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Cited by 5Obesity, Physical Activity, DietDiabetes, Cardiovascular Risks, and LipoproteinsCancer Risks and Factors

The prevalence of obesity and relationship between obesity indicators and chronic diseases in Northern Shaanxi, China

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Yang, Xiong, Hao, Xiaoxia, Liu, Mingxia, Hu, Yaoda, Wang, Xing, Liu, Yonglin·2024·Endokrynologia Polska
DOI 10.5603/ep.96227
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Abstract

INTRODUCTION: Obesity not only affects human health but also is an important risk factor for a variety of chronic diseases. Therefore, it is particularly important to analyse the epidemic trend of obesity and actively carry out the prevention and control of obesity in the population. MATERIAL AND METHODS: A total of 4565 adults were selected by multi-stage stratified random sampling in Shenmu, Shaanxi Province, China. Univariate analysis was used to explore the epidemic characteristics of obesity in this region. Multivariate logistic regression was used to analyse the relationship between obesity and chronic diseases. Finally, the prediction efficiency of different obesity indexes was analysed by drawing receiver operator characteristic curves (ROC). All statistical analysis was completed by SPSS 26.0 software. RESULTS: The prevalence rates of overweight, obesity, and central obesity were 39.9%, 18.2%, and 48.0%, respectively. After adjusting for other confounding factors, multivariate logistic regression analysis showed that overweight and obesity were risk factors for hypertension, dyslipidaemia, and hyperuricaemia. Central obesity is a risk factor for dyslipidaemia and hyperuricaemia. High level of waist-to-height ratio (WHtR) was a risk factor for dyslipidaemia and hyperuricaemia (p < 0.05). Obesity-related indicators: body mass index (BMI), waist circumference (WC), and WHtR, are strongly correlated with the increased risk of chronic diseases in northern Shaanxi, China. The optimal BMI cut-off values for predicting hypertension, dyslipidaemia, and hyperuricaemia were 24.27, 24.04, and 25.54, respectively. The optimal WC cut-off values for predicting dyslipidaemia and hyperuricaemia were 84.5 and 90.5, and WHtR cut-off values were 0.52 and 0.54, respectively. CONCLUSION: The problem of overweight, obesity, and central obesity in adults is serious in northern Shaanxi, China. Obesity of all types will increase the risk of chronic diseases. Therefore, a variety of preventive and therapeutic measures should be adopted to curb obesity and reduce the incidence of related chronic diseases.

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  1. Nyberg ST, Batty GD, Pentti J, et al. Obesity and loss of disease-free years owing to major non-communicable diseases: a multicohort study. Lancet Public Health. 2018; 3(10): e490-e497, doi: 10.1016/S2468-2667(18)30139-7, indexed in Pubmed: 30177479. · DOI
  2. Afshin A, Forouzanfar MH, Reitsma MB, et al. GBD 2015 Obesity Collabo- rators. Health Effects of Overweight and Obesity in 195 Countries over 25 Years. N Engl J Med. 2017; 377(1): 13-27, doi: 10.1056/NEJMoa1614362, indexed in Pubmed: 28604169. · DOI · Paper page
  3. Petrovskis A, Baquero B, Bekemeier B. Involvement of Local Health Departments in Obesity Prevention: A Scoping Review. J Public Health Manag Pract. 2022; 28(2): E345-E353, doi: 10.1097/PHH.0000000000001346, indexed in Pubmed: 33729187. · DOI
  4. Dhawan D, Sharma S. Abdominal Obesity, Adipokines and Non-com- municable Diseases. J Steroid Biochem Mol Biol. 2020; 203: 105737, doi: 10.1016/j.jsbmb.2020.105737, indexed in Pubmed: 32818561. · DOI
  5. Dampoudani N, Giakouvaki A, Diamantoudi D, et al. Physical Activ- ity, Body Mass Index (BMI) and Abdominal Obesity of Pre-Adolescent Children in the Region of Thrace, NE Greece, in Relation to Socio-De- mographic Characteristics. Children (Basel). 2022; 9(3), doi: 10.3390/chil- dren9030340, indexed in Pubmed: 35327711. · DOI
  6. Zhang X, Chen H, Gu K, et al. Association of Body Mass Index and Ab- dominal Obesity with the Risk of Airflow Obstruction: National Health and Nutrition Examination Survey (NHANES) 2007-2012. COPD. 2022; 19(1): 99-108, doi: 10.1080/15412555.2022.2032627, indexed in Pubmed: 35385365. · DOI
  7. Frank AP, de Souza Santos R, Palmer BF, et al. Determinants of body fat distribution in humans may provide insight about obesity-related health risks. J Lipid Res. 2019; 60(10): 1710-1719, doi: 10.1194/jlr.R086975, in- dexed in Pubmed: 30097511. · DOI
  8. Cong X, Liu S, Wang W, et al. Combined consideration of body mass index and waist circumference identifies obesity patterns associated with risk of stroke in a Chinese prospective cohort study. BMC Public Health. 2022; 22(1): 347, doi: 10.1186/s12889-022-12756-2, indexed in Pubmed: 35180873. · DOI
  9. Hariharan R, Odjidja EN, Scott D, et al. The dietary inflammatory index, obesity, type 2 diabetes, and cardiovascular risk factors and dis- eases. Obes Rev. 2022; 23(1): e13349, doi: 10.1111/obr.13349, indexed in Pubmed: 34708499. · DOI
  10. Stasi A, Cosola C, Caggiano G, et al. Obesity-Related Chronic Kidney Disease: Principal Mechanisms and New Approaches in Nutritional Management. Front Nutr. 2022; 9: 925619, doi: 10.3389/fnut.2022.925619, indexed in Pubmed: 35811945. · DOI
  11. Du H, Ren X, Bai J, et al. Research Progress of Ferroptosis in Adiposi- ty-Based Chronic Disease (ABCD). Oxid Med Cell Longev. 2022; 2022: 1052699, doi: 10.1155/2022/1052699, indexed in Pubmed: 35502211. · DOI
  12. Swainson MG, Batterham AM, Tsakirides C, et al. Prediction of whole-body fat percentage and visceral adipose tissue mass from five anthropometric variables. PLoS One. 2017; 12(5): e0177175, doi: 10.1371/journal.pone.0177175, indexed in Pubmed: 28493988. · DOI
  13. Li S, Wang Y, Ying Y, et al. Independent and Joint Associations of BMI and Waist Circumference With the Onset of Type 2 Diabetes Mellitus in Chinese Adults: Prospective Data Linkage Study. JMIR Public Health Surveill. 2023; 9: e39459, doi: 10.2196/39459, indexed in Pubmed: 36630180. · DOI
  14. Shri N, Singh S, Singh A. Prevalence and Predictors of Combined Body Mass Index and Waist Circumference Among Indian Adults. Int J Public Health. 2023; 68: 1605595, doi: 10.3389/ijph.2023.1605595, indexed in Pubmed: 37065643. · DOI
  15. Sayeed MA, Mahtab H, Latif ZA, et al. Waist-to-height ratio is a better obesity index than body mass index and waist-to-hip ratio for predicting diabetes, hypertension and lipidemia. Bangladesh Med Res Counc Bull. 2003; 29(1): 1-10, indexed in Pubmed: 14674615.
  16. Conway JM, Yanovski SZ, Avila NA, et al. Visceral adipose tissue differ- ences in black and white women. Am J Clin Nutr. 1995; 61(4): 765-771, doi: 10.1093/ajcn/61.4.765, indexed in Pubmed: 7702017. · DOI
  17. Wang J, Yang Ym, Zhu J, et al. Overweight is associated with improved survival and outcomes in patients with atrial fibrillation. Clin Res Cardiol. 2014; 103(7): 533-542, doi: 10.1007/s00392-014-0681-7, indexed in Pubmed: 24535378. · DOI
  18. Lim J, Park HS. Trends in the prevalence of underweight, obesity, abdominal obesity and their related lifestyle factors in Korean young adults, 1998-2012. Obes Res Clin Pract. 2018; 12(4): 358-364, doi: 10.1016/j. orcp.2017.04.004, indexed in Pubmed: 28483477. · DOI
  19. Alshamiri MQ, Mohd A Habbab F, Al-Qahtani SS, et al. Waist-to-Height Ratio (WHtR) in Predicting Coronary Artery Disease Compared to Body Mass Index and Waist Circumference in a Single Center from Saudi Arabia. Cardiol Res Pract. 2020; 2020: 4250793, doi: 10.1155/2020/4250793, indexed in Pubmed: 32257425. · DOI
  20. Yin R, Yin L, Li L, et al. Hypertension in China: burdens, guidelines and policy responses: a state-of-the-art review. J Hum Hypertens. 2022; 36(2): 126-134, doi: 10.1038/s41371-021-00570-z, indexed in Pubmed: 34215840. · DOI
  21. Jia W, Weng J, Zhu D, et al. Chinese Diabetes Society. Standards of medi- cal care for type 2 diabetes in China 2019. Diabetes Metab Res Rev. 2019; 35(6): e3158, doi: 10.1002/dmrr.3158, indexed in Pubmed: 30908791. · DOI
  22. Song Q, Liu X, Zhou W, et al. Night sleep duration and risk of each lipid profile abnormality in a Chinese population: a prospective cohort study. Lipids Health Dis. 2020; 19(1): 185, doi: 10.1186/s12944-020-01363-y, indexed in Pubmed: 32799877. · DOI
  23. Li Q, Li X, Wang J, et al. Diagnosis and treatment for hyperuricemia and gout: a systematic review of clinical practice guidelines and con- sensus statements. BMJ Open. 2019; 9(8): e026677, doi: 10.1136/bmjo- pen-2018-026677, indexed in Pubmed: 31446403. · DOI
  24. Janssen I, Katzmarzyk PT, Ross R. Waist circumference and not body mass index explains obesity-related health risk. Am J Clin Nutr. 2004; 79(3): 379-384, doi: 10.1093/ajcn/79.3.379, indexed in Pubmed: 14985210. · DOI
  25. Pan WH, Flegal KM, Chang HY, et al. Body mass index and obesity-re- lated metabolic disorders in Taiwanese and US whites and blacks: implications for definitions of overweight and obesity for Asians. Am J Clin Nutr. 2004; 79(1): 31-39, doi: 10.1093/ajcn/79.1.31, indexed in Pubmed: 14684394. · DOI
  26. Cooper AJ, Gupta SR, Moustafa AF, et al. Sex/Gender Differences in Obesity Prevalence, Comorbidities, and Treatment. Curr Obes Rep. 2021; 10(4): 458-466, doi: 10.1007/s13679-021-00453-x, indexed in Pubmed: 34599745. · DOI · Paper page
  27. Chooi YuC, Ding C, Magkos F. The epidemiology of obesity. Me- tabolism. 2019; 92: 6-10, doi: 10.1016/j.metabol.2018.09.005, indexed in Pubmed: 30253139. · DOI
  28. Liu J, Garstka MA, Chai Z, et al. Marriage contributes to higher obesity risk in China: findings from the China Health and Nutrition Survey. Ann Transl Med. 2021; 9(7): 564, doi: 10.21037/atm-20-4550, indexed in Pubmed: 33987262. · DOI
  29. Sucharda P. [Smoking and obesity]. Vnitr Lek. 2010; 56(10): 1053-1057, indexed in Pubmed: 21105451.
  30. Sørensen TIA, Martinez AR, Jørgensen TS. Epidemiology of Obesity. Handb Exp Pharmacol. 2022; 274: 3-27, doi: 10.1007/164_2022_581, indexed in Pubmed: 35419622. · DOI
  31. Hsieh TH, Lee JJ, Yu EWR, et al. Association between obesity and education level among the elderly in Taipei, Taiwan between 2013 and 2015: a cross-sectional study. Sci Rep. 2020; 10(1): 20285, doi: 10.1038/s41598-020-77306-5, indexed in Pubmed: 33219305. · DOI
  32. Kim TJ, Roesler NM, von dem Knesebeck O. Causation or selection -examining the relation between education and overweight/obesity in prospective observational studies: a meta-analysis. Obes Rev. 2017; 18(6): 660-672, doi: 10.1111/obr.12537, indexed in Pubmed: 28401630. · DOI
  33. Li Yi, Cai T, Wang H, et al. Achieved educational attainment, inherited genetic endowment for education, and obesity. Biodemography Soc Biol. 2021; 66(2): 132-144, doi: 10.1080/19485565.2020.1869919, indexed in Pubmed: 34182851. · DOI
  34. De Lorenzo A, Soldati L, Sarlo F, et al. New obesity classification criteria as a tool for bariatric surgery indication. World J Gastroenterol. 2016; 22(2): 681-703, doi: 10.3748/wjg.v22.i2.681, indexed in Pubmed: 26811617. · DOI
  35. Lara M, Bustos P, Amigo H, et al. Is waist circumference a better predictor of blood pressure, insulin resistance and blood lipids than body mass index in young Chilean adults? BMC Public Health. 2012; 12: 638, doi: 10.1186/1471-2458-12-638, indexed in Pubmed: 22882972. · DOI
  36. Li Xu, Katashima M, Yasumasu T, et al. Visceral fat area, waist circumfer- ence and metabolic risk factors in abdominally obese Chinese adults. Biomed Environ Sci. 2012; 25(2): 141-148, doi: 10.3967/0895-3988.2012.0 2.003, indexed in Pubmed: 22998819. · DOI
  37. Zang BY, He LX, Xue L. Intermittent Fasting: Potential Bridge of Obesity and Diabetes to Health? Nutrients. 2022; 14(5), doi: 10.3390/nu14050981, indexed in Pubmed: 35267959. · DOI
  38. Bragg F, Tang K, Guo Yu, et al. China Kadoorie Biobank (CKB) Col- laborative Group. Associations of General and Central Adiposity With Incident Diabetes in Chinese Men and Women. Diabetes Care. 2018; 41(3): 494-502, doi: 10.2337/dc17-1852, indexed in Pubmed: 29298802. · DOI
  39. Nyamdorj R, Qiao Q, Lam TH, et al. Decoda Study Group. BMI com- pared with central obesity indicators in relation to diabetes and hy- pertension in Asians. Obesity (Silver Spring). 2008; 16(7): 1622-1635, doi: 10.1038/oby.2008.73, indexed in Pubmed: 18421260. · DOI
  40. Movahed MR, Lee JZ, Lim WY, et al. Strong independent association between obesity and essential hypertension. Clin Obes. 2016; 6(3): 189-192, doi: 10.1111/cob.12139, indexed in Pubmed: 27166134. · DOI
  41. Duttaroy AK. Role of Gut Microbiota and Their Metabolites on Atherosclerosis, Hypertension and Human Blood Platelet Function: A Review. Nutrients. 2021; 13(1), doi: 10.3390/nu13010144, indexed in Pubmed: 33401598. · DOI
  42. Sun J, Sun M, Su Y, et al. Mediation effect of obesity on the association between triglyceride-glucose index and hyperuricemia in Chinese hy- pertension adults. J Clin Hypertens (Greenwich). 2022; 24(1): 47-57, doi: 10.1111/jch.14405, indexed in Pubmed: 34904367. · DOI
  43. Nishida C, Ko GT, Kumanyika S. Body fat distribution and noncom- municable diseases in populations: overview of the 2008 WHO Expert Consultation on Waist Circumference and Waist-Hip Ratio. Eur J Clin Nutr. 2010; 64(1): 2-5, doi: 10.1038/ejcn.2009.139, indexed in Pubmed: 19935820. · DOI
  44. Liu Y, Tong G, Tong W, et al. Can body mass index, waist circumfer- ence, waist-hip ratio and waist-height ratio predict the presence of multiple metabolic risk factors in Chinese subjects? BMC Public Health. 2011; 11: 35, doi: 10.1186/1471-2458-11-35, indexed in Pubmed: 21226967. · DOI
  45. Sinaga M, Worku M, Yemane T, et al. Optimal cut-off for obesity and markers of metabolic syndrome for Ethiopian adults. Nutr J. 2018; 17(1): 109, doi: 10.1186/s12937-018-0416-0, indexed in Pubmed: 30466421. · DOI · Paper page
  46. Li Q, Li R, Zhang S, et al. Relation of BMI and waist circumference with the risk of new-onset hyperuricemia in hypertensive patients. QJM. 2022; 115(5): 271-278, doi: 10.1093/qjmed/hcaa346, indexed in Pubmed: 33486528. · DOI

Cited by

Sorted by citations

Authors
Yang, X., Hao, X., Liu, M., Hu, Y., Wang, X., & Liu, Y.
Affiliations
  • Northwest University (CN)
  • Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
ORCID
Venue
Endokrynologia Polska
Publisher
VM Media Group sp. z o.o
Published
2024-02-27
Volume
75
Issue
1
Pages
71-82
ISSN
  • 0423-104X (ISSN-L)
  • 2299-8306
DOI
10.5603/ep.96227
OpenAlex
W4391261982
Cited by
5
References
1
Citations by year
2026: 2 · 2025: 2 · 2024: 1
FWCI
2.07
Type
journal article
Language
en
Open access
Licence
cc-by-nc-nd
Locations
  • Endokrynologia Polska (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
Funders
Natural Science Foundation of Shaanxi Province (2021SF-075)
Topics
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Obesity, Physical Activity, Diet
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
  • Health Sciences › Medicine › Oncology › Cancer Risks and Factors
Keywords
obesity prevalence, overweight, abdominal obesity, waist-to-height ratio, waist circumference, body mass index, hypertension, dyslipidemia, hyperuricemia, obesity-related chronic diseases, northern Shaanxi
MeSH terms
Adult, China, Humans, Hypertension, Obesity, Prevalence, Hyperuricemia, Dyslipidemias, Overweight, Obesity, Abdominal

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