Background: Nutrition labels are a tool to inform and encourage the public to make healthier food choices, but little information is available about use in multi-ethnic adolescent populations in the U.S. The purpose of this study was to examine associations between the level of nutrition label usage and healthy/unhealthy eating behaviors among a statewide representative sample of 8th and 11th-grade students in Texas. Methods: We analyzed cross-sectional associations between the Nutrition Facts label use and eating behaviors from a statewide sample of 8th and 11th-grade students in Texas, (n = 4730, weighted n = 710,731, mean age = 14.7 ± 1.6 years; 49% female, 51% Hispanic), who completed the 2019–2020 Texas School Physical Activity and Nutrition (TX SPAN) survey. Students self-reported their level of nutrition label usage to make food choices (5-point Likert scale from “Never” to “Always”) and previous day consumption of 26 food items (13 healthy, 13 unhealthy). The 26 food items were used to calculate a Healthy Eating Index (HEI) score (0–100), a Healthy Foods Index (HFI) score (0–100), and an Unhealthy Foods Index (UFI) score (0–100). Weighted linear regression models were employed to examine the associations between self-reported use of nutrition labels to make food choices and HEI, HFI, and UFI scores. Marginal predicted means of HEI, HFI, and UFI scores were calculated post hoc from linear regression models. The odds of consuming specific individual food items for nutrition label usage were also calculated from weighted logistic regression models. All linear and logistic regression models were adjusted for grade, sex, Body Mass Index (BMI), race/ethnicity, economic disadvantage, and percentage of English language learners by school. Results: A total of 11.0% of students reported always/almost always using nutrition labels to make food choices, 27.9% reported sometimes using them, while 61.0% indicated they never/almost never used nutrition labels to make food choices. The average HEI score among students in the sample was 47.7 ± 5.9. Nutrition Facts label usage was significantly and positively associated with HEI (b = 5.79, 95%CI: 4.45, 7.12) and HFI (b = 7.28, 95%CI:4.48, 10.07), and significantly and negatively associated with UFI (b = −4.30, 95%CI: −6.25, −2.34). A dose–response relationship was observed between nutrition label usage and HEI, HFI, and UFI scores, such that the strength of these associations increased with each one-point increase in nutrition label usage. Students who reported using nutrition labels always/almost always to make food choices had significantly higher odds of consuming healthy foods including baked meat, nuts, brown bread, vegetables, whole fruit, and yogurt (OR_range = 1.31–3.07), and significantly lower odds of consuming unhealthy foods including chips, cake, candy, and soda (OR_range = 0.48–0.68) compared to students who reported never/almost never using the Nutrition Facts label. Conclusions: Using the Nutrition Facts labels to make food choices is beneficially associated with healthy and unhealthy eating among 8th and 11th-grade students, although the proportion of students using nutrition labels to make their food choices was low. Public health efforts should be made to improve nutrition literacy and encourage nutrition label use among secondary students in the United States.

Shortly after the identification of COVID-19, public health experts recommended the use of face masks and social distancing to slow the spread of the virus. Early research indicates that there are associations between gender, age, and mask-wearing behavior. The primary aim of this paper was to explore how demographics, location, and mask mandates may affect COVID-19 mitigation strategies such as mask-wearing and social distancing. A prospective, cross-sectional observational study was conducted in Houston, TX from January to April 2021 at three outdoor locations: an urban park, an urban park with a trail, and a farmer’s market. During each two-hour data collection period, trained observers recorded the total number of people in the designated spaces; people were categorized by approximate age, sex, race/ethnicity, physical activity level, social distancing, and mask adherence using the Systematic Observation of Mask Adherence and Distancing (SOMAD) protocol. Multivariable logistic regression was used to determine associations with gender, race, age, location, and the mask mandate. A total of 7778 observations were recorded after exclusion of inconclusive demographic data. Females had higher odds, reported as an odds ratio, of mask use than males (OR = 1.35, 95% CI 1.18–1.54). Compared to White individuals, Asian individuals had higher odds of mask use (OR = 1.84, 95% CI 1.48–2.30). The odds of mask use were higher while the Texas mask mandate was in effect (OR = 1.60, 95% CI 1.40–1.84). Regarding location, the odds of mask use were much higher in the urban park than in the urban park with a trail (OR = 13.33). Individuals had higher odds of social distancing at the urban park with a trail compared to the farmer’s market (OR = 4.61, 95% CI 4.10–5.17). Mask wearing and social distancing behaviors differ by demographics, locality, and mask mandate. Thus, state policies can be effective tools to encourage mask wearing for disease mitigation.

Objective: Assess the accuracy of the Texas School Physical Activity and Nutrition (SPAN) survey’s diet quality index against the 24 h recall-based Healthy Eating Index (HEI-2020). Methods: Fifty-one rising third and fourth graders (mean age 9.5 yrs., SD = 1.03 yrs.) from a summer program completed the SPAN survey and a 24 h dietary recall on the same day. The study compared SPAN HEI scores from survey food frequency items to HEI-2020 scores from recalls using Nutrition Data System for Research (NDS-R) software, evaluating correlations and agreement metrics. Results: SPAN HEI averaged 36.87 (SD = 3.78), while recall-derived HEI was 49.05 (SD = 11.92). The mean difference between indices was 12.18 (SD = 10.83), with an absolute difference of 13.51 (SD = 9.01). Bland–Altman analysis indicated limits of agreement from −9.05 to 33.40. Spearman correlation between SPAN HEI and recall HEI was r = 0.44 (p < 0.01), with an ICC of 0.45 (95% CI = 0.04, 0.68). Conclusions and Implications: After comparing HEI scores from both tools, SPAN HEI and HEI-2020 demonstrated a moderate correlation, indicating that SPAN HEI may serve as a practical and less burdensome alternative for large-scale dietary assessments. While further validation is needed, these findings suggest its potential utility in monitoring diet quality at the population level.