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Varela JJ, Mattei J, Sotres-Alvarez D, Mossavar-Rahmani Y, McClain AC, Maldonado LE, Daviglus ML, Stephenson BJK. Examining Generalizability across Different Surveys: Comparing Nutrient-Based Food Patterns and Their Cross-Sectional Associations with Cardiometabolic Health in the United States Hispanic/Latino Adults. Curr Dev Nutr 2024; 8:103797. [PMID: 39104805 PMCID: PMC11298582 DOI: 10.1016/j.cdnut.2024.103797] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2024] [Revised: 06/05/2024] [Accepted: 06/11/2024] [Indexed: 08/07/2024] Open
Abstract
Background Ethnicity, cultural background, and geographic location differ significantly within the United States Hispanic/Latino population. These variations can greatly define diet and its relationship with cardiometabolic disease, thus influencing generalizability of results. Objectives We aimed to examine nutrient-based food patterns (NBFPs) of Hispanic/Latino adults and their association with cardiometabolic risk factors (dyslipidemia, hypertension, obesity, diabetes) across 2 United States population-based studies with differing sampling strategies. Methods Data were collected from Mexican or other Hispanic adult participants from 2007-2012 National Health and Nutrition Examination Survey (NHANES) (n = 3605) and 2007-2011 Hispanic Community Health Survey/Study of Latinos (HCHS/SOL, n = 14,416). NBFPs were derived using factor analysis on nutrient intake data estimated from 24-h dietary recalls and interpreted using common foods in which these nutrients are prominent. Cross-sectional associations between NBFPs (quintiles) and cardiometabolic risk factors, defined by clinical measures and self-report, were estimated using survey-weighted multivariable-adjusted logistic models, accounting for multiple testing. Results Five NBFPs were identified in both studies: 1) meats, 2) grains/legumes, 3) fruits/vegetables, 4) dairy, and 5) fats/oils. Associations with cardiometabolic risk factors differed by NBFP and study. In HCHS/SOL, the odds of diabetes were lower for persons in the highest quintile of meats NBFP (odds ratio [OR]: 0.73; 95% confidence interval [CI]: 0.58, 0.92) and odds were higher for those in the lowest quintile of fruits/vegetables (OR: 0.71; 95% CI: 0.55, 0.93) compared to those in the third (moderate intake) quintile. Those in the fourth quintile of dairy NBFP had higher odds of hypertension than those in the third quintile (OR: 1.31; 95% CI: 1.01, 1.70). In NHANES, the odds of hypertension were higher for those in the fourth quintile of dairy (OR: 1.88; 95% CI: 1.10, 3.24) than those in the third quintile. Conclusions Diet-disease relationships among Hispanic/Latino adults vary according to 2 population-based studies. These differences have research and practical implications when generalizing inferences on heterogeneous underrepresented populations.
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Affiliation(s)
- Jeanette J Varela
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, United States
| | - Josiemer Mattei
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, United States
| | - Daniela Sotres-Alvarez
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Yasmin Mossavar-Rahmani
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Amanda C McClain
- School of Exercise and Nutritional Sciences, College of Health and Human Services, San Diego State University College of Health and Human Services, San Diego, CA, United States
| | - Luis E Maldonado
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Martha L Daviglus
- Institute of Minority Health Research, University of Illinois at Chicago, Chicago, IL, United States
| | - Briana JK Stephenson
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, United States
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Jayedi A, Shafiei Neyestanak M, Djafarian K, Shab-Bidar S. Temporal patterns of energy intake identified by the latent class analysis in relation to prevalence of overweight and obesity in Iranian adults. Br J Nutr 2023; 130:2002-2012. [PMID: 37132327 DOI: 10.1017/s000711452300096x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
We aimed to identify temporal patterns of energy intake and investigate their association with adiposity. We performed a cross-sectional study of 775 adults in Iran. Information about eating occasions across the day was collected by three 24-h dietary recalls. Latent class analysis (LCA) was used to identify temporal eating patterns based on whether or not an eating occasion occurred within each hour of the day. We applied binary logistic regression to estimate the OR and 95 % CI of overweight and obesity (defined as BMI of 25-29·9 and ≥ 30 kg/m2, respectively) across temporal eating patterns while controlling for potential confounders. LCA grouped participants into three exclusive sub-groups named 'Conventional', 'Earlier breakfast' and 'Later lunch'. The 'Conventional' class was characterised by high probability of eating occasions at conventional meal times. 'Earlier breakfast' class was characterised by high probability of a breakfast eating occasion 1 h before the conventional pattern and a dinner eating occasion 1 h after the conventional pattern, and the 'Later lunch' class was characterised by a high probability of a lunch eating occasion 1 h after the conventional pattern. Participants in the 'Earlier breakfast' pattern had a lower likelihood of obesity (adjusted OR: 0·56, 95 % CI: 0·35, 0·95) as compared with the 'Conventional' pattern. There was no difference in the prevalence of obesity or overweight between participants in the 'Later lunch' and the 'Conventional' patterns. We found an inverse association between earlier eating pattern and the likelihood of obesity, but reverse causation may be a plausible explanation.
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Affiliation(s)
- Ahmad Jayedi
- Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences, Tehran, Iran
| | - Mahdi Shafiei Neyestanak
- Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Kurosh Djafarian
- Department of Clinical Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences, Tehran, Iran
| | - Sakineh Shab-Bidar
- Social Determinants of Health Research Center, Semnan University of Medical Sciences, Semnan, Iran
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Jeong S, Lee H, Jung S, Kim JY, Park S. Higher energy consumption in the evening is associated with increased odds of obesity and metabolic syndrome: findings from the 2016-2018 Korea National Health and Nutrition Examination Survey (7th KNHANES). Epidemiol Health 2023; 45:e2023087. [PMID: 37752794 PMCID: PMC10867517 DOI: 10.4178/epih.e2023087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2023] [Accepted: 09/04/2023] [Indexed: 09/28/2023] Open
Abstract
OBJECTIVES Chrono-nutrition emphasizes meal timing in preventing obesity and metabolic disorders. This study explores the impact of temporal dietary patterns (TDPs) on obesity and metabolic syndrome (MetS) in Korean adults aged 20 years to 65 years. METHODS We utilized dynamic time warping method and Kernel k-means clustering to investigate diet quality and the odds ratios (ORs) of obesity and MetS with different TDPs using data from the 7th Korea National Health and Nutrition Examination Survey. RESULTS Participants were divided into three groups based on relative energy intake over 24 hours. After adjusting for age and gender, Cluster 3 (with the highest proportion of energy intake in the evening) had the lowest Healthy Eating Index scores compared to other clusters. Following adjustment for key covariates, Cluster 3 showed the highest values for body mass index, waist circumference, blood pressure, total cholesterol, and triglycerides. Compared to Cluster 1 (with a lower proportion of energy intake in the evening), Cluster 2 and Cluster 3 had ORs for obesity of 1.12 (95% confidence interval [CI], 0.97 to 1.30) and 1.19 (95% CI, 1.03 to 1.37), respectively. For MetS, the ORs were 1.26 (95% CI, 1.08 to 1.48) and 1.37 (95% CI, 1.17 to 1.61) when comparing Cluster 2 and Cluster 3 to Cluster 1. CONCLUSIONS This study reveals that individuals with higher energy intake in the evening have increased odds of obesity and MetS, even after adjusting for major covariates, including age and total energy intake.
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Affiliation(s)
- Sarang Jeong
- The Korean Institute of Nutrition, Hallym University, Chuncheon, Korea
| | - Hajoung Lee
- EyeLight Data Science Laboratory, Seoul National University College of Medicine, Seoul, Korea
- Department of Ophthalmology, Seoul National University Hospital, Seoul, Korea
| | - Sukyoung Jung
- Chungnam National University Hospital Biomedical Research Institute, Daejeon, Korea
- Department of Epidemiology, Milken Institute School of Public Health, The George Washington University, Washington, DC, USA
| | - Jee Young Kim
- National Food Safety Information Service, Seoul, Korea
| | - Sohyun Park
- The Korean Institute of Nutrition, Hallym University, Chuncheon, Korea
- Department of Food Science and Nutrition, Hallym University, Chuncheon, Korea
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4
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Chen YE, Loy SL, Chen LW. Chrononutrition during Pregnancy and Its Association with Maternal and Offspring Outcomes: A Systematic Review and Meta-Analysis of Ramadan and Non-Ramadan Studies. Nutrients 2023; 15:nu15030756. [PMID: 36771469 PMCID: PMC9921927 DOI: 10.3390/nu15030756] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 01/19/2023] [Accepted: 01/30/2023] [Indexed: 02/05/2023] Open
Abstract
Much evidence suggests that food intakes and eating patterns are major determinants of the phase of peripheral circadian clocks, and desynchronization between them is thought to contribute to the development of metabolic disorders. However, much remains to be understood about how different dimensions of chrononutrition during pregnancy affect pregnant women's and their offspring's health outcomes. Therefore, we systematically reviewed and integrated all emerging evidence on chrononutrition during pregnancy (including meal skipping, meal frequency, night eating, and (Ramadan) fasting) and their relationships with maternal and offspring outcomes. The results suggest that meal skipping and night eating during pregnancy were generally associated with adverse pregnancy and birth outcomes, whereas no strong conclusion could be reached for meal frequency. In our meta-analysis, Ramadan fasting did not seem to be related with birth weight or gestational age at birth, but evidence for other mother-offspring outcomes was inconsistent. To further elucidate the effect of chrononutrition factors on maternal and offspring health outcomes, larger and well-conducted prospective cohort and interventional studies are needed. In addition, information on covariates such as physical activity, sleep, diet quality and quantity, fasting days, fasting period per day, and trimester exposure should also be collected and considered during analysis.
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Affiliation(s)
- Yu-En Chen
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, No. 17 Xu-Zhou Road, Taipei 10055, Taiwan
| | - See Ling Loy
- Department of Reproductive Medicine, KK Women’s and Children’s Hospital, Singapore 229899, Singapore
- Duke-NUS Medical School, Singapore 169857, Singapore
| | - Ling-Wei Chen
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, No. 17 Xu-Zhou Road, Taipei 10055, Taiwan
- Master of Public Health Program, College of Public Health, National Taiwan University, No. 17 Xu-Zhou Road, Taipei 10055, Taiwan
- Correspondence:
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Lee BY, Ordovás JM, Parks EJ, Anderson CAM, Barabási AL, Clinton SK, de la Haye K, Duffy VB, Franks PW, Ginexi EM, Hammond KJ, Hanlon EC, Hittle M, Ho E, Horn AL, Isaacson RS, Mabry PL, Malone S, Martin CK, Mattei J, Meydani SN, Nelson LM, Neuhouser ML, Parent B, Pronk NP, Roche HM, Saria S, Scheer FAJL, Segal E, Sevick MA, Spector TD, Van Horn L, Varady KA, Voruganti VS, Martinez MF. Research gaps and opportunities in precision nutrition: an NIH workshop report. Am J Clin Nutr 2022; 116:1877-1900. [PMID: 36055772 PMCID: PMC9761773 DOI: 10.1093/ajcn/nqac237] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Revised: 04/06/2022] [Accepted: 08/30/2022] [Indexed: 02/01/2023] Open
Abstract
Precision nutrition is an emerging concept that aims to develop nutrition recommendations tailored to different people's circumstances and biological characteristics. Responses to dietary change and the resulting health outcomes from consuming different diets may vary significantly between people based on interactions between their genetic backgrounds, physiology, microbiome, underlying health status, behaviors, social influences, and environmental exposures. On 11-12 January 2021, the National Institutes of Health convened a workshop entitled "Precision Nutrition: Research Gaps and Opportunities" to bring together experts to discuss the issues involved in better understanding and addressing precision nutrition. The workshop proceeded in 3 parts: part I covered many aspects of genetics and physiology that mediate the links between nutrient intake and health conditions such as cardiovascular disease, Alzheimer disease, and cancer; part II reviewed potential contributors to interindividual variability in dietary exposures and responses such as baseline nutritional status, circadian rhythm/sleep, environmental exposures, sensory properties of food, stress, inflammation, and the social determinants of health; part III presented the need for systems approaches, with new methods and technologies that can facilitate the study and implementation of precision nutrition, and workforce development needed to create a new generation of researchers. The workshop concluded that much research will be needed before more precise nutrition recommendations can be achieved. This includes better understanding and accounting for variables such as age, sex, ethnicity, medical history, genetics, and social and environmental factors. The advent of new methods and technologies and the availability of considerably more data bring tremendous opportunity. However, the field must proceed with appropriate levels of caution and make sure the factors listed above are all considered, and systems approaches and methods are incorporated. It will be important to develop and train an expanded workforce with the goal of reducing health disparities and improving precision nutritional advice for all Americans.
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Affiliation(s)
- Bruce Y Lee
- Health Policy and Management, City University of New York Graduate School of Public Health and Health Policy, New York, NY, USA
| | - José M Ordovás
- USDA-Human Nutrition Research Center on Aging at Tufts University, Boston, MA, USA
| | - Elizabeth J Parks
- Nutrition and Exercise Physiology, University of Missouri School of Medicine, MO, USA
| | | | - Albert-László Barabási
- Network Science Institute and Department of Physics, Northeastern University, Boston, MA, USA
| | | | - Kayla de la Haye
- Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Valerie B Duffy
- Allied Health Sciences, University of Connecticut, Storrs, CT, USA
| | - Paul W Franks
- Novo Nordisk Foundation, Hellerup, Denmark, Copenhagen, Denmark, and Lund University Diabetes Center, Sweden
- The Lund University Diabetes Center, Malmo, SwedenInsert Affiliation Text Here
| | - Elizabeth M Ginexi
- National Institutes of Health, Office of Behavioral and Social Sciences Research, Bethesda, MD, USA
| | - Kristian J Hammond
- Computer Science, Northwestern University McCormick School of Engineering, IL, USA
| | - Erin C Hanlon
- Department of Medicine, The University of Chicago, Chicago, IL, USA
| | - Michael Hittle
- Epidemiology and Clinical Research, Stanford University, Stanford, CA, USA
| | - Emily Ho
- Public Health and Human Sciences, Linus Pauling Institute, Oregon State University, Corvallis, OR, USA
| | - Abigail L Horn
- Information Sciences Institute, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA
| | | | | | - Susan Malone
- Rory Meyers College of Nursing, New York University, New York, NY, USA
| | - Corby K Martin
- Ingestive Behavior Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA, USA
| | - Josiemer Mattei
- Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Simin Nikbin Meydani
- USDA-Human Nutrition Research Center on Aging at Tufts University, Boston, MA, USA
| | - Lorene M Nelson
- Epidemiology and Population Health, Stanford University, Stanford, CA, USA
| | | | - Brendan Parent
- Grossman School of Medicine, New York University, New York, NY, USA
| | | | - Helen M Roche
- UCD Conway Institute, School of Public Health, Physiotherapy, and Sports Science, University College Dublin, Dublin, Ireland
| | - Suchi Saria
- Johns Hopkins University, Baltimore, MD, USA
| | - Frank A J L Scheer
- Brigham and Women's Hospital, Boston, MA, USA
- Medicine and Neurology, Harvard Medical School, Boston, MA, USA
| | - Eran Segal
- Computer Science and Applied Math, Weizmann Institute of Science, Rehovot, Israel
| | - Mary Ann Sevick
- Grossman School of Medicine, New York University, New York, NY, USA
| | - Tim D Spector
- Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom
| | - Linda Van Horn
- Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Krista A Varady
- Kinesiology and Nutrition, University of Illinois at Chicago, Chicago, IL, USA
| | - Venkata Saroja Voruganti
- Nutrition and Nutrition Research Institute, Gillings School of Public Health, The University of North Carolina, Chapel Hill, NC, USA
| | - Marie F Martinez
- Health Policy and Management, City University of New York Graduate School of Public Health and Health Policy, New York, NY, USA
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6
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The Discovery of Data-Driven Temporal Dietary Patterns and a Validation of Their Description Using Energy and Time Cut-Offs. Nutrients 2022; 14:nu14173483. [PMID: 36079740 PMCID: PMC9460307 DOI: 10.3390/nu14173483] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Revised: 08/18/2022] [Accepted: 08/21/2022] [Indexed: 12/01/2022] Open
Abstract
Data-driven temporal dietary patterning (TDP) methods were previously developed. The objectives were to create data-driven temporal dietary patterns and assess concurrent validity of energy and time cut-offs describing the data-driven TDPs by determining their relationships to BMI and waist circumference (WC). The first day 24-h dietary recall timing and amounts of energy for 17,915 U.S. adults of the National Health and Nutrition Examination Survey 2007−2016 were used to create clusters representing four TDPs using dynamic time warping and the kernel k-means clustering algorithm. Energy and time cut-offs were extracted from visualization of the data-derived TDPs and then applied to the data to find cut-off-derived TDPs. The strength of TDP relationships with BMI and WC were assessed using adjusted multivariate regression and compared. Both methods showed a cluster, representing a TDP with proportionally equivalent average energy consumed during three eating events/day, associated with significantly lower BMI and WC compared to the other three clusters that had one energy intake peak/day at 13:00, 18:00, and 19:00 (all p < 0.0001). Participant clusters of the methods were highly overlapped (>83%) and showed similar relationships with obesity. Data-driven TDP was validated using descriptive cut-offs and hold promise for obesity interventions and translation to dietary guidance.
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Song X, Wang H, Su C, Wang Z, Du W, Hu H, Huang F, Zhang J, Jia X, Jiang H, Ouyang Y, Li L, Bai J, Zhang X, Ding G, Zhang B. Trajectories of energy intake distribution and subsequent risk of hyperglycemia among Chinese adults: findings from the China Health and Nutrition Survey (1997-2018). Eur J Nutr 2022; 61:1417-1427. [PMID: 34837523 PMCID: PMC8921126 DOI: 10.1007/s00394-021-02745-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2021] [Accepted: 09/29/2021] [Indexed: 02/02/2023]
Abstract
AIMS Few studies have examined the secular trend of the energy intake distribution, and its effect on future risk of hyperglycemia. This study aims to describe trajectories of energy intake distribution over 12 years and relate them to subsequent risk of hyperglycemia over 9 years of follow-up. METHODS Our study used ten waves of data from the CHNS survey, a population-based longitudinal survey in China, ongoing since 1989. We examined a cohort of adult participants who were free from diabetes but had at least three waves of dietary data from 1997 to 2009. We assessed energy intake using three consecutive 24 h recalls. We used these data to identify trajectory groups of energy intake distribution by multi-trajectory model based on energy intake proportions of breakfast, lunch, and dinner. We followed up participants for hyperglycemia, diabetes, and impaired fasting glucose for 9 years from 2009 to 2018. Outcomes were ascertained with fasting glucose, serum HbA1c, and self-report of diabetes and/or glucose-lowering medication. We estimated relative risk (RR) for hyperglycemia, diabetes, and impaired fasting glucose by identified trajectory groups using multilevel mixed-effects modified Poisson regression with robust (sandwich) estimation of variance. Gender difference was additionally examined. RESULTS A total of 4417 participants were included. Four trajectory groups were identified, characterized and labeled by "Energy evenly distributed with steady trend group" (Group 1), "Dinner and lunch energy dominant with relatively steady trend group" (Group 2), "Dinner energy dominant with increasing trend and breakfast energy with declining trend group" (Group 3), and "breakfast and dinner energy dominant with increasing trend group" (Group 4). During 48,091 person-years, 1053 cases of incident hyperglycemia occurred, 537 cases of incident diabetes occurred, and 516 cases of impaired fasting glucose occurred. Compared with Group 1, Group 3 was associated with higher subsequent risk of incident hyperglycemia in 9 years of follow-up (RR = 1.28, 95% CI = 1.02, 1.61). No association was found for incident diabetes and impaired fasting glucose. Among males, Group 3 was associated with higher risk of incident hyperglycemia in 9 years of follow-up (RR = 1.44, 95% CI = 1.07, 1.94). No relationship was found in females. CONCLUSIONS Energy intake distribution characterized by over 40% of energy intake from dinner with a rising trend over years was associated with higher long-term risk of hyperglycemia in Chinese adults.
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Affiliation(s)
- Xiaoyun Song
- Chinese Center for Disease Control and Prevention, National Institute for Nutrition and Health, Beijing, 100050 China
| | - Huijun Wang
- Chinese Center for Disease Control and Prevention, National Institute for Nutrition and Health, Beijing, 100050 China
| | - Chang Su
- Chinese Center for Disease Control and Prevention, National Institute for Nutrition and Health, Beijing, 100050 China
| | - Zhihong Wang
- Chinese Center for Disease Control and Prevention, National Institute for Nutrition and Health, Beijing, 100050 China
| | - Wenwen Du
- Chinese Center for Disease Control and Prevention, National Institute for Nutrition and Health, Beijing, 100050 China
| | - Haojie Hu
- Chinese Center for Disease Control and Prevention, National Institute for Nutrition and Health, Beijing, 100050 China
| | - Feifei Huang
- Chinese Center for Disease Control and Prevention, National Institute for Nutrition and Health, Beijing, 100050 China
| | - Jiguo Zhang
- Chinese Center for Disease Control and Prevention, National Institute for Nutrition and Health, Beijing, 100050 China
| | - Xiaofang Jia
- Chinese Center for Disease Control and Prevention, National Institute for Nutrition and Health, Beijing, 100050 China
| | - Hongru Jiang
- Chinese Center for Disease Control and Prevention, National Institute for Nutrition and Health, Beijing, 100050 China
| | - Yifei Ouyang
- Chinese Center for Disease Control and Prevention, National Institute for Nutrition and Health, Beijing, 100050 China
| | - Li Li
- Chinese Center for Disease Control and Prevention, National Institute for Nutrition and Health, Beijing, 100050 China
| | - Jing Bai
- Chinese Center for Disease Control and Prevention, National Institute for Nutrition and Health, Beijing, 100050 China
| | - Xiaofan Zhang
- Chinese Center for Disease Control and Prevention, National Institute for Nutrition and Health, Beijing, 100050 China
| | - Gangqiang Ding
- Chinese Center for Disease Control and Prevention, National Institute for Nutrition and Health, Beijing, 100050 China
| | - Bing Zhang
- Chinese Center for Disease Control and Prevention, National Institute for Nutrition and Health, Beijing, 100050 China
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Veronda AC, Irish LA. Evaluation of the Chrononutrition Profile - Questionnaire in an online community sample of adults. Eat Behav 2022; 45:101633. [PMID: 35533464 PMCID: PMC9899487 DOI: 10.1016/j.eatbeh.2022.101633] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Revised: 04/15/2022] [Accepted: 04/20/2022] [Indexed: 02/07/2023]
Abstract
Chrononutrition (i.e., circadian timing of food intake) has been linked to indicators of health status such as body weight and insulin resistance. A measure of general chrononutrition patterns, the Chrononutrition Profile - Questionnaire, has been developed and preliminary evidence of validity and reliability of the measure has been documented in a homogenous group of undergraduates. However, this measure has not yet been validated in an online, community-based sample. The present study therefore aimed to evaluate the validity of the Chrononutrition Profile - Questionnaire in a web-based community sample. Analyses suggested that the Chrononutrition Profile - Questionnaire displays acceptable validity for use in diverse community samples of adults, with moderate to strong correlations (r = 0.39-0.91) between the Chrononutrition Profile - Questionnaire and measures of dietary intake and sleep. This measure is suitable for use in a variety of settings, by stakeholders and scientists, and may contribute to future development of health behavior interventions and research programs centered around chrononutrition.
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Affiliation(s)
- Allison C. Veronda
- Department of Psychology, North Dakota State University, Fargo, ND, United States,Corresponding author at: Dept. 2765, P.O. Box 6050, Fargo, ND 58108-6050, United States., (A.C. Veronda), (L.A. Irish)
| | - Leah A. Irish
- Department of Psychology, North Dakota State University, Fargo, ND, United States,Center for Biobehavioral Research, Sanford Research-North, Fargo, ND, United States
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9
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Lin L, Guo J, Aqeel MM, Gelfand SB, Delp EJ, Bhadra A, Richards EA, Hennessy E, Eicher-Miller HA. Joint temporal dietary and physical activity patterns: associations with health status indicators and chronic diseases. Am J Clin Nutr 2022; 115:456-470. [PMID: 34617560 PMCID: PMC8827100 DOI: 10.1093/ajcn/nqab339] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2021] [Accepted: 10/01/2021] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Diet and physical activity (PA) are independent risk factors for obesity and chronic diseases including type 2 diabetes mellitus (T2DM) and metabolic syndrome (MetS). The temporal sequence of these exposures may be used to create patterns with relations to health status indicators. OBJECTIVES The objectives were to create clusters of joint temporal dietary and PA patterns (JTDPAPs) and to determine their association with health status indicators including BMI, waist circumference (WC), fasting plasma glucose, glycated hemoglobin, triglycerides, HDL cholesterol, total cholesterol, blood pressure, and disease status including obesity, T2DM, and MetS in US adults. METHODS A 24-h dietary recall and random day of accelerometer data of 1836 participants from the cross-sectional NHANES 2003-2006 data were used to create JTDPAP clusters by constrained dynamic time warping, coupled with a kernel k-means clustering algorithm. Multivariate regression models determined associations between the 4 JTDPAP clusters and health and disease status indicators, controlling for potential confounders and adjusting for multiple comparisons. RESULTS A JTDPAP cluster with proportionally equivalent energy consumed at 2 main eating occasions reaching ≤1600 and ≤2200 kcal from 11:00 to 13:00 and from 17:00 to 20:00, respectively, and the highest PA counts among 4 clusters from 08:00 to 20:00, was associated with significantly lower BMI (P < 0.0001), WC (P = 0.0001), total cholesterol (P = 0.02), and odds of obesity (OR: 0.2; 95% CI: 0.1, 0.5) than a JTDPAP cluster with proportionally equivalent energy consumed reaching ≤1600 and ≤1800 kcal from 11:00 to 14:00 and from 17:00 to 21:00, respectively, and high PA counts from 09:00 to 12:00. CONCLUSIONS The joint temporally patterned sequence of diet and PA can be used to cluster individuals with meaningful associations to BMI, WC, total cholesterol, and obesity. Temporal patterns hold promise for future development of lifestyle patterns that integrate additional temporal and contextual activities.
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Affiliation(s)
- Luotao Lin
- Department of Nutrition Science, Purdue University, West Lafayette, IN, USA
| | - Jiaqi Guo
- School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA
| | - Marah M Aqeel
- Department of Nutrition Science, Purdue University, West Lafayette, IN, USA
| | - Saul B Gelfand
- School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA
| | - Edward J Delp
- School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA
| | - Anindya Bhadra
- Department of Statistics, Purdue University, West Lafayette, IN, USA
| | | | - Erin Hennessy
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA
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Song X, Wang H, Su C, Wang Z, Du W, Huang F, Zhang J, Jia X, Jiang H, Ouyang Y, Li L, Bai J, Zhang X, Ding G, Zhang B. Trajectories of Energy Intake Distribution and Risk of Dyslipidemia: Findings from the China Health and Nutrition Survey (1991-2018). Nutrients 2021; 13:3488. [PMID: 34684489 PMCID: PMC8538511 DOI: 10.3390/nu13103488] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Revised: 09/24/2021] [Accepted: 09/28/2021] [Indexed: 01/21/2023] Open
Abstract
Few studies have examined the secular trend of energy intake distribution. This study aims to describe trajectories of energy intake distribution and determine their association with dyslipidemia risk. Data of 2843 adult participants from the China Health and Nutrition Survey (CHNS) were analyzed. Trajectory groups of energy intake distribution were identified by multi-trajectory model over 27 years. Multilevel mixed-effects modified Poisson regression with robust estimation of variance was used to calculate risk ratio for incident dyslipidemia in a 9-year follow-up. Four trajectory groups were identified: "Energy evenly distributed group" (Group 1), "Lunch and dinner energy dominant group" (Group 2), "Dinner energy dominant group" (Group 3), "breakfast and dinner energy dominant group" (Group 4). Compared with Group 1, Group 3 was associated with higher risk of dyslipidemia (RR = 1.48, 95% CI = 1.26, 1.75), hypercholesterolemia (RR = 1.96, 95% CI = 1.37, 2.81) and high low-density lipoproteins cholesterols (LDL-C) (RR = 2.41, 95% CI = 1.82, 3.20). A U-shape was observed between cumulative average proportion of dinner energy and dyslipidemia risk (p for non-linear = 0.01), with stronger relationship at 40% and above. Energy intake distribution characterized by higher proportion of dinner energy, especially over 40% was associated with higher dyslipidemia risk in Chinese adults.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | | | | | - Bing Zhang
- Chinese Center for Disease Control and Prevention, National Institute for Nutrition and Health, Beijing 100050, China; (X.S.); (H.W.); (C.S.); (Z.W.); (W.D.); (F.H.); (J.Z.); (X.J.); (H.J.); (Y.O.); (L.L.); (J.B.); (X.Z.); (G.D.)
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11
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Entwistle MR, Schweizer D, Cisneros R. Dietary patterns related to total mortality and cancer mortality in the United States. Cancer Causes Control 2021; 32:1279-1288. [PMID: 34382130 PMCID: PMC8492557 DOI: 10.1007/s10552-021-01478-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Accepted: 07/05/2021] [Indexed: 01/07/2023]
Abstract
Purpose This study investigated the association between dietary patterns, total mortality, and cancer mortality in the United States. Methods We identified the four major dietary patterns at baseline from 13,466 participants of the NHANES III cohort using principal component analysis (PCA). Dietary patterns were categorized into ‘prudent’ (fruits and vegetables), ‘western’ (red meat, sweets, pastries, oils), ‘traditional’ (red meat, legumes, potatoes, bread), and ‘fish and alcohol’. We estimated hazard ratios for total mortality, and cancer mortality using Cox regression models. Results A total of 4,963 deaths were documented after a mean follow-up of 19.59 years. Higher adherence to the ‘prudent’ pattern was associated with the lowest risk of total mortality (5th vs. 1st quintile HR 0.90, 95% CI 0.82–0.98), with evidence that all-cause mortality decreased as consumption of the pattern increased. No evidence was found that the ‘prudent’ pattern reduced cancer mortality. The ‘western’ and the ‘traditional’ patterns were associated with up to 22% and 16% increased risk for total mortality (5th vs. 1st quintile HR 1.22, 95% CI 1.11–1.34; and 5th vs. 1st quintile HR 1.16, 95% CI 1.06–1.27, respectively), and up to 33% and 15% increased risk for cancer mortality (5th vs. 1st quintile HR 1.33, 95% CI 1.10–1.62; and 5th vs. 1st quintile HR 1.15, 95% CI 1.06–1.24, respectively). The associations between adherence to the ‘fish and alcohol’ pattern and total mortality, and cancer mortality were not statistically significant. Conclusion Higher adherence to the ‘prudent’ diet decreased the risk of all-cause mortality but did not affect cancer mortality. Greater adherence to the ‘western’ and ‘traditional’ diet increased the risk of total mortality and mortality due to cancer.
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Affiliation(s)
- Marcela R Entwistle
- Department of Public Health, College of Social Sciences, Humanities and Arts, University of California, 5200 North Lake Road, Merced, CA, 95343, USA
| | | | - Ricardo Cisneros
- Department of Public Health, College of Social Sciences, Humanities and Arts, University of California, 5200 North Lake Road, Merced, CA, 95343, USA.
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12
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Aqeel M, Guo J, Lin L, Gelfand S, Delp E, Bhadra A, Richards EA, Hennessy E, Eicher-Miller HA. Temporal physical activity patterns are associated with obesity in U.S. adults. Prev Med 2021; 148:106538. [PMID: 33798532 PMCID: PMC8489165 DOI: 10.1016/j.ypmed.2021.106538] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Revised: 01/31/2021] [Accepted: 03/28/2021] [Indexed: 11/26/2022]
Abstract
Few attempts have been made to incorporate multiple aspects of physical activity (PA) to classify patterns linked with health. Temporal PA patterns integrating time and activity counts were created to determine their association with health status. Accelerometry data from the National Health and Nutrition Examination Survey 2003-2006 was used to pattern PA counts and time of activity from 1999 adults with one weekday of activity. Dynamic time warping and kernel k-means clustering partitioned 4 participant clusters representing temporal PA patterns. Multivariate regression models determined associations between clusters and health status indicators and obesity, type 2 diabetes, and metabolic syndrome. Cluster 1 with a temporal PA pattern of the lowest activity counts reaching 4.8e4 cph from 6:00-23:00 was associated with higher body mass index (BMI) (β = 2.5 ± 0.6 kg/m2, 95% CI: 1.0, 4.1), higher waist circumference (WC) (β = 6.4 ± 1.3 cm, 95% CI: 2.8, 10.0), and higher odds of obesity (OR: 2.4; 95% CI: 1.3, 4.4) compared with Cluster 3 with activity counts reaching 9.6e4-1.2e5 cph between 16:00-21:00. Cluster 1 was also associated with higher BMI (β = 1.5 ± 0.5 kg/m2, 95% CI: 0.1, 2.8) and WC (β = 3.6 ± 1.3 cm, 95% CI: 0.1, 7.0) compared to Cluster 4 with activity counts reaching 9.6e4 cph between 8:00-11:00. A Temporal PA pattern with the lowest PA counts had significantly higher mean BMI and WC compared to temporal PA patterns of higher activity counts performed early (8:00-11:00) or late (16:00-21:00) throughout the day. Temporal PA patterns appear to meaningfully link to health status.
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Affiliation(s)
- Marah Aqeel
- Department of Nutrition Science, Purdue University, West Lafayette, IN 47907, USA.
| | - Jiaqi Guo
- School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN 47907, USA.
| | - Luotao Lin
- Department of Nutrition Science, Purdue University, West Lafayette, IN 47907, USA.
| | - Saul Gelfand
- School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN 47907, USA.
| | - Edward Delp
- School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN 47907, USA.
| | - Anindya Bhadra
- Department of Statistics, Purdue University, West Lafayette, IN 47907, USA.
| | | | - Erin Hennessy
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA 02111, USA.
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13
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Eicher-Miller HA, Prapkree L, Palacios C. Expanding the Capabilities of Nutrition Research and Health Promotion Through Mobile-Based Applications. Adv Nutr 2021; 12:1032-1041. [PMID: 33734305 PMCID: PMC8166539 DOI: 10.1093/advances/nmab022] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Revised: 12/30/2020] [Accepted: 02/04/2021] [Indexed: 11/13/2022] Open
Abstract
Mobile-based applications are popular and prevalently used in the US population. Applications focusing on nutrition offer platforms for quantifying and changing behaviors to improve dietary intake. Such behavior changes can intervene in the relation of diet to promote health and prevent disease. Mobile applications offer a safe and convenient way to collect user data and share it back to users, researchers, and to health care providers. Other lifestyle factors like activity, sleep, and sedentary behavior, can also be quantified and included in investigations of how lifestyle is related to health. Yet, challenges in the assessment offered through mobile applications and effectiveness to change behavior still remain, including rigorous evaluation, demonstration of successful health improvement, and participant engagement. The data mobile applications generate, however, expands opportunities for discovery of the integrated and time-based nature of various daily activities in relation to health. This article is a summary of a symposium at Nutrition 2020 Live Online on the role of mobile applications as a tool for nutrition research and health promotion. The types and capabilities of mobile applications, challenges in their evaluation and use in research, and opportunities for the data they generate along with a specific example, are reviewed.
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Affiliation(s)
| | - Lukkamol Prapkree
- Department of Dietetics and Nutrition, Robert Stempel College of Public Health & Social Work, Florida International University, Miami, FL, USA
| | - Cristina Palacios
- Department of Dietetics and Nutrition, Robert Stempel College of Public Health & Social Work, Florida International University, Miami, FL, USA
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Association of Time-of-Day Energy Intake Patterns with Nutrient Intakes, Diet Quality, and Insulin Resistance. Nutrients 2021; 13:nu13030725. [PMID: 33668801 PMCID: PMC7996289 DOI: 10.3390/nu13030725] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2021] [Revised: 02/06/2021] [Accepted: 02/17/2021] [Indexed: 12/18/2022] Open
Abstract
Evidence shows time-of-day of energy intake are associated with health outcomes; however, studies of time-of-day energy patterns and their health implication are still lacking in the Asian population. This study aims to examine the time-of-day energy intake pattern of Chinese adults and to examine its associations with nutrient intakes, diet quality, and insulin resistance. Dietary data from three 24-h recalls collected during the 2015 China Health and Nutrition Survey (CHNS) were analyzed (n = 8726, aged ≥ 18 years). Time-of-day energy intake patterns were determined by latent class analysis (LCA). General Linear Models and Multilevel Mixed-effects Logistic Regression Models were applied to investigate the associations between latent time-of-day energy intake patterns, energy-adjusted nutrient intakes, diet quality score, and insulin resistance. Three time-of-day energy intake patterns were identified. Participants in the “Evening dominant pattern” were younger, had higher proportions of alcohol drinkers and current smokers. The “Evening dominant pattern” was associated with higher daily energy intake and a higher percentage of energy from fat (%) (p < 0.001), as well as higher insulin resistance risk (OR = 1.21; 95% CI: 1.05, 1.40), after adjusting for multivariate covariates. The highest diet quality score was observed in participants with “Noon dominant pattern” (p < 0.001). A higher proportion of energy in the later of the day was associated with insulin resistance in free-living individuals.
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