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. 2023 Aug 1;6(8):e2330024.
doi: 10.1001/jamanetworkopen.2023.30024.

Association of Sustained Low or High Income and Income Changes With Risk of Incident Type 2 Diabetes Among Individuals Aged 30 to 64 Years

Jimin Clara Park  1 , Ga Eun Nam  2 , Jinna Yu  3 , Ketrell L McWhorter  4 , Junxiu Liu  5 , Hong Seok Lee  6 , Seong-Su Lee  7 , Kyungdo Han  8
Affiliations

Association of Sustained Low or High Income and Income Changes With Risk of Incident Type 2 Diabetes Among Individuals Aged 30 to 64 Years

Jimin Clara Park et al. JAMA Netw Open. .

Abstract

Importance: Evidence of the association between income fluctuation and risk of type 2 diabetes (T2D) is scarce.

Objective: To investigate whether sustained low or high income and income changes are associated with incidence of T2D.

Design, setting, and participants: In this population-based cohort study, more than 7.8 million adults without T2D aged 30 to 64 years from a nationally representative sample from the Korean Health Insurance Service database were enrolled in 2012 and followed up to 2019 (median follow-up, 6.3 years [IQR, 6.1-6.6 years]).

Exposures: Twenty quantiles of monthly health insurance premiums determined income levels. Income quartiles were annually analyzed from 2008 to 2012. Beneficiaries of the Medical Aid Program were regarded as those with very low income. A decrease in income was indicated as a reduction of 25% or more in income compared with income in the previous year.

Main outcomes and measures: The primary outcome was incident T2D based on the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision codes E11 to E14, 1 or more claims of antidiabetic medication, or a fasting glucose level of 126 mg/dL or higher. Multivariable Cox proportional hazards models were used to assess the association of low- or high-income status and income changes with incidence of T2D.

Results: Of 7 821 227 participants (mean [SD] age, 46.4 [9.3] years; 54.9% men), 359 931 (4.6%) developed T2D at least 1 year after enrollment. Individuals who repeatedly experienced low and very low income for 5 years showed 22% (hazard ratio [HR], 1.22 [95% CI, 1.21-1.23]) and 57% (1.57 [95% CI, 1.53-1.62]) higher T2D risk compared with those who never experienced low and very low income, respectively. In contrast, individuals who were repeatedly in high-income quartiles showed lower T2D risk compared with those who never experienced high income (HR, 0.86 [95% CI, 0.85-0.86]). The number of income decreases was associated with elevated T2D risk (≥2 vs 0 income decreases: HR, 1.08 [95% CI, 1.06-1.11]; P < .001 for trend). When income quartile status was compared between 2008 and 2012, individuals who experienced an income increase had lowered T2D risk, while those who experienced an income decrease had elevated T2D risk in each income quartile group.

Conclusions and relevance: This cohort study found that individuals who experienced sustained low-income status or an income decrease had elevated T2D risk, while those who had sustained high-income status or an income increase had lowered T2D risk.

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Conflict of interest statement

Conflict of Interest Disclosures: None reported.

Figures

Figure.
Figure.. Participant Flow Diagram
SI conversion factor: To convert fasting glucose to millimoles per liter, multiply by 0.0555.
See this image and copyright information in PMC

References

    1. Sun H, Saeedi P, Karuranga S, et al. . IDF Diabetes Atlas: global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045. Diabetes Res Clin Pract. 2022;183:109119. doi:10.1016/j.diabres.2021.109119 - DOI - PMC - PubMed
    1. Hu FB, Manson JE, Stampfer MJ, et al. . Diet, lifestyle, and the risk of type 2 diabetes mellitus in women. N Engl J Med. 2001;345(11):790-797. doi:10.1056/NEJMoa010492 - DOI - PubMed
    1. Mayer-Davis EJ, Costacou T. Obesity and sedentary lifestyle: modifiable risk factors for prevention of type 2 diabetes. Curr Diab Rep. 2001;1(2):170-176. doi:10.1007/s11892-001-0030-x - DOI - PubMed
    1. McWhorter KL, Park YM, Gaston SA, Fang KB, Sandler DP, Jackson CL. Multiple sleep dimensions and type 2 diabetes risk among women in the Sister Study: differences by race/ethnicity. BMJ Open Diabetes Res Care. 2019;7(1):e000652. doi:10.1136/bmjdrc-2019-000652 - DOI - PMC - PubMed
    1. Agardh E, Allebeck P, Hallqvist J, Moradi T, Sidorchuk A. Type 2 diabetes incidence and socio-economic position: a systematic review and meta-analysis. Int J Epidemiol. 2011;40(3):804-818. doi:10.1093/ije/dyr029 - DOI - PubMed