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Duan Y, Xu C, Wang W, Wang X, Xu N, Zhong J, Gong W, Zheng W, Wu YH, Myers A, Chu L, Lu Y, Delzell E, Hsing AW, Yu M, He W, Zhu S. Smoking-related gut microbiota alteration is associated with obesity and obesity-related diseases: results from two cohorts with sibling comparison analyses. BMC Med 2025; 23:146. [PMID: 40059170 PMCID: PMC11892230 DOI: 10.1186/s12916-025-03969-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2024] [Accepted: 02/25/2025] [Indexed: 05/13/2025] Open
Abstract
BACKGROUND Individuals who smoke tend to have a lower body mass index (BMI) but face an increased risk of obesity-related diseases. This study investigates this paradox from the perspective of gut microbiota. METHODS We conducted microbiome analyses to identify smoking-related microbial genera and created a smoking-related microbiota index (SMI) using 16S rRNA sequencing data from 4000 male participants in WELL-China cohort and Lanxi cohort. We employed logistic regression to explore the association between SMI and obesity indices derived from dual-energy X-ray absorptiometry. Cox regression analyses were conducted to explore the association of SMI with incident of obesity-related diseases. To further control for unmeasured familial confounders, sibling comparison analyses were conducted using between-within (BW) model. RESULTS The smoking-related microbiota index (SMI) showed a positive association with BMI and other obesity indices. Further analyses revealed that SMI is linked to obesity-related diseases, with hazard ratios (95% confidence intervals) of 1.97 (1.41-2.75) for incident diabetes, 1.31 (1.01-1.71) for major adverse cardiovascular events, and 1.70 (1.05-2.75) for obesity-related cancers. Results from sibling comparison analyses reinforced these findings. CONCLUSIONS While smoking may reduce weight through various mechanisms, alterations in gut microbiota related to smoking are associated with weight gain. Further research is required to determine if changes in the smoking-related microbiome contribute to weight gain following smoking cessation.
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Affiliation(s)
- Yiting Duan
- Department of Nutrition and Food Hygiene, Children'S Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang, China
- School of Public Health, School of Medicine, Chronic Disease Research Institute, the Children'S Hospital, National Clinical Research Center for Child Health, Zhejiang University, 866 Yu-Hang-Tang Road, Hangzhou, Zhejiang, 310058, China
| | - Chengquan Xu
- Department of Nutrition and Food Hygiene, Children'S Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang, China
- School of Public Health, School of Medicine, Chronic Disease Research Institute, the Children'S Hospital, National Clinical Research Center for Child Health, Zhejiang University, 866 Yu-Hang-Tang Road, Hangzhou, Zhejiang, 310058, China
| | - Wenjie Wang
- Department of Nutrition and Food Hygiene, Children'S Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang, China
- School of Public Health, School of Medicine, Chronic Disease Research Institute, the Children'S Hospital, National Clinical Research Center for Child Health, Zhejiang University, 866 Yu-Hang-Tang Road, Hangzhou, Zhejiang, 310058, China
| | - Xiaoyan Wang
- Department of Nutrition and Food Hygiene, Children'S Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang, China
- School of Public Health, School of Medicine, Chronic Disease Research Institute, the Children'S Hospital, National Clinical Research Center for Child Health, Zhejiang University, 866 Yu-Hang-Tang Road, Hangzhou, Zhejiang, 310058, China
| | - Nuo Xu
- Department of Nutrition and Food Hygiene, Children'S Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang, China
- School of Public Health, School of Medicine, Chronic Disease Research Institute, the Children'S Hospital, National Clinical Research Center for Child Health, Zhejiang University, 866 Yu-Hang-Tang Road, Hangzhou, Zhejiang, 310058, China
| | - Jieming Zhong
- Department of NCDs Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, 3399 Bin-Sheng Road, Hangzhou, Zhejiang, 310051, China
| | - Weiwei Gong
- Department of NCDs Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, 3399 Bin-Sheng Road, Hangzhou, Zhejiang, 310051, China
| | - Weifang Zheng
- Lanxi Red Cross Hospital, Lanxi, Zhejiang, 321102, China
| | - Yi-Hsuan Wu
- Department of Medicine, Stanford Prevention Research Center, Stanford School of Medicine, Stanford University, Palo Alto, CA, 94304, USA
| | - April Myers
- Department of Medicine, Stanford Prevention Research Center, Stanford School of Medicine, Stanford University, Palo Alto, CA, 94304, USA
| | - Lisa Chu
- Department of Medicine, Stanford Prevention Research Center, Stanford School of Medicine, Stanford University, Palo Alto, CA, 94304, USA
| | - Ying Lu
- Department of Biomedical Data Sciences, Stanford School of Medicine, Stanford University, Palo Alto, CA, 94305, USA
- Department of Epidemiology and Population Health, Stanford School of Medicine, Stanford University, Palo Alto, CA, 94305, USA
| | - Elizabeth Delzell
- Department of Medicine, Stanford Prevention Research Center, Stanford School of Medicine, Stanford University, Palo Alto, CA, 94304, USA
| | - Ann W Hsing
- Department of Medicine, Stanford Prevention Research Center, Stanford School of Medicine, Stanford University, Palo Alto, CA, 94304, USA
- Department of Epidemiology and Population Health, Stanford School of Medicine, Stanford University, Palo Alto, CA, 94305, USA
- Stanford Cancer Institute, Stanford School of Medicine, Stanford University, Palo Alto, CA, 94305, USA
| | - Min Yu
- Department of NCDs Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, 3399 Bin-Sheng Road, Hangzhou, Zhejiang, 310051, China.
| | - Wei He
- Department of Nutrition and Food Hygiene, Children'S Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang, China.
- School of Public Health, School of Medicine, Chronic Disease Research Institute, the Children'S Hospital, National Clinical Research Center for Child Health, Zhejiang University, 866 Yu-Hang-Tang Road, Hangzhou, Zhejiang, 310058, China.
| | - Shankuan Zhu
- Department of Nutrition and Food Hygiene, Children'S Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang, China.
- School of Public Health, School of Medicine, Chronic Disease Research Institute, the Children'S Hospital, National Clinical Research Center for Child Health, Zhejiang University, 866 Yu-Hang-Tang Road, Hangzhou, Zhejiang, 310058, China.
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Gao C, Meng X, Liu W, Qi Q, Yan Y. Identification of sensitive periods of weight status transition over the lifespan in Chinese population. BMC Med 2024; 22:507. [PMID: 39501260 PMCID: PMC11536718 DOI: 10.1186/s12916-024-03721-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/06/2024] [Accepted: 10/22/2024] [Indexed: 11/09/2024] Open
Abstract
BACKGROUND The prevalence of high body mass index (BMI) is increasing in both children and adults worldwide. However, it is unclear whether vulnerabilities to maintenance and transition of weight status vary throughout the lifespan. OBJECTIVE We aimed to characterize dynamic transitions of weight statuses across different life stages and to identify the sensitive periods for maintenance, onset, and resolution of obesity. METHODS This longitudinal study included a total of 23,179 participants aged 6-80 years with 95,994 BMI measurements from the China Health and Nutrition Survey 1989-2015. To examine the heterogeneity in transitions of weight statuses across different life stages, we divided participants into 8 sub-cohorts based on baseline ages by 10-year intervals, i.e., 6-10 years, 11-20 years, 21-30 years, 31-40 years, 41-50 years, 51-60 years, 61-70 years, and 71-80 years. We estimated the probabilities of transitioning between weight statuses at a given follow-up year by baseline age using generalized linear mixed-effects models. RESULTS The predicted prevalence of obesity decreased from 6 years, bottomed at around 20 years, increased thereafter, peaked at around 55 years, and then decreased gradually. In general, participants with underweight had lower probabilities of maintaining the same status compared to those with normal weight, overweight, or obesity for all age groups. For 10-year follow-up, individuals aged 21-30 years had the highest probabilities of transitioning from normal weight to obesity and transitioning from overweight to obesity compared to those in other age groups. Individuals aged 6-20 years had the highest probabilities of transitioning from obesity to normal weight and transitioning from overweight to normal weight. Individuals in all adult age groups had higher probabilities of maintaining obesity status than children and adolescents. CONCLUSIONS Young adulthood is the most sensitive period for obesity onset, whereas childhood and adolescence are the most sensitive periods for obesity resolution. The findings suggest the heterogeneity of susceptibilities to weight status transitions across different life stages and highlight the importance of the development of age-appropriate approaches for the prevention and intervention of obesity.
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Affiliation(s)
- Chaonan Gao
- Center for Non-Communicable Disease Management, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Xin Meng
- Center for Non-Communicable Disease Management, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Wei Liu
- Center for Non-Communicable Disease Management, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Qianjin Qi
- Center for Non-Communicable Disease Management, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Yinkun Yan
- Center for Non-Communicable Disease Management, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China.
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Yu Y, Zhang Z, Gao X, Hu S, Speakman JR. Dietary Patterns of Healthy Underweight Individuals Compared to Normal-BMI Individuals Using Photographic Food Diaries. Nutrients 2024; 16:3637. [PMID: 39519470 PMCID: PMC11547498 DOI: 10.3390/nu16213637] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2024] [Revised: 10/18/2024] [Accepted: 10/24/2024] [Indexed: 11/16/2024] Open
Abstract
BACKGROUND Previously, we found that healthy underweight (HU) subjects, with BMI < 18.5, eat about 12% less food (by calories) each day. It is presently unclear whether this lower intake is associated with them making food choices that provide high satiation and satiety. METHODS Using 7-day photographic records of food intake, we analyzed 52 HU and 50 normal-weight participants. RESULTS We included 52 HU and 50 normal-weight participants in the final analysis. HU individuals ate 25% fewer calories than normal-weight individuals. Their intake included a higher % of rice (p = 0.0013) and vegetables (p = 0.0006) and a lower % of livestock meat (p = 0.0007), poultry meat (p < 0.0001), and starchy roots (p = 0.0015), compared with the normal-weight population. The percent energy from carbohydrates was significantly higher (p = 0.0234), and the % energy from fat was significantly lower (p < 0.0001) in the HU group, with no difference in the % energy from protein. HU individuals sourced more of their protein from plants. Dietary patterns were grouped into three clusters, with 24 individuals grouped into cluster 1 (87.5% normal-weight population), 28 individuals into cluster 2 (64.3% normal-weight group), and 50 individuals into cluster 3 (78% HU group). CONCLUSIONS The HU group ate less overall and had proportionally more rice and vegetables and less poultry and livestock meat, starchy roots, and drinks. With respect to macronutrients, they also ate a greater % carbohydrates and less % fat, and they sourced more of their protein intake from plant sources. HU individuals did not follow a low-carbohydrate lifestyle.
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Affiliation(s)
- Ying Yu
- Shenzhen Key Laboratory of Metabolic Health, Center for Energy Metabolism and Reproduction, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China;
| | - Zhengjie Zhang
- Health Sciences Institute, China Medical University, Shenyang 110122, China;
| | - Xinrui Gao
- Beijing Engineering and Technology Research Center of Food Additives, National Soybean Processing Industry Technology Innovation Center, Beijing Technology and Business University, Beijing 100048, China;
| | - Sumei Hu
- Shenzhen Key Laboratory of Metabolic Health, Center for Energy Metabolism and Reproduction, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China;
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - John R. Speakman
- Shenzhen Key Laboratory of Metabolic Health, Center for Energy Metabolism and Reproduction, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China;
- Health Sciences Institute, China Medical University, Shenyang 110122, China;
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
- School of Biological Sciences, University of Aberdeen, Aberdeen AB24 3FX, UK
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Sharma AK, Khandelwal R, Wolfrum C. Futile cycles: Emerging utility from apparent futility. Cell Metab 2024; 36:1184-1203. [PMID: 38565147 DOI: 10.1016/j.cmet.2024.03.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Revised: 02/15/2024] [Accepted: 03/11/2024] [Indexed: 04/04/2024]
Abstract
Futile cycles are biological phenomena where two opposing biochemical reactions run simultaneously, resulting in a net energy loss without appreciable productivity. Such a state was presumed to be a biological aberration and thus deemed an energy-wasting "futile" cycle. However, multiple pieces of evidence suggest that biological utilities emerge from futile cycles. A few established functions of futile cycles are to control metabolic sensitivity, modulate energy homeostasis, and drive adaptive thermogenesis. Yet, the physiological regulation, implication, and pathological relevance of most futile cycles remain poorly studied. In this review, we highlight the abundance and versatility of futile cycles and propose a classification scheme. We further discuss the energetic implications of various futile cycles and their impact on basal metabolic rate, their bona fide and tentative pathophysiological implications, and putative drug interactions.
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Affiliation(s)
- Anand Kumar Sharma
- Laboratory of Translational Nutrition Biology, Institute of Food, Nutrition and Health, ETH Zurich, Schwerzenbach, Switzerland.
| | - Radhika Khandelwal
- Laboratory of Translational Nutrition Biology, Institute of Food, Nutrition and Health, ETH Zurich, Schwerzenbach, Switzerland
| | - Christian Wolfrum
- Laboratory of Translational Nutrition Biology, Institute of Food, Nutrition and Health, ETH Zurich, Schwerzenbach, Switzerland.
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Abstract
Recent advances in pharmacotherapies that promote appetite suppression have shown remarkable weight loss. Therapies targeting energy expenditure lag behind, and as such none have yet been identified to be safe and efficacious for sustaining negative energy balance toward weight loss. Multiple energy dissipating pathways have been identified in adipose tissue and muscle. The molecular effectors of some of these pathways have been identified, but much is still left to be learned about their regulation. Understanding the molecular underpinnings of metabolic inefficiency in adipose tissue and muscle is required if these pathways are to be therapeutically targeted in the context of obesity and obesity-accelerated diseases.
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Affiliation(s)
- Lawrence Kazak
- Rosalind & Morris Goodman Cancer Institute, McGill University, Montreal, QC H3A 1A3, Canada
- Department of Biochemistry, McGill University, Montreal, QC H3G 1Y6, Canada
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Lund J, Clemmensen C. Physiological protection against weight gain: evidence from overfeeding studies and future directions. Philos Trans R Soc Lond B Biol Sci 2023; 378:20220229. [PMID: 37482786 PMCID: PMC10363696 DOI: 10.1098/rstb.2022.0229] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2023] [Accepted: 04/24/2023] [Indexed: 07/25/2023] Open
Abstract
Body weight is under physiological regulation. When body fat mass decreases, a series of responses are triggered to promote weight regain by increasing food intake and decreasing energy expenditure. Analogous, in response to experimental overfeeding, excessive weight gain is counteracted by a reduction in food intake and possibly by an increase in energy expenditure. While low blood leptin and other hormones defend against weight loss, the signals that oppose overfeeding-induced fat mass expansion are still unknown. In this article, we discuss insights gained from overfeeding interventions in humans and intragastric overfeeding studies in rodents. We summarize the knowledge on the relative contributions of energy intake, energy expenditure and energy excretion to the physiological defence against overfeeding-induced weight gain. Furthermore, we explore literature supporting the existence of unidentified endocrine and non-endocrine pathways that defend against weight gain. Finally, we discuss the physiological drivers of constitutional thinness and suggest that overfeeding of individuals with constitutional thinness represents a gateway to understand the physiology of weight gain resistance in humans. Experimental overfeeding, combined with modern multi-omics techniques, has the potential to unveil the long-sought signalling pathways that protect against weight gain. Discovering these mechanisms could give rise to new treatments for obesity. This article is part of a discussion meeting issue 'Causes of obesity: theories, conjectures and evidence (Part I)'.
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Affiliation(s)
- Jens Lund
- Novo Nordisk Foundation Center for Basic Metabolic Research. Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Christoffer Clemmensen
- Novo Nordisk Foundation Center for Basic Metabolic Research. Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark
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7
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Wang D, Townsend LK, DesOrmeaux GJ, Frangos SM, Batchuluun B, Dumont L, Kuhre RE, Ahmadi E, Hu S, Rebalka IA, Gautam J, Jabile MJT, Pileggi CA, Rehal S, Desjardins EM, Tsakiridis EE, Lally JSV, Juracic ES, Tupling AR, Gerstein HC, Paré G, Tsakiridis T, Harper ME, Hawke TJ, Speakman JR, Blondin DP, Holloway GP, Jørgensen SB, Steinberg GR. GDF15 promotes weight loss by enhancing energy expenditure in muscle. Nature 2023; 619:143-150. [PMID: 37380764 PMCID: PMC10322716 DOI: 10.1038/s41586-023-06249-4] [Citation(s) in RCA: 86] [Impact Index Per Article: 43.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Accepted: 05/23/2023] [Indexed: 06/30/2023]
Abstract
Caloric restriction that promotes weight loss is an effective strategy for treating non-alcoholic fatty liver disease and improving insulin sensitivity in people with type 2 diabetes1. Despite its effectiveness, in most individuals, weight loss is usually not maintained partly due to physiological adaptations that suppress energy expenditure, a process known as adaptive thermogenesis, the mechanistic underpinnings of which are unclear2,3. Treatment of rodents fed a high-fat diet with recombinant growth differentiating factor 15 (GDF15) reduces obesity and improves glycaemic control through glial-cell-derived neurotrophic factor family receptor α-like (GFRAL)-dependent suppression of food intake4-7. Here we find that, in addition to suppressing appetite, GDF15 counteracts compensatory reductions in energy expenditure, eliciting greater weight loss and reductions in non-alcoholic fatty liver disease (NAFLD) compared to caloric restriction alone. This effect of GDF15 to maintain energy expenditure during calorie restriction requires a GFRAL-β-adrenergic-dependent signalling axis that increases fatty acid oxidation and calcium futile cycling in the skeletal muscle of mice. These data indicate that therapeutic targeting of the GDF15-GFRAL pathway may be useful for maintaining energy expenditure in skeletal muscle during caloric restriction.
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Affiliation(s)
- Dongdong Wang
- Centre for Metabolism, Obesity and Diabetes Research, McMaster University, Hamilton, Ontario, Canada
- Division of Endocrinology and Metabolism, Department of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Logan K Townsend
- Centre for Metabolism, Obesity and Diabetes Research, McMaster University, Hamilton, Ontario, Canada
- Division of Endocrinology and Metabolism, Department of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Geneviève J DesOrmeaux
- Department of Human Health and Nutritional Sciences, University of Guelph, Guelph, Ontario, Canada
| | - Sara M Frangos
- Department of Human Health and Nutritional Sciences, University of Guelph, Guelph, Ontario, Canada
| | - Battsetseg Batchuluun
- Centre for Metabolism, Obesity and Diabetes Research, McMaster University, Hamilton, Ontario, Canada
- Division of Endocrinology and Metabolism, Department of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Lauralyne Dumont
- Department of Pharmacology-Physiology, Centre de Recherche du Centre Hospitalier Universitaire de Sherbrooke, Université de Sherbrooke, Sherbrooke, Quebec, Canada
| | - Rune Ehrenreich Kuhre
- Global Obesity and Liver Disease Research, Global Drug Discovery, Novo Nordisk, Maaloev, Denmark
- Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Elham Ahmadi
- Centre for Metabolism, Obesity and Diabetes Research, McMaster University, Hamilton, Ontario, Canada
- Division of Endocrinology and Metabolism, Department of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Sumei Hu
- Key Laboratory of Geriatric Nutrition and Health, Ministry of Education, Beijing Technology and Business University, Beijing, China
- Shenzhen Key Laboratory of Metabolic Health, Center for Energy Metabolism and Reproduction, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Irena A Rebalka
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Jaya Gautam
- Centre for Metabolism, Obesity and Diabetes Research, McMaster University, Hamilton, Ontario, Canada
- Division of Endocrinology and Metabolism, Department of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Maria Joy Therese Jabile
- Centre for Metabolism, Obesity and Diabetes Research, McMaster University, Hamilton, Ontario, Canada
- Division of Endocrinology and Metabolism, Department of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Chantal A Pileggi
- Department of Biochemistry, Microbiology and Immunology, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada
- Ottawa Institute of Systems Biology, University of Ottawa, Ottawa, Ontario, Canada
| | - Sonia Rehal
- Centre for Metabolism, Obesity and Diabetes Research, McMaster University, Hamilton, Ontario, Canada
- Division of Endocrinology and Metabolism, Department of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Eric M Desjardins
- Centre for Metabolism, Obesity and Diabetes Research, McMaster University, Hamilton, Ontario, Canada
- Division of Endocrinology and Metabolism, Department of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Evangelia E Tsakiridis
- Centre for Metabolism, Obesity and Diabetes Research, McMaster University, Hamilton, Ontario, Canada
- Division of Endocrinology and Metabolism, Department of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - James S V Lally
- Centre for Metabolism, Obesity and Diabetes Research, McMaster University, Hamilton, Ontario, Canada
- Division of Endocrinology and Metabolism, Department of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Emma Sara Juracic
- Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, Ontario, Canada
| | - A Russell Tupling
- Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, Ontario, Canada
| | - Hertzel C Gerstein
- Centre for Metabolism, Obesity and Diabetes Research, McMaster University, Hamilton, Ontario, Canada
- Division of Endocrinology and Metabolism, Department of Medicine, McMaster University, Hamilton, Ontario, Canada
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, Ontario, Canada
| | - Guillaume Paré
- Centre for Metabolism, Obesity and Diabetes Research, McMaster University, Hamilton, Ontario, Canada
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, Ontario, Canada
- Thrombosis and Atherosclerosis Research Institute, McMaster University, Hamilton Health Sciences, Hamilton, Ontario, Canada
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada
| | - Theodoros Tsakiridis
- Centre for Metabolism, Obesity and Diabetes Research, McMaster University, Hamilton, Ontario, Canada
- Department of Oncology, McMaster University, Hamilton, Ontario, Canada
| | - Mary-Ellen Harper
- Department of Biochemistry, Microbiology and Immunology, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada
- Ottawa Institute of Systems Biology, University of Ottawa, Ottawa, Ontario, Canada
| | - Thomas J Hawke
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Ontario, Canada
| | - John R Speakman
- Shenzhen Key Laboratory of Metabolic Health, Center for Energy Metabolism and Reproduction, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
- School of Biological Sciences, University of Aberdeen, Aberdeen, UK
- CAS Center for Excellence in Animal Evolution and Genetics (CCEAEG), Kunming, China
| | - Denis P Blondin
- Department of Pharmacology-Physiology, Centre de Recherche du Centre Hospitalier Universitaire de Sherbrooke, Université de Sherbrooke, Sherbrooke, Quebec, Canada
- Division of Neurology, Department of Medicine, Centre de Recherche du Centre Hospitalier Universitaire de Sherbrooke, Université de Sherbrooke, Sherbrooke, Quebec, Canada
| | - Graham P Holloway
- Department of Human Health and Nutritional Sciences, University of Guelph, Guelph, Ontario, Canada
| | - Sebastian Beck Jørgensen
- Global Obesity and Liver Disease Research, Global Drug Discovery, Novo Nordisk, Maaloev, Denmark
- Bio Innovation Hub Transformational Research Unit, Novo Nordisk, Boston, MA, USA
| | - Gregory R Steinberg
- Centre for Metabolism, Obesity and Diabetes Research, McMaster University, Hamilton, Ontario, Canada.
- Division of Endocrinology and Metabolism, Department of Medicine, McMaster University, Hamilton, Ontario, Canada.
- Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, Ontario, Canada.
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8
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Affiliation(s)
- Anand Kumar Sharma
- Laboratory of Translational Nutrition Biology, Institute of Food, Nutrition and Health, ETH Zurich, Zurich, Switzerland.
| | - Christian Wolfrum
- Laboratory of Translational Nutrition Biology, Institute of Food, Nutrition and Health, ETH Zurich, Zurich, Switzerland.
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9
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Yan W, Meng Y, Wang L, Zhang T, Chen L, Li H. Research on the Relationship between Physical Literacy, Physical Activity and Sedentary Behavior. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:16455. [PMID: 36554337 PMCID: PMC9779016 DOI: 10.3390/ijerph192416455] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 11/27/2022] [Accepted: 12/05/2022] [Indexed: 06/17/2023]
Abstract
UNLABELLED During the COVID-19 pandemic, college students' health-related physical activity and physical literacy aroused widespread concern. This study evaluated the relationship among physical literacy (PL), sedentary behavior (SB), light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA); we further explored whether LAP and SB mediated the association between PL and MVPA. METHODS This study was based on a cross-sectional survey of Chinese college students. The Perceived Physical Literacy Instrument Scale (PPLI-SC) and International Physical Activity Questionnaire Short Form (IPAQ-SF) were used to investigate the PL, MVPA, LPA, and SB. RESULTS There were 2996 valid questionnaires with 829 boys and 2167 girls. The MVPA, LPA, and PL of boys were significantly higher than girls, while the SB values were significantly lower in girls (p < 0.01). The correlation analysis showed that there was a significant correlation between the two indexes except for SB and LPA. Path analysis shows that PL directly, significantly, and positively affects MVPA. PL reduces SB (β = -0.085, p < 0.001) and increases LPA (β = 0.097, p < 0.001). The total mediation effect accounted for 14.014%, and the mediation effects of SB and LPA accounted for 4.417% and 9.597%, respectively. CONCLUSIONS LPA and SB partially mediated the relation between PL and MVPA. SB and LPA partially explain the impact of PL on MVPA. The findings suggest that managing SB and improving LPA could play a significant indirect role in increasing the positive effect of PL on MVPA and that increasing the opportunities for LPA increased the MVPA for Chinese college students.
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Affiliation(s)
- Wenjing Yan
- Key Laboratory of the Ministry of Education of Exercise and Physical Fitness, School of Sport Science, Beijing Sport University, Beijing 100084, China
- School of Physical Education, Shanxi Normal University, Taiyuan 030000, China
| | - Yihan Meng
- Key Laboratory of the Ministry of Education of Exercise and Physical Fitness, School of Sport Science, Beijing Sport University, Beijing 100084, China
| | - Lina Wang
- Key Laboratory of the Ministry of Education of Exercise and Physical Fitness, School of Sport Science, Beijing Sport University, Beijing 100084, China
| | - Ting Zhang
- Key Laboratory of the Ministry of Education of Exercise and Physical Fitness, School of Sport Science, Beijing Sport University, Beijing 100084, China
| | - Leqin Chen
- School of Physical Education, Shanxi Normal University, Taiyuan 030000, China
| | - Hongjuan Li
- Key Laboratory of the Ministry of Education of Exercise and Physical Fitness, School of Sport Science, Beijing Sport University, Beijing 100084, China
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