Skip to main content
Top
Published in: BMC Endocrine Disorders 1/2018

Open Access 01-12-2018 | Research article

Socioeconomic status and time in glucose target range in people with type 2 diabetes: a baseline analysis of the GP-OSMOTIC study

Authors: Mei Lyn Tan, Jo-Anne Manski-Nankervis, Sharmala Thuraisingam, Alicia Jenkins, David O’Neal, John Furler

Published in: BMC Endocrine Disorders | Issue 1/2018

Login to get access

Abstract

Background

Optimal glycaemia, reflected by glycated haemoglobin (HbA1c) levels, is key in reducing type 2 diabetes (T2D) complications. However, most people with T2D have suboptimal recall and understanding of HbA1c. Continuous glucose monitoring (CGM) measures glucose levels every 5 to 15-min over days and may be more readily understood. Given that T2D is more common in lower socioeconomic settings, we aim to study relationships between socioeconomic status (SES) and percentage time in glucose target range (TIR) which is a key metric calculated from CGM.

Methods

Analysis of baseline data from the General Practice Optimising Structured MOnitoring To Improve Clinical outcomes (GP-OSMOTIC) randomised controlled trial (October 2016 – November 2017) of 300 people with T2D from 25 Victorian General Practices. FreeStyle Libre Pro® sensor patch was used for this study. SES was defined by the Index of Relative Socio-economic Disadvantage (IRSD) and educational attainment. Univariable and multivariable mixed-effects linear regression analyses controlling for age, BMI, diet, exercise and study arm were performed.

Results

One hundred and sixty-seven (60.1%) participants were male, the mean (SD) participant age was 61.0 (9.7) years, and the mean (SD) duration of CGM use was 12.3 (2.5) days. The 10th IRSD decile (least disadvantaged) was associated with a 15% higher TIR vs. the 1st decile (most disadvantaged) (95% CI 5, 25; p = 0.003) and a 0.6% lower HbA1c (95% CI 0.1, 1; p = 0.03). There was no evidence of an association between educational attainment and TIR/HbA1c.

Conclusion

Higher SES measured at an area level is associated with better achievement of glycaemic target using complementary measures of HbA1c and TIR in the GP-OSMOTIC cohort. Given that TIR may be more easily used in patient education and self-management support compared to HbA1c values, the social gradient identified in TIR provides an opportunity for clinicians and policy makers to address health inequities in T2D.

Trial registration

Australian and New Zealand Clinical Trials Registry Trial ACTRN12616001372​471, prospective, Date registered 4/10/2016.
Literature
1.
go back to reference National Health Survey First Results, Cat. No. 4363.0.55.001. Australian bureau of Statistics; 2015. National Health Survey First Results, Cat. No. 4363.0.55.001. Australian bureau of Statistics; 2015.
3.
go back to reference General Practice Management of Type 2 Diabetes: 2016-2018. Royal Australian College of General Practitioners; 2016. General Practice Management of Type 2 Diabetes: 2016-2018. Royal Australian College of General Practitioners; 2016.
4.
go back to reference Diabetes: Australian facts 2008. In Diabetes series no8 Cat no CVD 40 Australian Institute of Health and Welfare; 2008. Diabetes: Australian facts 2008. In Diabetes series no8 Cat no CVD 40 Australian Institute of Health and Welfare; 2008.
5.
go back to reference Cross R, Bonney A, Mayne DJ, Weston KM. Cross-sectional study of area-level disadvantage and glycaemic-related risk in community health service users in the Southern.IML research (SIMLR) cohort. Aust Health Rev. 2017; Cross R, Bonney A, Mayne DJ, Weston KM. Cross-sectional study of area-level disadvantage and glycaemic-related risk in community health service users in the Southern.IML research (SIMLR) cohort. Aust Health Rev. 2017;
6.
go back to reference Beard E, Clark M, Hurel S, Cooke D. Do people with diabetes understand their clinical marker of long-term glycemic control (HbA1c levels) and does this predict diabetes self-care behaviours and HbA1c? Patient Educ Couns. 2010;80:227–32.CrossRefPubMed Beard E, Clark M, Hurel S, Cooke D. Do people with diabetes understand their clinical marker of long-term glycemic control (HbA1c levels) and does this predict diabetes self-care behaviours and HbA1c? Patient Educ Couns. 2010;80:227–32.CrossRefPubMed
7.
go back to reference Heisler M, Piette JD, Spencer M, Kieffer E, Vijan S. The relationship between knowledge of recent HbA1c values and diabetes care understanding and self-management. Diabetes Care. 2005;28:816–22.CrossRefPubMed Heisler M, Piette JD, Spencer M, Kieffer E, Vijan S. The relationship between knowledge of recent HbA1c values and diabetes care understanding and self-management. Diabetes Care. 2005;28:816–22.CrossRefPubMed
8.
go back to reference Harwell TS, Dettori N, McDowall JM, Quesenberry K, Priest L, Butcher MK, Flook BN, Helgerson SD, Gohdes D. Do persons with diabetes know their (AIC) number? The Diabetes Educator. 2002;28:99–105.CrossRefPubMed Harwell TS, Dettori N, McDowall JM, Quesenberry K, Priest L, Butcher MK, Flook BN, Helgerson SD, Gohdes D. Do persons with diabetes know their (AIC) number? The Diabetes Educator. 2002;28:99–105.CrossRefPubMed
10.
go back to reference Ayotte BJ, Allaire JC, Bosworth H. The associations of patient demographic characteristics and health information recall: the mediating role of health literacy. Neuropsychol Dev Cogn B Aging Neuropsychol Cogn. 2009;16:419–32.CrossRefPubMed Ayotte BJ, Allaire JC, Bosworth H. The associations of patient demographic characteristics and health information recall: the mediating role of health literacy. Neuropsychol Dev Cogn B Aging Neuropsychol Cogn. 2009;16:419–32.CrossRefPubMed
11.
go back to reference Scott TL, Gazmararian JA, Williams MV, Baker DW. Health literacy and preventive health care use among Medicare enrollees in a managed care organization. Med Care. 2002;40:395–404.CrossRefPubMed Scott TL, Gazmararian JA, Williams MV, Baker DW. Health literacy and preventive health care use among Medicare enrollees in a managed care organization. Med Care. 2002;40:395–404.CrossRefPubMed
12.
go back to reference Brewer KW, Chase HP, Owen S, Garg SK. Slicing the pie. Correlating HbA--values with average blood glucose values in a pie chart form. Diabetes Care. 1998;21:209–12.CrossRefPubMed Brewer KW, Chase HP, Owen S, Garg SK. Slicing the pie. Correlating HbA--values with average blood glucose values in a pie chart form. Diabetes Care. 1998;21:209–12.CrossRefPubMed
13.
go back to reference The Diabetes Control Complications Trial Research Group. The Effect of Intensive Treatment of Diabetes on the Development and Progression of Long-Term Complications in Insulin-Dependent Diabetes Mellitus. N Engl J Med. 1993;329:977–86. The Diabetes Control Complications Trial Research Group. The Effect of Intensive Treatment of Diabetes on the Development and Progression of Long-Term Complications in Insulin-Dependent Diabetes Mellitus. N Engl J Med. 1993;329:977–86.
14.
go back to reference Effect of intensive blood-glucose control with metformin on complications in overweight patients with type 2 diabetes (UKPDS 34). UK prospective diabetes study (UKPDS) group. Lancet. 1998;352:854–65. Effect of intensive blood-glucose control with metformin on complications in overweight patients with type 2 diabetes (UKPDS 34). UK prospective diabetes study (UKPDS) group. Lancet. 1998;352:854–65.
15.
go back to reference National Evidence Based Guideline for Blood Glucose Control in Type 2 Diabetes. The Boden Institue of obesity, nutrition and exercise. The University of Sydney; 2009. National Evidence Based Guideline for Blood Glucose Control in Type 2 Diabetes. The Boden Institue of obesity, nutrition and exercise. The University of Sydney; 2009.
16.
go back to reference Ohkubo Y, Kishikawa H, Araki E, Miyata T, Isami S, Motoyoshi S, Kojima Y, Furuyoshi N, Shichiri M. Intensive insulin therapy prevents the progression of diabetic microvascular complications in Japanese patients with non-insulin-dependent diabetes mellitus: a randomized prospective 6-year study. Diabetes Res Clin Pract. 1995;28:103–17. Ohkubo Y, Kishikawa H, Araki E, Miyata T, Isami S, Motoyoshi S, Kojima Y, Furuyoshi N, Shichiri M. Intensive insulin therapy prevents the progression of diabetic microvascular complications in Japanese patients with non-insulin-dependent diabetes mellitus: a randomized prospective 6-year study. Diabetes Res Clin Pract. 1995;28:103–17.
18.
go back to reference Johnson DW, Jones GRD, Mathew TH, Ludlow MJ, Doogue MP, Jose MD, Langham RG, Lawton PD, McTaggart SJ, Peake MJ, et al. Chronic kidney disease and automatic reporting of estimated glomerular filtration rate: new developments and revised recommendations. Med J Aust. 2012;197:224–5. Johnson DW, Jones GRD, Mathew TH, Ludlow MJ, Doogue MP, Jose MD, Langham RG, Lawton PD, McTaggart SJ, Peake MJ, et al. Chronic kidney disease and automatic reporting of estimated glomerular filtration rate: new developments and revised recommendations. Med J Aust. 2012;197:224–5.
19.
go back to reference Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap) - a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42:377–81.CrossRefPubMed Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap) - a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42:377–81.CrossRefPubMed
21.
go back to reference Pink B: Technical paper: socio-economic indexes for areas (SEIFA). 2013. Pink B: Technical paper: socio-economic indexes for areas (SEIFA). 2013.
22.
go back to reference Emoto N, Okajima F, Goto R. A socioeconomic and behavioral survey of patients with difficult-to-control type 2 diabetes mellitus reveals an association between diabetic retinopathy and educational attainment. Patient Preference & Adherence. 2016;10:2151–62.CrossRef Emoto N, Okajima F, Goto R. A socioeconomic and behavioral survey of patients with difficult-to-control type 2 diabetes mellitus reveals an association between diabetic retinopathy and educational attainment. Patient Preference & Adherence. 2016;10:2151–62.CrossRef
23.
go back to reference Xiaoming T, Jihu L, Xiaolin Z, Bin Z, Jiao S, Linong J, Dayi H, Changyu P, Yuxin H, Suyuan J, et al. Association between socioeconomic status and metabolic control and diabetes complications: a cross-sectional nationwide study in Chinese adults with type 2 diabetes mellitus. Cardiovasc Diabetol. 2016;15:1–10.CrossRef Xiaoming T, Jihu L, Xiaolin Z, Bin Z, Jiao S, Linong J, Dayi H, Changyu P, Yuxin H, Suyuan J, et al. Association between socioeconomic status and metabolic control and diabetes complications: a cross-sectional nationwide study in Chinese adults with type 2 diabetes mellitus. Cardiovasc Diabetol. 2016;15:1–10.CrossRef
24.
go back to reference Schillinger D, Barton LR, Karter AJ, Wang F, Adler N. Does literacy mediate the relationship between education and health outcomes? A study of a low-income population with diabetes. Public Health Rep. 2006;121:245–54.CrossRefPubMedPubMedCentral Schillinger D, Barton LR, Karter AJ, Wang F, Adler N. Does literacy mediate the relationship between education and health outcomes? A study of a low-income population with diabetes. Public Health Rep. 2006;121:245–54.CrossRefPubMedPubMedCentral
25.
go back to reference Goudswaard AN, Stolk RP, Zuithoff P, Rutten GE. Patient characteristics do not predict poor glycaemic control in type 2 diabetes patients treated in primary care. Eur J Epidemiol. 2004;19:541–5.CrossRefPubMed Goudswaard AN, Stolk RP, Zuithoff P, Rutten GE. Patient characteristics do not predict poor glycaemic control in type 2 diabetes patients treated in primary care. Eur J Epidemiol. 2004;19:541–5.CrossRefPubMed
26.
go back to reference Saydah SH, Imperatore G, Beckles GL. Socioeconomic status and mortality: contribution of health care access and psychological distress among U.S. adults with diagnosed diabetes. Diabetes Care. 2013;36:49–55.CrossRefPubMed Saydah SH, Imperatore G, Beckles GL. Socioeconomic status and mortality: contribution of health care access and psychological distress among U.S. adults with diagnosed diabetes. Diabetes Care. 2013;36:49–55.CrossRefPubMed
27.
go back to reference Bachmann MO, Eachus J, Hopper CD, Davey Smith G, Propper C, Pearson NJ, Williams S, Tallon D, Frankel S. Socio-economic inequalities in diabetes complications, control, attitudes and health service use: a cross-sectional study. Diabet Med. 2003;20:921–9.CrossRefPubMed Bachmann MO, Eachus J, Hopper CD, Davey Smith G, Propper C, Pearson NJ, Williams S, Tallon D, Frankel S. Socio-economic inequalities in diabetes complications, control, attitudes and health service use: a cross-sectional study. Diabet Med. 2003;20:921–9.CrossRefPubMed
28.
go back to reference Laraia BA, Karter AJ, Warton EM, Schillinger D, Moffet HH, Adler N. Place matters: neighborhood deprivation and cardiometabolic risk factors in the diabetes study of northern California (DISTANCE). Soc Sci Med. 2012;74:1082–90.CrossRefPubMedPubMedCentral Laraia BA, Karter AJ, Warton EM, Schillinger D, Moffet HH, Adler N. Place matters: neighborhood deprivation and cardiometabolic risk factors in the diabetes study of northern California (DISTANCE). Soc Sci Med. 2012;74:1082–90.CrossRefPubMedPubMedCentral
29.
go back to reference Morgan M. Measuring social inequality: occupational classifications and their alternatives. Community Med. 1983;5:116–24.PubMed Morgan M. Measuring social inequality: occupational classifications and their alternatives. Community Med. 1983;5:116–24.PubMed
30.
go back to reference Dutton TT, Gavid; Oldenburg, Brian: Measuring socioeconomic position in population health monitoring and health research. 2005. Dutton TT, Gavid; Oldenburg, Brian: Measuring socioeconomic position in population health monitoring and health research. 2005.
31.
go back to reference de Vries McClintock HF, Wiebe DJ, Odonnell AJ, Morales KH, Small DS, Bogner HR, OʼDonnell AJ. Neighborhood social environment and patterns of adherence to oral hypoglycemic agents among patients with type 2 diabetes mellitus. Family & Community Health. 2015;38:169–79.CrossRef de Vries McClintock HF, Wiebe DJ, Odonnell AJ, Morales KH, Small DS, Bogner HR, OʼDonnell AJ. Neighborhood social environment and patterns of adherence to oral hypoglycemic agents among patients with type 2 diabetes mellitus. Family & Community Health. 2015;38:169–79.CrossRef
Metadata
Title
Socioeconomic status and time in glucose target range in people with type 2 diabetes: a baseline analysis of the GP-OSMOTIC study
Authors
Mei Lyn Tan
Jo-Anne Manski-Nankervis
Sharmala Thuraisingam
Alicia Jenkins
David O’Neal
John Furler
Publication date
01-12-2018
Publisher
BioMed Central
Published in
BMC Endocrine Disorders / Issue 1/2018
Electronic ISSN: 1472-6823
DOI
https://doi.org/10.1186/s12902-018-0279-6

Other articles of this Issue 1/2018

BMC Endocrine Disorders 1/2018 Go to the issue