Selected age- and sex-specific percentiles are presented for 4,054 Mexican American children ages 1-18 years who were included in the third National Health and Nutrition Examination Survey (NHANES III, 1988-1994). These percentile values are compared with corresponding percentiles for Mexican Americans from the Hispanic Health and Nutrition Examination Survey (HHANES, 1982-1984). In each sex, the weight and weight/stature(2) percentiles from NHANES III were significantly larger than those from HHANES. For weight, the NHANES III values tended to be clearly larger after 11 years in males and females, and they were larger for weight/stature(2) at the 50th and 90th percentiles in each sex after 6 years. For stature, the NHANES III values were significantly larger at the 90th percentile among females, but the differences were not significant for any other percentiles among females or males. In comparison with non-Hispanic White children, Mexican American children tend to be shorter and heavier, especially after the preschool period. The similarity of the findings for stature from NHANES III and HHANES indicates that the shorter statures of Mexican Americans are not cohort-specific. The tendency to larger values for weight/stature(2) in Mexican Americans has important public heath implications since this ratio tends to track after early childhood, and high ratios in adulthood constitute an important risk factor for common diseases such as diabetes mellitus and coronary heart disease. Am. J. Hum. Biol. 11:673-686, 1999. Copyright 1999 Wiley-Liss, Inc.
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http://dx.doi.org/10.1002/(SICI)1520-6300(199909/10)11:5<673::AID-AJHB10>3.0.CO;2-I | DOI Listing |
Glob Epidemiol
June 2025
Business Analytics (BANA) Program, Business School, University of Colorado, 1475 Lawrence St. Denver, CO 80217-3364, USA.
AI-assisted data analysis can help risk analysts better understand exposure-response relationships by making it relatively easy to apply advanced statistical and machine learning methods, check their assumptions, and interpret their results. This paper demonstrates the potential of large language models (LLMs), such as ChatGPT, to facilitate statistical analyses, including survival data analyses, for health risk assessments. Through AI-guided analyses using relatively recent and advanced methods such as Individual Conditional Expectation (ICE) plots using Random Survival Forests and Heterogeneous Treatment Effects (HTEs) estimated using Causal Survival Forests, population-level exposure-response functions can be disaggregated into individual-level exposure-response functions.
View Article and Find Full Text PDFJ Affect Disord
January 2025
Department of Anesthesiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China; Ambulatory Surgery Center, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China. Electronic address:
Background: Individuals with metabolic syndrome (MetS) are at a higher risk of developing depressive symptoms, with inflammation hypothesized to mediate this association. This study used data from the National Health and Nutrition Examination Survey (NHANES) (2015-2020) to investigate the relationship between MetS and depression and assess the mediating role of inflammatory markers.
Methods: This cross-sectional study included 20,520 participants.
Nutrients
January 2025
Division of Epidemiology, Vanderbilt Epidemiology Center, Department of Medicine, Vanderbilt University Medical Center, Vanderbilt University School of Medicine, Nashville, TN 37203, USA.
Unlabelled: Metabolic dysfunction associated steatotic liver disease (MASLD) has been associated with increased risks of all-cause and cardiovascular disease (CVD) mortality. Identification of modifiable risk factors that may contribute to higher risks of mortality could facilitate targeted and intensive intervention strategies in this population. This study aims to examine whether the magnesium depletion score (MDS) is associated with all-cause and CVD mortality among individuals with MASLD or metabolic and alcohol associated liver disease (MetALD).
View Article and Find Full Text PDFNutrients
January 2025
Office of Minority Health and Health Disparities Research, Georgetown Lombardi Comprehensive Cancer Center, Georgetown University, 1010 New Jersey Ave. SE, Washington, DC 20003, USA.
Background/objectives: Nutrient-poor diet quality is a major driver of the global burden of metabolic syndrome (MetS). The US ranks among the lowest in diet quality and has the highest rate of immigration, which may present unique challenges for non-US-native populations who experience changes in access to health-promoting resources. This study examined associations among MetS, nativity status, diet quality, and interaction effects of race-ethnicity among Hispanic, Asian, Black, and White US-native and non-US-native adults.
View Article and Find Full Text PDFFront Nutr
January 2025
Chair of Epidemiology, University of Augsburg, Augsburg, Germany.
Objective: Monitoring dietary habits is crucial for identifying shortcomings and delineating countermeasures. About 20 years after the last population-based surveys in Bavaria and Germany, dietary habits were assessed to describe the intake distributions and compare these with recommendations at food and nutrient level.
Methods: The 3rd Bavarian Food Consumption Survey (BVS III) was designed as a diet survey representative of adults in Bavaria; from 2021 to 2023, repeated 24-h diet recalls were collected by telephone using the software GloboDiet©.
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