Background
An integrated delivery system (IDS) is a collaborative network of organizations that provides or arranges to provide a coordinated continuum of services to a defined population and is willing to be held clinically and fiscally accountable for the outcomes and health status of the population served [
1]. In areas where physicians are hard to find, the introduction of IDS may be one of the best solutions to overcome the dilemma of specialist shortages and geographic barriers. Studies have shown that residents of remote areas had lower healthcare utilization compared to residents of urban areas and that this difference could probably be attributed to inequality of access [
2‐
4]. Access to healthcare is important and measurable in the performance of health systems around the world. Andersen’s behavior model provides measures of access to medical care [
5]. The framework divides access into two dimensions: potential and realized access [
6]. Potential access is defined as the system availability, community characteristics, individual predisposing characteristics (such as age, sex, race, education, occupation and health habits), individual enabling characteristics (such as income, insurance, and travel time), and individual need (such as perceived health, worry and symptoms) [
6,
7]. Realized access is the actual use of services and is measured by an objective indicator (utilization) and a subjective indicator (consumer satisfaction) [
7]. Although the objective of IDS in healthcare services is explicit, the outcomes of accessibility after its implementation in medically underserved areas such as an offshore island have not yet been well established through empirical research.
The National Health Insurance (NHI) program in Taiwan (instituted in 1995) is a single-payer system that covers 99 % of the population with an average of 80 % satisfaction [
8‐
10]. Coverage has reached 100 % since 1999 for the aborigines and residents of offshore islands after the government subsidized their health insurance premium [
11]. The residents living in rural districts are also exempted from copayment when they seek healthcare at their local facilities [
11]. This NHI program has attracted worldwide attention due to its success in both stabilizing healthcare expenses and reducing health disparity across various socioeconomic gradients [
12‐
15]. However, the distribution of physicians and of medical equipments tends to be centralized. Taiwan consists of a number of sparsely populated mountainous areas and islands where natural factors limit the willingness of healthcare providers to work there and therefore the residents of such regions suffer from interrupted healthcare services. The accessibility of medical facility is thus a main concern of people in rural areas.
To overcome the geographic barrier and offer easy access to medical services, the Bureau of NHI initiated an IDS program in November 1999 that currently covers all mountainous and outlying islands in the country to provide a continuum of healthcare services [
16]. Matsu Archipelago, a former military stronghold and historic area of Taiwan, lies almost 200 km from Taiwan proper across the Taiwan Strait. The transportation of residents and travelers depends solely on planes or ferries, and unfortunately, it is often hampered by foggy or bad weather. Therefore, general practitioners in Matsu are relatively scarce, let alone specialists such as ophthalmologists. To improve accessibility, Taipei City Hospital contracted the IDS program and began rotating its ophthalmologists to Matsu in 2000 to provide ophthalmic services (6 days per fortnight), excluding intraocular and laser surgery [
8]. During the week without an ophthalmologist, eye services were delivered by local general practitioners. In addition, the Health Promotion Administration has launched a community-based integrated screening project that has included annual eye screening for cataracts and glaucoma in Matsu since 2002. Nevertheless, residents’ vision-related quality of life (VRQoL) and ophthalmic accessibility after IDS implementation in Matsu have never been investigated.
This study aimed to assess the ophthalmic accessibility of residents in an outlying island under the provision of IDS. Utilization and satisfaction measures were used as indicators of actual, or realized, access [
7]. We also investigated VRQoL via the 25-item National Eye Institute Visual Function Questionnaire (NEI-VFQ-25) and explored the associations between frequently seen eye diseases and VRQoL on a community basis.
Methods
Residents of Nangan (major island of Matsu) who were 50 years of age or older were identified as eligible to participate this study, which was conducted from May to June 2014. They accounted for more than 60 % of the population of Matsu, according to the national census [
17]. The age selection criterion was based on evidence that two-thirds of the visual impairment (including blindness) worldwide occurs in this age group [
18]. The participants were required to have sufficient cognitive ability to understand and complete the face-to-face survey. Experienced interviewers were selected from local residents and attended seminars hosted by one of the authors beforehand to facilitate the survey. The questionnaire consisted of two parts: the first part was NEI-VFQ-25, and the second was a constructed questionnaire about socioeconomic status, clinical information, the utilization of and satisfaction with ophthalmic healthcare. All participants completed these questionnaires anonymously. The institutional review board of Taipei City Hospital approved this survey and waived the signed consent sheet (TCHIRB-1020122-E). The study was conducted in accordance with the tenets of the Declaration of Helsinki.
The NEI-VFQ-25 is the most commonly used patient-reported outcome measure to assess vision-targeted functioning and well-being based on factors identified as important by persons with various chronic eye diseases [
19‐
21]. It consists of 25 core items to measure 12 domains of visual function. The NEI-VFQ-25 Taiwan Chinese version has been formatted according to standard procedures (including forward translation, backward translation, examination of the translation quality by bilingual speakers, and a pilot test) [
22]. The NEI-VFQ-25 scores were analyzed and converted to a 100-point score in which 100 represented the best possible and 0 represented the worst. Twelve subscale scores and a single composite score were calculated according to the standard algorithm for scoring [
21]. The composite score was derived from the average of subscale scores excluding “general health” [
23,
24] and “driving” [
19,
22] because more than 40 % of participants did not drive. Likewise, the composite score ranged from 0 to 100, with higher scores indicating better quality of life. The other part of the questionnaire originated from the National Health Interview Survey provided by the National Health Research Institutes [
25]. Information regarding socio-demographic data (age, gender, residential village, religion, education level, occupation, marital status, annual household income), unmet needs to seek ophthalmic care and the utilization of and satisfaction with ophthalmic care were also included. The questionnaires were scrutinized by 5 experts for content validity.
Dependent variables included the utilization of ophthalmic care, satisfaction with ophthalmic care and VRQoL (composite score of NEI-VFQ-25). An unmet ophthalmic need was defined as residents not consulting eye doctors despite eye discomfort (such as blurred vision, aching, itching or burning sensation) within the past half year. An ophthalmic referral was defined as a referral (to Taiwan proper) made by ophthalmologists or physicians for participants due to ophthalmic problems. Predisposing (age, gender, religion, education, marital status, occupation, duration of residence, health habits) and enabling factors (residential village, annual household income, commercial insurance) were considered as predictors. Continuous variables were compared using Student’s t test. Categorical variables were analyzed using the X2 test. The logistic regression method was used when the dependent variable was dichotomous. Linear regression was used when the dependent variable was continuous. A P value below 0.05 (two-tailed) was considered statistically significant. The reliability of the questionnaires was assessed using Cronbach’s α test.
Results
Nine hundred questionnaires were administered during the study period and a total of 851 questionnaires were returned. Ten questionnaires did not contain enough information for this study and were subsequently excluded. In the end, 841 questionnaires were considered valid and eligible for this study (response rate 93.4 %). These participants accounted for 63 % of the entire eligible population. The socio-demographic characteristics of these participants are summarized in Table
1. The participant age ranged from 50 to 101 years with a mean age of 63.7 (±10.7) years. Females comprised 51.5 % of the participants and predominated in each age group. Most (84.3 %) participants had lived on Matsu Island for more than 20 years, and 49.4 % of the participants lived in the neighborhood of the healthcare facility. The education level of 32.7 % was at least senior high school, while 23.3 % of the participants were illiterate. A total of 45.1 % of participants had private medical insurance. The annual household income was lower than 500,000 New Taiwan dollars for more than half of participants.
Table 1
Socio-demographic characteristics, health habits, and illness characteristics of study participants (N = 841)
Sex |
Male | 408 | 48.5 |
Female | 433 | 51.5 |
Age (years) |
63.7 (50–101) | ±10.7 | – |
Residential village |
Neighborhood of healthcare facility | 415 | 49.4 |
Other area | 426 | 50.6 |
Years of residence in Matsu |
< 20 years | 132 | 15.7 |
20–40 years | 71 | 8.4 |
> 40 years | 634 | 75.4 |
Unspecified | 4 | 0.5 |
Religion |
No | 55 | 6.5 |
Traditional folk belief | 621 | 73.8 |
Buddism/Taoism | 138 | 16.4 |
Christianity | 18 | 2.1 |
Others | 9 | 1.1 |
Education |
Primary school completed or less | 459 | 54.6 |
Junior high school | 105 | 12.5 |
Senior high school | 215 | 25.6 |
College or higher | 60 | 7.1 |
Unspecified | 2 | 0.2 |
Marital status |
Never married | 15 | 1.8 |
Married or cohabiting | 663 | 78.8 |
Divorced or separated | 26 | 3.1 |
Widowed | 113 | 13.4 |
Unspecified | 24 | 2.9 |
Main occupation |
Housekeeper | 146 | 17.3 |
Public servant | 126 | 15.0 |
Teacher | 8 | 1.0 |
Worker, farmer or fisher | 185 | 22.0 |
Businessman | 76 | 9.0 |
Other | 77 | 9.2 |
No/unemployment/retired | 218 | 25.9 |
Unspecified | 5 | 0.6 |
Commercial insurance |
Yes | 379 | 45.1 |
No | 462 | 54.9 |
Annual household income |
≤ NTD 500,000 | 434 | 51.6 |
> NTD 500,000, ≤ 800,000 | 165 | 19.6 |
> NTD 800,000, ≤ 1,000,000 | 118 | 14.0 |
> NTD 1,000,000, ≤ 1,500,000 | 85 | 10.1 |
> NTD 1,500,000 | 33 | 3.9 |
Unspecified | 6 | 0.7 |
Alcohol consumption |
No | 478 | 56.8 |
Rare (<1 time/month) | 97 | 11.5 |
Yes | 266 | 31.6 |
Tobacco use |
Never | 696 | 82.8 |
Quit | 41 | 4.9 |
Current | 104 | 12.4 |
Daily sun exposure time (hours) |
< 3 | 624 | 75.1 |
3 ~ 5 | 109 | 13.1 |
> 5 | 98 | 11.8 |
Comorbid condition (multiple)a |
None | 304 | 36.1 |
Hypertension | 439 | 52.2 |
Rheumatoid arthritis | 163 | 19.4 |
Diabetes | 99 | 11.8 |
Heart disease | 72 | 8.6 |
Asthma or chronic lung disease | 25 | 3.0 |
Others | 50 | 5.9 |
Eye diseases diagnosed by ophthalmologist (multiple)a |
None | 311 | 37.0 |
Cataract | 376 | 44.7 |
Cataract (mild) | 259 | 30.8 |
Cataract (moderate or severe) | 117 | 13.9 |
Dry eye | 130 | 15.5 |
Glaucoma | 73 | 8.7 |
Retinal disease | 41 | 4.9 |
High myopia (≤ − 6 Diopters) | 34 | 4.0 |
Others | 58 | 6.9 |
Total | 841 | 100 |
Common comorbid conditions included hypertension (52.2 %), arthritis (19.4 %) and diabetes mellitus (11.8 %). Common eye diseases included cataract (44.7 %), dry eye (15.5 %) and glaucoma (8.7 %). Sixty-one percent of participants had utilized the IDS in the past year (Table
2). Only 14 % of participants had a history of being referred to Taiwan, traveling by planes or ferries, for further eye care, and 18 % of participants had unmet ophthalmic care needs during the past 6 months. Most participants (94 %) considered eye healthcare in Matsu to be accessible and convenient, as 87 % of participants spent twenty minutes or less to reach eye care. Overall, 88 % of the participants were satisfied with the eye care provided by the IDS.
Table 2
Utilization and satisfaction with ophthalmic care of study participants (N =841)
Ophthalmic utilization |
Visit IDS ophthalmic clinic in the past year |
Yes No | 513 328 | 61.0 39.0 |
History of ophthalmic referral |
Yes No | 115 726 | 13.7 86.3 |
Unmet ophthalmic need within the past six monthsb |
Yes No | 148 693 | 17.6 82.4 |
Ophthalmic satisfaction |
Satisfactiona |
Satisfied Dissatisfied | 741 100 | 88.1 11.9 |
Total | 841 | 100 |
Predisposing factors (age, duration of residence, occupation) and comorbid conditions were associated with ophthalmic referrals. Older age, longer years of residence, the non-working group, and more (≥ 2) comorbid conditions were associated with more ophthalmic referrals compared to their counterparts (odds ratio (OR) 3.23, 95 % confidence interval (CI) 2.04–5.00,
P < 0.001; OR 2.40, 95 % CI 1.36–4.23,
P < 0.001; OR 2.38, 95 % CI 1.59–3.57,
P < 0.001; OR 2.82, 95 % CI 1.88–4.22,
P < 0.001, respectively; see Table
3, Model A). Predisposing (age, duration of residence, marital status, religion) and enabling (residential village) factors were associated with the utilization of the IDS ophthalmic clinic in the past year. Older age, living in the neighborhood of the healthcare facility, longer years of residence, being married or cohabiting, and being Buddhist/Taoist were associated with more utilization of ophthalmic visits than their counterparts (OR 1.39, 95 % CI 1.05–1.82,
P = 0.020; OR 2.13, 95 % CI 1.64–2.86,
P < 0.001; OR 1.79, 95 % CI 1.30–2.45,
P < 0.001; OR 1.56, 95 % CI 1.14–2.17,
P = 0.008; and OR 1.72, 95 % CI 1.03–2.78,
P = 0.019, respectively; see Table
3, Model B). Predisposing factors (age, occupation), comorbid conditions, and enabling factor (commercial insurance status) were associated with unmet ophthalmic needs. Older age, the non-working group, no commercial insurance and more (≥2) comorbid conditions were associated with more unmet ophthalmic needs compared to their counterparts (OR 1.45, 95 % CI 1.01–2.08,
P = 0.04; OR 1.49, 95 % CI 1.04–2.13,
P = 0.027; OR 1.79, 95 % CI 1.22–2.56,
P = 0.002; OR 1.61, 95 % CI 1.10–2.33,
P = 0.014, respectively; see Table
3, Model C).
Table 3
Multiple logistic regression of association between predisposing and enabling factors and utilization (model A: referral; model B: seek eye care within the past year; model C: unmet ophthalmic need)
Sex (male) | 1.03 | (0.70–1.54) | 0.867 | 0.93 | (0.49–1.11) | 0.599 | 1.02 | (0.71–1.45) | 0.915 |
Age (50–60 yrs) | 3.23 | (2.04–5.00) | < 0.001 | 1.39 | (1.05–1.82) | 0.020 | 1.45 | (1.01–2.08) | 0.040 |
Village (not neighborhood of healthcare facility) | 0.97 | (0.65–1.45) | 0.871 | 2.13 | ( 1.64–2.86) | < 0.001 | 1.10 | (0.77–1.56) | 0.611 |
Years of residence (< 40) | 2.40 | (1.36–4.23) | < 0.001 | 1.79 | ( 1.30–2.45) | < 0.001 | 1.49 | (0.96–2.33) | 0.082 |
Education (≤ junior high school) | 0.88 | (0.58–1.35) | 0.514 | 0.76 | ( 0.57–1.02) | 0.066 | 0.79 | (0.53–1.15) | 0.182 |
Marital status (not married/cohabiting) | 0.90 | (0.56–1.45) | 0.677 | 1.56 | ( 1.14–2.17) | 0.008 | 0.97 | (0.63–1.49) | 0.898 |
Occupation (working group) | 2.38 | (1.59–3.57) | < 0.001 | 1.16 | ( 0.88–1.54) | 0.277 | 1.49 | (1.04–2.13) | 0.027 |
Religion (non-Buddist or Taoist) | 0.74 | (0.40–1.35) | 0.320 | 1.72 | ( 1.03–2.78) | 0.019 | 1.25 | (0.66–2.38) | 0.489 |
Annual household income (≤ NTD 500,000) | 1.28 | (0.86–1.89) | 0.215 | 0.97 | ( 0.74–1.28) | 0.792 | 0.77 | (0.58–1.19) | 0.313 |
Commercial insurance (yes) | 1.41 | (0.94–2.13) | 0.094 | 0.83 | ( 0.63–1.09) | 0.179 | 1.79 | (1.22–2.56) | 0.002 |
Daily sun exposure time (< 3 hours) | 1.08 | (0.68–1.69) | 0.747 | 1.15 | ( 0.84–1.59) | 0.371 | 1.05 | (0.70–1.59) | 0.805 |
Comorbid condition (< 2 diseases) | 2.82 | (1.88–4.22) | < 0.001 | 1.20 | ( 0.88–1.64) | 0.247 | 1.61 | (1.10–2.33) | 0.014 |
Alcohol (no) | 0.72 | (0.48–1.09) | 0.122 | 0.97 | ( 0.74–1.28) | 0.861 | 1.22 | (0.85–1.75) | 0.263 |
Tobacco (no) | 0.76 | (0.49–1.33) | 0.342 | 0.61 | ( 0.42–0.87) | 0.007 | 1.05 | (0.66–1.67) | 0.841 |
Table
4 summarizes the results of the univariate and multivariate logistic regressions on dissatisfaction. The significant predictors of dissatisfaction were the neighborhood of the healthcare facility and the composite NEI-VFQ-25 score. Participants who did not live in the neighborhood of the facility were more dissatisfied than participants who lived in the neighborhood (OR 3.88, 95 % CI 2.85–5.28,
P < 0.001). Participants with a higher composite NEI-VFQ-25 score (> 85) were less dissatisfied than participants with a lower composite score (OR 0.58, 95 % CI 0.42–0.81,
P = 0.001).
Table 4
Univariate and multivariate logistic regression show factors that predict dissatisfaction of eye care
Sex (male) | 1.14 | (0.86–1.50) | 0.353 | – | – | – |
Age (50–60 yrs) | 0.78 | (0.59–1.03) | 0.075 | 0.75 | (0.54–1.06) | 0.107 |
Village (neighborhood of healthcare facility) | 4.00 | (2.97–5.38) | < 0.001 | 3.88 | (2.85–5.28) | < 0.001 |
Years of residence (< 40) | 0.74 | (0.54–1.01) | 0.059 | 0.77 | (0.53–1.11) | 0.163 |
Education (≤ junior high school) | 1.11 | (0.81–1.47) | 0.473 | – | – | – |
Marital status (married/cohabiting) | 0.86 | (0.61–1.21) | 0.382 | – | – | – |
Occupation (working group) | 1.20 | (0.91–1.59) | 0.192 | – | – | – |
Religion (non-Buddist or Taoist) | 0.64 | (0.40–1.01) | 0.054 | 0.70 | (0.42–1.17) | 0.174 |
Annual household income (≤ NTD 500,000) | 1.30 | (0.99–1.72) | 0.063 | 1.27 | (0.93–1.74) | 0.131 |
Commercial insurance (yes) | 0.92 | (0.69–1.21) | 0.542 | – | – | – |
Comorbid condition (no) | – | – | 0.674 | – | – | – |
1 disease | 1.03 | (0.74–1.42) | 0.870 | – | – | – |
2 diseases | 1.01 | (0.67–1.51) | 0.980 | – | – | – |
at least 3 diseases | 0.74 | (0.44–1.26) | 0.268 | – | – | – |
Alcohol (no) | 1.09 | (0.82–1.44) | 0.556 | – | – | – |
Tobacco (no) | 1.26 | (0.88–1.82) | 0.207 | – | – | – |
Daily sun exposure time (< 3 hours) | 0.66 | (0.48–0.92) | 0.015 | 0.81 | (0.56–1.15) | 0.235 |
Composite score of NEI-VFQ-25 (≤ 85) | 0.60 | (0.45–0.80) | 0.001 | 0.58 | (0.42–0.81) | 0.001 |
The reliability for NEI-VFQ-25 was 0.94 (Cronbach’s α value). The relationships between common eye diseases and the composite and subscale scores of NEI-VFQ-25 are summarized in Table
5. The higher the VRQoL, the less inconvenience and fewer difficulties were reported by the participants in the questionnaire. As shown in Table
5, for all participants, the most inconvenience experienced was “general health” (42.8 ± 25.6), followed by “general vision” (62.7 ± 16.7), “vision specific role difficulties” (74.1 ± 23.6) and “ocular pain” (80.1 ± 17.8). The least inconvenience experienced was found for “color vision” (95.3 ± 14.1), followed by “driving” (95.0 ± 10.2), “vision specific social functioning” (93.8 ± 9.1) and “peripheral vision” (89.8 ± 14.2). For patients with cataracts, the composite score and all subscale scores were significantly lower than for patients without cataracts (
P < 0.05). For patients with glaucoma, the composite and all subscale scores were significantly lower (
P < 0.05) than for patients without glaucoma, except for the subscales of “general health” (
P = 0.083), “near activities” (
P = 0.124), “social functioning” (
P = 0.185) and “color vision” (
P = 0.346). For patients with dry eyes, the composite and all subscale scores were not significantly lower (
P > 0.05) than for patients without dry eyes except for the subscale score of “ocular pain” (
P < 0.001). Furthermore, we conducted multivariate linear regression on the composite score of NEI-VFQ-25 regarding predisposing and enabling factors and other predictors (Table
6). Predisposing factors (age, marital status, occupation), comorbid condition, enabling factors (residential village, commercial insurance, annual household income), cataracts and glaucoma were significantly associated with the composite NEI-VFQ-25 score. Older age (
P = 0.021), not living in the neighborhood of the healthcare facility (
P = 0.002), not being married or cohabiting (
P = 0.035), being in the non-working group (
P < 0.001), no commercial insurance (
P = 0.009), higher annual household income (
P = 0.012), more comorbid conditions (
P < 0.001), cataracts (
P < 0.001) and glaucoma (
P = 0.046) were associated with lower composite NEI-VFQ-25 scores compared to their counterparts.
Table 5
Change of subscale and composite scores of NEI-VFQ-25 regarding various eye diseases
General health | 42.8 ± 25.6 | 35.4 | 48.7 | < 0.001 | 37.7 | 43.3 | 0.083 | 39.9 | 43.3 | 0.181 |
General vision | 62.7 ± 16.7 | 57.0 | 67.1 | < 0.001 | 57.5 | 63.1 | 0.010 | 61.1 | 62.9 | 0.283 |
Ocular pain | 80.1 ± 17.8 | 74.3 | 84.7 | < 0.001 | 69.2 | 81.1 | < 0.001 | 73.4 | 81.2 | < 0.001 |
Near activities | 84.3 ± 15.4 | 78.7 | 88.8 | < 0.001 | 80.9 | 84.7 | 0.124 | 83.2 | 84.5 | 0.472 |
Distance activities | 87.7 ± 12.2 | 81.2 | 92.9 | < 0.001 | 80.6 | 88.4 | 0.001 | 86.9 | 87.9 | 0.574 |
Vision specific | | | | | | | | | | |
Social functioning | 93.8 ± 9.1 | 90.3 | 96.6 | < 0.001 | 91.6 | 94.0 | 0.185 | 94.5 | 93.7 | 0.534 |
Mental health | 81.7 ± 14.6 | 76.6 | 85.8 | < 0.001 | 75.9 | 82.3 | 0.006 | 80.9 | 81.9 | 0.569 |
Role difficulties | 74.1 ± 23.6 | 66.4 | 80.2 | < 0.001 | 61.6 | 75.3 | < 0.001 | 70.2 | 74.8 | 0.088 |
Dependency | 87.6 ± 14.8 | 81.4 | 92.6 | < 0.001 | 81.9 | 88.2 | 0.026 | 86.6 | 87.8 | 0.573 |
Driving | 95.0 ± 10.2 | 91.8 | 96.4 | < 0.001 | 90.9 | 95.4 | 0.013 | 93.1 | 95.3 | 0.100 |
Color vision | 95.3 ± 14.1 | 92.3 | 97.8 | < 0.001 | 93.8 | 95.5 | 0.346 | 96.5 | 95.1 | 0.309 |
Peripheral vision | 89.8 ± 14.2 | 84.4 | 94.1 | < 0.001 | 85.3 | 90.2 | 0.031 | 89.1 | 89.9 | 0.632 |
Composite score of NEI-VFQ-25 | 84.0 ± 15.2 | 78.8 | 88.2 | < 0.001 | 77.8 | 84.6 | 0.036 | 82.3 | 84.4 | 0.863 |
Table 6
Multivariate linear regression models of the relationship between vision-related quality of life (composite score of NEI-VFQ-25) and predictors
Intercept | 112.38 | 98.51 ~ 126.25 | < 0.001 | 120.77 | 113.97 ~ 127.56 | < 0.001 |
Sex (male) | −0.68 | −2.95 ~ 1.60 | 0.560 | – | – | – |
Age (50–60 yrs) | −3.01 | −5.59 ~ −0.42 | 0.023 | −2.81 | −5.19 ~ −0.43 | 0.021 |
Village (neighborhood of healthcare facility) | −3.17 | −5.05 ~ −1.29 | 0.001 | −2.99 | −4.85 ~ −1.13 | 0.002 |
Years of residence (< 40) | 1.22 | −1.09 ~ 3.53 | 0.300 | – | – | – |
Education (≤ junior high school) | 0.42 | −2.15 ~ 2.98 | 0.748 | – | – | – |
Religion (non-Buddist or Taoist) | 2.83 | −0.42 ~ 6.07 | 0.088 | – | – | – |
Marital status (married or cohabiting) | −2.45 | −4.88 ~ −0.02 | 0.048 | −2.56 | −4.94 ~ −0.18 | 0.035 |
Occupation (working group) | −5.24 | −7.57 ~ −2.90 | < 0.001 | −5.81 | −8.02 ~ −3.59 | < 0.001 |
Annual household income (≤ NTD 500,000) | −2.46 | −4.50 ~ −0.43 | 0.017 | −2.50 | −4.44 ~ −0.56 | 0.012 |
Commercial insurance (yes) | −2.84 | −5.03 ~ −0.65 | 0.011 | −2.82 | −4.94 ~ −0.70 | 0.009 |
Comorbid condition (< 2 diseases) | −4.66 | −6.96 ~ −2.35 | < 0.001 | −4.78 | −7.04 ~ −2.51 | < 0.001 |
Alcohol (no) | 0.51 | −1.60 ~ 2.62 | 0.634 | – | – | – |
Tobacco (no) | –1.36 | −4.16 ~ 1.45 | 0.343 | – | – | – |
Daily sun exposure time (< 3 hours) | 1.67 | –0.58 ~ 3.92 | 0.146 | – | – | – |
Cataract (no) | −4.90 | −6.97 ~ −2.82 | < 0.001 | −5.04 | −7.08 ~ −3.01 | < 0.001 |
Glaucoma (no) | −3.24 | −6.52 ~ 0.03 | 0.052 | −3.32 | −6.58 ~ −0.07 | 0.046 |
Acknowledgements
We thank the National Eye Institute as well as Dr. Jen-Chieh Lin for the provision of the Taiwan Chinese version of NEI-VFQ-25 for this study. We would also like to thank all ophthalmologists of Taipei City Hospital for working strenuously and devotedly to implement eye care services under IDS of Matsu for the past 15 years.