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As the prevalence of type 2 diabetes (T2D) has increased, the average age at diagnosis has fallen, and consequently diabetes in the second and third decades of life has become more common.[[1]] People who develop T2D early in life are at risk of microvascular complications of diabetes and cardiovascular disease. Compared to people with type 1 diabetes (T1D) of similar age and duration of diabetes, those with T2D tend to have higher glycated haemoglobin (HbA{{1c}}) levels and develop diabetes-related complications earlier.[[1–3]]

While various biological theories, including increasing prevalence of obesity in young people, genetics and intra-uterine programming, have been invoked to explain the rising prevalence of young-onset T2D, the role of socio-economic deprivation is critical.[[2,4]] In high-income countries, T2D in young people disproportionately affects Indigenous and minority communities, a phenomenon related to high rates of obesity and inequality.[[5–7]] In Aotearoa New Zealand, which has experienced marked increases in inequality, early onset T2D disproportionately affects the Indigenous Māori population, Pacific people (Pasifika), and those of South Asian descent.[[8,9]]

In a recent study we found that not only were risk factors for diabetes complications more prevalent in young people with T2D than in young people with T1D, but irrespective of diabetes type, there were also striking correlations between the prevalence of risk factors and a national index of socio-economic deprivation.[[10]] In this paper we have examined the healthcare usage of young people with T2D and T1D in this same cohort to try to identify what aspects of healthcare usage could underlie this relationship. The measures of healthcare usage considered in this study were primary care visits, referral to and attendance at diabetes outpatient services and hospital admissions.

Methods

People with T1D or T2D diabetes diagnosed between the ages of 15 and 30 who had been referred to secondary diabetes services in the greater Auckland region between January 2003 and August 2015 were identified by searching hospital databases. This study was conducted at adult diabetes centres; thus children were not included, minimising the possibility of congenital/syndromic causes of diabetes being mistakenly included. The use of the 15–30-year-old age band also allowed direct comparison with the notable work done by Constantino et al. in Australia regarding diabetes-related complications.[[3]] In order to obtain a sample of young people with T1D and T2D, individual medical records were reviewed for people referred between 15 and 35 years of age (to capture delayed referrals), who were <40 years old at the time of the study. The year of diagnosis and type of diabetes was established from clinical and laboratory records. HbA{{1c}} levels were collected from 2015–2016 (a median 8 years following diagnosis), and an individual’s mean HbA{{1c}} from all values available in the 2015–2016 period was calculated. As there is often uncertainty as to the date of onset of T2D, we also recorded the highest HbA{{1c}} in the year of diagnosis, given that this value was most likely to represent the situation prior to treatment.

Socio-economic deprivation was determined from the New Zealand Index of Deprivation (NZDep) 2013 schedule based on residency status and geographic living area, obtained from Primary Health Organisations’ enrolment demographic quarterly tables. Decile 1 represents the least deprived and decile 10 the most deprived area.[[11]]

The time from the year of diagnosis in primary care and other hospital services to the year of referral to specialist diabetes services was recorded for people with T2D from hospital databases across the three regional district health boards (DHB); this time (in years) was taken as the time to referral to DHB diabetes services. Delayed referral was defined as time to referral >1 year and this analysis was only conducted for the T2D group. Almost all people with T1D are referred to a diabetes specialist from the time of diagnosis and are offered continued follow-up by specialist diabetes services. We assume that the majority of people with T2D would be referred to public specialist services because retinal screening is carried out almost exclusively in these settings. Diabetes outpatient clinic appointments offered and attended across the greater Auckland region were recorded from hospital databases over the 2-year period, 2015–2016. An appointment offered but not attended was defined as “Did Not Attend” (DNA). A 2-year time frame was used to determine diabetes clinic attendance to capture those who may have only had an annual review. Ethnicity data and nation-wide hospital admissions over the same 2-year period were obtained from the National Minimum Dataset (coded data from public and private hospitals).[[12]] The presence or absence of a primary care (general practice) visit nation-wide over the prior 6 months and prior 1 year (2016) was also obtained from the Ministry of Health; 2-year data and the exact number of primary care visits was not available. Data on the demographic features, complications and medication use of both the T1D and T2D cohorts have been published previously.[[10]]

Statistical analysis

Data analysis was conducted using GraphPad Prism (version 6.00.283) and SAS/STAT software, Version 9.4 of the SAS System for Windows (SAS Institute Inc., Cary, NC, USA). Statistical tests were two-tailed and a significance level of 5% was maintained. For some analyses NZDep levels were divided into five groups (deciles 1–2; 3–4; 5–6 etc.). T-tests were used to compare means between two groups. χ[[2]] tests were used for comparison of categorical variables between groups. For non-normally distributed continuous variables non-parametric tests (Wilcoxon/Mann–Whitney tests/Kruskal–Wallis tests) were used and the results expressed as the median with interquartile range (IQR). Logistic regression was used to analyse the binary variable of delay in referral to specialist diabetes services (where no delay was defined as a referral within a year of diagnosis), with NZDep, age at diabetes diagnosis and HbA{{1c}} in the year of diagnosis included as explanatory variables.

Results

Primary care visits

Seven hundred and thirty-one young people with T1D and 1,350 with T2D were included in this study. More than 80% of both groups (86% and 83% for T1D and T2D respectively) had attended a primary care appointment in a 1-year period, and although the proportion was greater for people with T1D than those with T2D the difference was small (Table 1). There was no evidence of an association between the proportion of each group with at least one primary care visit and deprivation (Table 2), and there was no difference in mean HbA{{1c}} between those who did and did not have a primary care visit (Table 3). Of people with mean HbA{{1c}} ≥100 mmol/mol, 29% (23/79) of those with T1D and 33% (78/236) of those with T2D had not been seen in primary care in the preceding 6 months.

Referrals to secondary diabetes services

Between 2003 and 2014, the number of referrals increased substantially. In part this reflected Auckland’s population growth (increased by 17%),[[13]] but the rate of increase in referrals was greater for T2D (increased by a factor of 2.5) than for T1D (increased by a factor of 1.8). Over this period, among young people with T2D, referrals tripled for Pasifika people and doubled for Māori, while referrals for the European population increased by a factor of 1.3.

Forty-eight percent (n=653) of the T2D group were referred to specialist diabetes services in the year that they were diagnosed, while the remainder, defined in this study as a delayed referral, were referred a median 3 years (IQR 1, 5) after diagnosis. Ethnicity and NZDep were strongly related with 65% of indigenous Māori and 71% of Pasifika young people living in the lowest two decile areas.[[10]] Only one of these variables, NZDep, was used in logistic regression analysis. Multivariate logistic regression analysis showed for every decile increase in NZDep the odds of a delayed referral increased by 15% (OR 1.15, 95% CI 1.07–1.24, p=0.0003), following adjustment for age and HbA{{1c}} in the year of diagnosis. For every year increase in age at diagnosis, the odds of delayed referral increased by 6% (OR 1.06, 95% CI 1.02–1.10, p=0.004). For every 10 mmol/mol increase in HbA{{1c}} in the year of diagnosis, the odds of delayed referral decreased by 13% (OR 0.87, 95% CI 0.81–0.93, p<0.001), meaning a higher HbA{{1c}} at presentation prompted earlier referral. However, those who had had a delayed referral to diabetes services following diagnosis had a higher mean HbA{{1c}} in the 2015–2016 period (Table 3).

Diabetes clinic attendance

In the 2015–2016 period, people with T1D were offered significantly more per person diabetes clinic appointments than people with T2D (2 (IQR 0, 7) vs 0 (IQR 0, 2), p<0.001). Sixty percent of people with T1D had attended a diabetes clinic appointment in this 2-year period and 39% (n=282) had missed appointments (DNA) (Table 1). A smaller proportion, 37%, of the T2D group had attended a diabetes clinic with a smaller proportion of DNAs (30%, n=405). The likelihood of people missing appointments varied significantly between different deprivation quintiles in the T2D group (p=0.02, Table 2).

Seventeen percent (n=236) of people with T2D had an HbA{{1c}} >100mmol/mol. Only 47% of this group had a diabetes clinic attendance in the 2-year period. Of the 79 with T1D and HbA{{1c}} >100mmol/mol, 78% (n=62) had attended a clinic appointment (p <0.001).

The proportion of people with a DNA increased with increasing degrees of deprivation in the T2D group but in not the T1D group (Table 2). In both the T1D and T2D group those with missed appointments had a higher mean HbA{{1c}} in the 2015–2016 period (Table 3).

Hospital admissions

In both groups the proportion of people with a hospital admission increased significantly with NZDep categories (Table 2). For T1D the proportion increased from 29% in quintile 1 to 50% in quintile 5; for T2D it increased from 25% to 42%.

Of those with HbA{{1c}} >100mmol/mol, 50% (117/236) of the T2D group and 75% (59/79) of the T1D group had at least one admission over the prior 2-year period. In the T1D group, the mean HbA{{1c}} was significantly higher for those who had at least one admission (Table 3).

View Tables 1–3.

Discussion

Poverty is a key element in young-onset type 2 diabetes.[[6,14–18]] In Auckland, where the majority of young people with T2D live in the most socio-economically deprived areas, it is a risk factor for diabetes complications irrespective of diabetes type.[[10]] We found that the difficulties accessing appropriate healthcare underlie these findings. In the periods studied, the proportion of people with type 1 and type 2 diabetes who attended any primary care appointment was similar, with no relationship to NZDep status. Thirty-six percent of the T2D group had not seen a general practitioner in the preceding 6 months; a concern, as prescriptions are written for a maximum 3-month period. This may partly explain previously documented sub-optimal medication use in this group.[[10, 19]] Thirty-one percent of the T1D group had also not been seen in primary care in the preceding 6 months, however, as discussed below diabetes clinic attendance was higher in this group. Further detail regarding primary care visits was not available to determine whether diabetes was the main focus of these consultations.

Referrals for Māori young people with T2D doubled and referrals for Pasifika youth with T2D tripled over a 12-year period. For people with young-onset T2D, the great majority of referrals to secondary/specialist diabetes services (which in New Zealand are publicly funded) come from primary care. Just under half of those with T2D were referred to specialist diabetes services within a year of diagnosis. We found that those who had higher HbA{{1c}} values and were younger at diagnosis were referred earlier, but socio-economic status also had a significant association. For every decile increase in NZDep, the odds of a delayed referral (>1 year after diagnosis) increased by 15%, and those who had experienced a delayed referral had a significantly higher mean HbA{{1c}} in the 2015–2016 period (following a median duration of diabetes of 8 years).

Financial barriers may deter return to primary care following diagnosis for education, management or referral. Although funding for primary care in New Zealand is subsidised based on degree of socio-economic deprivation and age, it is not fully funded for this age group. Poor health literacy, psychosocial and economic stressors are also likely to be contributing factors.[[14,20]] In New Zealand, where the majority of Māori and Pasifika young people with T2D live in the most socio-economically deprived areas, overcoming communication barriers, eliminating discriminatory healthcare behaviour and providing accessible, culturally safe and appropriate care throughout the healthcare system is needed, as well as addressing practical barriers.[[21,22]]

The “DNA” or “did not attend” rate was high in both the T1D and T2D groups, but somewhat greater in the former. However, the number of appointments offered to people with T1D was substantially greater than the number offered to young people with T2D (in part because management concerns may be dominated by the acute complications of T1D), so overall their attendance was greater. In those with T2D (but not those with T1D), the DNA rate was higher among young people living in more socio-economically deprived areas.

The proportion of young people with hospital admissions increased with greater deprivation for both T1D and T2D, a finding that has been documented in the general diabetes population.[[23–25]] Inpatient time could be used as a “red flag” to link this high-risk population to better diabetes follow-up.

Young-onset T2D is associated with higher rates of microvascular complication and cardiovascular risk factors than people with T1D of similar duration, leading to greater morbidity and mortality in the long term.[[3,10,15]] However, we found that young people with T2D were offered fewer and attended less than half the appointments of their T1D counterparts. We found that young people with T2D are equally at risk of acute illness, as indicated by hospital admissions; there are compelling reasons, both from a short- and long-term perspective, why greater attention needs to be paid to young people with T2D. In particular, a more targeted approach by both primary care and diabetes services is needed to target young T2D people with HbA{{1c}} levels >100mmol/mol.

Primary care attendance was unrelated to deprivation in this study. The literature examining healthcare service use by young-onset T2D people is sparse, but studies from the general T2D population in France and Denmark have shown that general practice visits increased with decreasing socio-economic position, perhaps representing overall poor health.[[26,27]] Fosse-Edorh et al. found that people with T2D in France with financial difficulties visited general practitioners more often and specialists less often, and Hsu et al. reported that poorer diabetes populations in Taiwan attended diabetes clinics less often than the better off.[[28,29]] Healthcare systems differ in other countries; these results cannot be compared directly with other models of care, however, the results are applicable on a national level.

There are limitations to our paper. While each record was reviewed, c-peptide and antibody levels were not measured for each individual with diabetes included in this study, leaving the possibility of mislabelling in some cases; there may also be individuals with characteristics of both types of diabetes. Retrospective data collection for this relatively large cohort meant that it was not practical to obtain details regarding hospital admissions or primary care visits. We were also unable to collect diabetes clinic attendance data on a national level; this data was limited to the three Auckland district health boards. Primary care attendance data was only available for the prior 1-year period, and the exact number of primary care visits was also unavailable. This dataset does not capture people managed in primary care, so it may underestimate the number of young people with T2D in the Auckland region. In addition, several years have passed since this data was collected; the population of young people with T2D in Auckland would have increased since 2015, however, the model of care remains unchanged, and these results are therefore still relevant.

The past decade has seen a number of publications document the poor outcomes of youth with T2D, but their contact with the healthcare system and their barriers to care, such as socio-economic deprivation, are not explored. While healthcare systems across the globe may vary, improving diabetes care to this growing population is a common challenge.[[10,30]] Our data indicates that current models of care are not working well for young people with diabetes, particularly for those living in relative deprivation, which includes the majority of young people with T2D. Socio-economic deprivation plays a key role in important aspects of healthcare service use such as referral to specialist diabetes services, diabetes clinic non-attendance and hospital admissions in young people with T2D; deprivation needs to be addressed in developing a more equitable model of care, especially given increasing inequality in New Zealand.[[8]]

Summary

Abstract

Aim

Lower socio-economic status (SES) is linked to greater morbidity in people with young-onset type 2 (T2D) and type 1 diabetes (T1D). We assessed healthcare utilisation from this population and the impact of SES.

Method

Retrospective analysis of 1,350 people with T2D and 731 with T1D diagnosed between 15–30 years of age referred to secondary dia­betes services in Auckland, New Zealand. Primary care visits, referral to/attendance at diabetes clinics, and hospital admissions were recorded; their relationship to a validated national index of deprivation (NZDep) was assessed.

Results

The proportion with primary care attendance was similar in both groups with no significant variation with NZDep. For T2D, NZDep was a predictor of delayed referral (≧1-year post-diagnosis) to diabetes services, following adjustment for age and HbA{{1c}} in the year of diagnosis (OR 1.15 for every decile increase in NZDep, 95% CI 1.07–1.24, p=0.0003). The median number of appointments offered over a 2-year period was greater for T1D (2.0 (IQR 0, 7) vs (0 (IQR 0, 2), p<0.001); non-attendance increased with NZDep for T2D (p=0.016). The proportion with hospital admissions was similar in both groups and increased with NZDep (T1D p<0.001, T2D p=0.015).

Conclusion

SES impacts several measures of healthcare utilisation. Current healthcare models are inadequately servicing people with young-onset T2D.

Author Information

Sasini Wijayaratna: Diabetologist, Auckland Diabetes Centre, Greenlane Clinical Centre, Auckland District Health Board, PO Box 92189, Victoria Street West, Auckland 1142. Arier Lee: Biostatistician, Department of Population Health, Faculty of Medical and Health Sciences, The University of Auckland, Private Bag 92019, Auckland 1142. Emmanuel Jo: Honorary lecturer, Department of Medicine, Faculty of Medical and Health Sciences, The University of Auckland, Private Bag 92019, Auckland 1142. Manager, Analytics and Intelligence, Health Workforce Directorate, Ministry of Health, PO Box 5013, Wellington 6140. Hyun Young Park: Medical student, Department of Medicine, Faculty of Medical and Health Sciences, The University of Auckland, Private Bag 92019, Auckland 1142. Tim Cundy: Professor, Department of Medicine, Faculty of Medical and Health Sciences, The University of Auckland, Private Bag 92019, Auckland 1142. Warwick Bagg: Professor and deputy dean, Department of Medicine, Faculty of Medical and Health Sciences, The University of Auckland, Private Bag 92019, Auckland 1142.

Acknowledgements

Fiona Wu, A+ Trust Small Project Grant.

Correspondence

Sasini M. Wijayaratna: Auckland Diabetes Centre, Greenlane Clinical Centre, PO Box 92189, Victoria Street West Auckland 1142, New Zealand. Ph: 096309980.

Correspondence Email

SasiniW@adhb.govt.nz

Competing Interests

Nil.

1) Magliano DJ, Sacre JW, Harding JL, Gregg EW, Zimmet PZ, Shaw JE. Young-onset type 2 diabetes mellitus - implications for morbidity and mortality. Nat Rev Endocrinol. 2020;16:321-331.

2) Bjornstad P, Drews KL, Caprio S, Gubitosi-Klug R, Nathan DM, Tesfaldet B, et al. Long-term complications in youth-onset type 2 diabetes. N Engl J Med. 2021;385:416-426.

3) Constantino MI, Molyneaux L, Limacher-Gisler F, Al-Saeed A, Luo C, Wu T, et al. Long-term complications and mortality in young-onset diabetes: type 2 diabetes is more hazardous and lethal than type 1 diabetes. Diabetes Care. 2013;36:3863-9.

4) Srinivasan S, Chen L, Todd J, Divers J, Gidding S, Chernausek S, et al. ProDiGY Consortium. The first genome-wide association study for type 2 diabetes in youth: the Progress in Diabetes Genetics in Youth (ProDiGY) Consortium. Diabetes. 2021;70:996-1005.

5) Swinburn BA, Sacks G, Hall KD, McPherson K, Finegood DT, Moodie ML, et al. The global obesity pandemic: shaped by global drivers and local environments. Lancet. 2011;378:804-814.

6) McGavock J, Wicklow B, Dart AB. Type 2 diabetes in youth is a disease of poverty. Lancet. 2017;390:1829.

7) Volaco A, Cavalcanti AM, Filho RP, Précoma DB. Socioeconomic status: the missing link between obesity and diabetes mellitus? Curr Diabetes Rev. 2018;14: 321-326.

8) Parry B. Household incomes in New Zealand: trends in indicators of inequality and hardship 1982 to 2016. Wellington: Ministry of Social Development; 2017.

9) Chan WC, Jackson G, Wright CS, Orr-Walker B, Drury PL, Boswell DR, et al. The future of population registers: linking routine health datasets to assess a population’s current glycaemic status for quality improvement. BMJ Open 2014;4:e003975-003975.

10) Wijayaratna S, Lee A, Park HY, Jo E, Wu F, Bagg W, Cundy T. Socioeconomic status and risk factors for complications in young people with type 1 or type 2 diabetes: a cross-sectional study. BMJ Open Diabetes Res Care. 2021;9:10.1136/bmjdrc-002485.

11) Atkinson J, Salmond C, Crampton P. NZDep2013 Index of Deprivation. Wellington: Department of Public Health, University of Otago; 2014.

12) Ministry of Health. National Minimum Dataset (Hospital Events) Data Dictionary. Wellington: Ministry of Health, 2014.

13) Statistics New Zealand: Statistics New Zealand’s Estimated Resident Population, 1996-2021. Available at: https://ecoprofile.infometrics.co.nz/auckland/Population/Growth. Accessed Jan 7 2021.

14) Viner R, White B, Christie D. Type 2 diabetes in adolescents: a severe phenotype posing major clinical challenges and public health burden. Lancet. 2017;389:2252-2260.

15) Dabelea D, Stafford JM, Mayer-Davis EJ, D'Agostino R Jr, Dolan L, Imperatore G, et al. Association of type 1 diabetes vs type 2 diabetes diagnosed during childhood and adolescence with complications during teenage years and young adulthood; SEARCH for Diabetes in Youth Research Group. JAMA. 2017;317:825-35.

16) Copeland KC, Zeitler P, Geffner M, Guandalini C, Higgins J, Hirst K, et al. Characteristics of adolescents and youth with recent-onset type 2 diabetes: the TODAY cohort at baseline. J Clin Endocrinol Metab. 2011;96:159-67.

17) Klingensmith GJ, Connor CG, Ruedy KJ, Beck RW, Kollman C, Haro H, et al. Presentation of youth with type 2 diabetes in the Pediatric Diabetes Consortium. Pediatr Diabetes. 2016;17:266-73.

18) Khanolkar AR, Amin R, Taylor-Robinson D, Viner R, Warner J, Stephenson T, et al. Ethnic minorities are at greater risk for childhood onset type 2 diabetes and poorer glycaemic control in England and Wales. J Adolesc Health. 2016;59:354-61.

19) Kunasegaran S, Beig J, Khanolkar M, Cundy, T. Adherence to medication, glycaemic control and hospital attendance in young adults with type 2 diabetes. Intern Med J. 2018 48:728-31.

20) Hill-Briggs F, Adler NE, Berkowitz SA, Chin MH, Gary-Webb TL, Navas-Acien A, et al. Social determinants of health and diabetes: a scientific review. Diabetes Care. 2020;44:258-79.

21) Stoner L, Matheson A, Hamlin M, Skidmore P. Environmental determinants of childhood obesity: a specific focus on Māori and Pasifika in New Zealand. Perspect Public Health. 2016;136:18-20.

22) Espiner E, Paine SJ, Weston M, Curtis E. Barriers and facilitators for Māori in accessing hospital services in Aotearoa New Zealand. N Z Med J. 2021;134:47-58.

23) Nishino Y, Gilmour S, Shibuya K. Inequality in diabetes-related hospital admissions in England by socioeconomic deprivation and ethnicity: facility-based cross-sectional analysis. PLoS ONE. 2015;10: e0116689.

24) Wild SH, McKnight JA, McConnachie A, Lindsay RS; Glasgow and Lothian Diabetes Register Data Group. Socioeconomic status and diabetes-related hospital admissions: a cross-sectional study of people with diagnosed diabetes. J Epidemiol Community Health. 2010;64:1022-4.

25) Kurani SS, Heien HC, Sangaralingham LR, Inselman JW, Shah ND, Golden SH, et al. Association of area-level socioeconomic deprivation with hypoglycemic and hyperglycemic crises in US adults with diabetes. JAMA Netw Open. 2022;5:e2143597

26) Lamy S, Ducros D, Diméglio C, Colineaux H, Fantin R, Berger E, et al. Disentangling the influence of living place and socioeconomic position on health services use among diabetes patients: A population-based study. PLoS ONE. 2017;12:e0188295.

27) Dalsgaard EM, Vedsted P, Fenger-Grøn M. Socioeconomic position and contact to general practice among persons with diabetes. Prim Care Diabetes. 2012;6:313-8.

28) Fosse-Edorh S, Fagot-Campagna A, Detournay B, Bihan H, Eschwege E, Gautier A, et al. Impact of socio‐economic position on health and quality of care in adults with type 2 diabetes in France: the Entred 2007 study. Diabet Med. 2015 Nov;32:1438-44.

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As the prevalence of type 2 diabetes (T2D) has increased, the average age at diagnosis has fallen, and consequently diabetes in the second and third decades of life has become more common.[[1]] People who develop T2D early in life are at risk of microvascular complications of diabetes and cardiovascular disease. Compared to people with type 1 diabetes (T1D) of similar age and duration of diabetes, those with T2D tend to have higher glycated haemoglobin (HbA{{1c}}) levels and develop diabetes-related complications earlier.[[1–3]]

While various biological theories, including increasing prevalence of obesity in young people, genetics and intra-uterine programming, have been invoked to explain the rising prevalence of young-onset T2D, the role of socio-economic deprivation is critical.[[2,4]] In high-income countries, T2D in young people disproportionately affects Indigenous and minority communities, a phenomenon related to high rates of obesity and inequality.[[5–7]] In Aotearoa New Zealand, which has experienced marked increases in inequality, early onset T2D disproportionately affects the Indigenous Māori population, Pacific people (Pasifika), and those of South Asian descent.[[8,9]]

In a recent study we found that not only were risk factors for diabetes complications more prevalent in young people with T2D than in young people with T1D, but irrespective of diabetes type, there were also striking correlations between the prevalence of risk factors and a national index of socio-economic deprivation.[[10]] In this paper we have examined the healthcare usage of young people with T2D and T1D in this same cohort to try to identify what aspects of healthcare usage could underlie this relationship. The measures of healthcare usage considered in this study were primary care visits, referral to and attendance at diabetes outpatient services and hospital admissions.

Methods

People with T1D or T2D diabetes diagnosed between the ages of 15 and 30 who had been referred to secondary diabetes services in the greater Auckland region between January 2003 and August 2015 were identified by searching hospital databases. This study was conducted at adult diabetes centres; thus children were not included, minimising the possibility of congenital/syndromic causes of diabetes being mistakenly included. The use of the 15–30-year-old age band also allowed direct comparison with the notable work done by Constantino et al. in Australia regarding diabetes-related complications.[[3]] In order to obtain a sample of young people with T1D and T2D, individual medical records were reviewed for people referred between 15 and 35 years of age (to capture delayed referrals), who were <40 years old at the time of the study. The year of diagnosis and type of diabetes was established from clinical and laboratory records. HbA{{1c}} levels were collected from 2015–2016 (a median 8 years following diagnosis), and an individual’s mean HbA{{1c}} from all values available in the 2015–2016 period was calculated. As there is often uncertainty as to the date of onset of T2D, we also recorded the highest HbA{{1c}} in the year of diagnosis, given that this value was most likely to represent the situation prior to treatment.

Socio-economic deprivation was determined from the New Zealand Index of Deprivation (NZDep) 2013 schedule based on residency status and geographic living area, obtained from Primary Health Organisations’ enrolment demographic quarterly tables. Decile 1 represents the least deprived and decile 10 the most deprived area.[[11]]

The time from the year of diagnosis in primary care and other hospital services to the year of referral to specialist diabetes services was recorded for people with T2D from hospital databases across the three regional district health boards (DHB); this time (in years) was taken as the time to referral to DHB diabetes services. Delayed referral was defined as time to referral >1 year and this analysis was only conducted for the T2D group. Almost all people with T1D are referred to a diabetes specialist from the time of diagnosis and are offered continued follow-up by specialist diabetes services. We assume that the majority of people with T2D would be referred to public specialist services because retinal screening is carried out almost exclusively in these settings. Diabetes outpatient clinic appointments offered and attended across the greater Auckland region were recorded from hospital databases over the 2-year period, 2015–2016. An appointment offered but not attended was defined as “Did Not Attend” (DNA). A 2-year time frame was used to determine diabetes clinic attendance to capture those who may have only had an annual review. Ethnicity data and nation-wide hospital admissions over the same 2-year period were obtained from the National Minimum Dataset (coded data from public and private hospitals).[[12]] The presence or absence of a primary care (general practice) visit nation-wide over the prior 6 months and prior 1 year (2016) was also obtained from the Ministry of Health; 2-year data and the exact number of primary care visits was not available. Data on the demographic features, complications and medication use of both the T1D and T2D cohorts have been published previously.[[10]]

Statistical analysis

Data analysis was conducted using GraphPad Prism (version 6.00.283) and SAS/STAT software, Version 9.4 of the SAS System for Windows (SAS Institute Inc., Cary, NC, USA). Statistical tests were two-tailed and a significance level of 5% was maintained. For some analyses NZDep levels were divided into five groups (deciles 1–2; 3–4; 5–6 etc.). T-tests were used to compare means between two groups. χ[[2]] tests were used for comparison of categorical variables between groups. For non-normally distributed continuous variables non-parametric tests (Wilcoxon/Mann–Whitney tests/Kruskal–Wallis tests) were used and the results expressed as the median with interquartile range (IQR). Logistic regression was used to analyse the binary variable of delay in referral to specialist diabetes services (where no delay was defined as a referral within a year of diagnosis), with NZDep, age at diabetes diagnosis and HbA{{1c}} in the year of diagnosis included as explanatory variables.

Results

Primary care visits

Seven hundred and thirty-one young people with T1D and 1,350 with T2D were included in this study. More than 80% of both groups (86% and 83% for T1D and T2D respectively) had attended a primary care appointment in a 1-year period, and although the proportion was greater for people with T1D than those with T2D the difference was small (Table 1). There was no evidence of an association between the proportion of each group with at least one primary care visit and deprivation (Table 2), and there was no difference in mean HbA{{1c}} between those who did and did not have a primary care visit (Table 3). Of people with mean HbA{{1c}} ≥100 mmol/mol, 29% (23/79) of those with T1D and 33% (78/236) of those with T2D had not been seen in primary care in the preceding 6 months.

Referrals to secondary diabetes services

Between 2003 and 2014, the number of referrals increased substantially. In part this reflected Auckland’s population growth (increased by 17%),[[13]] but the rate of increase in referrals was greater for T2D (increased by a factor of 2.5) than for T1D (increased by a factor of 1.8). Over this period, among young people with T2D, referrals tripled for Pasifika people and doubled for Māori, while referrals for the European population increased by a factor of 1.3.

Forty-eight percent (n=653) of the T2D group were referred to specialist diabetes services in the year that they were diagnosed, while the remainder, defined in this study as a delayed referral, were referred a median 3 years (IQR 1, 5) after diagnosis. Ethnicity and NZDep were strongly related with 65% of indigenous Māori and 71% of Pasifika young people living in the lowest two decile areas.[[10]] Only one of these variables, NZDep, was used in logistic regression analysis. Multivariate logistic regression analysis showed for every decile increase in NZDep the odds of a delayed referral increased by 15% (OR 1.15, 95% CI 1.07–1.24, p=0.0003), following adjustment for age and HbA{{1c}} in the year of diagnosis. For every year increase in age at diagnosis, the odds of delayed referral increased by 6% (OR 1.06, 95% CI 1.02–1.10, p=0.004). For every 10 mmol/mol increase in HbA{{1c}} in the year of diagnosis, the odds of delayed referral decreased by 13% (OR 0.87, 95% CI 0.81–0.93, p<0.001), meaning a higher HbA{{1c}} at presentation prompted earlier referral. However, those who had had a delayed referral to diabetes services following diagnosis had a higher mean HbA{{1c}} in the 2015–2016 period (Table 3).

Diabetes clinic attendance

In the 2015–2016 period, people with T1D were offered significantly more per person diabetes clinic appointments than people with T2D (2 (IQR 0, 7) vs 0 (IQR 0, 2), p<0.001). Sixty percent of people with T1D had attended a diabetes clinic appointment in this 2-year period and 39% (n=282) had missed appointments (DNA) (Table 1). A smaller proportion, 37%, of the T2D group had attended a diabetes clinic with a smaller proportion of DNAs (30%, n=405). The likelihood of people missing appointments varied significantly between different deprivation quintiles in the T2D group (p=0.02, Table 2).

Seventeen percent (n=236) of people with T2D had an HbA{{1c}} >100mmol/mol. Only 47% of this group had a diabetes clinic attendance in the 2-year period. Of the 79 with T1D and HbA{{1c}} >100mmol/mol, 78% (n=62) had attended a clinic appointment (p <0.001).

The proportion of people with a DNA increased with increasing degrees of deprivation in the T2D group but in not the T1D group (Table 2). In both the T1D and T2D group those with missed appointments had a higher mean HbA{{1c}} in the 2015–2016 period (Table 3).

Hospital admissions

In both groups the proportion of people with a hospital admission increased significantly with NZDep categories (Table 2). For T1D the proportion increased from 29% in quintile 1 to 50% in quintile 5; for T2D it increased from 25% to 42%.

Of those with HbA{{1c}} >100mmol/mol, 50% (117/236) of the T2D group and 75% (59/79) of the T1D group had at least one admission over the prior 2-year period. In the T1D group, the mean HbA{{1c}} was significantly higher for those who had at least one admission (Table 3).

View Tables 1–3.

Discussion

Poverty is a key element in young-onset type 2 diabetes.[[6,14–18]] In Auckland, where the majority of young people with T2D live in the most socio-economically deprived areas, it is a risk factor for diabetes complications irrespective of diabetes type.[[10]] We found that the difficulties accessing appropriate healthcare underlie these findings. In the periods studied, the proportion of people with type 1 and type 2 diabetes who attended any primary care appointment was similar, with no relationship to NZDep status. Thirty-six percent of the T2D group had not seen a general practitioner in the preceding 6 months; a concern, as prescriptions are written for a maximum 3-month period. This may partly explain previously documented sub-optimal medication use in this group.[[10, 19]] Thirty-one percent of the T1D group had also not been seen in primary care in the preceding 6 months, however, as discussed below diabetes clinic attendance was higher in this group. Further detail regarding primary care visits was not available to determine whether diabetes was the main focus of these consultations.

Referrals for Māori young people with T2D doubled and referrals for Pasifika youth with T2D tripled over a 12-year period. For people with young-onset T2D, the great majority of referrals to secondary/specialist diabetes services (which in New Zealand are publicly funded) come from primary care. Just under half of those with T2D were referred to specialist diabetes services within a year of diagnosis. We found that those who had higher HbA{{1c}} values and were younger at diagnosis were referred earlier, but socio-economic status also had a significant association. For every decile increase in NZDep, the odds of a delayed referral (>1 year after diagnosis) increased by 15%, and those who had experienced a delayed referral had a significantly higher mean HbA{{1c}} in the 2015–2016 period (following a median duration of diabetes of 8 years).

Financial barriers may deter return to primary care following diagnosis for education, management or referral. Although funding for primary care in New Zealand is subsidised based on degree of socio-economic deprivation and age, it is not fully funded for this age group. Poor health literacy, psychosocial and economic stressors are also likely to be contributing factors.[[14,20]] In New Zealand, where the majority of Māori and Pasifika young people with T2D live in the most socio-economically deprived areas, overcoming communication barriers, eliminating discriminatory healthcare behaviour and providing accessible, culturally safe and appropriate care throughout the healthcare system is needed, as well as addressing practical barriers.[[21,22]]

The “DNA” or “did not attend” rate was high in both the T1D and T2D groups, but somewhat greater in the former. However, the number of appointments offered to people with T1D was substantially greater than the number offered to young people with T2D (in part because management concerns may be dominated by the acute complications of T1D), so overall their attendance was greater. In those with T2D (but not those with T1D), the DNA rate was higher among young people living in more socio-economically deprived areas.

The proportion of young people with hospital admissions increased with greater deprivation for both T1D and T2D, a finding that has been documented in the general diabetes population.[[23–25]] Inpatient time could be used as a “red flag” to link this high-risk population to better diabetes follow-up.

Young-onset T2D is associated with higher rates of microvascular complication and cardiovascular risk factors than people with T1D of similar duration, leading to greater morbidity and mortality in the long term.[[3,10,15]] However, we found that young people with T2D were offered fewer and attended less than half the appointments of their T1D counterparts. We found that young people with T2D are equally at risk of acute illness, as indicated by hospital admissions; there are compelling reasons, both from a short- and long-term perspective, why greater attention needs to be paid to young people with T2D. In particular, a more targeted approach by both primary care and diabetes services is needed to target young T2D people with HbA{{1c}} levels >100mmol/mol.

Primary care attendance was unrelated to deprivation in this study. The literature examining healthcare service use by young-onset T2D people is sparse, but studies from the general T2D population in France and Denmark have shown that general practice visits increased with decreasing socio-economic position, perhaps representing overall poor health.[[26,27]] Fosse-Edorh et al. found that people with T2D in France with financial difficulties visited general practitioners more often and specialists less often, and Hsu et al. reported that poorer diabetes populations in Taiwan attended diabetes clinics less often than the better off.[[28,29]] Healthcare systems differ in other countries; these results cannot be compared directly with other models of care, however, the results are applicable on a national level.

There are limitations to our paper. While each record was reviewed, c-peptide and antibody levels were not measured for each individual with diabetes included in this study, leaving the possibility of mislabelling in some cases; there may also be individuals with characteristics of both types of diabetes. Retrospective data collection for this relatively large cohort meant that it was not practical to obtain details regarding hospital admissions or primary care visits. We were also unable to collect diabetes clinic attendance data on a national level; this data was limited to the three Auckland district health boards. Primary care attendance data was only available for the prior 1-year period, and the exact number of primary care visits was also unavailable. This dataset does not capture people managed in primary care, so it may underestimate the number of young people with T2D in the Auckland region. In addition, several years have passed since this data was collected; the population of young people with T2D in Auckland would have increased since 2015, however, the model of care remains unchanged, and these results are therefore still relevant.

The past decade has seen a number of publications document the poor outcomes of youth with T2D, but their contact with the healthcare system and their barriers to care, such as socio-economic deprivation, are not explored. While healthcare systems across the globe may vary, improving diabetes care to this growing population is a common challenge.[[10,30]] Our data indicates that current models of care are not working well for young people with diabetes, particularly for those living in relative deprivation, which includes the majority of young people with T2D. Socio-economic deprivation plays a key role in important aspects of healthcare service use such as referral to specialist diabetes services, diabetes clinic non-attendance and hospital admissions in young people with T2D; deprivation needs to be addressed in developing a more equitable model of care, especially given increasing inequality in New Zealand.[[8]]

Summary

Abstract

Aim

Lower socio-economic status (SES) is linked to greater morbidity in people with young-onset type 2 (T2D) and type 1 diabetes (T1D). We assessed healthcare utilisation from this population and the impact of SES.

Method

Retrospective analysis of 1,350 people with T2D and 731 with T1D diagnosed between 15–30 years of age referred to secondary dia­betes services in Auckland, New Zealand. Primary care visits, referral to/attendance at diabetes clinics, and hospital admissions were recorded; their relationship to a validated national index of deprivation (NZDep) was assessed.

Results

The proportion with primary care attendance was similar in both groups with no significant variation with NZDep. For T2D, NZDep was a predictor of delayed referral (≧1-year post-diagnosis) to diabetes services, following adjustment for age and HbA{{1c}} in the year of diagnosis (OR 1.15 for every decile increase in NZDep, 95% CI 1.07–1.24, p=0.0003). The median number of appointments offered over a 2-year period was greater for T1D (2.0 (IQR 0, 7) vs (0 (IQR 0, 2), p<0.001); non-attendance increased with NZDep for T2D (p=0.016). The proportion with hospital admissions was similar in both groups and increased with NZDep (T1D p<0.001, T2D p=0.015).

Conclusion

SES impacts several measures of healthcare utilisation. Current healthcare models are inadequately servicing people with young-onset T2D.

Author Information

Sasini Wijayaratna: Diabetologist, Auckland Diabetes Centre, Greenlane Clinical Centre, Auckland District Health Board, PO Box 92189, Victoria Street West, Auckland 1142. Arier Lee: Biostatistician, Department of Population Health, Faculty of Medical and Health Sciences, The University of Auckland, Private Bag 92019, Auckland 1142. Emmanuel Jo: Honorary lecturer, Department of Medicine, Faculty of Medical and Health Sciences, The University of Auckland, Private Bag 92019, Auckland 1142. Manager, Analytics and Intelligence, Health Workforce Directorate, Ministry of Health, PO Box 5013, Wellington 6140. Hyun Young Park: Medical student, Department of Medicine, Faculty of Medical and Health Sciences, The University of Auckland, Private Bag 92019, Auckland 1142. Tim Cundy: Professor, Department of Medicine, Faculty of Medical and Health Sciences, The University of Auckland, Private Bag 92019, Auckland 1142. Warwick Bagg: Professor and deputy dean, Department of Medicine, Faculty of Medical and Health Sciences, The University of Auckland, Private Bag 92019, Auckland 1142.

Acknowledgements

Fiona Wu, A+ Trust Small Project Grant.

Correspondence

Sasini M. Wijayaratna: Auckland Diabetes Centre, Greenlane Clinical Centre, PO Box 92189, Victoria Street West Auckland 1142, New Zealand. Ph: 096309980.

Correspondence Email

SasiniW@adhb.govt.nz

Competing Interests

Nil.

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2) Bjornstad P, Drews KL, Caprio S, Gubitosi-Klug R, Nathan DM, Tesfaldet B, et al. Long-term complications in youth-onset type 2 diabetes. N Engl J Med. 2021;385:416-426.

3) Constantino MI, Molyneaux L, Limacher-Gisler F, Al-Saeed A, Luo C, Wu T, et al. Long-term complications and mortality in young-onset diabetes: type 2 diabetes is more hazardous and lethal than type 1 diabetes. Diabetes Care. 2013;36:3863-9.

4) Srinivasan S, Chen L, Todd J, Divers J, Gidding S, Chernausek S, et al. ProDiGY Consortium. The first genome-wide association study for type 2 diabetes in youth: the Progress in Diabetes Genetics in Youth (ProDiGY) Consortium. Diabetes. 2021;70:996-1005.

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6) McGavock J, Wicklow B, Dart AB. Type 2 diabetes in youth is a disease of poverty. Lancet. 2017;390:1829.

7) Volaco A, Cavalcanti AM, Filho RP, Précoma DB. Socioeconomic status: the missing link between obesity and diabetes mellitus? Curr Diabetes Rev. 2018;14: 321-326.

8) Parry B. Household incomes in New Zealand: trends in indicators of inequality and hardship 1982 to 2016. Wellington: Ministry of Social Development; 2017.

9) Chan WC, Jackson G, Wright CS, Orr-Walker B, Drury PL, Boswell DR, et al. The future of population registers: linking routine health datasets to assess a population’s current glycaemic status for quality improvement. BMJ Open 2014;4:e003975-003975.

10) Wijayaratna S, Lee A, Park HY, Jo E, Wu F, Bagg W, Cundy T. Socioeconomic status and risk factors for complications in young people with type 1 or type 2 diabetes: a cross-sectional study. BMJ Open Diabetes Res Care. 2021;9:10.1136/bmjdrc-002485.

11) Atkinson J, Salmond C, Crampton P. NZDep2013 Index of Deprivation. Wellington: Department of Public Health, University of Otago; 2014.

12) Ministry of Health. National Minimum Dataset (Hospital Events) Data Dictionary. Wellington: Ministry of Health, 2014.

13) Statistics New Zealand: Statistics New Zealand’s Estimated Resident Population, 1996-2021. Available at: https://ecoprofile.infometrics.co.nz/auckland/Population/Growth. Accessed Jan 7 2021.

14) Viner R, White B, Christie D. Type 2 diabetes in adolescents: a severe phenotype posing major clinical challenges and public health burden. Lancet. 2017;389:2252-2260.

15) Dabelea D, Stafford JM, Mayer-Davis EJ, D'Agostino R Jr, Dolan L, Imperatore G, et al. Association of type 1 diabetes vs type 2 diabetes diagnosed during childhood and adolescence with complications during teenage years and young adulthood; SEARCH for Diabetes in Youth Research Group. JAMA. 2017;317:825-35.

16) Copeland KC, Zeitler P, Geffner M, Guandalini C, Higgins J, Hirst K, et al. Characteristics of adolescents and youth with recent-onset type 2 diabetes: the TODAY cohort at baseline. J Clin Endocrinol Metab. 2011;96:159-67.

17) Klingensmith GJ, Connor CG, Ruedy KJ, Beck RW, Kollman C, Haro H, et al. Presentation of youth with type 2 diabetes in the Pediatric Diabetes Consortium. Pediatr Diabetes. 2016;17:266-73.

18) Khanolkar AR, Amin R, Taylor-Robinson D, Viner R, Warner J, Stephenson T, et al. Ethnic minorities are at greater risk for childhood onset type 2 diabetes and poorer glycaemic control in England and Wales. J Adolesc Health. 2016;59:354-61.

19) Kunasegaran S, Beig J, Khanolkar M, Cundy, T. Adherence to medication, glycaemic control and hospital attendance in young adults with type 2 diabetes. Intern Med J. 2018 48:728-31.

20) Hill-Briggs F, Adler NE, Berkowitz SA, Chin MH, Gary-Webb TL, Navas-Acien A, et al. Social determinants of health and diabetes: a scientific review. Diabetes Care. 2020;44:258-79.

21) Stoner L, Matheson A, Hamlin M, Skidmore P. Environmental determinants of childhood obesity: a specific focus on Māori and Pasifika in New Zealand. Perspect Public Health. 2016;136:18-20.

22) Espiner E, Paine SJ, Weston M, Curtis E. Barriers and facilitators for Māori in accessing hospital services in Aotearoa New Zealand. N Z Med J. 2021;134:47-58.

23) Nishino Y, Gilmour S, Shibuya K. Inequality in diabetes-related hospital admissions in England by socioeconomic deprivation and ethnicity: facility-based cross-sectional analysis. PLoS ONE. 2015;10: e0116689.

24) Wild SH, McKnight JA, McConnachie A, Lindsay RS; Glasgow and Lothian Diabetes Register Data Group. Socioeconomic status and diabetes-related hospital admissions: a cross-sectional study of people with diagnosed diabetes. J Epidemiol Community Health. 2010;64:1022-4.

25) Kurani SS, Heien HC, Sangaralingham LR, Inselman JW, Shah ND, Golden SH, et al. Association of area-level socioeconomic deprivation with hypoglycemic and hyperglycemic crises in US adults with diabetes. JAMA Netw Open. 2022;5:e2143597

26) Lamy S, Ducros D, Diméglio C, Colineaux H, Fantin R, Berger E, et al. Disentangling the influence of living place and socioeconomic position on health services use among diabetes patients: A population-based study. PLoS ONE. 2017;12:e0188295.

27) Dalsgaard EM, Vedsted P, Fenger-Grøn M. Socioeconomic position and contact to general practice among persons with diabetes. Prim Care Diabetes. 2012;6:313-8.

28) Fosse-Edorh S, Fagot-Campagna A, Detournay B, Bihan H, Eschwege E, Gautier A, et al. Impact of socio‐economic position on health and quality of care in adults with type 2 diabetes in France: the Entred 2007 study. Diabet Med. 2015 Nov;32:1438-44.

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As the prevalence of type 2 diabetes (T2D) has increased, the average age at diagnosis has fallen, and consequently diabetes in the second and third decades of life has become more common.[[1]] People who develop T2D early in life are at risk of microvascular complications of diabetes and cardiovascular disease. Compared to people with type 1 diabetes (T1D) of similar age and duration of diabetes, those with T2D tend to have higher glycated haemoglobin (HbA{{1c}}) levels and develop diabetes-related complications earlier.[[1–3]]

While various biological theories, including increasing prevalence of obesity in young people, genetics and intra-uterine programming, have been invoked to explain the rising prevalence of young-onset T2D, the role of socio-economic deprivation is critical.[[2,4]] In high-income countries, T2D in young people disproportionately affects Indigenous and minority communities, a phenomenon related to high rates of obesity and inequality.[[5–7]] In Aotearoa New Zealand, which has experienced marked increases in inequality, early onset T2D disproportionately affects the Indigenous Māori population, Pacific people (Pasifika), and those of South Asian descent.[[8,9]]

In a recent study we found that not only were risk factors for diabetes complications more prevalent in young people with T2D than in young people with T1D, but irrespective of diabetes type, there were also striking correlations between the prevalence of risk factors and a national index of socio-economic deprivation.[[10]] In this paper we have examined the healthcare usage of young people with T2D and T1D in this same cohort to try to identify what aspects of healthcare usage could underlie this relationship. The measures of healthcare usage considered in this study were primary care visits, referral to and attendance at diabetes outpatient services and hospital admissions.

Methods

People with T1D or T2D diabetes diagnosed between the ages of 15 and 30 who had been referred to secondary diabetes services in the greater Auckland region between January 2003 and August 2015 were identified by searching hospital databases. This study was conducted at adult diabetes centres; thus children were not included, minimising the possibility of congenital/syndromic causes of diabetes being mistakenly included. The use of the 15–30-year-old age band also allowed direct comparison with the notable work done by Constantino et al. in Australia regarding diabetes-related complications.[[3]] In order to obtain a sample of young people with T1D and T2D, individual medical records were reviewed for people referred between 15 and 35 years of age (to capture delayed referrals), who were <40 years old at the time of the study. The year of diagnosis and type of diabetes was established from clinical and laboratory records. HbA{{1c}} levels were collected from 2015–2016 (a median 8 years following diagnosis), and an individual’s mean HbA{{1c}} from all values available in the 2015–2016 period was calculated. As there is often uncertainty as to the date of onset of T2D, we also recorded the highest HbA{{1c}} in the year of diagnosis, given that this value was most likely to represent the situation prior to treatment.

Socio-economic deprivation was determined from the New Zealand Index of Deprivation (NZDep) 2013 schedule based on residency status and geographic living area, obtained from Primary Health Organisations’ enrolment demographic quarterly tables. Decile 1 represents the least deprived and decile 10 the most deprived area.[[11]]

The time from the year of diagnosis in primary care and other hospital services to the year of referral to specialist diabetes services was recorded for people with T2D from hospital databases across the three regional district health boards (DHB); this time (in years) was taken as the time to referral to DHB diabetes services. Delayed referral was defined as time to referral >1 year and this analysis was only conducted for the T2D group. Almost all people with T1D are referred to a diabetes specialist from the time of diagnosis and are offered continued follow-up by specialist diabetes services. We assume that the majority of people with T2D would be referred to public specialist services because retinal screening is carried out almost exclusively in these settings. Diabetes outpatient clinic appointments offered and attended across the greater Auckland region were recorded from hospital databases over the 2-year period, 2015–2016. An appointment offered but not attended was defined as “Did Not Attend” (DNA). A 2-year time frame was used to determine diabetes clinic attendance to capture those who may have only had an annual review. Ethnicity data and nation-wide hospital admissions over the same 2-year period were obtained from the National Minimum Dataset (coded data from public and private hospitals).[[12]] The presence or absence of a primary care (general practice) visit nation-wide over the prior 6 months and prior 1 year (2016) was also obtained from the Ministry of Health; 2-year data and the exact number of primary care visits was not available. Data on the demographic features, complications and medication use of both the T1D and T2D cohorts have been published previously.[[10]]

Statistical analysis

Data analysis was conducted using GraphPad Prism (version 6.00.283) and SAS/STAT software, Version 9.4 of the SAS System for Windows (SAS Institute Inc., Cary, NC, USA). Statistical tests were two-tailed and a significance level of 5% was maintained. For some analyses NZDep levels were divided into five groups (deciles 1–2; 3–4; 5–6 etc.). T-tests were used to compare means between two groups. χ[[2]] tests were used for comparison of categorical variables between groups. For non-normally distributed continuous variables non-parametric tests (Wilcoxon/Mann–Whitney tests/Kruskal–Wallis tests) were used and the results expressed as the median with interquartile range (IQR). Logistic regression was used to analyse the binary variable of delay in referral to specialist diabetes services (where no delay was defined as a referral within a year of diagnosis), with NZDep, age at diabetes diagnosis and HbA{{1c}} in the year of diagnosis included as explanatory variables.

Results

Primary care visits

Seven hundred and thirty-one young people with T1D and 1,350 with T2D were included in this study. More than 80% of both groups (86% and 83% for T1D and T2D respectively) had attended a primary care appointment in a 1-year period, and although the proportion was greater for people with T1D than those with T2D the difference was small (Table 1). There was no evidence of an association between the proportion of each group with at least one primary care visit and deprivation (Table 2), and there was no difference in mean HbA{{1c}} between those who did and did not have a primary care visit (Table 3). Of people with mean HbA{{1c}} ≥100 mmol/mol, 29% (23/79) of those with T1D and 33% (78/236) of those with T2D had not been seen in primary care in the preceding 6 months.

Referrals to secondary diabetes services

Between 2003 and 2014, the number of referrals increased substantially. In part this reflected Auckland’s population growth (increased by 17%),[[13]] but the rate of increase in referrals was greater for T2D (increased by a factor of 2.5) than for T1D (increased by a factor of 1.8). Over this period, among young people with T2D, referrals tripled for Pasifika people and doubled for Māori, while referrals for the European population increased by a factor of 1.3.

Forty-eight percent (n=653) of the T2D group were referred to specialist diabetes services in the year that they were diagnosed, while the remainder, defined in this study as a delayed referral, were referred a median 3 years (IQR 1, 5) after diagnosis. Ethnicity and NZDep were strongly related with 65% of indigenous Māori and 71% of Pasifika young people living in the lowest two decile areas.[[10]] Only one of these variables, NZDep, was used in logistic regression analysis. Multivariate logistic regression analysis showed for every decile increase in NZDep the odds of a delayed referral increased by 15% (OR 1.15, 95% CI 1.07–1.24, p=0.0003), following adjustment for age and HbA{{1c}} in the year of diagnosis. For every year increase in age at diagnosis, the odds of delayed referral increased by 6% (OR 1.06, 95% CI 1.02–1.10, p=0.004). For every 10 mmol/mol increase in HbA{{1c}} in the year of diagnosis, the odds of delayed referral decreased by 13% (OR 0.87, 95% CI 0.81–0.93, p<0.001), meaning a higher HbA{{1c}} at presentation prompted earlier referral. However, those who had had a delayed referral to diabetes services following diagnosis had a higher mean HbA{{1c}} in the 2015–2016 period (Table 3).

Diabetes clinic attendance

In the 2015–2016 period, people with T1D were offered significantly more per person diabetes clinic appointments than people with T2D (2 (IQR 0, 7) vs 0 (IQR 0, 2), p<0.001). Sixty percent of people with T1D had attended a diabetes clinic appointment in this 2-year period and 39% (n=282) had missed appointments (DNA) (Table 1). A smaller proportion, 37%, of the T2D group had attended a diabetes clinic with a smaller proportion of DNAs (30%, n=405). The likelihood of people missing appointments varied significantly between different deprivation quintiles in the T2D group (p=0.02, Table 2).

Seventeen percent (n=236) of people with T2D had an HbA{{1c}} >100mmol/mol. Only 47% of this group had a diabetes clinic attendance in the 2-year period. Of the 79 with T1D and HbA{{1c}} >100mmol/mol, 78% (n=62) had attended a clinic appointment (p <0.001).

The proportion of people with a DNA increased with increasing degrees of deprivation in the T2D group but in not the T1D group (Table 2). In both the T1D and T2D group those with missed appointments had a higher mean HbA{{1c}} in the 2015–2016 period (Table 3).

Hospital admissions

In both groups the proportion of people with a hospital admission increased significantly with NZDep categories (Table 2). For T1D the proportion increased from 29% in quintile 1 to 50% in quintile 5; for T2D it increased from 25% to 42%.

Of those with HbA{{1c}} >100mmol/mol, 50% (117/236) of the T2D group and 75% (59/79) of the T1D group had at least one admission over the prior 2-year period. In the T1D group, the mean HbA{{1c}} was significantly higher for those who had at least one admission (Table 3).

View Tables 1–3.

Discussion

Poverty is a key element in young-onset type 2 diabetes.[[6,14–18]] In Auckland, where the majority of young people with T2D live in the most socio-economically deprived areas, it is a risk factor for diabetes complications irrespective of diabetes type.[[10]] We found that the difficulties accessing appropriate healthcare underlie these findings. In the periods studied, the proportion of people with type 1 and type 2 diabetes who attended any primary care appointment was similar, with no relationship to NZDep status. Thirty-six percent of the T2D group had not seen a general practitioner in the preceding 6 months; a concern, as prescriptions are written for a maximum 3-month period. This may partly explain previously documented sub-optimal medication use in this group.[[10, 19]] Thirty-one percent of the T1D group had also not been seen in primary care in the preceding 6 months, however, as discussed below diabetes clinic attendance was higher in this group. Further detail regarding primary care visits was not available to determine whether diabetes was the main focus of these consultations.

Referrals for Māori young people with T2D doubled and referrals for Pasifika youth with T2D tripled over a 12-year period. For people with young-onset T2D, the great majority of referrals to secondary/specialist diabetes services (which in New Zealand are publicly funded) come from primary care. Just under half of those with T2D were referred to specialist diabetes services within a year of diagnosis. We found that those who had higher HbA{{1c}} values and were younger at diagnosis were referred earlier, but socio-economic status also had a significant association. For every decile increase in NZDep, the odds of a delayed referral (>1 year after diagnosis) increased by 15%, and those who had experienced a delayed referral had a significantly higher mean HbA{{1c}} in the 2015–2016 period (following a median duration of diabetes of 8 years).

Financial barriers may deter return to primary care following diagnosis for education, management or referral. Although funding for primary care in New Zealand is subsidised based on degree of socio-economic deprivation and age, it is not fully funded for this age group. Poor health literacy, psychosocial and economic stressors are also likely to be contributing factors.[[14,20]] In New Zealand, where the majority of Māori and Pasifika young people with T2D live in the most socio-economically deprived areas, overcoming communication barriers, eliminating discriminatory healthcare behaviour and providing accessible, culturally safe and appropriate care throughout the healthcare system is needed, as well as addressing practical barriers.[[21,22]]

The “DNA” or “did not attend” rate was high in both the T1D and T2D groups, but somewhat greater in the former. However, the number of appointments offered to people with T1D was substantially greater than the number offered to young people with T2D (in part because management concerns may be dominated by the acute complications of T1D), so overall their attendance was greater. In those with T2D (but not those with T1D), the DNA rate was higher among young people living in more socio-economically deprived areas.

The proportion of young people with hospital admissions increased with greater deprivation for both T1D and T2D, a finding that has been documented in the general diabetes population.[[23–25]] Inpatient time could be used as a “red flag” to link this high-risk population to better diabetes follow-up.

Young-onset T2D is associated with higher rates of microvascular complication and cardiovascular risk factors than people with T1D of similar duration, leading to greater morbidity and mortality in the long term.[[3,10,15]] However, we found that young people with T2D were offered fewer and attended less than half the appointments of their T1D counterparts. We found that young people with T2D are equally at risk of acute illness, as indicated by hospital admissions; there are compelling reasons, both from a short- and long-term perspective, why greater attention needs to be paid to young people with T2D. In particular, a more targeted approach by both primary care and diabetes services is needed to target young T2D people with HbA{{1c}} levels >100mmol/mol.

Primary care attendance was unrelated to deprivation in this study. The literature examining healthcare service use by young-onset T2D people is sparse, but studies from the general T2D population in France and Denmark have shown that general practice visits increased with decreasing socio-economic position, perhaps representing overall poor health.[[26,27]] Fosse-Edorh et al. found that people with T2D in France with financial difficulties visited general practitioners more often and specialists less often, and Hsu et al. reported that poorer diabetes populations in Taiwan attended diabetes clinics less often than the better off.[[28,29]] Healthcare systems differ in other countries; these results cannot be compared directly with other models of care, however, the results are applicable on a national level.

There are limitations to our paper. While each record was reviewed, c-peptide and antibody levels were not measured for each individual with diabetes included in this study, leaving the possibility of mislabelling in some cases; there may also be individuals with characteristics of both types of diabetes. Retrospective data collection for this relatively large cohort meant that it was not practical to obtain details regarding hospital admissions or primary care visits. We were also unable to collect diabetes clinic attendance data on a national level; this data was limited to the three Auckland district health boards. Primary care attendance data was only available for the prior 1-year period, and the exact number of primary care visits was also unavailable. This dataset does not capture people managed in primary care, so it may underestimate the number of young people with T2D in the Auckland region. In addition, several years have passed since this data was collected; the population of young people with T2D in Auckland would have increased since 2015, however, the model of care remains unchanged, and these results are therefore still relevant.

The past decade has seen a number of publications document the poor outcomes of youth with T2D, but their contact with the healthcare system and their barriers to care, such as socio-economic deprivation, are not explored. While healthcare systems across the globe may vary, improving diabetes care to this growing population is a common challenge.[[10,30]] Our data indicates that current models of care are not working well for young people with diabetes, particularly for those living in relative deprivation, which includes the majority of young people with T2D. Socio-economic deprivation plays a key role in important aspects of healthcare service use such as referral to specialist diabetes services, diabetes clinic non-attendance and hospital admissions in young people with T2D; deprivation needs to be addressed in developing a more equitable model of care, especially given increasing inequality in New Zealand.[[8]]

Summary

Abstract

Aim

Lower socio-economic status (SES) is linked to greater morbidity in people with young-onset type 2 (T2D) and type 1 diabetes (T1D). We assessed healthcare utilisation from this population and the impact of SES.

Method

Retrospective analysis of 1,350 people with T2D and 731 with T1D diagnosed between 15–30 years of age referred to secondary dia­betes services in Auckland, New Zealand. Primary care visits, referral to/attendance at diabetes clinics, and hospital admissions were recorded; their relationship to a validated national index of deprivation (NZDep) was assessed.

Results

The proportion with primary care attendance was similar in both groups with no significant variation with NZDep. For T2D, NZDep was a predictor of delayed referral (≧1-year post-diagnosis) to diabetes services, following adjustment for age and HbA{{1c}} in the year of diagnosis (OR 1.15 for every decile increase in NZDep, 95% CI 1.07–1.24, p=0.0003). The median number of appointments offered over a 2-year period was greater for T1D (2.0 (IQR 0, 7) vs (0 (IQR 0, 2), p<0.001); non-attendance increased with NZDep for T2D (p=0.016). The proportion with hospital admissions was similar in both groups and increased with NZDep (T1D p<0.001, T2D p=0.015).

Conclusion

SES impacts several measures of healthcare utilisation. Current healthcare models are inadequately servicing people with young-onset T2D.

Author Information

Sasini Wijayaratna: Diabetologist, Auckland Diabetes Centre, Greenlane Clinical Centre, Auckland District Health Board, PO Box 92189, Victoria Street West, Auckland 1142. Arier Lee: Biostatistician, Department of Population Health, Faculty of Medical and Health Sciences, The University of Auckland, Private Bag 92019, Auckland 1142. Emmanuel Jo: Honorary lecturer, Department of Medicine, Faculty of Medical and Health Sciences, The University of Auckland, Private Bag 92019, Auckland 1142. Manager, Analytics and Intelligence, Health Workforce Directorate, Ministry of Health, PO Box 5013, Wellington 6140. Hyun Young Park: Medical student, Department of Medicine, Faculty of Medical and Health Sciences, The University of Auckland, Private Bag 92019, Auckland 1142. Tim Cundy: Professor, Department of Medicine, Faculty of Medical and Health Sciences, The University of Auckland, Private Bag 92019, Auckland 1142. Warwick Bagg: Professor and deputy dean, Department of Medicine, Faculty of Medical and Health Sciences, The University of Auckland, Private Bag 92019, Auckland 1142.

Acknowledgements

Fiona Wu, A+ Trust Small Project Grant.

Correspondence

Sasini M. Wijayaratna: Auckland Diabetes Centre, Greenlane Clinical Centre, PO Box 92189, Victoria Street West Auckland 1142, New Zealand. Ph: 096309980.

Correspondence Email

SasiniW@adhb.govt.nz

Competing Interests

Nil.

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