Background
Governments around the world have been called on to move towards universal health coverage for their citizens [
1]. Such commitment requires that everyone receives needed health care services without experiencing financial difficulty [
1,
2]. Despite recent efforts to search for alternative health financing mechanisms [
3,
4], out-of-pocket payments are the primary mechanism to finance health services in low and middle income countries [
2,
5]. Large and unpredictable out-of-pocket expenses for health care services may push families to spend considerable proportions of their disposable income (also known as catastrophic health expenditure or CHE) and, at the most extreme, push households into poverty (also known as impoverishment) [
6‐
8].
There is evidence showing that certain countries and households are more likely to face financial hardship. Poorer and more unequal countries are more likely to have more households facing CHE [
9,
10]. In addition, households that are in rural areas, low income, have older adults, young children or disabled members, and lack health insurance are more likely to face CHE and impoverishment [
11‐
13]. The use of specific health services, such as inpatient care, prescription drugs and even visits to traditional healers, may also lead to CHE and impoverishment [
14‐
17].
Millions of people worldwide suffer from oral diseases [
18‐
20]. A total of US$298 billion are spent worldwide every year to cover the direct treatment costs associated with common oral conditions; a figure that represents 4.6% of health expenditure globally [
21]. Most dental services are provided by private dentists to patients and are financed and delivered largely separate from medical services [
22]. Out-of-pocket expenses make up a significant proportion of total dental expenditure, even in countries with high private dental insurance coverage like the Unites States [
23]. These features make dental care extremely costly and beyond most people’s means in developing countries. A recent multilevel study across 41 developing countries showed that up to 6.8% of households incurred dental care expenditure in the past four weeks that was equal or greater than 40% of their capacity to pay, the so-called catastrophic dental health expenditure [
24]. The problem with such an approach (i.e. including dental care rather than
any healthcare expenditure in the numerator for the calculation) is that it does not allow comparison of the relative contribution of different types of health care services to financial burden. For that, one needs to see whether households that paid for specific health services are more likely to face financial hardship defined using standard metrics such as CHE and impoverishment. Two early studies suggest dental care expenditure may be a key contributor to CHE. In South Korea, the proportion of CHE was higher in households that used dental services (24.6%) than in those that did not use them (7.8%), although other determinants of CHE were not accounted for during the analysis [
15]. In Iran, households that used dental services were, on average, four times more likely to incur CHE than those that did not use dental services [
16]. The impact of payments for dental care on impoverishment has not been formally assessed.
The primary aim of this study was to determine the impact of out-of-pocket payments for dental care on household finances in 40 low and middle income countries. A second aim was to compare the burden of payments for dental care with that for other health services.
Results
We analyzed data from 174,257 adults in 40 low and middle income countries with no missing values on variables of interest (62,961 in 17 LIC, 58,388 in 15 LMIC and 52,908 in 8 UMIC). The proportion of households with expenditure on dental care in the past four weeks was 7.0%, ranging from 1.5% in Myanmar and Laos to 23.7% in Russian Federation, without a clear pattern by national economic development. CHE and impoverishment were more common among poorer countries. The prevalence of CHE was 10.7%, ranging from 3.1% in Namibia to 29.8% in Bangladesh whereas the prevalence of impoverishment was 4.1%, varying from 0.5% in Czech Republic to 10.8% in Bangladesh (Table
1).
Table 1
Proportion of households facing catastrophic health expenditure (CHE), impoverishment and out-of-pocket payments for dental care in low, lower middle and upper middle income countries
Low | Bangladesh | 29.8 | (8.0–31.6) | 10.8 | (9.6–12.1) | 7.9 | (6.9–9.0) |
Income | Burkina Faso | 12.4 | (11.0–14.0) | 5.3 | (4.5–6.2) | 1.7 | (1.3–2.2) |
Countries | Chad | 6.6 | (5.1–8.3) | 3.1 | (2.2–4.2) | 3.3 | (2.4–4.4) |
| Comoros | 21.1 | (19.1–23.2) | 10.2 | (8.6–12.0) | 9.4 | (7.7–11.4) |
| Congo, Republic | 19.7 | (14.1–26.3) | 10.2 | (6.6–14.9) | 6.2 | (2.9–11.2) |
| Ivory Coast | 14.6 | (12.6–16.7) | 6.9 | (5.5–8.5) | 4.0 | (3.0–5.1) |
| Ethiopia | 7.1 | (5.7–8.8) | 3.0 | (2.3–3.9) | 1.8 | (1.2–2.7) |
| Ghana | 11.5 | (10.1–13.0) | 4.4 | (3.6–5.3) | 2.4 | (1.7–3.1) |
| India | 19.4 | (17.8–21.1) | 9.2 | (7.9–10.5) | 6.8 | (5.5–8.2) |
| Kenya | 6.9 | (5.8–8.2) | 3.1 | (2.4–3.9) | 4.5 | (3.5–5.8) |
| Lao PDR | 12.9 | (11.3–14.6) | 6.1 | (5.2–7.2) | 1.5 | (1.1–2.0) |
| Malawi | 4.3 | (3.5–5.2) | 2.0 | (1.5–2.5) | 1.7 | (1.3–2.3) |
| Mauritania | 4.8 | (3.5–6.5) | 2.2 | (1.5–3.0) | 7.5 | (5.8–9.6) |
| Myanmar | 11.5 | (10.0–13.1) | 3.9 | (3.3–4.6) | 1.5 | (1.1–2.0) |
| Pakistan | 23.4 | (20.5–26.5) | 9.6 | (8.1–11.2) | 10.0 | (7.3–13.2) |
| Senegal | 9.3 | (7.0–12.0) | 2.9 | (1.7–4.6) | 10.3 | (7.8–13.2) |
| Vietnam | 12.8 | (10.2–15.7) | 4.3 | (3.2–5.7) | 2.0 | (1.1–3.4) |
Lower | Bosnia & Herzegovina | 9.7 | (7.0–13.1) | 2.5 | (1.7–3.6) | 14.6 | (8.4–22.9) |
Middle | Brazil | 19.8 | (18.3–21.4) | 8.0 | (7.0–8.9) | 13.4 | (12.1–14.8) |
Income | China | 15.6 | (13.3–18.0) | 5.3 | (3.8–7.0) | 2.5 | (1.8–3.4) |
Countries | Dominican Republic | 8.8 | (7.1–10.7) | 4.4 | (3.5–5.3) | 5.5 | (4.4–6.7) |
| Georgia | 11.1 | (9.1–13.2) | 3.5 | (2.6–4.5) | 12.4 | (9.6–15.5) |
| Kazakhstan | 15.1 | (11.8–18.9) | 3.5 | (2.4–4.9) | 10.7 | (8.6–13.0) |
| Morocco | 20.3 | (18.5–22. 2) | 7.6 | (6.3–9.0) | 8.3 | (6.7–10.1) |
| Namibia | 3.1 | (2.4–3.8) | 1.2 | (0.8–1.7) | 2.3 | (1.6–3.1) |
| Paraguay | 14.4 | (13.2–15.7) | 5.3 | (4.6–6.0) | 12.3 | (11.1–13.7) |
| Philippines | 12 | (10.9–13.2) | 4.5 | (3.9–5.2) | 4.7 | (3.9–5.7) |
| Russian Federation | 8.4 | (6.2–11.0) | 3.3 | (2.0–5.1) | 23.7 | (19.8–27.9) |
| South Africa | 4.3 | (3.3–5.6) | 1.7 | (1.1–2.3) | 4.8 | (3.3–6.9) |
| Swaziland | 4.4 | (3.0–6.2) | 1.3 | (0.7–2.1) | 10.2 | (7.4–13.5) |
| Tunisia | 18.3 | (16.5–20.1) | 6.2 | (5.3–7.2) | 5.4 | (4.5–6.4) |
| Ukraine | 20.0 | (15.4–25.1) | 8 | (5.2–11.6) | 19.6 | (14.8–25.0) |
Upper | Croatia | 4.9 | (3.4–6.8) | 1.5 | (0.7–2.9) | 7.4 | (5.4–9.7) |
Middle | Czech Republic | 3.4 | (1.9–5.4) | 0.5 | (0.1–1.4) | 9.3 | (5.7–14.1) |
Income | Estonia | 11.0 | (9.0–13.2) | 2.8 | (2.0–3.8) | 16.5 | (14.0–19.3) |
Countries | Latvia | 11.1 | (8.5–14.0) | 3.7 | (2.1–5.8) | 11.9 | (9.2–14.9) |
| Malaysia | 4.1 | (3.4–4.9) | 1.6 | (1.2–2.0) | 6.1 | (5.4–7.0) |
| Mauritius | 11.6 | (10.0–13.3) | 1.9 | (1.4–2.5) | 5.5 | (4.5–6.6) |
| Mexico | 5.8 | (5.3–6.3) | 2.3 | (2.0–2.5) | 11.3 | (10.7–11.9) |
| Uruguay | 6.0 | (4.1–8.2) | 0.9 | (0.7–1.2) | 9.6 | (7.8–11.7) |
Households that paid for dental care had 1.88 (95% CI: 1.78–1.99) and 1.65 (95% CI: 1.52–1.80) greater odds of facing CHE and impoverishment, respectively, than those that did not pay for dental care, after controlling for all individual— and country-level covariates. An inverted V-shaped trend was noted in stratified analysis by World Bank’s income group. The odds of CHE were 1.52 (95% CI: 1.37–1.68), 2.34 (95% CI: 2.16–2.53) and 1.63 (95% CI: 1.45–1.83), and the odds of impoverishment were 1.38 (95% CI: 1.19–1.60), 1.90 (95% CI: 1.68–2.15) and 1.59 (95% CI: 1.31–1.92) in LIC, LMIC and UMIC, respectively. Older and less educated adults, poorer households, those in rural areas and having a child <5 years old, an adult >60 years old and no health insurance also have greater odds of facing CHE and impoverishment. At country level, higher out-of-pocket health expenditure was the only factor associated with greater odds of both CHE and impoverishment (Table
2).
Table 2
Odds ratios (95% confidence interval) of catastrophic health expenditure (CHE) and impoverishment by covariates in 40 low and middle income countries
Fixed effects: Individual Level |
Paid for dental care in last 4 weeks |
No | 1.00 | 1.00 | 1.00 | 1.00 |
Yes | 1.81 [1.72–1.91]*** | 1.88 [1.78–1.99]*** | 1.53 [1.41–1.65]*** | 1.65 [1.52–1.80]*** |
Insurance status |
None | 1.00 | 1.00 | 1.00 | 1.00 |
Some | 1.02 [0.96–1.07] | 0.99 [0.94–1.06] | 0.79 [0.73–0.87]*** | 0.87 [0.78–0.96]** |
All | 0.80 [0.76–0.85]*** | 0.80 [0.75–0.85]*** | 0.62 [0.56–0.70]*** | 0.71 [0.64–0.78]*** |
Sex |
Women | 1.00 | 1.00 | 1.00 | 1.00 |
Men | 0.96 [0.93–0.99]** | 0.97 [0.94–1.00] | 0.94 [0.89–0.98]* | 0.97 [0.92–1.02] |
Age |
18–29 years | 1.00 | 1.00 | 1.00 | 1.00 |
30–39 years | 0.97 [0.93–1.01] | 0.96 [0.91–1.00] | 0.96 [0.91–1.00] | 0.95 [0.89–1.02] |
40–49 years | 0.92 [0.87–0.96]* | 0.94 [0.89–0.99]* | 0.92 [0.86–0.99]* | 0.97 [0.89–1.05] |
50–59 years | 1.04 [0.99–1.09] | 1.06 [0.99–1.12] | 1.04 [0.99–1.14] | 1.08 [0.99–1.18] |
60–69 years | 1.26 [1.19–1.33] | 1.04 [0.96–1.12] | 1.25 [1.15–1.36]*** | 1.08 [0.96–1.21] |
70+ years | 1.18 [1.08–1.28]*** | 1.18 [1.08–1.28]*** | 1.35 [1.23–1.48]*** | 1.18 [1.04–1.33]** |
Marital Status |
Married | 1.00 | 1.00 | 1.00 | 1.00 |
Never married | 0.93 [0.88–0.98]** | 0.93 [0.88–0.98]** | 0.87 [0.81–0.92]*** | 0.98 [0.90–1.06] |
Previously married | 0.97 [0.93–1.02] | 0.97 [0.93–1.02] | 1.06 [0.99–1.13] | 0.99 [0.93–1.07] |
Education |
Primary school | 1.00 | 1.00 | 1.00 | 1.00 |
Secondary school | 0.93 [0.90–0.97] | 1.00 [0.96–1.04] | 0.72 [0.68–0.77]*** | 0.86 [0.80–0.92]*** |
College and above | 0.75 [0.71–0.80]*** | 0.79 [0.74–0.85]*** | 0.47 [0.43–0.54]*** | 0.62 [0.55–0.70]*** |
Household wealth |
First tertile (Poorest) | 1.00 | 1.00 | 1.00 | 1.00 |
Second tertile (Middle) | 1.11 [1.07–1.15]*** | 1.12 [1.08–1.17]*** | 0.98 [0.92–1.04] | 1.02 [0.96–1.08] |
Third tertile (Wealthiest) | 1.07 [1.02–1.10]*** | 1.08 [1.04–1.13]*** | 0.81 [0.76–0.86]*** | 0.89 [0.84–0.94]*** |
Household size |
1–2 members | 1.00 | 1.00 | 1.00 | 1.00 |
3–5 members | 0.95 [0.91–0.99]* | 0.93 [0.89–0.98]** | 1.01 [0.94–1.07] | 0.99 [0.92–1.08] |
> 5 members | 1.00 [0.96–1.06] | 0.89 [0.84–0.95]*** | 1.11 [1.03–1.20]** | 0.98 [0.90–1.08] |
Have child <5 years |
No | 1.00 | 1.00 | 1.00 | 1.00 |
Yes | 1.15 [1.11–1.19]*** | 1.25 [1.21–1.30]*** | 1.28 [1.22–1.37]*** | 1.34 [1.26–1.42]*** |
Have adult >60 years |
No | 1.00 | 1.00 | 1.00 | 1.00 |
Yes | 1.38 [1.33–1.42]*** | 1.34 [1.28–1.40]*** | 1.30 [1.24–1.40]*** | 1.26 [1.17–1.34]*** |
Urban/rural status |
Urban | 1.00 | 1.00 | 1.00 | 1.00 |
Rural | 1.06 [1.02–1.09]** | 1.02 [0.99–1.06] | 1.46 [1.39–1.54]*** | 1.31 [1.24–1.38]*** |
Fixed effects: Country Level |
GDP per capita (1000-increase) | 0.91 [0.84–0.99]* | 0.92 [0.86–1.00] | 0.85 [0.78–0.93]*** | 0.92 [0.85–0.99]* |
Gini index (1-percent increase) | 0.99 [0.98–1.01] | 1.00 [0.98–1.02] | 0.99 [0.98–1.01] | 1.00 [0.98–1.02] |
Out-of-pocket health expenditure | 1.02 [1.01–1.02]*** | 1.02 [1.01–1.03]*** | 1.02 [1.01–1.02]*** | 1.02 [1.01–1.03]*** |
Results remained unchanged after further adjustment for other types of health services used in the last 4 weeks (Table
3). Households paying for any type of health service had greater odds of facing CHE and impoverishment. However, services could be grouped depending on their impact on households. While health services in the first group (medications, hospitalization, medical tests and outpatient services) were associated with 2.57–4.13 greater odds of CHE and impoverishment, those in the second group (dental services, traditional medicine, health care products and other services) were associated with 1.53–1.92 greater odds only.
Table 3
Odds ratios (95% confidence interval) of catastrophic health expenditure (CHE) and impoverishment by type of health services in 40 low and middle income countries
Dental care | 7.0 | 1.88 [1.78-1.99]*** | 1.88 [1.78-1.99]*** |
Inpatient care | 4.2 | 3.93 [3.70-4.17]*** | 3.24 [2.99-3.53]*** |
Outpatient care | 14.1 | 3.11 [3.01-3.31]*** | 2.57 [2.47-2.73]*** |
Traditional medicine | 6.1 | 1.82 [1.72-1.92]*** | 1.81 [1.67-1.96]*** |
Medications or drugs | 42.7 | 4.13 [3.97-4.28]*** | 3.49 [3.29-3.70]*** |
Health care products | 3.5 | 1.88 [1.75-2.02]*** | 1.76 [1.56-1.95]*** |
Medical tests | 6.3 | 3.80 [3.62-3.99]*** | 2.88 [2.68-3.09]*** |
Other health services | 4.1 | 1.92 [1.80-2.05]*** | 1.53 [1.38-1.69]*** |
Discussion
This study shows that out-of-pocket payments for dental care can pose a considerable burden on households in low and middle income countries, to the extent of preventing expenditure on basic necessities and pushing families into poverty. Our findings also show that the impact of paying for dental care was similar to that of traditional medicine, health care products and other services but lower than that of medications, hospitalizations, medical tests and outpatient care.
Some study limitations need to be addressed. First, the WHS data are over a decade old. However, we know of no other internationally comparable data for low and middle income countries. Only 5 of the 40 countries evaluated (Croatia, Czech Republic, Estonia, Latvia and Uruguay) are now classified as high-income economies according to the latest World Bank’s ranking, supporting the relevance of our findings for most of the countries evaluated. In addition, the few countries with national data post-2010, like Brazil [
35], China [
12] and Ghana [
36], showed similar estimates for CHE and impoverishment to those reported in this analysis. Second, our analysis was based on cross-sectional data, and thus, unable to test for causal relationships. Although longitudinal panel data would be preferable to estimate the impact of spending on health care on living standards, often only cross-sectional data are available. Third, our expenditure estimates were derived from 14 items with a recall frame of 4 weeks. It has been previously shown that estimates of health expenditure are affected by the methodology used to collect data [
37‐
39]. However, the WHS expenditure data had good test-retest reliability [
30]. Fourth, spending on dental care was one of eight items used to gather information on households’ health expenditure. It is thus possible that some overlap between the 8 types of health services existed; for instance, those related to the use of drugs and/or traditional medicine for dental pain relief or children receiving dental treatment under general anesthesia in hospital settings. Therefore, our estimates may be somewhat conservative.
Our findings suggest that households were more likely to reduce spending on other goods and services, and be impoverished, disrupting their living standards, because a household member needed to use and pay for dental services. Although the impact of out-of-pocket expenses for dental care was noted across all World Bank’s income groups, an inverted V-shaped trend was identified by economic development. That is, a stronger impact of payments for dental care was found among LMIC than in LIC and UMIC. This trend may be explained by a combination of factors affecting countries as they move through the different stages of economic development. The impact of payments for dental care in LIC may be underestimated because people with treatment needs cannot afford the costs of dental services [
24] or the lack of dentists to provide appropriate treatment (dental services would then be rationed). The inverted V-shaped trend may thus represent those who can meet the costs to access needed dental care services. In LMIC, there will be more supply of private dental care providers and more perceived need for care which could increase the risk of households facing CHE and impoverishment. Households in UMIC may have expenditures than in other income groups but they are not catastrophic given greater economic resources in households, greater supply of dental providers and/or some level of public offer. Aside from economic development, we also found that countries with greater levels of out-of-pocket health expenditure also have more households facing CHE and impoverishment [
9]. Our findings also corroborate previous evidence characterizing households more likely to face the financial consequences of paying for health care [
11‐
17]. Poorer and rural households and those with young children, older adults and no health insurance were more likely to face CHE and impoverishment.
All types of health services had a financial impact on households. However, there was a clear separation between health services, which was not related to the typical split between inpatient vs. outpatient care. Indeed, buying medication over the counter had a similar effect as a hospital admission. Our findings also indicate that the impact of paying for dental care was lower than paying for medications, hospitalizations, diagnostics and outpatient care, but similar to that of traditional care, health care products (such as prescription glasses, hearing aids, prosthetic devices, etc.) and other health care services that were not included above. It is worth mentioning that the proportion of the population using dental services was smaller than that using other types of health services (especially medications and outpatient care), which highlights two interrelated possibilities; the lower availability of dental services, on one hand, and the fact that dental costs per session may be too high so as to cause financial shocks to families, on the other.
Looking forward, there are several policy options worth exploring to help reduce the economic burden caused by oral conditions. Oral and non-communicable diseases (NCDs) have shared determinants, and as such, can be addressed by common organized efforts. Regulating the tobacco and sugar industry can reduce the risks of several NCDs, including dental caries and periodontal disease. Beyond prevention, our results indicate that developing countries need to explore strategies to improve financial protection in the dental care sector. Alternative financing mechanisms for risk pooling and prepayments may be an sustainable option, although the status quo dental insurance model in developed countries still leads to affordability issues for consumers [
23]. The dental profession has the responsibility to advocate for the inclusion of dental care in ongoing debates on universal health coverage [
24]. Universal health coverage and insurance schemes should cover both prevention and control of oral diseases. In terms of research, it would be interesting to corroborate our findings with more recent data, even if that implies using a smaller sample of countries. Further studies could also expand on this area by looking into the mechanisms families use to cope with out-of-pocket expenditures for dental care. Given the dual nature of dental care, there is also a need for evaluating the impact of specific dental treatments, particularly those that are considered essential (disease treatment) and cosmetic/aesthetic.