| Literature DB >> 28498342 |
Akemi Nishide1, Misuzu Fujita2, Yasunori Sato3, Kengo Nagashima4, Sho Takahashi5, Akira Hata6.
Abstract
Background: This study aimed to evaluate whether income-related inequalities in access to dental care services exist in Japan.Entities:
Keywords: access to dental care services; inequality; socioeconomic status
Mesh:
Year: 2017 PMID: 28498342 PMCID: PMC5451975 DOI: 10.3390/ijerph14050524
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Subjects’ characteristics and description of access to dental care services from 1 April 2014 to 31 March 2015.
| Variables | Equivalent Income (Million Yen) 3 | |||||||
|---|---|---|---|---|---|---|---|---|
| All | 0.00 | 0.01–1.00 | 1.01–2.00 | 2.01–3.00 | ≥3.01 | |||
| Number of subjects | 216,211 | 37,918 | 70,575 | 63,303 | 23,162 | 21,253 | ||
| Men (%) 1 | 105,269 (48.7) | 16,674 (44.0) | 33,083 (46.9) | 32,292 (51.0) | 12,553 (54.2) | 10,667 (50.2) | <0.001 | <0.001 |
| Age 2 | 53.0 (19.8) | 51.4 (19.3) | 54.6 (20.0) | 54.1 (19.9) | 51.3 (19.6) | 49.6 (18.7) | <0.001 | <0.001 |
| 1 or 2 (%) | 154,222 (71.3) | 32,494 (85.7) | 49,698 (70.4) | 43,133 (68.1) | 152,04 (65.6) | 13,693 (64.4) | <0.001 | |
| 3 (%) | 35,299 (16.3) | 3260 (8.6) | 12,547 (17.8) | 11,120 (17.6) | 4472 (19.3) | 3900 (18.4) | ||
| 4 and more | 26,690 (12.3) | 2164 (5.7) | 8330 (11.8) | 9050 (14.3) | 3486 (15.1) | 3660 (17.2) | ||
| Chuo (%) | 43,349 (20.1) | 8691 (22.9) | 13,577 (19.2) | 11,883 (18.8) | 4702 (20.3) | 4496 (21.2) | <0.001 | |
| Hanamigawa (%) | 40,345 (18.7) | 6950 (18.3) | 13,449 (19.1) | 11,801 (18.6) | 4160 (18.0) | 3985 (18.8) | ||
| Inage (%) | 34,699 (16.1) | 5854 (15.4) | 11,087 (15.7) | 10,396 (16.4) | 3697 (16.0) | 3665 (17.2) | ||
| Wakaba (%) | 40,584 (18.8) | 7669 (20.2) | 13,026 (18.5) | 11,835 (18.7) | 4449 (19.2) | 3605 (17.0) | ||
| Midori (%) | 25,645 (11.9) | 3857 (10.2) | 8497 (12.0) | 7805 (12.3) | 2852 (12.3) | 2634 (12.4) | ||
| Mihama (%) | 31,589 (14.6) | 4897 (12.9) | 10,939 (15.5) | 9583 (15.1) | 3302.(14.3) | 2868 (13.5) | ||
| Users of dental care services 1 | 108,689 (50.3) | 16,471 (43.4) | 35,304 (50.0) | 33,418 (52.8) | 12,173 (52.6) | 11,323 (53.3) | <0.001 | <0.001 |
| The number of days for dental care services 2 | 7.7 (7.1) | 7.8 (7.2) | 7.8 (7.2) | 7.7 (7.0) | 7.5 (7.0) | 7.3 (6.8) | <0.001 | <0.001 |
1 Number of beneficiaries (percent). 2 Mean (standard deviation). 3 As of 29 November 2016, 1 US dollar was equivalent to 112.31 Japanese yen.
Figure 1(a) Probability of dental care service utilization and (b) mean number of days required for dental care services predicted using the generalized estimating equation based on equivalent income category from 1 April 2014 to 31 March 2015. The solid lines represent men and dotted lines represent women. Estimated probability and 95% confidence intervals are shown. The analysis of number of days required for dental care services included 108,689 beneficiaries who received dental care services from 1 April 2014 to 31 March 2015. Sex, equivalent income, age, residential area, number of family members, and the interaction between sex and equivalent income were included in the models. p-values for the linear trends for equivalent income categories for each sex were calculated. p-values for the test for homogeneity of slope, in which the null hypothesis was that there was no difference of linear trend coefficients for the equivalent income categories between men and women, were also calculated.
Figure 2Probability of all dental care utilization predicted using the generalized estimating equation for each age group based on equivalent income category from 1 April 2014 to 31 March 2015. (a) 0–8 years (n = 7320); (b) 9–16 years (n = 9075); (c) 17–29 years (n = 16,893); (d) 30–39 years (n = 18,907); (e) 40–49 years (n = 26,434); (f) 50–59 years (n = 21,285); (g) 60–69 years (n = 67,344); (h) 70–74 years (n = 48,953). Solid lines represent men and dotted lines represent women. Estimated probabilities and 95% confidence intervals are shown. Sex, equivalent income, residential area, number of family members, and the interaction between sex and equivalent income were included in the models. p-values for the linear trends for equivalent income categories for each sex were calculated. p-values for the test of the homogeneity of slope, in which null hypothesis was that there was no difference in the linear trend coefficients for the equivalent income categories between men and women, were also calculated.