Article Text

Socioeconomic status and risk factors for complications in young people with type 1 or type 2 diabetes: a cross-sectional study
  1. Sasini Wijayaratna1,2,
  2. Arier Lee3,
  3. Hyun Young Park2,
  4. Emmanuel Jo2,4,
  5. Fiona Wu1,
  6. Warwick Bagg1,2,
  7. Tim Cundy1,2
  1. 1Auckland Diabetes Centre, Auckland District Health Board, Auckland, New Zealand
  2. 2Department of Medicine, The University of Auckland Faculty of Medical and Health Sciences, Auckland, New Zealand
  3. 3Department of Population Health, The University of Auckland Faculty of Medical and Health Sciences, Auckland, New Zealand
  4. 4Health Workforce Directorate, New Zealand Ministry of Health, Wellington, New Zealand
  1. Correspondence to Dr Sasini Wijayaratna; sasiniw{at}adhb.govt.nz

Abstract

Introduction Young people with type 2 diabetes (T2D) develop complications earlier than those with type 1 diabetes (T1D) of comparable duration, but it is unclear why. This apparent difference in phenotype could relate to relative inequality.

Research design and methods Cross-sectional study of young people referred to secondary diabetes services in Auckland, Aotearoa-New Zealand (NZ): 731 with T1D and 1350 with T2D currently aged <40 years, and diagnosed between 15 and 30 years. Outcome measures were risk factors for complications (glycemic control, urine albumin/creatinine ratio (ACR), cardiovascular disease (CVD) risk) in relation to a validated national index of deprivation (New Zealand Deprivation Index (NZDep)).

Results Young people with T2D were an average 3 years older than those with T1D but had a similar duration of diabetes. 71% of those with T2D were of Māori or Pasifika descent, compared with 24% with T1D (p<0.001). T1D cases were distributed evenly across NZDep categories. 78% of T2D cases were living in the lowest four NZDep categories (p<0.001). In both diabetes types, body mass index (BMI) increased progressively across the NZDep spectrum (p<0.002), as did mean glycated hemoglobin (HbA1c) (p<0.001), the prevalence of macroalbuminuria (p≤0.01), and CVD risk (p<0.001). Adjusting for BMI, diabetes type, and duration and age, multiple logistic regression revealed deprivation was the strongest risk factor for poorly controlled diabetes (defined as HbA1c >64 mmol/mol, >8%); OR 1.17, 95% CI 1.13 to 1.22, p<0.0001. Ordinal logistic regression showed each decile increase in NZDep increased the odds of a higher ACR by 11% (OR 1.11, 95% CI 1.06 to 1.16, p<0.001) following adjustment for BMI, blood pressure, diabetes type and duration, HbA1c, and smoking status. Multiple linear regression indicated a 4% increase in CVD risk for every decile increase in NZDep, regardless of diabetes type.

Conclusions The apparent more aggressive phenotype of young-onset T2D is at least in part explicable by relative deprivation.

  • young adult
  • diabetes mellitus
  • type 2
  • poverty

Data availability statement

Data are available on reasonable request. All data relevant to the study are included in the article or uploaded as supplementary information.

http://creativecommons.org/licenses/by-nc/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

Statistics from Altmetric.com

Request Permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

Data availability statement

Data are available on reasonable request. All data relevant to the study are included in the article or uploaded as supplementary information.

View Full Text

Supplementary materials

  • Supplementary Data

    This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

Footnotes

  • Contributors SW (guarantor): study design, funding acquisition, data collection/analysis, literature search, writing manuscript. TC: study design, data analysis, literature search, writing manuscript. AL: data management, statistical analysis, tables, editing manuscript. HYP: data collection and analysis. EJ: data collection/linking/curation. FW: study design and funding acquisition. WB: project planning, funding acquisition, editing manuscript.

  • Funding A+Trust Project Grant (Number 6889) and Summer Studentship. All authors have completed the Unified Competing Interest form (available on request from the corresponding author) and declare: no support from any organization for the submitted work; no financial relationships with any organizations that might have an interest in the submitted work in the previous 3 years, no other relationships or activities that could appear to have influenced the submitted work. SW affirms with BMJ’s transparency policy.

  • Competing interests None declared.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.