Open Access

Rural–urban difference in the use of annual physical examination among seniors in Shandong, China: a cross-sectional study

  • Dandan Ge1,
  • Jie Chu2,
  • Chengchao Zhou1, 3Email author,
  • Yangyang Qian1,
  • Li Zhang1 and
  • Long Sun1
International Journal for Equity in Health201716:86

https://doi.org/10.1186/s12939-017-0585-z

Received: 2 February 2017

Accepted: 17 May 2017

Published: 23 May 2017

Abstract

Background

Regular physical examination contributes to early detection and timely treatment, which is helpful in promoting healthy behaviors and preventing diseases. The objective of this study is to compare the annual physical examination (APE) use between rural and urban elderly in China.

Methods

A total of 3,922 participants (60+) were randomly selected from three urban districts and three rural counties in Shandong Province, China, and were interviewed using a standardized questionnaire. We performed unadjusted and adjusted logistic regression models to examine the difference in the utilization of APE between rural and urban elderly. Two adjusted logistic regression models were employed to identify the factors associated with APE use in rural and urban seniors respectively.

Results

The utilization rates of APE in rural and urban elderly are 37.4% and 76.2% respectively. Factors including education level, exercise, watching TV, and number of non-communicable chronic conditions, are associated with APE use both in rural and urban elderly. Hospitalization, self-reported economic status, and health insurance are found to be significant (p < 0.05) predictors for APE use in rural elderly. Elderly covered by Urban Resident Basic Medical Insurance (URBMI) (p < 0.05, OR = 1.874) are more likely to use APE in urban areas.

Conclusions

There is a big difference in APE utilization between rural and urban elderly. Interventions targeting identified at-risk subgroups, especially for those rural elderly, are essential to reduce such a gap. To improve health literacy might be helpful to increase the utilization rate of APE among the elderly.

Keywords

Elderly Annual physical examination Health service use Rural–urban difference China

Background

Population aging has become a worldwide phenomenon, with China among some of the fastest-aging societies as the number of its seniors and life expectancy have been increasing over the past decades. National Bureau of Statistic of China reported that the proportion of China’s population aged 60 and above was 16.2% (221.8 million) at the end of 2015, representing an increase of 5.8% compared with that in 2000 [1, 2]. This demographic change has posed several challenges (i.e., social insurance, and public services) to the individuals, the family, and also the society [3]. Among which, healthcare service is an important issue which deserves concern.

The population aging is accompanied by an increase in prevalence of some diseases, especially of non-communicable chronic diseases (NCDs), such as cerebrovascular disease, heart disease, respiratory disease, diabetes, and hypertension, which place a heavy burden on the seniors and also their families [4]. Furthermore, the increase in the proportion of the older people in a country is found to be a driver of national health expenditure. Previous studies have demonstrated that periodic physical examination is an important and effective measure for illness prevention and health promotion through early detection and timely treatment [57]. Moreover, periodic physical examination (i.e., annual physical examination) is found to have a negative correlation with health expenditure among the seniors [8].

Many previous studies have explored the factors associated with the utilization of physical examination in China and found that the physical examination use is influenced by demographic characteristics, such as gender, education, income level, and marital status [911]. Ye and Wang found that the use of physical examination was higher among those elderly with poorer self-rated health in rural Wenling, China [12]. A study by Li et al. found that health literacy was an important risk factor for the use of physical examination among urban seniors in Chengdu [13]. However, most of the existing studies only focused on the rural or urban residents. To date, no studies have explored the difference in the use of periodic physical examination between rural and urban residents in China.

To remedy this situation, the present study aims to explore the difference in the use of annual physical examination (APE) between rural and urban areas in China. To do so, we have following specific objectives. First, we will compare the difference in use of APE between rural and urban seniors in China. Second, we will identify the risk factors associated with the use of APE in rural and urban elderly respectively.

Methods

Subjects

This cross-sectional study was conducted in Shandong province from November, 2011 to January, 2012. Shandong has the second largest total population in China, and its older people (60+) accounted for 15% of the total population (about 970million) in 2012 [14]. We employed a 3-stage cluster sampling method to selected participants. First, all of the districts and counties in Shandong were divided into three groups according to the GDP per capita in 2011. Second, one district and one county were randomly selected from each group. Three districts (Huaiyin, Dongchangfu, Zhangdian) and three counties (Qufu, Chiping, Leling) were chosen as study sites. Likewise, three sub-districts and three townships were then selected from each sampling district or county according the GDP per capita, respectively. Third, three communities or three villages were randomly selected from each selected sub-district and township (27 communities, and 27 villages). All of the elderly households of the sampling communities or villages were recruited into our survey. In total, 3922 participants were included in this study.

Variables

Social demographic characteristics

Social demographic characteristics included gender, age, education, marital status, self-reported economic status, health insurance, and the distance to the nearest health providers. The participants’ age was divided into three groups: 60−, 70−, and, 80+ years. Other demographic characteristics were categorized as follows: gender (male vs. female), education level (illiteracy or semiliterate, primary school, junior school, and senior school or above), residence (rural vs. urban), marital status (single vs. couple), economic status (poor, normal, and good), health insurance (Urban Employee Basic Medical Insurance, UEBMI; Urban Resident Basic Medical Insurance, URBMI; New cooperative medical scheme, NCMS; others; and none), and the distance to the nearest health providers (<1 km, 1 km+).

Health behaviors

We collected health behavior information of the participants, including smoking, drinking, exercise, watching TV. These characteristics were categorized as follows: smoking (yes vs. no), drinking (at least 1 time a week vs. no or less than 1 time a week), exercise (at least 3 times a week vs. less than 3 times a week), watching TV (yes vs. no).

Physical health

We collected the information about physical health, including number of NCDs (none, 1, 2, and, 3 or above), and hospitalization (yes vs. no).

ADL

This study applied Activity of Daily Living Scale (ADL) which consists of 14 questions to evaluate the ability to perform activities of daily living. Total score is 14 to 56, and the higher total score indicates worse ADL status [15]. A total score of 14 was suggestive of normal, which was coded into 1; a total score of 15 ~ 21 was suggestive of mild disabilities, which was coded into 2; and a total score of 22 and above was suggestive of apparent obstacles, which was coded into 3. The Cronbach’s α of the ADL in this study was 0.95.

APE

APE was measured by a question of “Did you have any physical examinations in the past twelve months”. The answer included “yes” [1] and “no” (0).

Statistical analysis

All statistical analyses were performed using SPSS 16.0. We employed unadjusted model to identify potential factors associated with APE use among the elderly. Two models, one unadjusted and one adjusted regression model, were used to examine the rural–urban difference in the APE use. Further, two binary logistic regression models were used to identify the factors associated with APE use in rural and urban elderly respectively.

Results

Of all respondents, rural elderly account for 54.9% (2153), urban elderly account for 45.1% (1769). And 37.4% of rural elderly use APE, 76.2% of urban elderly use APE (Table 1). Results from the unadjusted model are presented in the Table 1. Those who live in urban areas (p < 0.05), who have higher educational level (p < 0.05), who have a good economic status (p < 0.05), who often do exercise (p < 0.05), who watch TV (p < 0.05), who have one or more types of NCDs (p < 0.05), who have inpatient services (p < 0.05),who are covered by UEBMI (p < 0.005) or URBMI (p < 0.05) are more likely to use APE.
Table 1

Factors associated with annual physical examination among the seniors in Shandong, China, 2012

Characteristics

Total (N/%)

APEa Use (N/%)

Unadjusted model

Adjusted model

Yes

No

OR

95%CI

P

OR

95%CI

P

Observations

3922

2154 (54.9)

1768 (45.1)

      

Region

         

 Rural

2153 (54.9)

806 (37.4)

1347 (62.6)

1.00

  

1.00

  

 Urban

1769 (45.1)

1348 (76.2)

421 (23.8)

5.35

4.65–6.15

0.000

2.76

2.26–3.36

0.000

Gender

      

NAb

  

 Male

1822 (46.5)

1018 (55.9)

804 (44.1)

1.00

     

 Female

2100 (53.5)

1136 (54.1)

964 (45.9)

0.93

0.82–1.05

0.265

   

Age

     

0.082

NA

  

 60−

2569 (65.5)

1392 (54.2)

1177 (45.8)

1.00

     

 70−

1121 (28.6)

644 (57.4)

477 (42.6)

1.14

0.99–1.31

0.067

   

 80+

232 (5.9)

118 (50.9)

114 (49.1)

0.87

0.66–1.14

0.331

   

Education

     

0.000

  

0.000

 Illiteracy or semiliterate

1736 (44.3)

758 (43.7)

978 (56.3)

1.00

  

1.00

  

 Primary school

1175 (30.0)

680 (57.9)

495 (42.1)

1.77

1.52–2.05

0.000

1.30

1.10–1.55

0.002

 Junior school

597 (15.2)

391 (65.5)

206 (34.5)

2.44

2.01–2.97

0.000

1.30

1.04–1.63

0.020

 Senior school or above

414 (10.6)

325 (78.5)

89 (21.5)

4.71

3.65–6.06

0.000

1.95

1.45–2.62

0.000

Marital status

         

 Single

817 (20.8)

409 (50.1)

408 (49.9)

1.00

  

1.00

  

 Couple

3105 (79.2)

1745 (56.2)

1360 (43.8)

1.28

1.09–1.49

0.002

1.01

0.84–1.20

0.936

Economic status

     

0.000

  

0.060

 Poor

677 (17.3)

298 (44.0)

379 (56.0)

1.00

  

1.00

  

 Normal

2319 (59.1)

1251 (53.9)

1068 (46.1)

1.49

1.25–1.77

0.000

1.21

1.00–1.47

0.046

 Good

926 (23.6)

605 (65.3)

321 (34.7)

2.39

1.95–2.93

0.000

1.31

1.03–1.65

0.023

Smoking

         

 No

3041 (77.5)

1741 (57.3)

1300 (42.7)

1.00

  

1.00

  

 Yes

881 (22.5)

413 (46.9)

468 (53.1)

0.65

0.56–0.76

0.000

0.89

0.74–1.07

0.221

Drinking (time/a week)

         

 <1

3243 (82.7)

1805 (55.7)

1438 (44.3)

1.00

  

1.00

  

 ≥1

679 (17.3)

349 (51.4)

330 (48.6)

0.84

0.71–0.99

0.043

0.93

0.76–1.14

0.505

Exercise (time/a week)

         

 <3

1514 (38.6)

633 (41.8)

881 (58.2)

1.00

  

1.00

  

 ≥3

2408 (61.4)

1521 (63.2)

887 (36.8)

2.38

2.09–2.72

0.000

1.53

1.32–1.78

0.000

Watching TV

         

 No

470 (12.0)

179 (38.1)

291 (61.9)

1.00

  

1.00

  

 Yes

3452 (88.0)

1975 (57.2)

1477 (42.8)

2.17

1.78–2.65

0.000

1.69

1.34–2.12

0.000

Number of NCDsc

     

0.000

  

0.001

 None

1338 (34.1)

649 (48.5)

689 (51.5)

1.00

  

1.00

 

0.001

 1

1781 (45.4)

1006 (56.5)

775 (43.5)

1.37

1.19–1.58

0.000

1.29

1.10–1.52

0.002

 2

582 (14.8)

354 (60.8)

228 (39.2)

1.64

1.35–2.00

0.000

1.41

1.12–1.77

0.003

 3+

221 (5.6)

145 (65.6)

76 (34.4)

2.02

1.50–2.72

0.000

1.78

1.26–2.52

0.001

Hospitalization

         

 No

3355 (85.5)

1790 (53.4)

1565 (46.6)

1.00

  

1.00

  

 Yes

567 (14.5)

364 (64.2)

203 (35.8)

1.56

1.30–1.88

0.000

1.19

0.96–1.48

0.101

ADLd

     

0.000

  

0.247

 1

2854 (72.8)

1638 (57.4)

1216 (42.6)

1.00

  

1.00

  

 2

630 (16.1)

331 (52.5)

299 (47.5)

0.82

0.69–0.97

0.026

1.03

0.85–1.26

0.716

 3

438 (11.2)

185 (42.2)

253 (57.8)

0.54

0.44–0.66

0.000

0.83

0.65–1.05

0.133

The distance to the nearest health institutions (km)

         

 <1

3639 (92.8)

2024 (55.6)

1615 (44.4)

1.00

  

1.00

  

 ≥1

283 (7.2)

130 (45.9)

153 (54.1)

0.67

0.53–0.86

0.002

0.98

0.75–1.28

0.893

Type of health insurancee

     

0.000

  

0.000

 None

113 (2.9)

57 (50.4)

56 (49.6)

1.00

  

1.00

  

 UEBMI

808 (20.6)

658 (81.4)

150 (18.6)

4.31

2.86–6.48

0.000

2.13

1.36–3.33

0.001

 URBMI

470 (12.0)

370 (78.7)

100 (21.3)

3.63 `

2.36–5.58

0.000

2.18

1.37–3.46

0.001

 NCMS

2507 (63.9)

1053 (42.0)

1454 (58.0)

0.71

0.48–1.03

0.077

1.15

0.75–1.74

0.511

 Others

24 (0.6)

16 (66.7)

8 (33.3)

1.96

0.77–4.95

0.153

1.68

0.61–4.64

0.311

Note: The italics indicate significance

a APE annual physical examination

b NA not applicable

c NCDs Non-communicable chronic diseases

d ADL activity of daily living

e UEBMI, Urban Employee Basic Medical Insurance, URBMI Urban Resident Basic Medical Insurance, NCMS New cooperative medical scheme

The adjusted model shows that when controlling for other variables, the utilization rate of APE in the urban elderly is still statistically higher than that in rural elderly (AOR = 2.761, p = 0.000). In addition, the results also show that those who have higher educational level (p < 0.05), who often do exercise (p = 0.000), who watch TV (p = 0.000), who have one or more types of NCDs (p < 0.005), who are covered by UEBMI (p = 0.001) or URBMI (p = 0.001) are more likely to use APE.

Two adjusted binary logistic regression models are conducted to identify the factors associated with the use of APE in rural (Table 2) and urban seniors (Table 3) respectively. Four factors are found to be statistically associated with the APE use (p < 0.05) both in rural and urban elderly, including education level, exercise, watching TV, and the number of NCDs. Among rural elderly, those who experienced hospitalization use (AOR = 1.438, p = 0.011), who report good economic status (AOR = 1.600, p = 0.002), who are covered by some types of insurance (not NCMS) (AOR = 3.419, p = 0.010) were more likely to use APE. Among urban elderly, those who are covered URBMI (AOR = 1.874, p = 0.025) are more likely to use APE.
Table 2

Factors associated with the use of physical examination among rural elderly in Shandong, China (2012)

Characteristics

Total (N/%)

APEa Use (N/%)

Unadjusted model

Adjusted model

Yes

No

OR

95%CI

P

OR

95%CI

P

Observations

2153

806 (37.4)

1347 (62.6)

      

Gender

      

NAb

  

 Male

1045 (48.5)

396 (37.9)

649 (62.7)

1.00

     

 Female

1108 (51.5)

410 (37.0)

698 (63.0)

0.96

0.80–1.14

0.669

   

Age

     

0.326

NA

  

 60−

1468 (68.2)

563 (38.4)

905 (61.6)

1.00

     

 70−

550 (25.5)

199 (36.2)

351 (63.8)

0.91

1.74–1.11

0.371

   

 80+

135 (6.3)

44 (32.6)

91 (67.4)

0.77

0.53–1.13

0.188

   

Education

     

0.000

  

0.122

 Illiteracy or semiliterate

1206 (56.0)

409 (33.9)

797 (66.1)

1.00

  

1.00

  

 Primary school

631 (29.3)

252 (39.9)

379 (60.1)

1.29

1.06–1.58

0.011

1.13

0.92–1.39

0.238

 Junior school

215 (10.0)

90 (54.5)

125 (58.1)

1.40

1.04–1.88

0.025

1.16

0.85–1.58

0.342

 Senior school or above

101 (4.7)

55 (54.5)

46 (45.5)

2.33

1.54–3.50

0.000

1.66

1.06–2.58

0.025

Marital status

      

NA

  

 Single

504 (23.4)

171 (33.9)

333 (66.1)

1.00

     

 Couple

1649 (76.6)

635 (38.5)

1014 (61.5)

1.22

0.98–1.50

0.630

   

Economic status

     

0.000

  

0.010

 Poor

448 (20.8)

135 (30.1)

313 (69.9)

1.00

  

1.00

  

 Normal

1338 (62.1)

504 (37.7)

834 (62.3)

1.40

1.11–1.76

0.004

1.24

0.97–1.58

0.074

 Good

367 (17.0)

167 (45.5)

200 (54.5)

1.93

1.45–2.58

0.000

1.60

1.18–2.16

0.002

Smoking

      

NA

  

 No

640 (70.3)

570 (37.7)

943 (62.3)

1.00

     

 Yes

1513 (29.7)

236 (36.9)

404 (63.1)

0.96

0.79–1.17

0.726

   

Drinking (time/a week)

      

NA

  

 <1

1719 (79.8)

649 (37.8)

1070 (62.2)

1.00

     

 ≥1

434 (20.2)

157 (36.2)

277 (63.8)

0.93

0.75–1.16

0.544

   

Exercise (time/a week)

         

 <3

1051 (51.2)

359 (32.6)

743 (67.4)

1.00

  

1.00

  

 ≥3

1102 (48.8)

447 (42.5)

604 (57.5)

1.53

1.28–1.82

0.000

1.41

1.18–1.69

0.000

Watching TV

         

 No

304 (14.1)

75 (24.7)

229 (75.3)

1.00

  

1.00

  

 Yes

1849 (85.9)

731 (39.5)

1118 (60.5)

1.99

1.51–2.63

0.000

1.72

1.28–2.30

0.000

Number of NCDsc

     

0.001

  

0.000

 None

808 (37.5)

267 (33.1)

541 (67.0)

1.00

  

1.00

  

 1

963 (44.7)

368 (38.2)

595 (61.8)

1.25

1.03–1.52

0.024

1.32

1.07–1.62

0.008

 2

278 (12.9)

123 (44.2)

155 (55.8)

1.60

1.21–2.12

0.001

1.78

1.32–2.40

0.000

 3+

104 (4.8)

48 (46.2)

56 (53.8)

1.73

1.15–2.62

0.009

2.02

1.30–3.14

0.002

Hospitalization

         

 No

1900 (88.2)

688 (36.2)

1212 (63.8)

1.00

  

1.00

  

 Yes

253 (11.8)

688 (46.6)

135 (53.4)

1.54

1.18–2.00

0.001

1.43

1.08–1.90

0.011

ADLd

     

0.069

  

0.266

 1

1448 (67.3)

561 (38.7)

887 (61.3)

1.00

  

1.00

  

 2

399 (18.5)

148 (37.1)

251 (62.9)

0.93

0.74–1.17

0.548

0.92

0.72–1.17

0.502

 3

306 (14.2)

97 (31.7)

209 (68.3)

0.73

0.56–0.95

0.021

0.78

0.58–1.05

0.109

The distance to the nearest health institutions (km)

      

NA

  

 Less than 1 km

1933 (89.8)

727 (37.6)

1206 (62.4)

1.00

     

 1 km+

220 (10.2)

79 (35.9)

141 (64.1)

0.92

0.69–1.24

0.621

   

Type of health insurancee

     

0.000

  

0.014

 None

38 (1.8)

8 (21.1)

30 (78.9)

1.00

  

1.00

  

 NCMS

2036 (94.6)

750 (36.8)

1286 (63.2)

2.18

0.99–4.79

0.051

1.82

0.81–4.07

0.144

 Others

79 (3.7)

48 (60.8)

31 (39.2)

5.80

2.35–14.29

0.000

3.41

1.34–8.71

0.010

Note: Of the 2153 rural participants, 53(2.46%) older people had retired from urban areas

The italics indicate significance

a APE annual physical examination

b NA not applicable

c NCDs Non-communicable chronic diseases

d ADL activity of daily living

e NCMS New cooperative medical scheme

Table 3

Factors associated with the use of physical examination among urban elderly in Shandong, China (2012)

Characteristics

Total (N/%)

APEa Use (N/%)

Unadjusted model

Adjusted model

Yes

No

OR

95%CI

P

OR

95%CI

P

Observations

1769

1348 (76.2)

421 (23.8)

      

Gender

         

 Male

777 (43.9)

622 (80.1)

155 (19.9)

1.00

  

1.00

  

 Female

992 (56.1)

726 (53.9)

266 (26.8)

0.68

0.54–0.85

0.001

0.83

0.64–1.07

0.166

Age

     

0.486

NAb

  

 60−

1101 (62.2)

829 (75.3)

272 (24.7)

1.00

     

 70−

571 (32.2)

445 (77.9)

126 (22.1)

1.15

0.91–1.47

0.230

   

 80+

97 (5.5)

74 (76.3)

23 (23.7)

1.05

0.64–1.71

0.828

   

Education

     

0.000

  

0.001

 Illiteracy or semiliterate

530 (30.0)

349 (65.8)

181 (34.2)

1.00

  

1.00

  

 Primary school

544 (30.8)

428 (78.7)

116 (21.3)

1.91

1.45–2.51

0.000

1.59

1.18–2.13

0.002

 Junior school

382 (21.6)

301 (78.8)

81 (21.2)

1.92

1.42–2.62

0.000

1.44

1.03–2.03

0.033

 Senior school or above

313 (17.7)

270 (86.3)

43 (13.7)

3.25

2.25–4.70

0.000

2.26

1.49–3.44

0.000

Marital status

      

NA

  

 Single

313 (17.7)

238 (76.0)

75 (24.0)

1.00

     

 Couple

1456 (82.3)

1110 (76.2)

346 (23.8)

1.01

0.75–1.34

0.941

   

Economic status

     

0.101

  

0.520

 Poor

229 (12.9)

163 (71.2)

66 (28.8)

1.00

  

1.00

  

 Normal

981 (55.5)

747 (76.1)

234 (23.9)

1.29

0.93–1.78

0.118

1.19

0.85–1.66

0.305

 Good

559 (31.6)

438 (78.4)

121 (21.6)

1.46

1.03–2.07

0.032

1.07

0.74–1.56

0.692

Smoking

      

NA

  

 No

1528 (86.4)

177 (73.4)

64 (26.6)

1.00

     

 Yes

241 (13.6)

1171 (76.6)

357 (23.4)

1.18

0.87–1.61

0.280

   

Drinking (time/a week)

      

NA

  

 <1

1524 (86.2)

192 (78.4)

53 (21.6)

1.00

     

 ≥1

245 (13.8)

1156 (85.8)

368 (24.1)

1.15

0.83–1.59

0.391

   

Exercise (time/a week)

         

 <3

1357 (23.3)

274 (66.5)

138 (33.5)

1.00

  

1.00

  

 ≥3

412 (76.7)

1074 (79.1)

283 (20.9)

1.91

1.49–2.43

0.000

1.83

1.42–2.37

0.000

Watching TV

         

 No

166 (9.4)

104 (62.7)

62 (37.3)

1.00

  

1.00

  

 Yes

1603 (90.6)

1244 (77.6)

359 (22.4)

2.06

1.47–2.89

0.000

1.59

1.11–2.28

0.011

Number of NCDsc

     

0.026

  

0.074

 None

530 (30.0)

382 (72.1)

148 (27.9)

1.00

  

1.00

  

 1

818 (46.2)

638 (78.0)

180 (22.0)

1.37

1.06–1.76

0.014

1.32

1.01–1.73

0.037

 2

304 (17.2)

231 (76.0)

73 (24.0)

1.22

0.88–1.69

0.218

1.08

0.76–1.53

0.651

 3+

117 (6.6)

97 (82.9)

20 (17.1)

1.87

1.12–3.15

0.017

1.74

1.00–3.02

0.048

Hospitalization

      

NA

  

 No

1455 (82.2)

1102 (75.7)

353 (24.3)

1.00

     

 Yes

314 (17.8)

246 (78.3)

68 (21.7)

1.15

0.86–1.55

0.326

   

ADLd

     

0.021

  

0.218

 1

1406 (79.5)

1077 (76.6)

329 (23.4)

1.00

  

1.00

  

 2

231 (13.1)

183 (79.2)

48 (20.8)

1.16

0.82–1.63

0.381

1.34

0.93–1.94

0.108

 3

132 (7.5)

88 (66.7)

44 (33.3)

0.61

0.41–0.89

0.012

0.91

0.60–1.39

0.692

The distance to the nearest health institutions (km)

     

NA

   

 <1

1706 (96.4)

1297 (76.0)

409 (24.0)

1.00

     

 ≥1

63 (3.6)

51 (81.0)

12 (19.0)

1.34

0.70–2.53

0.369

   

Type of health insurancee

     

0.000

  

0.000

 None

75 (4.2)

49 (65.3)

26 (34.7)

1.00

  

1.00

  

 UEBMI

755 (42.7)

622 (82.4)

133 (17.6)

2.48

1.48–4.13

0.000

1.70

0.98–2.92

0.056

 URBMI

454 (25.7)

362 (79.7)

92 (20.3)

2.08

1.23–3.53

0.006

1.87

1.08–3.23

0.025

 Others

485 (27.4)

315 (64.9)

170 (35.1)

0.98

0.59–1.63

0.948

0.95

0.56–1.61

0.861

Note: The italics indicate significance

a APE annual physical examination

b NA not applicable

c NCDs Non-communicable chronic diseases

d ADL activity of daily living

e UEBMI Urban Employee Basic Medical Insurance, URBMI Urban Resident Basic Medical Insurance

Discussion

We find that 37.4% of the rural elderly and 76.2% of the urban elderly used APE. The prevalence in APE use among the rural elderly in this study is much lower than that reported among the elderly by Sun et al. (63.5%), which was conducted in rural areas of four provinces or municipalities (Zhejiang, Henan, Qinghai, and Chongqing) in China [16]. It is a little higher than the utilization rate of 10.5% for the rural elderly in Anhui province, China [17]. Likewise, the rate of the APE use among urban seniors of our study is a little lower than that among the elderly in urban Chengdu (84.1%) [13]. But it is higher than the reported rate of 54.1% in urban Xuzhou [18]. In different settings, there is a large variation of APE use both in rural and urban elderly in China.

Since the implementation of the new health care reform scheme of China in 2009, APE has been provided free to the seniors aged 65 and above in rural and urban communities. In some regions, this program is expanded to those aged 60 and above [19, 20]. The program aims to promote good health for the seniors and reduce medical burdens through APE. Some studies found that the proportion of the elderly beneficiaries increased rapidly since the initiation of the program [21, 22]. Unexpectedly, despite the free services, there is still a large proportion of the elderly have not yet used the APE. Among the rural seniors, the utilization rate of the APE is much lower, remaining only at about 37%. This finding indicates an urgent need for studies to identify the barriers for the use of the APE among the elderly in China, especially in rural areas.

The result of this study demonstrates a big difference in APE utilization among the seniors between rural and urban China, which was consistent with the findings from some international studies [23, 24]. A study in Texas showed that rural residents were less likely to receive preventive care than their counterparts in urban areas [25]. There might be three explanations for this finding. One explanation is that APE services are poorly accessible in rural areas. Despite the services are free of charge, the long distance to the designated health providers will probably discourage the seniors’ use of APE, especially for those with NCDs or poor ADL, due to the transportation cost and substantial time incurred [24]. Another explanation is that most of the rural China’s seniors are afraid of being detected some potential serious diseases, and may refuse to use the APE services provided free by the governments. Third, most of the organizations in which the elderly ever worked are still responsible for the arrangement of periodic physical examinations even after their retirement, and will remind them repeatedly when their APE is due [16]. The rural elderly, by contrast, will be seldom reminded to use APE.

Similar with previous studies, the current study shows that educational level, exercise, watching TV, NCDs are factors associated with APE use both in rural and urban elderly. Many studies indicated that those elderly with higher educational level also had higher level of health literacy and ability to access health services [26, 27]. A study about the effect of health literacy on utilization of essential public health services among the elderly indicated to improve the health literacy among the elderly could effectively increase the utilization of essential public health services including physical examination [28]. Some previous studies also indicated that watching TV was the most important way to acquire health knowledge for the Chinese people. Watching TV has been proved to be effective to increase people’s health literacy in China [2931]. A study by Lai and Kalyniak found that having one or more illness would increase the probability of having APE significantly among those aging Chinese Canadians, which was in agreement with the finding of this study [32]. In China, periodic physical examination is an effective way to monitor and manage NCDs. Thus, people who had NCDs (i.e., hypertension, diabetes) might have a higher utilization rate of APE [33].

Interestingly, the current study indicates that the rural elderly who used inpatients services are found to have higher utilization rate of APE, which is inconsistent with previous studies. A study in Japan indicated an association between an increased use of check-ups and reduced use of hospital inpatient services [34]. Tian et al. also found that people who received preventive care services had lower probabilities of hospitalization use in Taiwan. One explanation for this finding might be that the rural elderly who use APE are more aware and better informed of their health conditions and thus have more frequent visits to hospitals, including inpatient services. Further, economic status of the rural elderly is found to be associated with the APE use, which is in agreement with some previous studies [10, 12, 35].

This study has some limitations. First, the data and relevant analyses showed here derive from a cross-sectional survey, and the relationship between identified factors and APE use cannot be interpreted as cause and effect. Second, the information including economic status and some other variables were self-reported, leading to the possibility of self-report bias. Third, we did not decompose the contribution of different components of explanatory variables in the current study, and will have a more explicit analysis in the follow-up study.

Conclusion

This study demonstrates a big difference in the use of APE between rural (37.4%) and urban seniors (76.2%) in China. Despite being provided free, there is still a large proportion of the elderly who do not use the APE, which highlights a need to identify the barriers to the APE utilization, especially in rural China. Educational level, number of NCDs, and some other factors are found to be associated with APE use both in rural and urban elderly. Further, hospitalization, self-reported economic status are predictors for APE use in rural elderly. Based on these findings, some recommendations can be given. First, the government should develop targeting health promotion policies to improve health literacy among the elderly. Second, the communities should pay close attention to those identified at-risk subgroups so as to increase the APE use among the elderly.

Abbreviations

ADL: 

Activity of daily living

APE: 

Annual physical examination

NCDs: 

Non-communicable chronic disease

NCMS: 

New cooperative medical scheme

UEBMI: 

Urban employee basic medical insurance

URBMI: 

Urban resident basic medical insurance.

Declarations

Acknowledgements

We would like to thank the officials of local health agencies and all participants and staff at the study sites for their cooperate.

Funding

This work was funded by the National Science Foundation of China (71003067), and the Innovation Foundation of Shandong University (2012DX006, 2009TS012).

Availability of data and materials

No additional data are available.

Authors’ contributions

CZ, DG conceived the idea. CZ, DG, YQ, LZ participated in the statistical analysis and interpretation of the results. DG drafted the manuscript. CZ, JC, and LS gave many valuable comments on the draft and also polished it. All authors read and approved the final manuscript.

Competing interests

The authors declare there are no competing interests.

Consent for publication

Consent for publication was obtained from the participants.

Ethics approval and consent to participate

The Ethical Committee of Shandong University School of Public Health approved the study protocol. The investigation was conducted after the informed consents of all participants were obtained.

Publisher’s Note

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Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
School of Public Health, Shandong University
(2)
Shandong Centre for Disease Control and Prevention
(3)
Collaborative Innovation Center of Social Risks Governance in Health

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© The Author(s). 2017

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