Patterns and Predictors of Multimorbidity in the Azar Cohort

Overview

Journal Arch Iran Med

Specialty General Medicine

Date 2023 Aug 6

PMID 37543916

Authors

Mohammdhossein Somi

Alireza Ostadrahimi

Neda Gilani

Arash Haji Kamanaj

Sina Hassannezhad

Elnaz Faramarzi

Affiliations

Soon will be listed here.

Abstract

Background: The co-existence of chronic diseases (CDs), a condition defined as multimorbidity (MM), is becoming a major public health issue. Therefore, we aimed to determine the patterns and predictors of MM in the Azar Cohort.

Methods: We evaluated the prevalence of MM in 15,006 (35-70-year old) subjects of the Azar Cohort Study. MM was defined as the co-existence of two or more CDs. Data on the subjects' socioeconomic status, demographics, sleeping habits, and physical activity were collected using questionnaires.

Results: The overall prevalence of MM was 28.1%. The most prevalent CDs, in decreasing order, were obesity, hypertension, depression, and diabetes. Obesity, depression, and diabetes were the most co-occurring CDs. The MM risk increased significantly with age, illiteracy, and in females. Also, the subjects within the lowest tertile of physical activity level (OR=1.89; 95% CI: 1.75-2.05) showed higher MM risk than those with the highest level of physical activity. Findings regarding current smoking status indicated that being an ex-smoker or smoker of other types of tobacco significantly increased the risk of MM.

Conclusion: The reduction of MM is possible by promoting public health from an early age among people of various socioeconomic conditions. It is vital to offer the necessary health support to the aging population of Iran.

Citing Articles

Socioeconomic disparities in multimorbidity of chronic diseases in the RaNCD cohort study.

Safari Faramani R, Samian K, Najafi F, Salimi Y, Darbandi M Sci Rep. 2025; 15(1):3776.

PMID: 39885303 PMC: 11782684. DOI: 10.1038/s41598-025-87763-5.

How much disease risk is due to old age and established risk factors?.

Webster A PNAS Nexus. 2023; 2(9):pgad279.

PMID: 37705967 PMC: 10496869. DOI: 10.1093/pnasnexus/pgad279.

References

Boutayeb A, Boutayeb S, Boutayeb W . Multi-morbidity of non communicable diseases and equity in WHO Eastern Mediterranean countries. Int J Equity Health. 2013; 12:60. PMC: 3848740. DOI: 10.1186/1475-9276-12-60. View

Jike M, Itani O, Watanabe N, Buysse D, Kaneita Y . Long sleep duration and health outcomes: A systematic review, meta-analysis and meta-regression. Sleep Med Rev. 2017; 39:25-36. DOI: 10.1016/j.smrv.2017.06.011. View

Aminisani N, Rastgou L, Shamshirgaran S, Sarbakhsh P, Ghaderi S, Hyde M . Predictors of multimorbidity among the Kurdish population living in the Northwest of Iran. BMC Public Health. 2020; 20(1):1094. PMC: 7353723. DOI: 10.1186/s12889-020-09214-2. View

Huntley A, Johnson R, Purdy S, Valderas J, Salisbury C . Measures of multimorbidity and morbidity burden for use in primary care and community settings: a systematic review and guide. Ann Fam Med. 2012; 10(2):134-41. PMC: 3315139. DOI: 10.1370/afm.1363. View

He Q, Sun H, Wu X, Zhang P, Dai H, Ai C . Sleep duration and risk of stroke: a dose-response meta-analysis of prospective cohort studies. Sleep Med. 2017; 32:66-74. DOI: 10.1016/j.sleep.2016.12.012. View

Ioakeim-Skoufa I, Poblador-Plou B, Carmona-Pirez J, Diez-Manglano J, Navickas R, Gimeno-Feliu L . Multimorbidity Patterns in the General Population: Results from the EpiChron Cohort Study. Int J Environ Res Public Health. 2020; 17(12). PMC: 7345112. DOI: 10.3390/ijerph17124242. View

Ryan A, Murphy C, Boland F, Galvin R, Smith S . What Is the Impact of Physical Activity and Physical Function on the Development of Multimorbidity in Older Adults Over Time? A Population-Based Cohort Study. J Gerontol A Biol Sci Med Sci. 2018; 73(11):1538-1544. PMC: 6175019. DOI: 10.1093/gerona/glx251. View

Nicholson K, Rodrigues R, Anderson K, Wilk P, Guaiana G, Stranges S . Sleep behaviours and multimorbidity occurrence in middle-aged and older adults: findings from the Canadian Longitudinal Study on Aging (CLSA). Sleep Med. 2020; 75:156-162. DOI: 10.1016/j.sleep.2020.07.002. View

Fortin M, Haggerty J, Almirall J, Bouhali T, Sasseville M, Lemieux M . Lifestyle factors and multimorbidity: a cross sectional study. BMC Public Health. 2014; 14:686. PMC: 4096542. DOI: 10.1186/1471-2458-14-686. View

10.

Katon W . Clinical and health services relationships between major depression, depressive symptoms, and general medical illness. Biol Psychiatry. 2003; 54(3):216-26. DOI: 10.1016/s0006-3223(03)00273-7. View

11.

Ahmadi B, Alimohammadian M, Yaseri M, Majidi A, Boreiri M, Islami F . Multimorbidity: Epidemiology and Risk Factors in the Golestan Cohort Study, Iran: A Cross-Sectional Analysis. Medicine (Baltimore). 2016; 95(7):e2756. PMC: 4998618. DOI: 10.1097/MD.0000000000002756. View

12.

McPhail S . Multimorbidity in chronic disease: impact on health care resources and costs. Risk Manag Healthc Policy. 2016; 9:143-56. PMC: 4939994. DOI: 10.2147/RMHP.S97248. View

13.

Barnett K, Mercer S, Norbury M, Watt G, Wyke S, Guthrie B . Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study. Lancet. 2012; 380(9836):37-43. DOI: 10.1016/S0140-6736(12)60240-2. View

14.

Jackson C, Dobson A, Tooth L, Mishra G . Lifestyle and Socioeconomic Determinants of Multimorbidity Patterns among Mid-Aged Women: A Longitudinal Study. PLoS One. 2016; 11(6):e0156804. PMC: 4892503. DOI: 10.1371/journal.pone.0156804. View

15.

Shahar D, Shai I, Vardi H, Shahar A, Fraser D . Diet and eating habits in high and low socioeconomic groups. Nutrition. 2005; 21(5):559-66. DOI: 10.1016/j.nut.2004.09.018. View

16.

Farhang S, Faramarzi E, Amini Sani N, Poustchi H, Ostadrahimi A, Alizadeh B . Cohort Profile: The AZAR cohort, a health-oriented research model in areas of major environmental change in Central Asia. Int J Epidemiol. 2018; 48(2):382-382h. DOI: 10.1093/ije/dyy215. View

17.

Nagel G, Peter R, Braig S, Hermann S, Rohrmann S, Linseisen J . The impact of education on risk factors and the occurrence of multimorbidity in the EPIC-Heidelberg cohort. BMC Public Health. 2008; 8:384. PMC: 2614432. DOI: 10.1186/1471-2458-8-384. View

18.

Alexopoulos G, Raue P, Sirey J, Arean P . Developing an intervention for depressed, chronically medically ill elders: a model from COPD. Int J Geriatr Psychiatry. 2007; 23(5):447-53. DOI: 10.1002/gps.1925. View

19.

Ebrahimoghli R, Janati A, Sadeghi-Bazargani H, Hamishehkar H, Ghaffari S, Sanaat Z . Epidemiology of multimorbidity in Iran: An investigation of a large pharmacy claims database. Pharmacoepidemiol Drug Saf. 2019; 29(1):39-47. DOI: 10.1002/pds.4925. View

20.

Islami F, Pourshams A, Vedanthan R, Poustchi H, Kamangar F, Golozar A . Smoking water-pipe, chewing nass and prevalence of heart disease: a cross-sectional analysis of baseline data from the Golestan Cohort Study, Iran. Heart. 2012; 99(4):272-8. PMC: 3671096. DOI: 10.1136/heartjnl-2012-302861. View