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The levels and trends of metabolic risk factors in the elderly population at the national and sub-national scale in Iran from 1990 to 2016

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Abstract

Purpose

Describing the trends of metabolic risk factors (MRFs) in the elderly population.

Methods

We used modeled data from previous comprehensive systematic reviews for MRFs among adults aged ≥ 60 years. Two stages of age-specific Spatio-temporal modeling and Gaussian process regression were used to estimate the mean of MRFs. We used crosswalk modeling to estimate the prevalence of elevated and raised Total cholesterol (TC), overweight/obesity and obesity, hypertension, and diabetes. Estimates were analyzed based on combinations of sex, age, year, and province from 1990 to 2016.

Results

Comparing prevalence estimates from 2016 with those of 1990, in the elderly population, the age-standardized prevalence of overweight/obesity, obesity, diabetes, and hypertension increased, conversely, the prevalence of hypercholesteremia decreased. The prevalence of hypertension increased about 141.5% and 129.9% in men and women respectively. The age-standardized prevalence of diabetes increased about 109.5% in females, and 116.0% in males. Prevalence of elevated TC at the national level decreased to 67.4% (64.1–70.4) in women and to 51.1% (47.5–54.8) in men. These findings were almost shown across provinces. In general, the northern and western provinces had the highest prevalence of overweight/obesity in women in 2016.

Conclusion

The rising prevalence of most MRFs, as well as the greater prevalence and mean of all MRFs in women, necessitate effective public health policies to reduce the burden of non-communicable diseases and run preventive programs.

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Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

GBD :

Global Burden of Disease

GLMM :

Generalized Linear Mixed Model

GPR :

Gaussian Process Regression

NCD :

Non-Communicable Disease

SDG :

Sustainable Development Goals

MRFs :

Metabolic Risk Factors

UI :

Uncertainty Intervals

WHO :

World Health Organization

FPG :

Fasting Plasma Glucose

BMI :

Body Mass Index

TC :

Total Cholesterol

DBP :

Diastolic Blood Pressure

SBP :

Systolic Blood Pressure

NASBOD :

National and Sub-national Burden of Diseases, Injuries and Risk Factors

References

  1. World Health Organization. Preventing chronic diseases: a vital investment: WHO global report. World Health Organization. 2005. https://apps.who.int/iris/handle/10665/43314. Accessed October 2021

  2. Benziger CP, Roth GA, Moran AE. The Global Burden of Disease Study and the Preventable Burden of NCD. Glob Heart. 2016;11(4):393–7.

    PubMed  Google Scholar 

  3. GBDCoD Collaborators. Global, regional, and national age-sex specific mortality for 264 causes of death, 1980–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet. 2017;390(10100):1151–210.

    Google Scholar 

  4. Wagner KH, Brath H. A global view on the development of non communicable diseases. Prev Med. 2012;54(Suppl):S38-41.

    PubMed  Google Scholar 

  5. Kankeu HT, Saksena P, Xu K, Evans DB. The financial burden from non-communicable diseases in low- and middle-income countries: a literature review. Health Res Policy Syst. 2013;11:31.

    PubMed  PubMed Central  Google Scholar 

  6. Islam SM, Purnat TD, Phuong NT, Mwingira U, Schacht K, Froschl G. Non-communicable diseases (NCDs) in developing countries: a symposium report. Global Health. 2014;10:81.

    PubMed  PubMed Central  Google Scholar 

  7. Global Burden of Disease Stud. Results [database on the Internet]. Institute for Health Metrics and Evaluation (IHME). 2020. Available from: 2019.  http://ghdx.healthdata.org/gbd-results-tool. Accessed October 2021.

  8. Sheidaei A, Gohari K, Kasaeian A, Rezaei N, Mansouri A, Khosravi A, et al. National and Subnational Patterns of Cause of Death in Iran 1990–2015: Applied Methods. Arch Iran Med. 2017;20(1):2–11.

    PubMed  Google Scholar 

  9. Lim SS, Vos T, Flaxman AD, Danaei G, Shibuya K, Adair-Rohani H, et al. A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012;380(9859):2224–60.

    PubMed  PubMed Central  Google Scholar 

  10. Murray CJ, Ezzati M, Flaxman AD, Lim S, Lozano R, Michaud C, et al. GBD 2010: a multi-investigator collaboration for global comparative descriptive epidemiology. Lancet. 2012;380(9859):2055–8.

    PubMed  Google Scholar 

  11. Lopez AD. The evolution of the Global Burden of Disease framework for disease, injury and risk factor quantification: developing the evidence base for national, regional and global public health action. Global Health. 2005;1(1):5.

    PubMed  PubMed Central  Google Scholar 

  12. Gharipour M, Sadeghi M, Hosseini M, Andalib E, Boroujeni MB, Sarrafzadegan N. Effect of age on the phenotype of metabolic syndrome in developing country. Adv Biomed Res. 2015;4:103.

    PubMed  PubMed Central  Google Scholar 

  13. Noroozian M. The elderly population in iran: an ever growing concern in the health system. Iran J Psychiatry Behav Sci. 2012;6(2):1–6.

    PubMed  PubMed Central  Google Scholar 

  14. Sepanlou SG, Mehdipour P, Ghanbari A, Djalalinia S, Peykari N, Kasaeian A, et al. Levels and Trends of Hypertension at National and Subnational Scale in Iran from 1990 to 2016: A Systematic Review and Pooled Analysis. Arch Iran Med. 2021;24(4):306–16.

    PubMed  Google Scholar 

  15. Djalalinia S, Mehdipour P, Mohajer B, Mohebi F, Larijani B, Sepanlou SG, et al. Levels and Trends of BMI, Obesity, and Overweight at National and Sub-national Levels in Iran from 1990 to 2016; A Comprehensive Pooled Analysis of Half a Million Individuals. Arch Iran Med. 2021;24(5):344–53.

    PubMed  Google Scholar 

  16. Mehdipour P, Sepanlou S, Mohebi F, Ahmadvand A, Peykari N, Djalalinia S, Rezaei E, Moradi Y, Haghshenas R, Naderimagham S, Jamshidi H, Farzadfar F. The levels and trends of raised total cholesterol at national and sub-national scale in Iran from 1990 to 2016: systematic review and pooled analysis. 2019. https://doi.org/10.21203/rs.2.16011/v1

  17. Peykari N, Sepanlou SG, Djalalinia S, Kasaeian A, Parsaeian M, Ahmadvand A, et al. National and sub-national prevalence, trend, and burden of metabolic risk factors (MRFs) in Iran: 1990–2013, study protocol. Arch Iran Med. 2014;17(1):54–61.

    PubMed  Google Scholar 

  18. Sisti G, Colombi I. New blood pressure cut off for preeclampsia definition: 130/80 mmHg. Eur J Obstet Gynecol Reprod Biol. 2019;240:322–4.

    PubMed  Google Scholar 

  19. Djalalinia S, Qorbani M, Peykari N, Kelishadi R. Health impacts of Obesity. Pak J Med Sci. 2015;31(1):239–42.

    PubMed  PubMed Central  Google Scholar 

  20. Smith SC Jr, Allen J, Blair SN, Bonow RO, Brass LM, Fonarow GC, et al. AHA/ACC guidelines for secondary prevention for patients with coronary and other atherosclerotic vascular disease: 2006 update: endorsed by the National Heart, Lung, and Blood Institute. Circulation. 2006;113(19):2363–72.

    PubMed  Google Scholar 

  21. Farzadfar F, Delavari A, Malekzadeh R, Mesdaghinia A, Jamshidi HR, Sayyari A, et al. NASBOD 2013: design, definitions, and metrics. Arch Iran Med. 2014;17(1):7–15.

    PubMed  Google Scholar 

  22. Marques-Vidal P, Ruidavets JB, Amouyel P, Ducimetiere P, Arveiler D, Montaye M, et al. Change in cardiovascular risk factors in France, 1985–1997. Eur J Epidemiol. 2004;19(1):25–32.

    CAS  PubMed  Google Scholar 

  23. Laaser U, Breckenkamp J. Trends in risk factor control in Germany 1984–1998: high blood pressure and total cholesterol. Eur J Public Health. 2006;16(2):217–22.

    PubMed  Google Scholar 

  24. Arnett DK, Jacobs DR Jr, Luepker RV, Blackburn H, Armstrong C, Claas SA. Twenty-year trends in serum cholesterol, hypercholesterolemia, and cholesterol medication use: the Minnesota Heart Survey, 1980–1982 to 2000–2002. Circulation. 2005;112(25):3884–91.

    PubMed  Google Scholar 

  25. Carroll MD, Lacher DA, Sorlie PD, Cleeman JI, Gordon DJ, Wolz M, et al. Trends in serum lipids and lipoproteins of adults, 1960–2002. JAMA. 2005;294(14):1773–81.

    CAS  PubMed  Google Scholar 

  26. Ahmadvand A, Farzadfar F, Jamshidi HR, Mohammadi N, Holakouie-Naieni K. Using drug sales data to evaluate the epidemiology of cardiometabolic risk factors and their inequality: an ecological study on atorvastatin and total cholesterol in Iran. Med J Islam Repub Iran. 2015;29:260.

    PubMed  PubMed Central  Google Scholar 

  27. Moslemi M, Kheirandish M, Mazaheri RNF, Hosseini H, Jannat B, Mofid V, et al. National food policies in the Islamic Republic of Iran aimed at control and prevention of noncommunicable diseases. East Mediterr Health J. 2020;26(12):1556–64.

    PubMed  Google Scholar 

  28. Latifi SM, Moradi L, Shahbazian H, Aleali AM. A study of the prevalence of dyslipidemia among the adult population of Ahvaz. Iran Diabetes Metab Syndr. 2016;10(4):190–3.

    PubMed  Google Scholar 

  29. Ghassemi H, Harrison G, Mohammad K. An accelerated nutrition transition in Iran. Public Health Nutr. 2002;5(1A):149–55.

    PubMed  Google Scholar 

  30. Enayatrad M, Yavari P, Etemad K, Khodakarim S, Mahdavi S. Determining the Levels of Urbanization in Iran Using Hierarchical Clustering. Iran J Public Health. 2019;48(6):1082–90.

    PubMed  PubMed Central  Google Scholar 

  31. Bergier J, Kapka-Skrzypczak L, Bilinski P, Paprzycki P, Wojtyla A. Physical activity of Polish adolescents and young adults according to IPAQ: a population based study. Ann Agric Environ Med. 2012;19(1):109–15.

    PubMed  Google Scholar 

  32. Popkin BM. Nutrition Transition and the Global Diabetes Epidemic. Curr Diab Rep. 2015;15(9):64.

    PubMed  PubMed Central  Google Scholar 

  33. Mohebi F, Mohajer B, Yoosefi M, Sheidaei A, Zokaei H, Damerchilu B, et al. Physical activity profile of the Iranian population: STEPS survey, 2016. BMC Public Health. 2019;19(1):1266.

    PubMed  PubMed Central  Google Scholar 

  34. Hosseini SR, Zabihi A, Ebrahimi SH, Jafarian Amiri SR, Kheirkhah F, Bijani A. The Prevalence of Anemia and its Association with Depressive Symptoms among Older Adults in North of Iran. J Res Health Sci. 2018;18(4):e00431.

    PubMed  PubMed Central  Google Scholar 

  35. Akima H, Kano Y, Enomoto Y, Ishizu M, Okada M, Oishi Y, et al. Muscle function in 164 men and women aged 20–84 yr. Med Sci Sports Exerc. 2001;33(2):220–6.

    CAS  PubMed  Google Scholar 

  36. Kleinke F, Ulbricht S, Dorr M, Penndorf P, Hoffmann W, van den Berg N. A low-threshold intervention to increase physical activity and reduce physical inactivity in a group of healthy elderly people in Germany: Results of the randomized controlled MOVING study. PLoS One. 2021;16(9):e0257326.

    CAS  PubMed  PubMed Central  Google Scholar 

  37. Batsis JA, Zagaria AB. Addressing Obesity in Aging Patients. Med Clin North Am. 2018;102(1):65–85.

    PubMed  Google Scholar 

  38. Wang F, Meng LR, Zhang Q, Li L, Nogueira B, Ng CH, et al. Elder abuse and its impact on quality of life in nursing homes in China. Arch Gerontol Geriatr. 2018;78:155–9.

    PubMed  Google Scholar 

  39. Du Y, Oh C, No J. Associations between Sarcopenia and Metabolic Risk Factors: A Systematic Review and Meta-Analysis. J Obes Metab Syndr. 2018;27(3):175–85.

    PubMed  PubMed Central  Google Scholar 

  40. Bertuol C, Tozetto WR, Streb AR, Del Duca GF (2021) Combined relationship of physical inactivity and sedentary behaviour with the prevalence of noncommunicable chronic diseases: data from 52,675 Brazilian adults and elderly. Eur J Sport Sci 2021:1–10.

  41. Hobbs MS, Knuiman MW, Briffa T, Ngo H, Jamrozik K. Plasma cholesterol levels continue to decline despite the rising prevalence of obesity: population trends in Perth, Western Australia, 1980–1999. Eur J Cardiovasc Prev Rehabil. 2008;15(3):319–24. https://doi.org/10.1097/HJR.0b013e3282f3c76b.

    Article  PubMed  Google Scholar 

  42. Egan BM, Zhao Y, Axon RN. US trends in prevalence, awareness, treatment, and control of hypertension, 1988–2008. JAMA. 2010;303(20):2043–50.

    CAS  PubMed  Google Scholar 

  43. Wolf-Maier K, Cooper RS, Banegas JR, Giampaoli S, Hense HW, Joffres M, et al. Hypertension prevalence and blood pressure levels in 6 European countries, Canada, and the United States. JAMA. 2003;289(18):2363–9.

    PubMed  Google Scholar 

  44. Hata J, Ninomiya T, Hirakawa Y, Nagata M, Mukai N, Gotoh S, et al. Secular trends in cardiovascular disease and its risk factors in Japanese: half-century data from the Hisayama Study (1961–2009). Circulation. 2013;128(11):1198–205.

    PubMed  Google Scholar 

  45. Neuhauser HK, Adler C, Rosario AS, Diederichs C, Ellert U. Hypertension prevalence, awareness, treatment and control in Germany 1998 and 2008–11. J Hum Hypertens. 2015;29(4):247–53.

    CAS  PubMed  Google Scholar 

  46. Di Lonardo A, Donfrancesco C, Palmieri L, Vanuzzo D, Giampaoli S. Time Trends of High Blood Pressure Prevalence, Awareness and Control in the Italian General Population : Surveys of the National Institute of Health. High Blood Press Cardiovasc Prev. 2017;24(2):193–200.

    PubMed  Google Scholar 

  47. Kim HJ, Kim Y, Cho Y, Jun B, Oh KW. Trends in the prevalence of major cardiovascular disease risk factors among Korean adults: results from the Korea National Health and Nutrition Examination Survey, 1998–2012. Int J Cardiol. 2014;174(1):64–72.

    PubMed  Google Scholar 

  48. collaborators NCDC. NCD Countdown 2030: pathways to achieving Sustainable Development Goal target 3.4. Lancet. 2020;396(10255):918–34.

    Google Scholar 

  49. Anderson CA, Appel LJ, Okuda N, Brown IJ, Chan Q, Zhao L, et al. Dietary sources of sodium in China, Japan, the United Kingdom, and the United States, women and men aged 40 to 59 years: the INTERMAP study. J Am Diet Assoc. 2010;110(5):736–45.

    CAS  PubMed  PubMed Central  Google Scholar 

  50. Rezaei S, Mahmoudi Z, Sheidaei A, Aryan Z, Mahmoudi N, Gohari K, et al. Salt intake among Iranian population: the first national report on salt intake in Iran. J Hypertens. 2018;36(12):2380–9.

    CAS  PubMed  Google Scholar 

  51. Azadnajafabad S, Ebrahimi N, Mohammadi E, Ghasemi E, Saeedi Moghaddam S, Aminorroaya A, et al. Disparities and spatial variations of high salt intake in Iran: a subnational study of districts based on the small area estimation method. Public Health Nutr. 2021;24(18):6281–91.

    PubMed  Google Scholar 

  52. Esteghamati A, Noshad S, Nazeri A, Khalilzadeh O, Khalili M, Nakhjavani M. Patterns of fruit and vegetable consumption among Iranian adults: a SuRFNCD-2007 study. Br J Nutr. 2012;108(1):177–81.

    CAS  PubMed  Google Scholar 

  53. Esteghamati A, Etemad K, Koohpayehzadeh J, Abbasi M, Meysamie A, Khajeh E, et al. Awareness, Treatment and Control of Pre-hypertension and Hypertension among Adults in Iran. Arch Iran Med. 2016;19(7):456–64.

    PubMed  Google Scholar 

  54. Zamaninour N, Yoosefi M, Soleimanzadehkhayat M, Pazhuheian F, Saeedi Moghaddam S, Djalalinia S, et al. Distribution of Dietary Risk Factors in Iran: National and Sub-National Burden of Disease. Arch Iran Med. 2021;24(1):48–57.

    PubMed  Google Scholar 

  55. Dehghan A, Vasan SK, Fielding BA, Karpe F. A prospective study of the relationships between change in body composition and cardiovascular risk factors across the menopause. Menopause. 2021;28(4):400–6.

    PubMed  PubMed Central  Google Scholar 

  56. Danaei G, Finucane MM, Lu Y, Singh GM, Cowan MJ, Paciorek CJ, et al. National, regional, and global trends in fasting plasma glucose and diabetes prevalence since 1980: systematic analysis of health examination surveys and epidemiological studies with 370 country-years and 2.7 million participants. Lancet. 2011;378(9785):31–40.

    CAS  PubMed  Google Scholar 

  57. Jeon CY, Lokken RP, Hu FB, van Dam RM. Physical activity of moderate intensity and risk of type 2 diabetes: a systematic review. Diabetes Care. 2007;30(3):744–52.

    PubMed  Google Scholar 

  58. Esteghamati A, Larijani B, Aghajani MH, Ghaemi F, Kermanchi J, Shahrami A, et al. Diabetes in Iran: Prospective Analysis from First Nationwide Diabetes Report of National Program for Prevention and Control of Diabetes (NPPCD-2016). Sci Rep. 2017;7(1):13461.

    PubMed  PubMed Central  Google Scholar 

  59. Azizi F, Gouya MM, Vazirian P, Dolatshahi P, Habibian S. The diabetes prevention and control programme of the Islamic Republic of Iran. East Mediterr Health J. 2003;9(5–6):1114–21.

    CAS  PubMed  Google Scholar 

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Acknowledgements

The authors appreciate the partnership of Iran’s Ministry of Health and Medical Education’s Deputies of Public Health and Research and Technology.

Funding

This study was funded by the Iran Ministry of Health and Medical Education under number 981108956. We declare that the funding bodies had no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.

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Correspondence to Seyede Salehe Mortazavi.

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The ethics committee of Tehran University of Medical Sciences approved the study with the reference number of IR.TUMS.EMRI.REC.1398.045.

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The funder of the study had no role in the study design, data collection, analysis, interpretation, and drafting of the report. MS, as the corresponding author, had full access to the data in the study and had final responsibility for the decision to submit it for publication.

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Shokri Varniab, Z., Saeedi Moghaddam, S., Pourabhari Langroudi, A. et al. The levels and trends of metabolic risk factors in the elderly population at the national and sub-national scale in Iran from 1990 to 2016. J Diabetes Metab Disord 22, 1645–1655 (2023). https://doi.org/10.1007/s40200-023-01297-z

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