Monday, September 25, 2023

Household catastrophic health expenditures for rheumatoid arthritis: a single centre study from South India – Scientific Reports

General characteristics of study participants

The majority of the study participants were females (88.1%) with mean age (SD) of 55.57 ± 12.29 years. Almost 93 per cent of participants were from urban areas, and 89.4 per cent were literate. The patient’s household size ranged from 1 to 12, with a median (IQR) of 4 (2), and nearly 77 per cent of the households had one to three earning members in their family. Less than 3 per cent of the participants have smoking and alcohol consumption habits. As per body mass index (BMI), 34.7 per cent were overweight, 28.1 per cent were normal, 27.2 per cent were obese, and the rest (3.4%) were underweight. The mean disease duration among the participants was 8.65 ± 7.47 years with a median (IQR) of 7 (33), and 85 per cent of the study participants had moderate to severe disease activity [disease activity score (DAS)28 > 3.2]. At the same time, nearly 33 per cent reported a severe functional disability [Health Assessment Questionnaire (HAQ) > 1.5]. Only 8.1 per cent of participants said having health insurance, and 51.4 per cent of patients were assessed to have CHE. Table 1 depicts the general characteristics of the 320 RA patients examined in this study.

Table 1 General characteristics of study participants and frequency of facing CHEs.

Income and health expenditure pattern among RA patients

The mean (95% CI) household annual income of the participants was ₹710,492 (540,155 to 880,828) with a median (IQR) of ₹360,000 (420,000) [$4369 ($5097)]. The mean (95% CI) annual health expenditure for treating RA was estimated at ₹44,700 (41,710 to 47,690) with a median (IQR) of ₹39,210 (25,500) [$476 ($310)]. The corresponding mean (95% CI) and median (IQR) OOPE among RA patients per household were ₹40,698 (38,249 to 43,148) [$494 ($464 to $524)] and ₹36,450 (23,070) [$442 ($280)] respectively (Supplementary Table 1).

Catastrophic health expenditure and its major determinants among RA patients

Households experiencing CHE owing to RA were 51.4% (n = 162). The burden was shown to be higher in some subpopulations, including urban persons (90.7%), females (89.5%), families with 1–3 earning members (84.0%), patients with lower education levels (84.0%), and elderly (> 50 years) (66.7%). Similarly, CHE is more prevalent among obese persons (34.5%), patients with more than five years of illness (64.3%), Rheumatoid factor (RF) positive (75.3%), anti-citrullinated protein antibody (anti-CCP) positive (58.6%), and people with severe RA (48.1%). The presence of CHE is more evident among patients in the first (69.7%) and second (17.3%) income quartiles and patients with mild functional disability (45.1%) (Table 1).

The violin plots (Fig. 1) show a significant difference in the distribution of annual household income, erythrocyte sedimentation rate (ESR), disease severity, functional status, disease duration, and BMI for CHE and no CHE categories. The median (IQR) of ESR is 40 (35), DAS28 is 5.04 (1.74), HAQ score is 1.25 (1), and BMI 27.47 (7.3) are high among people experiencing CHE. Similarly, a higher disease duration is found among patients who experience CHE with a median (IQR) of 7 (9). Similarly, the median (IQR) household annual income of those who experience CHE is ₹240,000 (120,000), much lower than that of non-CHE people [₹600,000 (600,000)].

Figure 1

Violin plots for catastrophic health expenditure.

The number of earning members and income quartiles were the primary predictors of CHE in RA patients; families with no earning member and one to three earning members had an odds ratio (OR) (95% CI) of 68 (6.29–735.3) and 5.79 (1.66–20.23), respectively (p < 0.001). Patients in the first income quadrant had a greater likelihood of suffering CHE with an OR (95% CI) of 174 (53.48, 570.18) (p < 0.001). Other major drivers were unemployment [OR 2.25 (1.28–3.95)], participants from urban area [OR 0.33 (0.12–0.93)], households with less than five members [OR 0.43 (0.26–0.71)], all with p < 0.001 (Table 2).

Table 2 Association between facing CHEs and household characteristics from logistic regression.

When the potential risk factors for CHE in RA patients were examined, significant differences were found in family size, education level, job status, number of earning members, household income quartiles, BMI, and disease activity (Table 1). We used multivariate logistic regression to determine the effects of the above said factors on the likelihood that participants will have CHE. The logistic regression model was statistically significant (p < 0.001), χ2 = 221.77, and explained 51% (Nagelkerke R2) of the variance in CHE. Sensitivity analyses found that 78.4% (n = 247) and 22.5% (n = 71) of the households faced CHE, using 5% and 20% of household annual income thresholds for calculating CHE.

Concentration index for income inequality

The concentration index for annual household income with a score of 0.56 (p < 0.001) indicates that income is concentrated among the upper quintile (4th and 5th) participants. The Lorenz curve (Fig. 2a) shows that participants in the 5th quintile contributed roughly 40% of total income. On the contrary, the concentration index and Lorenz curve for CHE with a score of − 0.41 (p < 0.05) show that CHE is concentrated among participants in the lower income groups (Fig. 2b). Almost 80% of the CHE is contributed by low-income and lower-middle-income patients.

Figure 2
figure 2

Lorenz curve for income inequality among the study participants.

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