Skip to main content
SpringerLink
Log in

The association of diabetes risk score and body mass index with incidence of diabetes among urban and rural adult communities in Qingdao, China

  • Original Article
  • Published:
International Journal of Diabetes in Developing Countries Aims and scope Submit manuscript

Abstract

Background

The Qingdao diabetes risk score (QDRS) is an accurate tool for identifying individuals who are at a high risk for diabetes. This study was designed to determine the association of the QDRS with the incidence of diabetes in the general population in urban and rural settings.

Methods

A stratified, random, cluster-sampling method was used to select representative individuals in 2006 and 2009, and the follow-up survey was conducted from 2012 to 2015. Of 5851 participants, 3248 were available in cohort study. The individuals without data of FPG, 2 h PG was excluded in follow-up survey. Finally, a total of 3033 participants were included. Waist circumference, age, and family history of diabetes were collected to determine the QDRS. Cox proportional hazards regression models were used to evaluate the association of QDRS and BMI with the incidence of diabetes. Further, we assessed the relative excess risk due to interaction (RERI), synergy index (S), and attributable proportion due to interaction (AP).

Results

Their age-standardized cumulative incidence of diabetes was 16.9% and 10.8% among the urban and rural populations, respectively. In both urban and rural settings, individuals with a QDRS ≥ 14 had a significantly higher risk for diabetes than the individuals with a QDRS < 14 (hazard ratio (HR): 2.37 vs. 1.49; 95% CI 1.35–4.15 vs. 1.09–2.04). Further, having a QDRS of ≥ 14 concurrently with being overweight/obese showed an additive effect on the risk for diabetes in urban settings (RERI = 1.59, S = 2.34, AP = 42.06%). In contrast, a negative interaction was noted in rural settings (RERI = 0.07, S = 0.89, AP = 4.55%).

Conclusions

Having a QDRS ≥ 14 demonstrated a strong positive association with the incidence of diabetes. An elevated QDRS combined with BMI showed value in predicting the incidence of diabetes among high-risk populations for diabetes in urban but not rural settings.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

Abbreviations

AP:

attributable proportion due to interaction

CNY:

Chinese Yuan

CI:

confidence intervals

DBP:

diastolic blood pressure

DRS:

diabetes risk score

FPG:

fasting plasma glucose

HR:

hazard ratios

HC:

hip circumference

2-hPG:

2-h post-load plasma glucose

IDF:

International Diabetes Federation

OGTT:

oral glucose tolerance test

OR:

odds ratios

PA:

physical activity

QDDPP:

Qingdao Diabetes Prevention Program

RERI:

the relative excess risk due to interaction

S:

Synergy index

SBP:

systolic blood pressure

WC:

waist circumference

WHO:

World Health Organization

WHR:

waist-to-hip ratio

ZDRS:

Zung Depression Rating Scale

References

  1. International Diabetes Federation. IDF Diabetes Atlas-7th Edition. 2015. https://www.diabetesatlas.org/. Accessed 20 March 2018.

  2. Pan XR, Yang WY, Li GW, et al. Prevalence of diabetes and its risk factors in China, 1994. Diabetes Care. 1997;20(11):1664–9.

    Article  CAS  Google Scholar 

  3. Yang WY, Lu JM, Weng JP, et al. Prevalence of diabetes among men and women in China. NEngl J Med. 2010;362:1090–101.

    Article  CAS  Google Scholar 

  4. Xu Y, Wang LM, He J, et al. Prevalence and control of diabetes in Chinese adults. JAMA. 2013;310(9):948–59.

    Article  CAS  Google Scholar 

  5. Hu H, SawhneyM SL, et al. A systematic review of the direct economic burden of type 2 diabetes in China. Diabetes Care. 1997;20(11):1664–9.

    Article  Google Scholar 

  6. Zhou X, Pang Z, Gao W, et al. Performance of an A1C and fasting capillary blood glucose test for screening newly diagnosed diabetes and pre-diabetes defined by an oral glucose tolerance test in Qingdao, China. Diabetes Care. 2010;33(3):545–50.

    Article  CAS  Google Scholar 

  7. Gao WG, Dong YH, Pang ZC, et al. A simple Chinese risk score for undiagnosed diabetes. Diabet Med. 2010;27(3):274–81.

    Article  CAS  Google Scholar 

  8. Ritchie GE, Kengne AP, Joshi R, et al. Comparison of near-patient capillary glucose measurement and a risk assessment questionnaire in screening for type 2 diabetes in a high-risk population in rural India. Diabetes Care. 2011;34(1):44–9.

    Article  CAS  Google Scholar 

  9. Rolka DB, Narayan KM, Thompson TJ, et al. Performance of recommended screening tests for undiagnosed diabetes and dysglycemia. Diabetes Care. 2001;24(11):1899–903.

    Article  CAS  Google Scholar 

  10. Zhang Y, Sun J, Pang Z, et al. Evaluation of two screening methods for undiagnosed diabetes in China: an cost-effectiveness study. Prim Care Diabetes. 2013;7(4):275–82.

    Article  Google Scholar 

  11. Gomez-Arbelaez D, Alvarado-Jurado L, Ayala-Castillo M, et al. Evaluation of the Finnish Diabetes Risk Score to predict type 2 diabetes mellitus in a Colombian population: a longitudinal observational study. World J Diabetes. 2015;6(17):1337–44.

    Article  Google Scholar 

  12. Katoh S, Peltonen M, Zeniya M, et al. Analysis of the Japanese Diabetes Risk Score and fatty liver markers for incident diabetes in a Japanese cohort. Prim Care Diabetes. 2016;10(1):19–26.

    Article  Google Scholar 

  13. Dominguez LJ, Bes-Rastrollo M, Basterra-Gortari FJ, et al. Association of a Dietary Score with incident type 2 diabetes: the Dietary-Based Diabetes-Risk Score (DDS). PLoS One. 2015;10(11):e0141760.

    Article  Google Scholar 

  14. Molarius A, Seidell JC. Selection of anthropometric indicators for classification of abdominal fatness-a critical review. Int J Obes Relat Metab Disord. 1998;22(8):719–27.

    Article  CAS  Google Scholar 

  15. Vazquez G, Duval S, Jacobs DR, et al. Comparison of body mass index, waist circumference, and waist/hip ratio in predicting incident diabetes: a meta-analysis. Epidemiol Rev. 2007;29:115–28.

    Article  Google Scholar 

  16. Bell JA, Kivimaki M, Hamer M. Metabolically healthy obesity and risk of incident type 2 diabetes: a meta-analysis of prospective cohort studies. Obes Rev. 2014;15(6):504–15.

    Article  CAS  Google Scholar 

  17. Hossain P, Kawar B, El Nahas M. Obesity and diabetes in the developing world-a growing challenge. N Engl J Med. 2007;356(3):213–5.

    Article  CAS  Google Scholar 

  18. Gao WG, Dong YH, Pang ZC, et al. Increasing trend in the prevalence of type 2 diabetes and pre-diabetes in the Chinese rural and urban population in Qingdao, China. Diabet Med. 2009;26(12):1220–7.

    Article  CAS  Google Scholar 

  19. Disease Control, Ministry of Health of the People’s Republic of China. Chinese guidelines on overweight and obesity prevention and control in adults. Beijing: People’s Medical Publishing House; 2006. p. 1–5. (In Chinese)

    Google Scholar 

  20. WHO/IDF Consultation. Definition and Diagnosis of Diabetes Mellitus and Intermediate Hyperglycemia: Report of a WHO/International Diabetes Federation Consultation. Geneva: The World Health Organization Document Production Services; 2006.

    Google Scholar 

  21. World Health Organization-International Society of Hypertension Guidelines for the Management of Hypertension. Guidelines Sub-Committee. Blood Press Suppl. 1999;1:9–43.

    Google Scholar 

  22. Zung WW, Richards CB, Short MJ. Self-rating depression scale in an outpatient clinicFurther validation of the SDS. Arch Gen Psychiatry. 1965;13(6):508–15.

    Article  CAS  Google Scholar 

  23. Jia WP, Pang C, Chen L, et al. Epidemiological characteristics of diabetes mellitus and impaired glucose regulation in a Chinese adult population: the Shanghai Diabetes Studies, a cross-sectional 3-year follow-up study in Shanghai urban communities. Diabetologia. 2007;50(2):286–92.

    Article  CAS  Google Scholar 

  24. Gao W, Dong Y, Nan H, et al. The likelihood of diabetes based on the proposed definitions for impaired fasting glucose. Diabetes Res Clin Pract. 2008;79(1):151–5.

    Article  Google Scholar 

  25. Wang C, Li J, Xue H, et al. Type 2 diabetes mellitus incidence in Chinese: contributions of overweight and obesity. Diabetes Res Clin Pract. 2015;107(3):424–32.

    Article  Google Scholar 

  26. Ahlbom A, Alfredsson L. Interaction: a word with two meanings creates confusion. Eur J Epidemiol. 2005;20(7):563–4.

    Article  Google Scholar 

  27. Zhang YL, Gao WG, Pang ZC, et al. Diabetes self-risk assessment questionnaires coupled with a multimedia health promotion campaign are cheap and effective tools to increase public awareness of diabetes in a large Chinese population. Diabet Med. 2012;29(11):e425–9.

    Article  CAS  Google Scholar 

Download references

Acknowledgments

We are grateful to the participants, primary care doctors, and nurses who participated in this survey. Working spaces, facilities, and staff were provided by Qingdao Municipal Health Bureau and Qingdao CDC. Finally, we thank Medjaden Bioscience Limited [http://www.medjaden.com/index.html] for providing English language editing services. We are thankful to Prof. Qing qiao for helping us in the experimental designing and manuscript preparation.

Availability of data and materials

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

Funding

This study was supported by the World Diabetes Foundation (WDF05-108 and WDF07-308), Qingdao Outstanding Health Professional Development Fund, Qingdao Medical Research Guidance Program in 2017 (2017-WJZD129 and 2017-WJZD134).

Author information

Authors and Affiliations

  1. School of Public Health, Qingdao University, Qingdao, China

    Jianping Sun

  2. Qingdao Municipal Center for Disease Control and Prevention, Qingdao Institute of Prevention Medicine, Qingdao, China

    Jianping Sun, Jing Cui & Hualei Xin

  3. Qingdao Huangdao District Central Hospital, Qingdao, China

    Guorong Bao

  4. Institute of Microbiology, University of Agriculture Faisalabad, Punjab, Pakistan

    Nafeesa Yasmeen

  5. Government College University, Faisalabad, Pakistan

    Bilal Aslam

  6. College of Humanities and Law, South China Agricultural University, Guangzhou, China

    Li Shanshan

  7. Qingdao Fuwai Cardiovascular Hospital, Qingdao, 266000, China

    Peng Fu

  8. Medical Research Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University Guangzhou China, Guangzhou, China

    Zulqarnain Baloch

  9. College of Veterinary Medicine, South China Agricultural University, Guangzhou, 510642, China

    Zulqarnain Baloch

Authors
  1. Jianping Sun
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Guorong Bao
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jing Cui
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Nafeesa Yasmeen
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Bilal Aslam
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Hualei Xin
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Li Shanshan
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Peng Fu
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Zulqarnain Baloch
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Jianping Sun, Zulqarnain Baloch, and Peng Fu wrote and revised the draft manuscript and subsequent manuscripts and analyzed participant samples. Zulqarnain Baloch and Jing Cui designed the study and revised the draft manuscript. Nafeesa Yasmeen, Guorong Bao, Peng Fu, Hualei Xin, and Li Shanshan assisted with sample analysis. Jing Cui and Jianping Sun conceived and designed the study, appraised relevant studies, and assisted with drafting and revising the manuscript. All the authors read and approved the final manuscript.

Corresponding authors

Correspondence to Peng Fu or Zulqarnain Baloch.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest..

Consent for publication

Not applicable.

Ethics approval and consent to participate

The study was approved by the ethics committees of the University of Helsinki, Finland, Qingdao Municipal Center for Disease Control and Prevention, Qingdao, China. Informed consent was obtained from all individual participants included in the study.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sun, J., Bao, G., Cui, J. et al. The association of diabetes risk score and body mass index with incidence of diabetes among urban and rural adult communities in Qingdao, China. Int J Diabetes Dev Ctries 39, 730–738 (2019). https://doi.org/10.1007/s13410-019-00740-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13410-019-00740-3

Keywords

Search

Navigation