) (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e), hypertension (29.9% and 47.3%) (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e) and other diet-relation conditions (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). The excessive consumption of foods high in critical nutrients (e.g., sugars, fats, sodium) has emerged as a major dietary driver of NCD risk (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eInterpretive nutrition labels, such as front-of-package warning labels (WLs), aim to reduce unhealthy food consumption and support NCD management by providing simple, prominent information on excessive nutrients (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Nutrition facts labels (NFLs), mandatory in both Mexico and the U.S. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e), offer detailed quantitative information but require greater nutritional literacy. U.S. data show NFL usage rates of 61.6% among non-Mexican Americans and 60.0% among Mexican Americans (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). The 2017 International Food Policy Study (IFPS) survey found that NFL use among US Latinos (57%) was lower than among non-Latino Whites (70%) but higher than among Mexicans (38%) (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eRecent label policy changes include Mexico's 2020 implementation of octagonal WLs and U.S. NFL updates in 2021 (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Some studies have found lower usage of the NFLs among Mexican Americans compared to non-Latino U.S. residents; a discrepancy that has been attributed to language barriers that hinder interpretation in these subpopulations (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTo address the challenges of interpreting and using the NFL, front-of-package labeling systems aim to clearly and concisely communicate nutrition information about packaged foods at the point of product selection and consumption. In 2020, Mexico introduced black octagonal warning labels on the front of the packages that clearly identify foods with \"excessive\" levels of calories, sugars, sodium, saturated fat, or trans-fat, as well as warnings for products containing non-nutritive sweeteners (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Mexican consumers have shown a high level of understanding and acceptance of this labeling system (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSome subpopulations may be more prone to using food labels, particularly those who have diet-related illnesses that require closer monitoring of nutritional practices. Previous reports from the United States and Korea have shown that NFL use is associated with healthier food decision-making among individuals with NCDs (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). These studies, primarily cross-sectional, suggest that individuals with NCDs are more likely to use NFLs than those without NCDs, suggesting a positive association between NFL use and food decision-making among people with NCDs.\u003c/p\u003e\u003cp\u003eIn contrast, in Mexico, individuals with three or more NCDs were less likely to use the GDA label (OR: 0.34, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) compared with 0, 1, 2 or 3 NCDs (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). This finding highlights a potential gap in the effectiveness of labeling systems for individuals with multiple NCDs. Different NCDs may require specific types of nutritional information; for example, people with diabetes may seek nutrition information to identify products high in sugar, while people with hypertension may be more concerned about sodium content of foods. Understanding these nuances can help tailor labeling policies to better meet the needs of groups with different diet-related NCDs.\u003c/p\u003e\u003cp\u003eThis study aimed to assess the association between the diagnosis of diet-related NCDs and the use of WL among Mexican adults, as well as the perceived usefulness of each WL for making healthy food choices.\u003c/p\u003e\u003cp\u003eA secondary objective was to compare the association between having NCDs and using NFLs among three groups: non-Mexican American, Mexican American, and Mexican adults.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Study Design\u003c/h2\u003e\u003cp\u003eData was collected through the International Food Policy Study (IFPS), an online survey conducted annually among adults in five countries during November and December. Secondary data analyses were performed using 2021 and 2022 data from adults in the Mexico and United States arms of the IFPS.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Participants\u003c/h2\u003e\u003cp\u003eParticipants were recruited through the Nielsen Global Consumer Panel and Qualtrics online panels with their partners using non-probability sampling methods with age and sex quotas to obtain a diverse sample that better represented each country's demographic proportions. Eligibility criteria included being 18 years or older and residing in one of the selected countries. Oversampling strategies were implemented differently by country: in Mexico, participants with the lowest education levels were oversampled to improve representation of this group, while in the United States, there was specific oversampling of Mexican American participants.\u003c/p\u003e\u003cp\u003eFor this study, surveyed adults were categorized into three subpopulations: 1) \"Mexicans\" (adults residing in Mexico), 2) \"Mexican Americans\" (US adults of Mexican heritage), and 3) \"non-Mexican Americans\" (other US ethnic groups including White, Black/African American, Asian/Pacific Islander, Native American, and Hispanic/Latino individuals not of Mexican origin). Participants provided informed consent before the survey and received compensation according to their panel's standard incentive structure (28). Complete IFPS study methods are detailed in the Technical Reports (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Measures\u003c/h2\u003e\u003cp\u003e\u003cem\u003eUse of nutrition labels\u003c/em\u003e\u003c/p\u003e\u003cp\u003eNFL use was assessed with the question, \"How often do you use this type of food label when deciding to buy a food product?\" accompanied by an image of the country-specific NFL. Response options were categorized as \"not used\" (never, rarely) and \"used\" (sometimes, often, all the time). Mexican participants were also asked a similar question regarding the use of WL, accompanied by an image of the \u0026lsquo;excess calories\u0026rsquo; WL, with response options identical to those for the NFL. Use of WLs was only assessed in Mexico, and not in USA, because Mexico was the only country with a government endorsed front of package labeling scheme.\u003c/p\u003e\u003cp\u003e\u003cem\u003ePerceived usefulness of warning labels\u003c/em\u003e\u003c/p\u003e\u003cp\u003eAdditionally, in 2021, Mexican participants were shown images of all five WLs and asked to evaluate the usefulness of each WL with the question, \u0026ldquo;Which of these stamps, if any, has been most useful to choose healthier foods: excess calories, excess sugars, excess saturated fats, excess trans fats, excess sodium, none of the stamps have been useful, or all the stamps have been equally useful.\u003c/p\u003e\u003cp\u003e\u003cem\u003eType and number of diagnoses of diet-related non-communicable diseases (NCDs)\u003c/em\u003e\u003c/p\u003e\u003cp\u003eParticipants reported diagnoses for six diet-related NCDs (\u0026ldquo;Has a doctor, nurse, or other health professional ever told you that you have or had\u0026hellip;\u0026rdquo;), including the following: 1) hypertension or high blood pressure, 2) heart attack (myocardial infarction), 3) angina or coronary disease, 4) diabetes or high blood sugar, 5) high cholesterol, and 6) cancer (excluding skin cancer). Responses for each condition were categorized as \u0026ldquo;yes\u0026rdquo; or \u0026ldquo;no.\u0026rdquo;\u003c/p\u003e\u003cp\u003eThe total number of self-reported NCDs was calculated by summing the number of conditions reported by each participant out of 6. This was then classified into three categories: \u0026ldquo;none,\u0026rdquo; \u0026ldquo;1 to 2\u0026rdquo; and \u0026ldquo;3 or more.\u0026rdquo;\u003c/p\u003e\u003cp\u003e\u003cem\u003eCovariates\u003c/em\u003e\u003c/p\u003e\u003cp\u003eCovariates included sociodemographic characteristics and other relevant variables that may affect food choice, food intake, and NCD management. Sociodemographic characteristics included sex at birth, age group (18 to 30, 30, 30 to 39, 40 to 49, 50 to 59, 60 to 69, 70 to 100), and highest educational attainment using country-specific response options, recoded as: \u0026ldquo;low\u0026rdquo; (none, preschool, elementary school, middle school, high school, or basic normal education for Mexicans; none, 8th grade or lower, 9th grade, 10th grade, 11th grade, 12th grade or high school for Mexican Americans and non-Mexican Americans); \u0026ldquo;medium\u0026rdquo; (career and technical studies for Mexicans; associate degree for Mexican Americans and non-Mexican Americans); and \u0026ldquo;high\u0026rdquo; (bachelor's degree or higher for both all respondents). Additionally, participants' subjective income adequacy was assessed with the question, \u0026ldquo;Thinking about your total monthly income, how difficult or easy is it for you to make ends meet?\u0026rdquo; (Recoded as easy/very easy or neither easy nor difficult/difficult/very difficult. Body Mass Index (BMI) was calculated from self-reported weight and height, with participants classified into categories of BMI\u0026thinsp;\u0026lt;\u0026thinsp;24.9 kg/m\u0026sup2;, 25-29.9 kg/m\u0026sup2;, \u0026ge;\u0026thinsp;30 kg/m\u0026sup2;, or missing. Nutrition knowledge was assessed using the question, \u0026ldquo;How would you rate your nutrition knowledge?\u0026rdquo; Responses were categorized as \u0026ldquo;none\u0026rdquo; (not at all knowledgeable), \u0026ldquo;low\u0026rdquo; (a little knowledgeable, somewhat knowledgeable), or \u0026ldquo;high\u0026rdquo; (very knowledgeable, extremely knowledgeable).\u003c/p\u003e\u003cp\u003eSeveral characteristics associated with the use of nutrition labels were also included as covariates and assessed through the following questions: Do you have children (under 18 years old) living in your household? (\u0026ldquo;yes\u0026rdquo; or \u0026ldquo;no\u0026rdquo;); This question was included because research has shown that the WL system is beneficial for parents when selecting healthy foods for their children (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). To assess the role in household food shopping, participants were asked, \u0026ldquo;How much of the food shopping do you do in your household?\u0026rdquo; Responses were recategorized as \"primary shopper\u0026rdquo; (most) and \"non primary shopper\u0026rdquo; (share equally with other(s); some, but less than other(s), none).\u003c/p\u003e\u003cp\u003eParticipants who either declined to respond or answered 'don\u0026rsquo;t know\u0026rsquo; questions regarding the use of nutrition labeling (WL and NFL), diagnosis of NCDs, or adjustment covariates were excluded from the analytic sample (\u003cb\u003eSupplementary Fig.\u0026nbsp;1\u003c/b\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Statistical Analysis\u003c/h2\u003e\u003cp\u003eDescriptive statistics characterized the sample based on sociodemographic variables, dietary behaviors, and NCDs by analytic subpopulation of interest (i.e., Mexican, Mexican American, non-Mexican American). To estimate associations between diagnosis of specific NCDs and nutrition label use, adjusted logistic regression models were estimated separately for each subpopulation. These models independently estimated the associations between NFL or WL usage among Mexicans and each NCD diagnosis. Subsequently, a multivariate logistic regression model incorporating the entire analytic sample of non-Mexican Americans, Mexicans, and Mexican Americans was developed to evaluate the association between NFL usage and NCD diagnosis stratified by these subpopulations. Separate models were also developed based on the number of NCDs in each subpopulation. Furthermore, models treating the NCD variable as a continuous variable were run to assess how label usage and the perceived usefulness of warning labels varied with the increasing number of diseases. All models were adjusted for survey year, age, sex at birth, income adequacy, educational level, nutrition knowledge, presence of children under 18 years in the household, household shopping role, and BMI categories to control for potential confounding factors. Post-stratification weights were applied in all analyses. These were constructed using a raking algorithm with census population estimates for each country based on age group, sex, region, education, and ethnicity. Data analyses were performed using STATA version 16.0. Statistical significance was established with a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.01 and a 99% confidence interval.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eThe final analytic sample across 2021 and 2022 included 23,951 participants; of these 46.5% were non-Mexican Americans (n\u0026thinsp;=\u0026thinsp;6,710), 25.5% were Mexican Americans (n\u0026thinsp;=\u0026thinsp;6,101), and 28.0% were Mexicans (n\u0026thinsp;=\u0026thinsp;11,140) (\u003cb\u003eSupplementary Fig.\u0026nbsp;1\u003c/b\u003e). Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e displays the sociodemographic characteristics, nutrition labeling use, and prevalence of NCDs across analytic subpopulations.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSociodemographic characteristics, nutrition labeling use, and diagnosis of NCDs by subpopulation. International Food Policy Study 2021 and 2022 (n\u0026thinsp;=\u0026thinsp;23,951)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMexicans\u003c/p\u003e\u003cp\u003e(Mx)\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;11,140)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMexican Americans\u003c/p\u003e\u003cp\u003e(Ma)\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;6,101)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon-Mexican American\u003c/p\u003e\u003cp\u003e(n-Ma)\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;6,710)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003ep-\u003c/em\u003evalue\u003c/p\u003e\u003cp\u003eMx vs Ma\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003ep-\u003c/em\u003evalue\u003c/p\u003e\u003cp\u003eMx vs n-Ma\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003ep-\u003c/em\u003evalue\u003c/p\u003e\u003cp\u003eMa vs n-Ma\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e% (99% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e% (99% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e% (99% CI)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSociodemographic characteristics\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eYear\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e48.56 (46.81\u0026ndash;50.33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e49.74 (47.85\u0026ndash;51.64)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e50.99 (49.19\u0026ndash;52.79)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.240\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.220\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e51.44 (49.67\u0026ndash;53.19)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e50.26 (48.36\u0026ndash;52.15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e49.01 (41.21\u0026ndash;50.81)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSex at birth\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e47.24 (45.49\u0026ndash;48.99)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e47.18 (45.29\u0026ndash;49.08)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e48.81 (47.01\u0026ndash;50.61)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.955\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.107\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.109\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e52.76 (51.01\u0026ndash;54.51)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e52.82 (50.92\u0026ndash;54.71)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e51.19 (49.39\u0026ndash;52.99)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge group (years)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e18 to 30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e27.40 (25.97\u0026ndash;28.88)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29.16 (27.50-30.88)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15.53 (14.21\u0026ndash;16.94)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e30 to 39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e23.68 (22.27\u0026ndash;25.15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27.70 (26.02\u0026ndash;29.44)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14.79 (13.55\u0026ndash;16.12)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e40 to 49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17.90 (16.72\u0026ndash;19.14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20.32 (18.82\u0026ndash;21.89)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15.72 (14.46\u0026ndash;17.06)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e50 to 59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18.94 (17.45\u0026ndash;20.53)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13.48 (12.24\u0026ndash;14.81)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e17.85 (16.52\u0026ndash;19.25)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e60 to 69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9.47 (8.28\u0026ndash;10.80)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.04 (6.07\u0026ndash;8.16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e21.82 (20.37\u0026ndash;23.35)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e70 to 100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.61 (1.97\u0026ndash;3.44)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.30 (1.78\u0026ndash;2.97)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14.30 (13.12\u0026ndash;15.57)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEducational level\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLow\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e74.88 (73.53\u0026ndash;76.19)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e65.29 (63.63\u0026ndash;66.91)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e50.84 (49.04\u0026ndash;52.63)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMedium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9.70 (8.66\u0026ndash;10.86)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10.50 (9.74\u0026ndash;11.30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10.14 (9.40-10.93)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15.41 (14.58\u0026ndash;16.28)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24.22 (22.77\u0026ndash;25.72)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e39.02 (37.34\u0026ndash;40.74)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePerceived income adequacy\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEasy or very easy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10.38 (9.45\u0026ndash;11.39)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25.84 (24.25\u0026ndash;27.49)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e42.45 (40.70-44.22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNeither easy nor difficult\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e40.22 (38.51\u0026ndash;41.95)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e38.32 (36.50-40.18)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30.35 (28.69\u0026ndash;32.07)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDifficult or very difficult\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e49.40 (47.64\u0026ndash;51.17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e35.84 (34.02\u0026ndash;37.71)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27.20 (25.60-28.85)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePresence of children (under 18) in the household\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e50.72 (48.96\u0026ndash;52.48)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e45.26 (43.38\u0026ndash;47.15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e25.65 (24.14\u0026ndash;27.23)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePrimary shopping role for household\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e68.62 (66.98\u0026ndash;70.22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e67.25 (65.45\u0026ndash;69.01)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e70.58 (68.88\u0026ndash;72.22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.143\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.031\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNutrition knowledge\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNot at all/ a little knowledgeable\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e44.21 (42.47\u0026ndash;45.98)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e33.56 (31.78\u0026ndash;35.39)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e34.41 (32.70-36.15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.026\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSomewhat knowledgeable\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e46.19 (44.44\u0026ndash;47.95)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e42.37 (40.51\u0026ndash;44.26)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e39.81 (38.06\u0026ndash;41.59)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVery/extremely knowledgeable\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9.60 (8.65\u0026ndash;10.63)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24.07 (22.51\u0026ndash;25.69)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e25.78 (24.25\u0026ndash;27.37)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBMI (kg/m\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;24.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e32.31 (30.72\u0026ndash;33.95)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30.81 (29.11\u0026ndash;32.57)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e37.49 (35.76\u0026ndash;39.26)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e25.0 to 29.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e29.43 (27.84\u0026ndash;31.07)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e28.53 (26.85\u0026ndash;30.27)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e28.49 (26.91\u0026ndash;30.12)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16.73 (15.42\u0026ndash;18.12)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e28.68 (26.99\u0026ndash;30.43)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e24.26 (22.74\u0026ndash;25.84)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMissing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e21.53 (20.11\u0026ndash;23.03)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11.98 (10.76\u0026ndash;13.31)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9.76 (8.72\u0026ndash;10.91)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNutrition labeling use\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNutrition facts table (NFL) use\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUsed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e69.81 (68.16\u0026ndash;71.41)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e77.61 (75.99\u0026ndash;79.16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e80.13 (78.62\u0026ndash;81.56)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNot used\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30.19 (28.59\u0026ndash;31.84)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22.39 (20.84\u0026ndash;24.01)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e19.87 (18.44\u0026ndash;21.38)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFront-of-pack warning label (WL) use\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUsed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e77.46 (75.96\u0026ndash;78.88)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNot used\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22.54 (21.12\u0026ndash;24.04)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNon-Communicable Diseases (NCDs)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNCD diagnosis\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypertension\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e23.50 (21.96\u0026ndash;25.11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25.22 (23.60-26.91)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e37.33 (35.60-39.09)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.051\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHeart attack\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.62 (2.10\u0026ndash;3.27)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.08 (2.49\u0026ndash;3.81)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.16 (4.42\u0026ndash;6.01)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.172\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAngina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.66 (2.14\u0026ndash;3.29)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.60 (2.90\u0026ndash;4.46)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.36 (4.62\u0026ndash;6.20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiabetes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13.00 (11.74\u0026ndash;14.37)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15.17 (13.83\u0026ndash;16.60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e16.10 (14.84\u0026ndash;17.45)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.207\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh cholesterol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24.34 (22.78\u0026ndash;25.97)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21.16 (19.67\u0026ndash;22.74)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e32.45 (30.80-34.15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCancer (excluding skin cancer)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.03 (1.59\u0026ndash;2.59)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.20 (3.49\u0026ndash;5.05)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.12 (6.25\u0026ndash;8.09)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNumber of NCD diagnoses (categorical)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e58.77 (56.99\u0026ndash;60.53)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e60.26 (58.38\u0026ndash;62.10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e46.96 (45.17\u0026ndash;48.77)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1 or 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e35.16 (33.45\u0026ndash;36.91)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30.69 (28.97\u0026ndash;32.46)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e39.78 (38.04\u0026ndash;41.55)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3 or more\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.07 (5.20\u0026ndash;7.07)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9.06 (7.99\u0026ndash;10.25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13.25 (12.08\u0026ndash;14.52)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e\u003cp\u003eThe p-value was calculated using Pearson's chi-squared test.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eIn the adjusted independent logistic regression models for each NCD (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) it was observed that non-Mexican Americans were 68% more likely to use the NFL when diagnosed with diabetes (AOR 1.68, 99% CI: 1.26\u0026ndash;2.24) compared to those without an NCD diagnosis. Furthermore, non-Mexican Americans were 48% more likely to use the NFL when they had 3 or more NCD diagnoses (AOR 1.48, 99% CI: 1.07\u0026ndash;2.06) compared to those without any NCD diagnosis. When analyzing the NCD variable as a continuous measure, it was found that for each diagnosed NCD among non-Mexican Americans, the likelihood of using the NFL increased by 16% (AOR 1.16, 99% CI: 1.02\u0026ndash;1.32).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAssociation between the diagnosis of NCDs and the use of nutritional labeling in Mexican, Mexican American and non-Mexican American adults. IFPS 2021 and 2022\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eUse of NFL\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUse of WL\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMexican\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMexican American\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon-Mexican American\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMexican\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003en\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11,140\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6,101\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6,710\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e11,140\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAOR (99% CI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAOR (99% CI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAOR (99% CI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eAOR (99% CI)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDiagnosis of NCDs\u003c/b\u003e\u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eref\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eref\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eref\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003eref\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypertension\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.01 (0.82\u0026ndash;1.24)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.09 (0.86\u0026ndash;1.38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.09 (0.88\u0026ndash;1.35)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.02 (0.82\u0026ndash;1.27)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHeart attack\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.18 (0.66\u0026ndash;2.08)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.09 (0.61\u0026ndash;1.97)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.57 (0.96\u0026ndash;2.57)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.11 (0.61\u0026ndash;2.02)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAngina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.05 (0.63\u0026ndash;1.76)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.85 (0.94\u0026ndash;3.63)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.57 (0.97\u0026ndash;2.53)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.33 (0.73\u0026ndash;2.43)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiabetes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.02 (0.78\u0026ndash;1.34)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.17 (0.87\u0026ndash;1.56)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e1.68 (1.26\u0026ndash;2.24)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.13 (0.84\u0026ndash;1.52)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh cholesterol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.94 (0.76\u0026ndash;1.15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.21 (0.95\u0026ndash;1.56)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.06 (0.85\u0026ndash;1.31)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.90 (0.72\u0026ndash;1.11)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCancer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.40 (0.77\u0026ndash;2.56)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.19 (0.71\u0026ndash;1.99)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.14 (0.78\u0026ndash;1.69)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.37 (0.74\u0026ndash;2.57)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNumber of NCD diagnoses\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e(categorical)\u003c/b\u003e\u003csup\u003e\u003cb\u003eb\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eref\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eref\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eref\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003eref\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1 to 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.92 (0.77\u0026ndash;1.11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.08 (0.86\u0026ndash;1.35)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.14 (0.91\u0026ndash;1.42)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.00 (0.82\u0026ndash;1.22)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3 or more\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.07 (0.72\u0026ndash;1.59)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.37 (0.93\u0026ndash;2.02)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e1.48 (1.07\u0026ndash;2.06)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.06 (0.69\u0026ndash;1.63)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNumber of NCD diagnoses\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e(continuous)\u003c/b\u003e\u003csup\u003e\u003cb\u003ec\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.00 (0.87\u0026ndash;1.14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.05 (0.91\u0026ndash;1.22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e1.16 (1.02\u0026ndash;1.32)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.01 (0.92\u0026ndash;1.12)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003csup\u003ea\u003c/sup\u003eIndependent logistic regression models for each type of NCD and each subpopulation, adjusted for: survey year, sex, age group, educational level, income adequacy, children under 18 in the household, shopping role for household, nutrition knowledge, and BMI categories.\u003c/p\u003e\u003cp\u003e\u003csup\u003eb\u003c/sup\u003eIndependent logistic regression models for each subpopulation, adjusted for: survey year, sex, age group, educational level, income adequacy, children under 18 in the household, shopping role for household, nutrition knowledge, and BMI categories.\u003c/p\u003e\u003cp\u003e\u003csup\u003ec\u003c/sup\u003eA logistic regression model was conducted using the NCD variable as a continuous measure.\u003c/p\u003e\u003cp\u003eBold numbers indicate statistical significance (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e\u003cp\u003eIFPS\u0026thinsp;=\u0026thinsp;International Food Policy Study (waves 2021 and 2022); NCDs\u0026thinsp;=\u0026thinsp;Non-Communicable Diseases; NFL\u0026thinsp;=\u0026thinsp;Nutrition Facts Label; WL\u0026thinsp;=\u0026thinsp;Warning Label; AOR\u0026thinsp;=\u0026thinsp;Adjusted Odds Ratio; CI\u0026thinsp;=\u0026thinsp;Confidence Interval.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the results of the association between NCD diagnosis and the perceived usefulness of WLs for selecting healthier foods among Mexican adults from the 2021 survey. Adults diagnosed with diabetes were more likely to perceive the \"Excess Sugars\" WL as the most useful when choosing healthier foods (AOR 1.65, 99% CI: 1.07\u0026ndash;2.54) compared to those without any NCD diagnosis. Adults diagnosed with high cholesterol were more likely to perceive the \"Excess Sodium\" WL as the most useful for choosing healthier foods (AOR 1.89, 99% CI: 1.15\u0026ndash;3.12) compared to those without any NCD diagnosis.\u003c/p\u003e\u003cp\u003eRegarding the number of diagnosed NCDs among Mexican adults (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), those with 1 or 2 diagnoses were more likely to perceive the \"Excess Sodium\" WL as the most useful for choosing healthier foods (AOR 1.72, 99% CI: 1.08\u0026ndash;2.73) compared to those without any NCD diagnoses. Furthermore, adults with 3 or more NCDs were more likely to perceive the \"Excess Sugars\" WL as the most useful for selecting healthier options (AOR 1.96, 99% CI: 1.04\u0026ndash;3.71) compared to individuals without any diagnoses. In the regression model examining the number of NCDs as a continuous variable, it was observed that for each diagnosed NCD among Mexican adults, the likelihood of perceiving the \"Excess Sodium\" WL (AOR 1.21, 99% CI: 1.02\u0026ndash;1.44) and the \"Excess Sugars\" WL (AOR 1.21, 99% CI: 1.05\u0026ndash;1.39) as the most useful when choosing healthier foods increased.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAssociation between the type and number of diagnosed NCDs and the perceived usefulness of warning labels for selecting healthier foods among Mexican adults. IFPS 2021 (n\u0026thinsp;=\u0026thinsp;5,430)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eExcess calories\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eExcess sodium\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eExcess trans fats\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eExcess sugars\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eExcess saturated fats\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNone of the stamps have been useful\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eAll of the stamps have been equally useful\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAOR (99% CI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAOR (99% CI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAOR (99% CI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAOR (99% CI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eAOR (99% CI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eAOR (99% CI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eAOR (99% CI)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDiagnosis of NCDs\u003c/b\u003e\u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eref\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eref\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eref\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eref\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003eref\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003eref\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cem\u003eref\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypertension\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.85 (0.53\u0026ndash;1.38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.59 (0.97\u0026ndash;2.61)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.14 (0.65\u0026ndash;2.03)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.39 (0.99\u0026ndash;1.95)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.88 (0.58\u0026ndash;1.32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.90 (0.62\u0026ndash;1.31)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.81 (0.60\u0026ndash;1.08)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHeart attack\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.86 (0.35\u0026ndash;2.15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.63 (0.19\u0026ndash;2.06)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.11 (0.71\u0026ndash;1.74)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.22 (0.49\u0026ndash;3.05)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.62 (0.21\u0026ndash;1.87)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.38 (0.62\u0026ndash;3.10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.00 (0.48\u0026ndash;2.07)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAngina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.58 (0.20\u0026ndash;1.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.31 (0.09\u0026ndash;1.04)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.82 (0.23\u0026ndash;2.92)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.51 (0.67\u0026ndash;3.39)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.20 (0.49\u0026ndash;2.91)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.00 (0.33\u0026ndash;3.01)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.04 (0.48\u0026ndash;2.25)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiabetes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.81 (0.41\u0026ndash;1.62)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.44 (0.75\u0026ndash;2.77)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.55 (0.23\u0026ndash;1.29)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e1.65 (1.07\u0026ndash;2.54)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.53 (0.27\u0026ndash;1.04)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.97 (0.59\u0026ndash;1.60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.01 (0.69\u0026ndash;1.47)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh cholesterol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.64 (0.39\u0026ndash;1.06)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e1.89 (1.15\u0026ndash;3.12)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.17 (0.68\u0026ndash;2.01)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.34 (0.96\u0026ndash;1.87)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.79 (0.51\u0026ndash;1.22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.80 (0.54\u0026ndash;1.17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.98 (0.74\u0026ndash;1.30)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCancer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.10 (0.26\u0026ndash;4.66)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.32 (0.07\u0026ndash;1.40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.15 (0.37\u0026ndash;3.56)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.16 (0.45-3.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.57 (0.15\u0026ndash;2.10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.45 (0.48\u0026ndash;4.40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.01 (0.43\u0026ndash;2.38)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNumber of NCD diagnoses (categorical)\u003c/b\u003e\u003csup\u003e\u003cb\u003eb\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eref\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eref\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eref\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eref\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003eref\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003eref\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cem\u003eref\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1 or 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.72 (0.48\u0026ndash;1.10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e1.72 (1.08\u0026ndash;2.73)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.50 (0.93\u0026ndash;2.43)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.25 (0.93\u0026ndash;1.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.83 (0.57\u0026ndash;1.20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.93 (0.66\u0026ndash;1.30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.87 (0.67\u0026ndash;1.11)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3 or more\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.88 (0.34\u0026ndash;2.31)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.59 (0.64\u0026ndash;3.39)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.70 (0.24\u0026ndash;2.06)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e1.96 (1.04\u0026ndash;3.71)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.65 (0.26\u0026ndash;1.62)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.80 (0.37\u0026ndash;1.74)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.82 (0.46\u0026ndash;1.46)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNumber of NCD diagnoses (continuous)\u003c/b\u003e\u003csup\u003e\u003cb\u003ec\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.85 (0.66\u0026ndash;1.09)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e1.21 (1.02\u0026ndash;1.44)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.00 (0.82\u0026ndash;1.21)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e1.21 (1.05\u0026ndash;1.39)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.85 (0.69\u0026ndash;1.04)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.95 (0.80\u0026ndash;1.14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.96 (0.84\u0026ndash;1.09)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e\u003cp\u003e\u003csup\u003ea\u003c/sup\u003eIndependent logistic regression models for each type of NCD and each warning label, adjusted for: survey year, sex, age group, educational level, income adequacy, children under 18 in the household, shopping role for household, nutrition knowledge, and BMI categories.\u003c/p\u003e\u003cp\u003e\u003csup\u003eb\u003c/sup\u003eIndependent logistic regression model for each warning label, adjusted for: survey year, sex, age group, educational level, income adequacy, children under 18 in the household, shopping role for household, nutrition knowledge, and BMI categories.\u003c/p\u003e\u003cp\u003e\u003csup\u003ec\u003c/sup\u003eA logistic regression model was conducted using the NCD variable as a continuous measure.\u003c/p\u003e\u003cp\u003eIFPS\u0026thinsp;=\u0026thinsp;International Food Policy Study (waves 2021 and 2022); NCDs\u0026thinsp;=\u0026thinsp;Non-Communicable Diseases, AOR\u0026thinsp;=\u0026thinsp;Adjusted Odds Ratio, CI\u0026thinsp;=\u0026thinsp;Confidence Interval\u003c/p\u003e\u003cp\u003eBold numbers indicate statistical significance at a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.01.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study explored the use of the NFL and WLs across Mexicans, Mexican Americans, and non-Mexican Americans, with a focus on differences by NCD diagnosis. While a general trend of increased NFL use with more NCDs was observed, statistically significant differences were found only among non-Mexican Americans, particularly those with diabetes or three or more NCDs. This supports previous evidence suggesting that individuals with chronic conditions have greater nutrition awareness due to more frequent healthcare interactions, including dietary counseling (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOne study from the ENSANUT 2016 found that Mexican adults with hypertension, diabetes, or three or more NCDs tended to use the GDA front-of-package labeling system less than those without diagnoses (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Additionally, ENSANUT 2018 data showed that individuals with NCDs were more likely to read the NFL than the GDA (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). This trend may be explained by the complexity of the GDA labeling system, which required nutritional knowledge, time, and mathematical calculations for proper use, making it difficult for most consumers to understand (\u003cspan additionalcitationids=\"CR23 CR24\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn contrast, our findings showed that WL use (77.5%) exceeded NFL use (69.8%) among Mexicans, and no significant differences were found in WL use by NCD status. This suggests that WLs are widely adopted regardless of diagnosis (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e) regardless of NCD status. Supporting this, a prior Mexican study found no significant variation in WL use among those with diabetes or hypertension (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e).\u003c/p\u003e\u003cp\u003ePrevious studies in adult populations have reported that WLs encourage the selection of foods with lower amounts of critical nutrients (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). While our findings did not support the hypothesis that individuals with NCDs generally use WLs more frequently due to a heightened interest in avoiding excessive levels of critical nutrients to better manage their conditions (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e), we observed a notableassociation when analyzing the perceived usefulness of WLs related to the critical nutrient to the diagnosed NCD.\u003c/p\u003e\u003cp\u003eFor instance, individuals with diabetes were more likely to consider the \"Excess sugars\" label to be most useful when choosing healthy foods, and those with high cholesterol were more likely to find the \"Excess sodium\" label as most useful. Additionally, as the number of diagnosed NCDs increased, so did the likelihood of considering these two labels as the most useful for making informed food choices. This suggests a heightened awareness among individuals with NCDs regarding the importance of certain critical nutrients in the onset and progression of these diseases.\u003c/p\u003e\u003cp\u003eSimilarly, our study found that among the Mexican population, the likelihood of considering the \"Excess sodium,\" \"Excess trans-fat,\" and \"Excess sugars\" WLs as useful doubled with an increasing number of NCDs. These findings align with evidence that warning label-type systems provide interpretative elements that quickly convey the nutritional quality of products, helping consumers choose those considered more beneficial for their health (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Experimental studies conducted in various countries have shown that WLs enhance consumers' ability to understand nutrition information and discourage the selection of products high in nutrients linked to NCDs (\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eConsistent with our findings, previous research based on 2017 IFPS data has shown that the overall U.S. population reports higher use of NFLs (70.00% vs 80.13% in our study) compared to the Mexican population (38.00% vs 69.81% in our study) and the U.S. Latino population (57.00% vs 77.61% in our study) (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). The greater use of NFLs among Americans could be attributed to the fact that NFLs is the primary tool available for obtaining nutrition information on packaged products, as there is no mandatory front-of-package labeling system in the United States (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). Conversely, Mexico\u0026rsquo;s recently implemented WL system might partly explain the lower use of NFLs in this population compared to subpopulations residing in the United States. However, an increase in NFL use has been observed in Mexico in recent years compared to the pre-implementation stage of the WL system (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). Despite these trends, further data are needed to determine why NFL use remains higher in the United States compared to Mexico.\u003c/p\u003e\u003cp\u003eOne of the study's main strengths is the large sample size, including NFL use data collected over two years, which allowed for rigorous statistical analyses. However, certain limitations should be acknowledged. Firstly, although oversampling of low education populations in Mexico and weighting techniques was applied to enhance representativeness, participant recruitment relied on non-probabilistic sampling, limiting generalizability to the national level.\u003c/p\u003e\u003cp\u003eAdditionally, the cross-sectional design of our study prevents causal inferences between nutrition labels use and NCD presence. Furthermore, data on years since diagnosis and adherence to medical or nutritional treatment were not collected. These factors should be considered when interpreting our results, as they may influence both nutritional label use and NCD management.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn conclusion, our findings highlight the potential of food labeling as an essential tool for individuals with health conditions. This underscores the need to promote the use of interpretive labels, such as the WLs, among populations with NCDs to support informed food choices that can contribute to both prevention and effective management of these conditions.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAOR: Adjusted odds ratio\u003c/p\u003e\n\u003cp\u003eBMI: Body mass index\u003c/p\u003e\n\u003cp\u003eCI: Confidence interval\u003c/p\u003e\n\u003cp\u003eENSANUT: Encuesta Nacional de Salud y Nutrición\u003c/p\u003e\n\u003cp\u003eGDA: Guideline daily amounts\u003c/p\u003e\n\u003cp\u003eIFPS: International Food Policy Study\u003c/p\u003e\n\u003cp\u003eNFL: Nutrition facts label\u003c/p\u003e\n\u003cp\u003eNCD: Non-communicable disease\u003c/p\u003e\n\u003cp\u003eNCDs: Non-communicable diseases\u003c/p\u003e\n\u003cp\u003eNIH: National Institutes of Health\u003c/p\u003e\n\u003cp\u003eOR: Odds ratio\u003c/p\u003e\n\u003cp\u003eU.S.: United States\u003c/p\u003e\n\u003cp\u003eWL: Warning label\u003c/p\u003e\n\u003cp\u003eWLs: Warning labels\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study received ethical approval from the Research Ethics Committee at the University of Waterloo (REB #30829), the Institutional Review Board at the University of South Carolina, and the Research Ethics Committee at the National Institute of Public Health in Mexico. All participants provided informed consent prior to participation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets analyzed during the current study are not publicly available. Data are available from the International Food Policy Study (contact: Dr. Christine White, University of Waterloo) upon reasonable request and with permission from the study team.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFunding for the International Food Policy Study was provided by a Canadian Institutes of Health Research (CIHR) Project Grant (PJT162167), with additional support from the National Institute of Diabetes and Digestive and Kidney Disorders of the National Institutes of Health (NIH) (R01 DK128967). The content is solely the responsibility of the authors and does not necessarily represent the official views of the CIHR or NIH.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIsabel García-Perfecto: Formal analysis, Investigation, Methodology, Writing – original draft.\u003cbr\u003e\u0026nbsp;Alejandra Contreras-Manzano: Resources, Formal analysis, Methodology, Supervision, Writing – review \u0026amp; editing.\u003cbr\u003e\u0026nbsp;Kathia Larissa Quevedo: Methodology, Supervision, Writing – review \u0026amp; editing.\u003cbr\u003e\u0026nbsp;Christine M. White: Funding acquisition, Writing – review \u0026amp; editing.\u003cbr\u003e\u0026nbsp;Lana Vanderlee: Writing – review \u0026amp; editing.\u003cbr\u003e\u0026nbsp;Rachel E. Davis: Supervision, Writing – review \u0026amp; editing.\u003cbr\u003e\u0026nbsp;Cecilia I. Oviedo-Solís: Supervision, Writing – review \u0026amp; editing.\u003cbr\u003e\u0026nbsp;James F. Thrasher: Supervision, Writing – review \u0026amp; editing.\u003cbr\u003e\u0026nbsp;Simón Barquera: Writing – review \u0026amp; editing.\u003cbr\u003e\u0026nbsp;David Hammond: Writing – review \u0026amp; editing.\u003cbr\u003e\u0026nbsp;Claudia Nieto: Writing – review \u0026amp; editing.\u003cbr\u003e\u0026nbsp;Dai Fang: Writing – review \u0026amp; editing.\u003cbr\u003e\u0026nbsp;Alejandra Jáuregui: Supervision, Writing – review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of generative AI and AI-assisted technologies in the writing process\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDuring the preparation of this work, the author(s) used DeepL (OpenAI) to improve the readability and language of the manuscript, including translation into English. After using this tool, the author(s) carefully reviewed and edited the content as needed and take(s) full responsibility for the content of the published article.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets analyzed during the current study are not publicly available. Data are available from the International Food Policy Study (contact: Dr. Christine White, University of Waterloo) upon reasonable request and with permission from the study team.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eOrganizaci\u0026oacute;n Mundial de la Salud. Enfermedades no transmisibles [Internet]. 2022 [cited 2023 Oct 2]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/es/news-room/fact-sheets/detail/noncommunicable-diseases#:~:text=Cada%20a%C3%B1o%2C%2017%20millones%20de,de%20ingresos%20bajos%20y%20medianos\u003c/span\u003e\u003cspan address=\"https://www.who.int/es/news-room/fact-sheets/detail/noncommunicable-diseases#:~:text=Cada%20a%C3%B1o%2C%2017%20millones%20de,de%20ingresos%20bajos%20y%20medianos\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGlobal Obesity Observatory. Ranking (% obesity by country) [Internet]. 2024 [cited 2024 Sep 19]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://data.worldobesity.org/rankings/\u003c/span\u003e\u003cspan address=\"https://data.worldobesity.org/rankings/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBasto-Abreu A, Reyes-Garcia A, Stern D, Torres-Ibarra L, Rojas-Mart\u0026iacute;nez R, Aguilar-Salinas CA, et al. Cascadas de tamizaje y atenci\u0026oacute;n de la diabetes tipo 2 en M\u0026eacute;xico. Salud Publica Mex. 2024;66(4):528\u0026ndash;36.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eU.S. Centers for Disease Control and Prevention. National Diabetes Statistics Report [Internet]. 2024 [cited 2024 Sep 19]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cdc.gov/diabetes/php/data-research/index.html\u003c/span\u003e\u003cspan address=\"https://www.cdc.gov/diabetes/php/data-research/index.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCampos-Nonato I, Oviedo-Sol\u0026iacute;s C, Hern\u0026aacute;ndez-Barrera L, M\u0026aacute;rquez-Murillo M, G\u0026oacute;mez-\u0026Aacute;lvarez E, Alcocer-D\u0026iacute;az L, et al. Detecci\u0026oacute;n, atenci\u0026oacute;n y control de hipertensi\u0026oacute;n arterial. Salud Publica Mex. 2024;66(4):537\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eU.S. Centers for Disease Control and Prevention. High Blood Pressure Facts [Internet]. 2022 [cited 2024 Sep 19]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cdc.gov/high-blood-pressure/data-research/facts-stats/index.html\u003c/span\u003e\u003cspan address=\"https://www.cdc.gov/high-blood-pressure/data-research/facts-stats/index.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eElder JP. Mexico and the USA: the world\u0026rsquo;s leaders in the obesity epidemic. Salud Publica Mex. 2013;55:355.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOrganizaci\u0026oacute;n Panamericana de la Salud. El etiquetado frontal como instrumento de pol\u0026iacute;tica para prevenir enfermedades no transmisibles en la Regi\u0026oacute;n de las Am\u0026eacute;ricas [Internet]. 2020 [cited 2023 Aug 9]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://iris.paho.org/bitstream/handle/10665.2/53013/OPSNMHRF200033_spa.pdf?sequence=5\u0026amp;isAllowed=y\u003c/span\u003e\u003cspan address=\"https://iris.paho.org/bitstream/handle/10665.2/53013/OPSNMHRF200033_spa.pdf?sequence=5\u0026amp;isAllowed=y\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKaufer-Horwitz M, Tolentino-Mayo L, J\u0026aacute;uregui A, S\u0026aacute;nchez-Baz\u0026aacute;n K, Bourges H, Mart\u0026iacute;nez S et al. Sistema de etiquetado frontal de alimentos y bebidas para M\u0026eacute;xico: una estrategia para la toma de decisiones saludables. salud publica mex. 2018;60(4).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDiario Oficial de la Federaci\u0026oacute;n. MODIFICACI\u0026Oacute;N a la Norma Oficial Mexicana NOM-051-SCFI/SSA1-2010, Especificaciones generales de etiquetado para alimentos y bebidas no alcoh\u0026oacute;licas preenvasados-Informaci\u0026oacute;n comercial y sanitaria, publicada el 5 de abril de 2010. [Internet]. 2020 [cited 2023 Sep 20]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.dof.gob.mx/normasOficiales/8150/seeco11_C/seeco11_C.html\u003c/span\u003e\u003cspan address=\"https://www.dof.gob.mx/normasOficiales/8150/seeco11_C/seeco11_C.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eU.S. Food and Drug administration. What\u0026rsquo;s on the Nutrition Facts Label [Internet]. 2024 [cited 2024 Apr 4]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.fda.gov/food/nutrition-facts-label/whats-nutrition-facts-label\u003c/span\u003e\u003cspan address=\"https://www.fda.gov/food/nutrition-facts-label/whats-nutrition-facts-label\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOllberding NJ, Wolf RL, Contento I. Food Label Use and Its Relation to Dietary Intake among US Adults. J Am Diet Assoc. 2010;110(8):1233\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNieto C, J\u0026aacute;uregui A, Contreras-Manzano A, Arillo-Santillan E, Barquera S, White CM, et al. Understanding and use of food labeling systems among Whites and Latinos in the United States and among Mexicans: Results from the International Food Policy Study, 2017. Int J Behav Nutr Phys Activity. 2019;16(1):87.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eInstituto Nacional de Salud P\u0026uacute;blica. Encuesta Nacional de Salud y Nutrici\u0026oacute;n 2021 sobre COVID-19. Resultados Nacionales [Internet]. 2022 [cited 2022 Dec 26]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://ensanut.insp.mx/encuestas/ensanutcontinua2021/doctos/informes/220804_Ensa21_digital_4ago.pdf\u003c/span\u003e\u003cspan address=\"https://ensanut.insp.mx/encuestas/ensanutcontinua2021/doctos/informes/220804_Ensa21_digital_4ago.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePost 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\u0026ndash;32.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePark SG, Kim HJ, Kwon YM, Kong MH. Nutrition Label Use and Its Relation to Dietary Intake among Chronic Disease Patients in Korea: Results from the 2008\u0026ndash;2009 Fourth Korean National Health and Nutrition Examination Survey (KNHANES-IV). Korean J Health Promotion. 2014;14(4):131.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNieto C, Tolentino-Mayo L, Monterrubio-Flores E, Medina C, Pati\u0026ntilde;o SRG, Aguirre-Hern\u0026aacute;ndez R et al. Nutrition Label Use Is Related to Chronic Conditions among Mexicans: Data from the Mexican National Health and Nutrition Survey 2016. J Acad Nutr Diet [Internet]. 2020 May [cited 2023 Mar 11];120(5):804\u0026ndash;14. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pubmed.ncbi.nlm.nih.gov/31585829/\u003c/span\u003e\u003cspan address=\"https://pubmed.ncbi.nlm.nih.gov/31585829/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eInternational Food Policy Study. International Food Policy Study. Methods [Internet]. 2023 [cited 2023 Oct 25]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://foodpolicystudy.com/methods/\u003c/span\u003e\u003cspan address=\"https://foodpolicystudy.com/methods/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLimbu YB, McKinley C, Gautam RK, Ahirwar AK, Dubey P, Jayachandran C. Nutritional knowledge, attitude, and use of food labels among Indian adults with multiple chronic conditions. Br Food J. 2019;121(7):1480\u0026ndash;94.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHong Swoo, Oh SW, Lee C, Kwon H, Hyeon Jhyeon, Gwak Jseop. Association between Nutrition Label Use and Chronic Disease in Korean Adults: The Fourth Korea National Health and Nutrition Examination Survey 2008\u0026ndash;2009. J Korean Med Sci. 2014;29(11):1457.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLewis JE, Arheart KL, LeBlanc WG, Fleming LE, Lee DJ, Davila EP, 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\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTolentino-Mayo L, Sagaceta-Mej\u0026iacute;a J, Cruz-Casarrubias C, R\u0026iacute;os-Cort\u0026aacute;zar V, Jauregui A, Barquera S. Comprensi\u0026oacute;n y uso del etiquetado frontal nutrimental Gu\u0026iacute;as Diarias de Alimentaci\u0026oacute;n de alimentos y bebidas industrializados en M\u0026eacute;xico. Salud Publica Mex. 2020;62(6):786\u0026ndash;97.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOrganizaci\u0026oacute;n P, de la Salud. Organizaci\u0026oacute;n Mundial de la Salud. Estudio de pol\u0026iacute;ticas sobre el etiquetado nutricional frontal en las Am\u0026eacute;ricas: Evoluci\u0026oacute;n y resultados [Internet]. 2022 [cited 2024 Mar 22]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.paho.org/es/documentos/estudio-politicas-sobre-etiquetado-nutricional-frontal-americas-evolucion-resultados\u003c/span\u003e\u003cspan address=\"https://www.paho.org/es/documentos/estudio-politicas-sobre-etiquetado-nutricional-frontal-americas-evolucion-resultados\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDalia S, Lizbeth T. Barquera Sim\u0026oacute;n. Revisi\u0026oacute;n del etiquetado frontal: an\u0026aacute;lisis de las Gu\u0026iacute;as Diarias de Alimentaci\u0026oacute;n (GDA) y su comprensi\u0026oacute;n por estudiantes de nutrici\u0026oacute;n en M\u0026eacute;xico. 2011 [cited 2023 Aug 10]; Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://elpoderdelconsumidor.org/wp-content/uploads/2015/07/Etiquetado-Evaluaci%C3%B3n-GDA-por-Barquera-y-col.pdf\u003c/span\u003e\u003cspan address=\"https://elpoderdelconsumidor.org/wp-content/uploads/2015/07/Etiquetado-Evaluaci%C3%B3n-GDA-por-Barquera-y-col.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVargas-Meza J, J\u0026aacute;uregui A, Contreras-Manzano A, Nieto C, Barquera S. Acceptability and understanding of front-of-pack nutritional labels: an experimental study in Mexican consumers. BMC Public Health. 2019;19(1):1751.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMontes de Oca-Ju\u0026aacute;rez O, Fern\u0026aacute;ndez-Villa JM, Gonz\u0026aacute;lez-Lara M, Garc\u0026iacute;a-Pe\u0026ntilde;a C. Uso y comprensi\u0026oacute;n del etiquetado nutricional en personas mayores mexicanas: un estudio secundario de la Encuesta Nacional de Salud y Nutrici\u0026oacute;n (ENSANUT 2021). Gac Med Mex. 2024;160(3).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAres G, Ant\u0026uacute;nez L, Curutchet MR, Gim\u0026eacute;nez A. Warning labels as a policy tool to encourage healthier eating habits. Curr Opin Food Sci. 2023;51:101011.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCabrera M, Mach\u0026iacute;n L, Arr\u0026uacute;a A, Ant\u0026uacute;nez L, Curutchet MR, Gim\u0026eacute;nez A, et al. Nutrition warnings as front-of-pack labels: influence of design features on healthfulness perception and attentional capture. Public Health Nutr. 2017;20(18):3360\u0026ndash;71.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSong J, Brown MK, Tan M, MacGregor GA, Webster J, Campbell NRC, et al. Impact of color-coded and warning nutrition labelling schemes: A systematic review and network meta-analysis. PLoS Med. 2021;18(10):e1003765.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTaillie LS, Hall MG, Popkin BM, Ng SW, Murukutla N. Experimental Studies of Front-of-Package Nutrient Warning Labels on Sugar-Sweetened Beverages and Ultra-Processed Foods: A Scoping Review. Nutrients. 2020;12(2):569.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eThe Food Industry Association. Facts up front. GMA-FMI Voluntary Front-of-Pack Nutrition Labeling System [Internet]. 2012 [cited 2024 Apr 3]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.fmi.org/docs/health-and-wellness/nk_style_guide_for_implementers-2012.pdf?sfvrsn=2\u003c/span\u003e\u003cspan address=\"https://www.fmi.org/docs/health-and-wellness/nk_style_guide_for_implementers-2012.pdf?sfvrsn=2\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eActon RB, Rynard VL, Adams J, Bhawra J, Cameron AJ, Contreras-Manzano A, et al. Awareness, use and understanding of nutrition labels among adults from five countries: Findings from the 2018\u0026ndash;2020 International Food Policy Study. Appetite. 2023;180:106311.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"non-communicable diseases, nutrition label, front of pack labeling, warning labels, critical nutrients","lastPublishedDoi":"10.21203/rs.3.rs-7521567/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7521567/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eDiet-related non-communicable diseases (NCDs) are a leading cause of morbidity and mortality worldwide. Front-of-package warning labels (WLs) and nutrition facts labels (NFLs) have been implemented to help consumers make healthier choices, yet little is known about their use among individuals with NCDs or across different population groups. Understanding these patterns is essential to evaluate labeling policies and their potential to support healthier diets. This study aimed to examine the association between NCD diagnosis and WL use among Mexican adults, and to compare NFL use across Mexican, Mexican American, and non-Mexican American adults.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThis study used cross-sectional data from the 2021 and 2022 International Food Policy Study. We analyzed self-reported WL and NFL use and NCD diagnoses (diabetes, hypertension, heart disease, high cholesterol, cancer) among adults in Mexico, Mexican Americans, and non-Mexican Americans. Multivariate logistic regression models assessed associations between label use and NCD status, adjusting for sociodemographic and health-related confounders.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eAmong 23,951 adults, NFL use was highest among non-Mexican Americans (80.1%) and lowest among Mexicans (69.8%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). NFL use was significantly associated with diabetes and multiple NCDs in non-Mexican Americans. In Mexico, WL use (77.4%) exceeded NFL use. Mexicans with diabetes and high cholesterol reported that \u0026ldquo;Excess Sugar\u0026rdquo; and \u0026ldquo;Excess Sodium\u0026rdquo; labels were particularly helpful.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eLabeling use varied across populations and NCD status. Findings highlight the importance of promoting interpretive front-of-package labels, especially among individuals with NCDs, to encourage healthier food choices and reduce diet-related disease burden.\u003c/p\u003e","manuscriptTitle":"Association between the diagnosis of diet-related non-communicable diseases and the use of nutritional labeling among Mexican, Mexican American, and non-Mexican American adults: a cross-sectional study from the International Food Policy Study 2021– 2022","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-23 18:54:59","doi":"10.21203/rs.3.rs-7521567/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-10T16:31:48+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-05T12:02:36+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-05T10:40:54+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-03T00:38:51+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-02T12:54:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"27982257194971398537876491617386159816","date":"2025-10-01T16:24:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"239125352031890506715537290069938346234","date":"2025-09-30T18:16:51+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-29T05:39:35+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-21T22:57:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"111230055149359080686268534154404142805","date":"2025-09-18T15:09:39+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"143732155274489626941911506039624004177","date":"2025-09-18T07:00:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"320382060955293501162967437655346362053","date":"2025-09-17T19:41:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"176628961887572172304894453056193495119","date":"2025-09-17T02:50:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"57163991805792635727903862145240742471","date":"2025-09-16T11:40:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"248549745290329925455733576323823947358","date":"2025-09-15T18:31:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"309028703602159665751814104162417859983","date":"2025-09-15T17:18:28+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-15T17:03:41+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-09-05T08:46:38+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-04T12:56:40+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-04T12:55:42+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2025-09-03T00:36:38+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d9c684fc-72a0-4450-9ce4-25e62c1a50d8","owner":[],"postedDate":"September 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-08T16:12:48+00:00","versionOfRecord":{"articleIdentity":"rs-7521567","link":"https://doi.org/10.1186/s12889-025-25874-4","journal":{"identity":"bmc-public-health","isVorOnly":false,"title":"BMC Public Health"},"publishedOn":"2025-12-06 15:57:42","publishedOnDateReadable":"December 6th, 2025"},"versionCreatedAt":"2025-09-23 18:54:59","video":"","vorDoi":"10.1186/s12889-025-25874-4","vorDoiUrl":"https://doi.org/10.1186/s12889-025-25874-4","workflowStages":[]},"version":"v1","identity":"rs-7521567","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7521567","identity":"rs-7521567","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}