In this study, the catastrophic pharmaceutical expenditures of diabetes medicines are being comprehensively investigated in different treatment schedules. The budget share and capacity to pay approaches were used to explore the catastrophic treatments and the incidence of catastrophic financial effects among rural and urban Iranian households. The new thresholds for the pharmaceutical sector were set considering the share of pharmaceutical expenditures (PE) to total health expenditures in Iran.
To the best of our knowledge, the present study can be mentioned as the first to assess medication therapy's catastrophic expenditures in different mono-and combination treatment schedules. In the previous studies, only a limited number of medicines were assessed [8, 13, 15, 17, 24, 25], while this study covers a range of treatment schedules.
The results showed that the OOP payment increased with increasing doses of medicines in initial treatment or when switched to second-line options. However, the treatment is still affordable. No one has encountered catastrophe expenditures with mono-and dual and sometimes triple oral therapies, even in rural areas. These findings align with Amiresmaili and Emrani's work which showed that only a tiny fraction, 0.007% of Iranian families, were required to pay over 40% of their income for Metformin . In addition, Zaheer et al. study revealed that generic essential diabetes medicines in 17 surveyed countries were affordable except in a few countries in the low-income group, including Tanzania .
Treatment schedules were catastrophic when Insulin was added to oral medication therapies. In line with the previous studies, Insulin is a significant contributor to catastrophic expenditures [27,28,29]. According to the Prospective Urban Rural Epidemiology (PURE) study at 604 communities in 17 low-, middle-and high-income countries around the world, Insulin was the least affordable medicine . This study used micro-level data. The consistency of our results with such studies encourages promoting a macro-level assessment. This would help to compare different time scales and assess different diseases.
The lowest-income households in rural areas are at most risk of being pushed toward a catastrophic border . This shows where to target and aim to improve access for more vulnerable households, mainly where budget impacts are low. It is also essential to consider other factors such as treatment pathways, consumption and volume of medicines, and potential budget impact.
Different studies confirmed that rural residences were significantly at risk of CHEs [30,31,32,33]. This may be due to their low income, low education level, or delay in disease diagnosis [34, 35]. According to the results of the latest population and housing census (2016), the rural population is less than the urban population in Iran. In better words, 74% of the country's population lives in urban areas and just 26% in rural areas . Meanwhile, a wide socio-economic gap caused by extreme urbanization has also been reported in urban areas of the country .
The results showed that more catastrophic treatments were observed in the budget share approach, and a higher proportion of households faced catastrophic expenditures. Cylus et al.  showed the difference between standard methods and emphasized the overestimation effects of the "budget share method." This is in line with the results presented in the current study.
Furthermore, Niëns et al.  showed that variations in the thresholds of catastrophic payments could lead to significant discrepancies in the results. If individuals were permitted to consider no higher than 1.0% of their daily income on glibenclamide, it would not be affordable to over 99% of the people; however, if the threshold is increased to 10%, glibenclamide would not be affordable for over17% of the people . There are concerns because deliberate changes in threshold levels would seriously influence estimations on affordability along with its impact on the policymakers . Defining adjusted thresholds for different parts of health expenditure may be the best option for developing policies to protect more individuals. Niëns et al. (Year) encouraged attempting to deal with an established mixture of methods and thresholds regarding affordability .
Mszar et al. revealed that although having diabetes increases the odds of financial hardship, individuals with concurrent atherosclerotic cardiovascular disease and diabetes had the highest relative odds of expressing an inability to pay at all when compared with those with neither of the condition (odds ratio, 2.69; 95% CI, 2.21–3.28) .
In using macro-data, the mean expenditure in each income decile was used while assuming the linearity of income. While the distribution of income in each income group could be skewed since most individuals in the group could be potentially in the lower income bracket than the average. The average income for each income may be overestimated, and thus, the catastrophic effects of the medicines may be underestimated in the analysis. In addition, although using macro-level data is simple and generalizable, there is no access to individual-level data, so it is not possible to provide further analysis based on the actual status of each household like population income status, household size etc.