1. INTRODUCTION
Despite widespread availability overseas and established clinical efficacy in Type 2 diabetes (T2D) Sodium‐Glucose Transport Protein 2 Inhibitors (SGLT2i) and Glucagon‐Like Peptide‐1 Receptor Agonists (GLP1RA) medications have not been funded for use in Aotearoa New Zealand (NZ) until 2021. 1 However, T2D associates with significant health inequity in NZ, particularly for Māori (Indigenous population) and Pacific peoples 2 , 3 and SGLT2i (empagliflozin) and GLP1RA (dulaglutide) are now funded under special authority criteria with prioritised access for Māori and Pacific people. 1 Whilst initial use of these medications by Māori and Pacific has been relatively high 4 there is still concern that medication use may not be consistent because of systemic 5 and patient‐level factors. 6
Medication adherence, often measured by the Medication Possession Ratio (MPR) is a key metric for measuring the effective use of such treatments, with an MPR >0.8 being a consensus cutoff as a proxy for good adherence. 7 Using this, this study aims to characterise the MPR of empagliflozin and/or dulaglutide in a cohort of NZ patients with T2D and to determine if inequity in empagliflozin/dulaglutide use exists.
2. METHODS
Primary care clinical and demographic data were collected from 302 general practice clinics across the Waikato/Auckland regions of NZ for the period of February 2021 to August 2022 to coincide with the funded availability of empagliflozin and dulaglutide from Feb 1 2021. This cohort comprised 57 633 patients (23 280 NZ European, 11 675 Māori, 10 414 Pacific, 10 940 Asian, 925 Middle Eastern/Latin American/African (MELAA), 509 Others). Dispensing data from the Ministry of Health's Pharmaceutical dispensed medication database (February 2021–December 2022) was linked to calculate the MPR for empagliflozin and dulaglutide users with at least two dispensing events as described previously. 8 The extra four months of data were to allow for medications dispensed towards the end of the initial 18‐month study period, noting that prescriptions are valid fully funded for 90 days. Patients who had been co‐prescribed both medications on the same day (n = 122) were removed from the dataset as patients are only funded for one class of medication (SGLT2i or GLP1RA) at any given time. Criteria for medication access has been reported elsewhere. 4
The MPR of newly initiated empagliflozin and dulaglutide were calculated by summing the days of medication supply and dividing by the total number of days of the dispensing period. As a control (i.e., using a medication that was not newly initiated) the MPR for metformin in those patients who had ≥2 dispensing events of either empagliflozin or dulaglutide was also calculated.
MPRs were described by patient (age group, gender, ethnicity and mean HbA1c) and practice‐level factors clinic location (rural/urban), Māori health provider (Yes/No), after‐hours clinic hours (Yes/No) and/or a very low cost [patient fees] access (VLCA practice; Yes/No; government initiative to support health access for high needs communities) as well as the use of concurrent glucose‐lowering medications during the same study period. Subgroup differences were analysed with Student's t‐tests and chi‐square, and logistic regression was used to estimate the odds ratio of a patient having good adherence (MPR ≥ 0.8), 7 adjusting for diabetes treatment regimen, mean HbA1c, age, gender, ethnicity and rurality. Data analyses were performed in Python 3.7 (Python Software Foundation, Beaverton, USA), with significance accepted at p < 0.05.
The full project was granted ethics approval by the NZ Health and Disability Ethics Committee (ref: 19/CEN/8).
3. RESULTS
Of the total cohort (n = 57 633), 22 331 met the clinical criteria for access to an SGLT2i and/or GLP1RA agent. Of this, 13 430 (60.1%) had been dispensed one of these agents at least once, and 13 056 (58.5%) had at least two dispensing events (n = 11 049 empagliflozin and n = 2007 dulaglutide [mean 10.9 ± 11.2 and 4.7 ± 3.3 dispensing events, respectively, p < 0.001]). Metformin was prescribed to 9749 empagliflozin users (88.3%) and to 1677 (83.7%) dulaglutide users.
Both medications were used more in older patients, with 80% of patients for both drugs aged ≥45 years. Empagliflozin users were more likely to be male (58.3% vs. female 41.7%), while dulaglutide users were more likely to be female (55.4% vs. males 44.6%; p < 0.001). Insulin use was higher in dulaglutide users (56.9% vs. 39.6% for empagliflozin; p < 0.05) though the use of other medications was comparable across both groups. The characteristics of these patients and medication use are shown in Table 1, whilst the logistic regression of variables impacting the likelihood of an MPR ≥ 0.8 is given in Table 2.
TABLE 1.
Baseline characteristics, mean MPR and proportion of patients with MPR ≥ 0.8 for empagliflozin, dulaglutide and metformin.
| ≥2 dispensing, N (%) | Mean (SD) MPR | p value* | MPR ≥ 0.8****, N (%) | p value** | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Empagliflozin | Metformin (on empagliflozin) | Dulaglutide | Metformin (on dulaglutide) | Empagliflozin | Metformin (on empagliflozin) | Dulaglutide | Metformin (on dulaglutide) | Empagliflozin | Metformin (on empagliflozin) | Dulaglutide | Metformin (on dulaglutide) | |||
| Total, n (%) | 11 049 | 9749 (88.3) | 2007 | 1677 (83.7) | 0.87 (0.23) | 0.95 (0.14) | 0.92 (0.18) | 0.94 (0.15) | <0.001 | 8418 (76.2) | 8749 (89.7) | 1689 (84.2) | 1465 (87.4) | <0.001 |
| Age, median [Q1, Q3] | 59.0 [51.0, 66.0] | 56.0 [48.0, 64.0] | 57 [49.0,64.0] | 59.0 [52.0, 66.0] | 55.9 [55.3, 56.4] | <0.001 | ||||||||
| Age, n (%) | ||||||||||||||
| 16–25 | 63 (0.6) | 47 (0.5) | 30 (1.5) | 25 (1.5) | 0.78 (0.26) | 0.83 (0.24) | 0.82 (0.26) | 0.85 (0.21) | <0.001 | 35 (55.6) | 29 (61.7) | 21 (70.0) | 16 (64.0) | <0.001 |
| 26–34 | 300 (2.7) | 253 (2.6) | 100 (5.0) | 78 (4.7) | 0.80 (0.26) | 0.88 (0.21) | 0.84 (0.20) | 0.89 (0.19) | 182 (60.7) | 189 (74.7) | 60 (60.0) | 61 (78.2) | ||
| 35–44 | 1072 (9.7) | 919 (9.4) | 231 (11.5) | 195 (11.6) | 0.84 (0.24) | 0.92 (0.17) | 0.93 (0.15) | 0.90 (0.19) | 727 (67.8) | 777 (84.5) | 193 (83.5 | 157 (80.5) | ||
| 45–59 | 4438 (40.2) | 3994 (41.0) | 851 (42.4) | 730 (43.5) | 0.88 (0.22) | 0.95 (0.14) | 0.93 (0.16) | 0.95 (0.14) | 3315 (74.7) | 3592 (89.9) | 724 (85.1) | 653 (89.5) | ||
| 60–75 | 5176 (46.9) | 4536 (46.5) | 795 (39.6) | 649 (38.7) | 0.90 (0.20) | 0.96 (0.13) | 0.93 (0.18) | 0.94 (0.14) | 4159 (80.4) | 4162 (91.8) | 691 (86.9) | 578 (89.1) | ||
| Ethnicity, n (%) | ||||||||||||||
| European | 3781 (34.2) | 3258 (33.0) | 856 (42.3) | 692 (40.9) | 0.93 (0.18) | 0.96 (0.13) | 0.94 (0.16) | 0.95 (0.14) | <0.001 | 3155 (83.8) | 2966 (91.6) | 745 (87.0) | 620 (89.6) | <0.001 |
| Māori | 2990 (27.1) | 2538 (26.4) | 676 (34.0) | 575 (34.6) | 0.88 (0.23) | 0.92 (0.17) | 0.92 (0.17) | 0.97 (0.09) | 2203 (73.7) | 2174 (85.7) | 559 (82.7) | 481 (83.7) | ||
| Pacific | 2624 (23.7) | 2458 (25.3) | 291 (14.4) | 256 (15.2) | 0.83 (0.24) | 0.95 (0.14) | 0.87 (0.22) | 0.93 (0.16) | 1758 (67.0) | 2203 (89.6) | 228 (78.4) | 221 (86.3) | ||
| Asian | 1445 (13.1) | 1308 (13.4) | 144 (7.2) | 119 (7.1) | 0.89 (0.21) | 0.97 (0.12) | 0.93 (0.17) | 0.97 (0.09) | 1140 (78.9) | 1229 (94.0) | 120 (83.8) | 112 (94.1) | ||
| MELAA | 118 (1.1) | 105 (1.1) | 17 (0.8) | 16 (1.0) | 0.87 (0.23) | 0.98 (0.06) | 0.96 (0.08) | 0.96 (0.10) | 87 (73.7) | 103 (98.1) | 15 (88.2) | 15 (93.8) | ||
| Other | 91 (0.8) | 82 (0.8) | 23 (1.2) | 19 (1.3) | 0.92 (0.19) | 0.95 (0.15) | 0.94 (0.17) | 0.90 (0.23) | 75 (82.4) | 74 (90.3) | 22 (95.7) | 16 (84.2) | ||
| NZDep18, n (%) | ||||||||||||||
| Quintile 1 | 1560 (14.3) | 1364 (14.2) | 318 (16.1) | 272 (16.5) | 0.91 (0.20) | 0.95 (0.14) | 0.95 (0.15) | 0.96 (0.12) | 0.652 | 1309 (83.9) | 1233 (90.4) | 294 (92.5) | 244 (89.7) | 0.235 |
| Quintile 2 | 2638 (24.3) | 2313 (24.1) | 502 (25.4) | 409 (24.7) | 0.91 (0.20) | 0.95 (0.14) | 0.91 (0.18) | 0.94 (0.15) | 2194 (83.2) | 2085 (90.1) | 418 (83.3) | 354 (86.6) | ||
| Quintile 3 | 2374 (21.8) | 2056 (21.4) | 488 (24.7) | 398 (24.1) | 0.89 (0.21) | 0.93 (0.17) | 0.90 (0.20) | 0.91 (0.18) | 1891 (79.7) | 1818 (88.4) | 400 (82.0) | 332 (83.4) | ||
| Quintile 4 | 1636 (15.0) | 1469 (15.3) | 272 (13.8) | 233 (14.1) | 0.83 (0.24) | 0.95 (0.13) | 0.92 (0.17) | 0.94 (0.15) | 1145 (70.0) | 1334 (90.8) | 227 (83.5) | 205 (88.0) | ||
| Quintile 5 | 2667 (24.5) | 2408 (25.1) | 397 (20.1) | 341 (20.6) | 0.81 (0.25) | 0.95 (0.14) | 0.91 (0.18) | 0.95 (0.14) | 1723 (64.6) | 2153 (89.5) | 329 (82.9) | 309 (90.6) | ||
| Male, n (%) | 6439 (58.3) | 5832 (59.8) | 895 (44.6) | 781 (46.6) | 0.89 (0.21) | 0.95 (0.14) | 0.93 (0.17) | 0.94 (0.13) | <0.001 | 5036 (78.2) | 5245 (89.9) | 756 (84.5) | 693 (88.7) | <0.001 |
| Urban, n (%) | 9211 (83.4) | 8182 (83.9) | 1676 (83.5) | 1416 (84.4) | 0.87 (0.22) | 0.95 (0.14) | 0.92 (0.18) | 0.94 (0.15) | <0.001 | 6837 (74.2) | 7342 (89.7) | 1415 (84.4) | 1244 (87.8) | 0.017 |
| CVRD status | ||||||||||||||
| Yes | 6838 (61.9) | 6042 (62.0) | 1175 (58.5) | 966 (57.6) | 0.87 (0.23) | 0.95 (0.14) | 0.92 (0.18) | 0.95 (0.14) | <0.001 | 5210 (76.2) | 5438 (90.0) | 999 (85.0) | 844 (87.4) | 0.017 |
| No | 2448 (22.2) | 2200 (22.6) | 454 (22.6) | 381 (22.7) | 0.89 (0.22) | 0.95 (0.13) | 0.93 (0.17) | 0.95 (0.14) | 1928 (78.7) | 1997 (90.8) | 390 (85.9) | 340 (89.2) | ||
| Unknown | 1763 (16.0) | 1507 (15.5) | 378 (18.8) | 330 (19.7) | 0.86 (0.23) | 0.94 (0.15) | 0.90 (0.19) | 0.92 (0.16) | 1280 (72.6) | 1314 (87.2) | 300 (79.4) | 281 (85.2) | ||
| HbA1c (%), mean (SD) |
8.5 (3.8) [69 (18) mmol/mol] |
8.5 (3.8) [69 (18) mmol/mol] |
8.7 (3.9) [72 (19) mmol/mol] |
8.7 (3.9) [72 (19) mmol/mol] |
8.4 (3.6) [68 (16) mmol/mol] |
8.5 (3.8) [69 (18) mmol/mol] |
8.6 (3.9) [70 (19) mmol/mol] |
8.6 (3.8) [70 (18) mmol/mol] |
<0.001 | |||||
| HbA1c, n (%) | ||||||||||||||
| <8% (64 mmol/mol) | 5128 (46.7) | 4595 (47.4) | 833 (41.7) | 697 (41.8) | 0.91 (0.20) | 0.96 (0.12) | 0.94 (0.15) | 0.95 (0.13) | <0.001 | 4214 (82.2) | 4269 (92.9) | 723 (86.8) | 623 (89.4) | 0.003 |
| >8% (64 mmol/mol) | 5862 (53.3) | 5100 (52.6) | 1165 (58.3) | 971 (58.2) | 0.86 (0.23) | 0.93 (0.16) | 0.91 (0.19) | 0.93 (0.16) | 4171 (71.2) | 4438 (87.0) | 959 (82.3) | 834 (85.9) | ||
| Māori provider, n (%) | 866 (8.0) | 742 (7.8) | 235 (12.3) | 198 (12.5) | 0.85 (0.25) | 0.94 (0.14) | 0.93 (0.16) | 0.93 (0.16) | <0.001 | 589 (68.0) | 660 (88.9) | 191 (81.3) | 174 (87.9) | <0.001 |
| After‐hours clinic, n (%) | 4377 (40.4) | 3876 (40.5) | 705 (36.0) | 608 (37.3) | 0.87 (0.22) | 0.95 (0.13) | 0.91 (0.18) | 0.94 (0.14) | <0.001 | 3249 (74.2) | 3501 (90.3) | 594 (84.3) | 536 (88.2) | 0.027 |
| VLCA, n (%) | 5612 (50.8) | 4956 (50.8) | 942 (46.9) | 784 (46.8) | 0.87 (0.23) | 0.95 (0.14) | 0.91 (0.19) | 0.93 (0.16) | <0.001 | 4166 (74.2) | 4433 (89.4) | 785 (84.3) | 680 (86.7) | 0.002 |
| Dispensing of other glucose‐lowering therapies | ||||||||||||||
| Metformin dispensed, n (%) | 9917 (89.8) | N/A | 1718 (85.6) | N/A | 0.88 (0.22) | N/A | 0.92 (0.18) | N/A | <0.001 | 7580 (76.5) | N/A | 1445 (84.2) | N/A | <0.001 |
| Insulin dispensed, n (%) | 4417 (40.0) | 3694 (37.9) | 1157 (57.6) | 919 (54.8) | 0.89 (0.22) | 0.95 (0.14) | 0.92 (0.18) | 0.94 (0.15) | <0.001 | 3335 (75.5) | 3365 (91.1) | 961 (83.2) | 817 (89.0) | <0.001 |
| Other***, n (%) | 8312 (75.2) | 7496 (76.9) | 1432 (71.4) | 1236 (73.7) | 0.89 (0.21) | 0.95 (0.13) | 0.93 (0.17) | 0.95 (0.14) | <0.001 | 6331 (76.0) | 6834 (91.1) | 1228 (85.7) | 1113 (90.0) | <0.001 |
p value for mean MPR empagliflozin versus dulaglutide.
p value for MPR ≥ 0.8 empagliflozin versus dulaglutide.
Other medication = vildagliptin, sulphonylureas, pioglitazone, acarbose.
Percentages in the column on MPR ≥ 0.8 are calculated based on individuals with ≥2 dispensings.
TABLE 2.
Regression table of variables impacting the likelihood of an MPR ≥0.8 for empagliflozin and/or dulaglutide.
| Variables | Odds Ratio | 95% confidence interval | p value |
|---|---|---|---|
| Patient‐level variables | |||
| Age in years | |||
| 18–25 | REF | ||
| 26–34 | 2.42 | 1.84–3.19 | <0.001 |
| 35–44 | 3.48 | 2.81–4.30 | <0.001 |
| 45–59 | 4.74 | 3.94–5.70 | <0.001 |
| 60–75 | 5.39 | 4.52–6.43 | <0.001 |
| Ethnicity | |||
| European | REF | ||
| Māori | 0.67 | 0.59–0.76 | <0.001 |
| Pacific | 0.45 | 0.40–0.52 | <0.001 |
| Asian | 0.78 | 0.66–0.91 | 0.002 |
| MELAA | 0.57 | 0.38–0.87 | 0.009 |
| Other | 0.94 | 0.55–1.62 | 0.828 |
| Gender | |||
| Male | REF | ||
| Female | 0.98 | 0.90–1.07 | 0.667 |
| HbA1c | |||
| <8% (64 mmol/mol) | REF | ||
| >8% (64 mmol/mol) | 0.63 | 0.57–0.69 | < 0.001 |
| Practice‐level Variables | |||
| Rurality | |||
| Urban | REF | ||
| Rural | 1.83 | 1.58–2.13 | < 0.001 |
| Māori provider | |||
| No | REF | ||
| Yes | 0.67 | 0.57–0.79 | < 0.001 |
| After‐hours clinic | |||
| No | REF | ||
| Yes | 0.93 | 0.84–1.02 | 0.103 |
| VLCA | |||
| No | REF | ||
| Yes | 0.99 | 0.90–1.09 | 0.830 |
| Dispensing of other glucose‐lowering therapies | |||
| Metformin (n, %) | |||
| No | REF | ||
| Yes | 1.24 | 1.08–1.43 | 0.002 |
| Insulin | |||
| No | REF | ||
| Yes | 1.17 | 1.06–1.28 | 0.001 |
| Other a | |||
| No | REF | ||
| Yes | 1.25 | 1.13–1.39 | < 0.001 |
Other medication = vildagliptin, sulphonylureas, pioglitazone, acarbose.
The mean MPR was 0.87 ± 0.23 for empagliflozin and 0.92 ± 0.18 for dulaglutide, with mean metformin MPRs of 0.95 ± 0.14 and 0.94 ± 0.15, respectively (p < 0.001; Table 1). Logistic regression showed that the proportion of individuals with MPR above 0.8 increased with advancing age after adjusting for other variables (≥60 years vs. 16–25 years; OR = 5.39; 95% CI = 4.52–6.43; p < 0.001; Table 2).
In logistic regression, mean MPR was comparable for both males and females and for the proportion of patients with an MPR greater than 0.8 across different levels of socioeconomic deprivation (all p > 0.05; Tables 1 and 2).
However, the proportion of patients with an MPR ≥ 0.8 differed by ethnicity, with fewer Māori and Pacific patients meeting this target for ‘good adherence’ (Table 1). With logistic regression, Māori, MELAA and Pacific patients had a lower odds ratio of having MPR ≥ 0.8 compared to Europeans (Table 2).
Medication adherence (mean MPR and the proportion of patients with an MPR ≥ 0.8) was significantly higher in patients with a lower HbA1c (<8% [64 mmol/mol] vs. ≥8%; Table 1), in patients enrolled in a rural versus urban clinic (Table 2), and with dulaglutide versus empagliflozin use (Table 1). In contrast, patients enrolled with a Māori provider were significantly less likely to have a MPR ≥ 0.8 compared to those enrolled with a standard westernised healthcare provider (OR = 0.67; 95% CI = 0.58–0.79; p < 0.001; Table 2). Higher MPR for dulaglutide due to VLCA status and presence of after‐hours access (Table 1) were not sustained after adjustment for other variables (Table 2).
4. DISCUSSION
Whilst good adherence to empagliflozin and dulaglutide was observed overall, significant health inequity persists with the use of these medications for Māori and Pacific peoples with T2D, despite the use of funded availability through special authority criteria and prioritised access for these groups. 1 , 4 Reducing barriers to healthcare access and optimising SGLT2i/GLP1RA use for these communities should remain a priority, 9 particularly given the increasing body of evidence that these medications can significantly reduce the health equity gap. 10 In particular, targeted strategies may be required, including culturally tailored support for Māori Health providers and for clinicians engaging with younger patients and those with higher‐risk glycaemia, all of which are associated with lower levels of medication adherence. However, challenges with medication supply 5 must also be addressed if patients are to receive maximum pharmaceutical benefit, though this must also be balanced against patient preference for oral vs. injectable medication use and the individual cardiovascular and renal disease risk. We suggest that differences in medication adherence likely occur in other countries with ethnically diverse populations, and these should be reviewed to ensure health equity, particularly for minority groups.
AUTHOR CONTRIBUTIONS
Sara Mustafa contributed to writing—original draft, review and editing and formal analysis. Christopher Mayo contributed to methodology and formal analysis. Ryan Paul contributed to writing—review and editing, supervision, methodology and conceptualisation. Mark Rodrigues contributed to methodology and formal analysis. Rinki Murphy contributed to writing—review and editing, supervision and conceptualisation. Rawiri Keenan contributed to writing—review and editing, supervision and conceptualisation. Lynne Chepulis contributed to writing—review and editing, supervision, methodology, investigation, conceptualisation and project administration.
FUNDING INFORMATION
This work was supported by the New Zealand Health Research Council Health Delivery Research Project Grant (21/839). The funder played no role in the preparation of the data or manuscript or the decision to submit for publication.
CONFLICT OF INTEREST STATEMENT
The authors declare no conflicts of interest.
ACKNOWLEDGEMENTS
We thank the primary healthcare organisations across the Waikato and Auckland regions of NZ for extracting and providing the relevant datasets. Open access publishing facilitated by The University of Waikato, as part of the Wiley ‐ The University of Waikato agreement via the Council of Australian University Librarians.
Mustafa S, Mayo C, Paul R, et al. Inequity in adherence to empagliflozin and dulaglutide for type 2 diabetes in Aotearoa New Zealand. Diabetes Obes Metab. 2025;27(9):5356‐5361. doi: 10.1111/dom.16558
DATA AVAILABILITY STATEMENT
The data may be shared upon reasonable request to the corresponding author.
REFERENCES
- 1. Pharmac . Decision to fund two new medicines for type 2 diabetes. Accessed February 2021. https://www.pharmac.govt.nz/news‐and‐resources/consultations‐and‐decisions/decision‐to‐fund‐two‐new‐medicines‐for‐type‐2‐diabetes
- 2. Yu D, Cai Y, Osuagwu UL, et al. Ethnic differences in metabolic achievement between Māori, Pacific, and European New Zealanders with type 2 diabetes. Diabetes Res Clin Pract. 2022;189:109910. [DOI] [PubMed] [Google Scholar]
- 3. Atlantis E, Joshy G, Williams M, Simmons D. Diabetes among Māori and other ethnic groups in New Zealand. Diabetes Mellitus in Developing Countries and Underserved Communities. Springer International Publishing; 2017:165‐190. [Google Scholar]
- 4. Chepulis L, Rodrigues M, Gan H, et al. Real world initiation of newly funded empagliflozin and dulaglutide under special authority for patients with type 2 diabetes in New Zealand. BMC Health Serv Res. 2025;25(1):433. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. PHARMAC . Dulaglutide (Trulicity) and liraglutide (Victoza): supply issue. PHARMAC 2024. https://pharmac.govt.nz/medicine-funding-and-supply/medicine-notices/dulaglutide
- 6. McGovern A, Tippu Z, Hinton W, Munro N, Whyte M, de Lusignan S. Comparison of medication adherence and persistence in type 2 diabetes: a systematic review and meta‐analysis. Diabetes Obes Metab. 2018;20(4):1040‐1043. [DOI] [PubMed] [Google Scholar]
- 7. Karve S, Cleves MA, Helm M, Hudson TJ, West DS, Martin BC. Good and poor adherence: optimal cut‐point for adherence measures using administrative claims data. Curr Med Res Opin. 2009;25(9):2303‐2310. [DOI] [PubMed] [Google Scholar]
- 8. Chepulis L, Mayo C, Morison B, et al. Metformin adherence in patients with type 2 diabetes and its association with glycated haemoglobin levels. J Prim Health Care. 2020;12(4):318‐326. [DOI] [PubMed] [Google Scholar]
- 9. Graham R, Masters‐Awatere B. Experiences of Māori of Aotearoa New Zealand's public health system: a systematic review of two decades of published qualitative research. Aust N Z J Public Health. 2020;44(3):193‐200. [DOI] [PubMed] [Google Scholar]
- 10. Chepulis L, Keenan R, Rodrigues M, et al. SGLT2I/GLP1RA agents appear to be improving clinical outcomes in New Zealand patients with type 2 diabetes and cardiovascular/renal disease. N Z Med J. 2024;137(1597):100‐114. [Google Scholar]
Associated Data
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Data Availability Statement
The data may be shared upon reasonable request to the corresponding author.