The Association of Underlying Diseases and Age-Related Cataracts in Iranian Patients

Document Type : Original article

Authors

1 Department of Medicine, School of Medicine, Babol University of Medical Sciences, Babol, Iran

2 Department of Ophthalmology, Ayatollah Rouhani Hospital, Babol University of Medical Sciences, Babol, Iran

3 Department of Biostatistics, School of Medicine, Babol University of Medical Sciences, Babol, Iran

4 Department of Ophthalmology, Islamic Azad University of Sari Branch, Sari, Iran

Abstract

Abstract 
Background: Age-Related Cataracts (ARC) is a multifactorial ocular dysfunction resulting inblurred lens, visual reduction, and blindness. Various underlying diseases are involved in increasing the risk of ARC. The purpose of this study was to investigate the association of underlying diseases and related medications with ARC in Iranian patients. 
Methods: In this case-control study, 353 patients (age between 40 to 70 years) with ARC were referred to Rouhani Hospital, Babol, Iran, and 343 control individuals (age between 40 to 70 years) participated. The history of underlying diseases of participants was collected by history-taking and self-expression. The cataract intensity and type determination was based on the Lens Opacities Classification System III (LOCS Ш). 
Results: Our results show that obesity (p <0.001), diabetes mellitus (OR = 0.422, 95% CI [0.285, 0.625], p<0.001) ,and hypertension (OR = 0.518, 95% CI [0.378, 0.712], p<0.001) are associated with prevalence of ARC (more prevalent in ARC patients compared to controls). The posterior subcapsular ARC is more prevalent in asthmatic ARC patients compared to non-asthmatic ARC patients (p=0.019). The prevalence of cortical ARC is higher in anemic ARC patients compared to non-anemic ARC patients (p=0.031). Cortical and posterior subcapsular ARC prevalence is higher in rheumatic ARC patients than non-rheumatic ARC patients (p=0.006). Also, atorvastatin use plays a preventive role in ARC (p=0.031). 
Conclusion: Our results established that obesity, diabetes mellitus, hypertension, and asthma are associated with the prevalence of ARC. Also, atorvastatin, as a routine medication, plays a preventive role in ARC. Furthermore, asthma, anemia, and rheumatism are involved in prevalence of certain types of ARC.  

Keywords


Abstract 
Background: Age-Related Cataracts (ARC) is a multifactorial ocular dysfunction resulting inblurred lens, visual reduction, and blindness. Various underlying diseases are involved in increasing the risk of ARC. The purpose of this study was to investigate the association of underlying diseases and related medications with ARC in Iranian patients. 
Methods: In this case-control study, 353 patients (age between 40 to 70 years) with ARC were referred to Rouhani Hospital, Babol, Iran, and 343 control individuals (age between 40 to 70 years) participated. The history of underlying diseases of participants was collected by history-taking and self-expression. The cataract intensity and type determination was based on the Lens Opacities Classification System III (LOCS Ш). 
Results: Our results show that obesity (p <0.001), diabetes mellitus (OR = 0.422, 95% CI [0.285, 0.625], p<0.001) ,and hypertension (OR = 0.518, 95% CI [0.378, 0.712], p<0.001) are associated with prevalence of ARC (more prevalent in ARC patients compared to controls). The posterior subcapsular ARC is more prevalent in asthmatic ARC patients compared to non-asthmatic ARC patients (p=0.019). The prevalence of cortical ARC is higher in anemic ARC patients compared to non-anemic ARC patients (p=0.031). Cortical and posterior subcapsular ARC prevalence is higher in rheumatic ARC patients than non-rheumatic ARC patients (p=0.006). Also, atorvastatin use plays a preventive role in ARC (p=0.031). 
Conclusion: Our results established that obesity, diabetes mellitus, hypertension, and asthma are associated with the prevalence of ARC. Also, atorvastatin, as a routine medication, plays a preventive role in ARC. Furthermore, asthma, anemia, and rheumatism are involved in prevalence of certain types of ARC.  
Keywords: Age-related cataract, Diabetes mellitus, Hypertension, Asthma
Introduction 
Age-Related Cataract (ARC) is a multifactorial ocular dysfunction resulting in blurred lenses, visual reduction, and blindness (1). Approximately, 50% of the causes of ARC are genetic, and the rest are related to aging, environmental, and systemic factors (2). Poor nutrition, male sex, white race, and age are involved in the development of ARC (3). Other factors include the use of drugs (corticosteroids), eye inflammation, diabetes, alcohol consumption, smoking, hypertension, body mass index, gender, trauma, eye diseases, and eye surgery. Therefore, the risk factors play an essential role in ARC. Surgery, which has many side effects and has many financial and economic costs, is the only therapeutic approach for ARC treatment. Therefore, applying a preventive approach to ARC leads to a reduction of ARC’s prevalence. Alongside correction of lifestyle-related risk factors, the treatment or control of underlying diseases is helpful in a decrease in ARC development. Identifying the possible risk factors for ARC can lead to effective prevention and treatment of the disease (4). 
Various underlying diseases are involved in increasing the risk of ARC, i.e. secondary ocular diseases (retinopathy of prematurity, retinal detachment, aniridia, retinitis pigmentosa, and uveitis), congenital diseases (cytomegalic inclusion disease, cockayne syndrome, congenital syphilis, and rubella), genetic disorders (Down syndrome, Edwards syndrome, and Patau syndrome), infectious diseases (onchocerciasis, toxoplasmosis, leprosy, cysticercosis, and varicella), and
metabolic diseases (cerebrotendinous xanthomatosis, diabetes mellitus, Fabry disease, Lowe syndrome,
Wilson disease, galactosemia cataract, homocy-
stinuria, hypoparathyroidism, hypothyroidism, hyper-
parathyroidism, hypervitaminosis D, hypocalcemia, and mucopolysaccharidoses) (5-8). However, the association of other underlying diseases with ARC is not fully characterized yet (9).
The risk factors of ARC for the Asian population are not well-known (10). Most studies have assessed risk factors for different types of cataracts in Western countries. A small number of studies on cataracts have recently been performed in Asian countries such as Japan, Taiwan, Singapore, and China (10-13). In Iran, accurate statistics on the number of people with cataracts are not available, and it is estimated that about 100,000 cataract surgeries are performed annually in Iran (14). In this study, the purpose was to investigate the association of underlying diseases (i.e. obesity, diabetes mellitus, anemia, hypertension, rheumatoid arthritis, and asthma) with ARC in Iranian patients. 

Materials and Methods
Sample 
In this case-control study, 353 patients with ARC were referred to Rouhani Hospital, Babol, Iran, and 343 control individuals participated. The history of underlying diseases of participants was recorded through history-taking and self-expression. Also, participants without ARC and other ocular complications were considered as controls. 
The criteria for admission were patients having ARC for more than years  confirmed by clinical examination by an ophthalmologist recommending surgery. In this study, patients with congenital cataracts, a history of other eye surgeries on the eye with cataract, a history of trauma to the eye with cataract, secondary cataracts, patients with lens opacity due to contact with certain chemicals, patients with retinal and uveal disorders (like uveitis, Retinitis Pigmentosa (RP), toxoplasmosis scars), diabetic retinopathy patients, as well as patients younger than 40 years were excluded from the study. Also, individuals older than 70 years were excluded from this study (in the patient and control group) due to the normalization of participants regarding age. 

Clinical experiments
The cataract intensity and type determination were based on the Lens Opacities Classification System III (LOCS Ш) (15). Accordingly, the nuclear cataract has six degrees (N1-N6), the cortical cataract has six degrees (C1-C5), and the posterior subcapsular cataract has 5 degrees (P1-P5). The types of ARC were divided into four types based on the degrees obtained with the LOCS Ш system: 1) Nuclear type (N≥4, C≤ 2 and P≤ 2), 2) Cortical type (C≥3, P≤2 and N≤3), 3) Posterior subcapsular type (P≥3, C≤2 and N≤3), 4) Mixed type (which can be in four modes: (i) N≥4, C≥3, and any P, (ii) N≥4, P≥3, and any C, (iii) N≤3, C≤2 and P≤2, and (iv) P≥3, C≥3 and any N). The intensity of ARC was divided into mild (NC≤4, C≤3 and P≤3), moderate (N=5, C=4, and P=4), and severe (N=6, C=5, and P=5). Also, anemia status was classified as anemic (hemoglobin less than 12 mg/dl) and normal (hemoglobin equal and more than 12 mg/dl) states. Hypertension was defined as systolic pressure of at least 140 or diastolic pressure of at least 90 mmHg. Also, diabetes mellitus was defined by fasting plasma glucose level of 126 mg/dL (7.0 mmol/L) or higher. Other diseases were diagnosed by specialist physicians.
 
Statistical analysis 
All statistical analyses were performed using SPSS v.21 (IBM, USA). Due to two answer choices regarding the disease (yes/no), the number of participants in each group was reported via percentage (%). The level of significance was considered 5% (p<0.05). Also, one-way ANOVA followed by post-hoc multiple comparisons (via Bonferroni method) and chi-square were used for statistical analysis. 

Results
Demographic statistics  
In this cross-sectional study during 2017-2018, 353 patients with ARC (58.82±5.32-year-old) and 342 controls (58.07±4.05-year-old) have participated. From 353 ARC patients, 213 (60.3%) and 140 (39.7%) individuals were female and male, respectively. The results show that the prevalence of ARC in males is higher than in females (p<0.001). Also, there is no significant association between sex and type of ARC (p=0.107); nuclear ARC is more prevalent in males than females. Regarding ARC severity, 110 (31.2%) patients were diagnosed with mild ARC. Also, 108 (30.6%) and 135 (38.2%) cases were classified as patients with moderate and severe ARC, respectively. 
The association of obesity, diabetes mellitus, hypertension, and asthma with the prevalence of ARC
Obesity significantly increases the risk of ARC (p<0.001).  In normal Body Mass Index (BMI) (18.5 to 25 kg/m2), there was no significant difference between patients and controls, but chi-square analysis showed that the prevalence of ARC is more in obese individuals. Also, diabetes mellitus (OR=0.422, 95% CI [0.285, 0.625], p<0.001) and hypertension (OR=0.518, 95%CI [0.378, 0.712], p<0.001) were significantly more prevalent in ARC patients compared to normal individuals.
Our results show that there is a reveres significant association between heart failure (OR=3.727, 95% CI [2.173, 6.394], p<0.001), renal failure (OR=3.203, 95% CI [1.256, 8.169], p=0.010), osteoporosis (OR=5.269, 95% CI [2.940, 9.442], p<0.001), osteoarthritis (OR=16.604, 95% CI [0.347, 26.645], p<0.001), and allergy (OR=15.636, 95% CI [6.700, 36.490], p<0.001) with ARC. In other words, the mentioned diseases are less prevalent in ARC patients compared to the normal group. Furthermore, our results established no association between anemia (OR=1.129, 95% CI [0.821, 1.552], p=0.454) and rheumatism (OR=1.602, 95%CI [0.914, 2.807], p=0.098) with the prevalence of ARC (Tables 1 and 2). 

The association of anemia and rheumatism with the type of ARC
Anemia is not associated with ARC, but in ARC patients, anemia status was significantly associated with the type of ARC (p=0.031). The prevalence of cortical ARC is higher in anemic ARC patients compared to non-anemic ARC patients. Also, rheumatism was not associated with the prevalence of ARC, but in ARC patients, rheumatism status was significantly associated with the type of ARC (p=0.006). The prevalence of cortical and posterior subcapsular ARC is higher in rheumatic ARC patients compared to non-rheumatic ARC patients. Other underlying diseases and medications are not associated with the type of ARC. Also, none of the underlying diseases and medications are associated with the intensity of ARC (Table 3).

The association of atorvastatin and corticos- teroids with prevalence of ARC, its type, and intensity 
Our statistical analysis shows a significant association between the use of atorvastatin and the prevalence of ARC (p=0.031). In other words, atorvastatin plays a preventive role in ARC. However, there were no associations between atorvastatin and corticosteroids with the type (p=0.192 and 0.435, respectively) and intensity of ARC (p=0.463 and 0.935, respectively). 

Discussion 
ARC are multifactorial ocular pathologic states culminating in blurred vision and blindness (1). As a multifactorial disease, ARC is affected by underlying diseases and lifestyles. Due to the high-cost burdens of ARC, it is crucial to reduce the risk of ARC. The correction of lifestyle is a preventive approach to reducing ARC’s complications (6,16). Furthermore, the treatment of underlying diseases, which play a critical role in development of ARC, can prevent ARC. The purpose of this study was to investigate the possible associations between underlying diseases and ARC.
Our results show that obesity, diabetes mellitus, hypertension, and asthma are associated with ARC in Iranian patients. A 2014 study by Rim et al on South Korean people over the age of 40 was conducted and examined the association of cataracts with the diet of individuals between 2008 and 2010. It was found that older age, low monthly income, low education, hypercholesterolemia, hypertension, and diabetes mellitus were independently associated with any type of cataracts (17). This study suggests that optimal control of blood pressure, blood sugar, and cholesterol can help reduce the prevalence of cataracts in the South Korean population. In a 2013 meta-analysis by Prokofyeva et al on a selective population ranging in age from 40 to 95 years (between 1990 and 2009) who were clinically diagnosed with cataracts, it was found that smoking, diabetes mellitus, chronic asthma, bronchitis, and cardiovascular diseases increase the risk of cataracts (18). 
In our study, the frequency of mixed cataracts (43.6%) and the frequency of nuclear type (24.1%) were higher than other types. Also, the severe type of ARC with 38.2% frequency was the most prevalent one regarding intensity among patients. In our study, out of 353 patients, 213 (60.3%) were women, and this percentage was not statistically significant, but in the subgroups, according to Bonferroni’s method, it was found that the frequency of nuclear cataracts in men (30.7%) is significantly more than women (19.7%). In a 2014 study by Rim et al in South Korea, it was found that all types of cataracts (anterior polar cataracts) were more common in women compared to men (17). 
In our study, a significant difference was observed in the BMI in the control group and the patient group, and it was found that BMI>25 is associated with ARC. In a 2011 study in Tehran by Sahebalzamani et al on 322 patients with ARC, it was stated that most patients are in the obesse group with BMI between 25 to 30 kg/m2 (19). In our study, diabetes mellitus was a risk factor for ARC, and statisticallysignificant differences were found between two groups of patients and controla. Similar to our findings, in the study by Prokofyeva et al, Hojati et al, and Rim et al, diabetes mellitus was considered a risk factor for ARC (17,18,20).
The difference between the two groups of patients and controls over asthma was statistically significant in our study, indicating that asthma is an effective factor for development of ARC. Also, Prokofyeva et al found that asthma and chronic bronchitis increased the risk of cataracts (18). Also, our study found a significant association between asthma and posterior subcapsular ARC.
In our study, there was no statistically significant difference between corticosteroid use and ARC. Prokofyeva et al found that corticosteroids increase the risk of cataracts (18). In a study by Hekari et al, corticosteroid was a predisposing factor for ARC (21). Also, there was no significant relationship between corticosteroid use and certain types of ARC in our study. 
It is recommended that a future prospective study be implemented that put a regimen for people on a special diet for 5 to 10 years, and then investigate the reduced effect of  mentioned factors on decreasing the risk of ARC.

 

Table 1. The association of underlying diseases and ARC

Type

Parameters

Group

Total

OR (95%CI)

p-value

Case

Control

Demographic data

Sex

Female

Count

213

255

468

1.905 (1.379, 2.630)

<0.001

% within sex

45.5%

54.5%

100.0%

Male

Count

140

88

228

% within sex

61.4%

38.6%

100.0%

 

Body Mass Index (BMI)

Normal

(18.5 to 25)

Count

86

93

179

-

<0.001

% within BMI

48.0%

52.0%

100.0%

Fat

(25 to 30)

Count

138

180

318

% within BMI

43.4%

56.6%

100.0%

Obese

(more than 30)

Count

129

70

199

% within BMI

64.8%

35.2%

100.0%

Diabetes mellitus

Disease

Count

93

45

138

0.422 (0.285, 0.625)

<0.001

% within diabetes

67.4%

32.6%

100.0%

Normal

Count

260

298

558

% within diabetes

46.6%

53.4%

100.0%

Underlying diseases

Hypertension

Disease

Count

150

95

245

0.518 (0.378, 0.712)

<0.001

% within hypertension

61.2%

38.8%

100.0%

Normal

Count

203

248

451

% within hypertension

45.0%

55.0%

100.0%

Heart failures

Disease

Count

19

60

79

3.727 (2.173, 6.394)

<0.001

% within heart failures

24.1%

75.9%

100.0%

Normal

Count

334

283

617

% within heart failures

54.1%

45.9%

100.0%

Renal failures

Disease

Count

6

18

24

3.203 (1.256, 8.169)

0.010

% within renal failures

25.0%

75.0%

100.0%

Normal

Count

347

325

672

% within renal failures

51.6%

48.4%

100.0%

Anemia

Anemic

Count

109

115

224

1.129 (0.821, 1.552)

0.454

 

% within anemia

48.7%

51.3%

100.0%

Normal

Count

244

228

472

% within anemia

51.7%

48.3%

100.0%

 

Asthma

Disease

Count

9

0

9

-

0.003

 

% within asthma

100.0%

0.0%

100.0%

 

Normal

Count

344

343

687

 

% within asthma

50.1%

49.9%

100.0%

 

Osteoporosis

Disease

Count

15

65

80

5.269 (2.940, 9.442)

<0.001

 

% within osteoporosis

18.8%

81.3%

100.0%

 

Normal

Count

338

278

616

 

% within osteoporosis

54.9%

45  .1%

100.0%

 

Rheumatism

Disease

Count

22

33

55

1.602 (0.914, 2.807)

0.098

 

 

% within rheumatism

40.0%

60.0%

100.0%

 

Normal

Count

331

310

641

 

% within rheumatism

51.6%

48.4%

100.0%

Medications

Osteoarthritis

Disease

Count

23

184

207

16.604 (10.347, 26.645)

<0.001

% within osteoarthritis

11.1%

88.9%

100.0%

Normal

Count

330

159

489

% within osteoarthritis

67.5%

32.5%

100.0%

Allergy

Disease

Count

6

73

79

15.636 (6.700, 36.490)

<0.001

% within osteoarthritis

7.6%

92.4%

100.0%

Normal

Count

347

270

617

% within osteoarthritis

56.2%

43.8%

100.0%

Corticosteroids

Using

Count

19

9

28

0.474 (0.211, 1.062)

0.064

% within corticosteroids

67.9%

32.1%

100.0%

Not using

Count

334

334

668

% within corticosteroids

50.0%

50.0%

100.0%

 

Atorvastatin

Use

Count

75

131

206

2.290 (1.638, 3.203)

<0.001

 

% within atorvastatin

36.4%

63.6%

100.0%

 

Not using

Count

278

212

490

 

% within atorvastatin

56.7%

43.3%

100.0%

 

 

Table 2. The association of underlying diseases and type of ARC

Type

Parameter

Type of ARC

p-value

Nuclear

Cortical

Posterior subcapsular

Mixed

Total

Demographic

Sex

Female

Count

42

41

55

75

213

0.107

% within sex

19.7%

19.2%

25.8%

35.2%

100.0%

Male

Count

43

21

29

47

140

% within sex

30.7%

15.0%

20.7%

33.6%

100.0%

 

Body Mass Index (BMI)

Normal

(18.5 to 25)

Count

27

17

16

26

86

0.057

 

% within BMI

31.4%

19.8%

18.6%

30.2%

100.0%

Fat

(25 to 30)

Count

36

28

29

45

138

% within BMI

26.1%

20.3%

21.0%

32.6%

100.0%

Obese

(more than 30)

Count

22

17

39

51

129

% within BMI

17.1%

13.2%

30.2%

39.5%

100.0%

 

Diabetes mellitus

Disease

Count

16

15

22

40

93

0.155

 

% within diabetes

17.2%

16.1%

23.7%

43.0%

100.0%

 

Normal

Count

69

47

62

82

260

 

% within diabetes

26.5%

18.1%

23.8%

31.5%

100.0%

 

Hypertension

Disease

Count

28

30

34

58

150

0.141

 

 

% within hypertension

18.7%

20.0%

22.7%

38.7%

100.0%

 

Normal

Count

57

32

50

64

203

 

% within hypertension

28.1%

15.8%

24.6%

31.5%

100.0%

 

Heart failures

Disease

Count

1

4

5

9

19

0.251

 

 

% within heart failures

5.3%

21.1%

26.3%

47.4%

100.0%

 

Normal

Count

84

58

79

113

334

 

% within heart failures

25.1%

17.4%

23.7%

33.8%

100.0%

Underlying diseases

Renal failures

Disease

Count

1

0

2

3

6

0.601

% within renal failures

16.7%

0.0%

33.3%

50.0%

100.0%

Normal

Count

84

62

82

119

347

% within renal failures

24.2%

17.9%

23.6%

34.3%

100.0%

Anemia

Anemic

Count

19

27

22

41

109

0.031

% within anemia

17.4%

24.8%

20.2%

37.6%

100.0%

Normal

 

 

Count

66

35

62

81

244

% within anemia

27.0%

14.3%

25.4%

33.2%

100.0%

Asthma

Disease

Count

0

1

6

2

9

0.019

% within asthma

0.0%

11.1%

66.7%

22.2%

100.0%

Normal

Count

85

61

78

120

344

% within asthma

24.7%

17.7%

22.7%

34.9%

100.0%

 

Osteoporosis

Disease

Count

1

4

4

6

15

0.407

 

% within osteoporosis

6.7%

26.7%

26.7%

40.0%

100.0%

 

Normal

Count

84

58

80

116

338

 

% within osteoporosis

24.9%

17.2%

23.7%

34.3%

100.0%

 

Rheumatism

Disease

Count

0

4

11

7

22

0.006

 

% within rheumatism

0.0%

18.2%

50.0%

31.8%

100.0%

 

Normal

Count

85

58

73

115

331

 

% within rheumatism

25.7%

17.5%

22.1%

34.7%

100.0%

 

Osteoarthritis

Disease

Count

5

1

6

11

23

0.283

 

% within osteoarthritis

21.7%

4.3%

26.1%

47.8%

100.0%

 

Normal

Count

80

61

78

111

330

 

% within osteoarthritis

24.2%

18.5%

23.6%

33.6%

100.0%

 

Allergy

Disease

Count

1

1

3

1

6

0.481

 

% within osteoarthritis

16.7%

16.7%

50.0%

16.7%

100.0%

 

Normal

Count

84

61

81

121

347

 

% within osteoarthritis

24.2%

17.6%

23.3%

34.9%

100.0%

Medications

Corticosteroids

Use

Count

1

3

7

8

19

0.192

% within Corticosteroids

5.3%

15.8%

36.8%

42.1%

100.0%

Not use

Count

84

59

77

114

334

% within Corticosteroids

25.1%

17.7%

23.1%

34.1%

100.0%

 

Atorvastatin

Use

Count

14

14

16

31

75

0.435

 

% within atorvastatin

18.7%

18.7%

21.3%

41.3%

100.0%

 

Not use

Count

71

48

68

91

278

 

% within atorvastatin

25.5%

17.3%

24.5%

32.7%

100.0%

 

Table 3. The association of underlying diseases and intensity of ARC

Type

Parameter

Intensity

p-value

Mild

Moderate

Severe

Total

Demographic

Sex

Female

Count

59

66

88

213

0.181

% within sex

27.7%

31.0%

41.3%

100.0%

Male

Count

51

42

47

140

% within sex

36.4%

30.0%

33.6%

100.0%

 

Body Mass Index (BMI)

Normal

(18.5 to 25)

Count

28

26

32

86

0.866

% within BMI

32.6%

30.2%

37.2%

100.0%

Fat

(25 to 30)

Count

44

45

49

138

% within BMI

31.9%

32.6%

35.5%

100.0%

Obese

(more than 30)

Count

38

37

54

129

% within BMI

29.5%

28.7%

41.9%

100.0%

Underlying diseases

Diabetes mellitus

Disease

Count

24

27

42

93

0.241

% within diabetes

25.8%

29.0%

45.2%

100.0%

Normal

Count

86

81

93

260

% within diabetes

33.1%

31.2%

35.8%

100.0%

Hypertension

Disease

Count

42

41

67

150

0.102

% within hypertension

28.0%

27.3%

44.7%

100.0%

Normal

Count

68

67

68

203

% within hypertension

33.5%

33.0%

33.5%

100.0%

 

Heart failures

Disease

Count

4

6

9

19

0.576

 

% within heart failures

21.1%

31.6%

47.4%

100.0%

 

Normal

Count

106

102

126

334

 

% within heart failures

31.7%

30.5%

37.7%

100.0%

 

Renal failures

Disease

Count

1

2

3

6

0.724

 

% within renal failures

16.7%

33.3%

50.0%

100.0%

 

Normal

Count

109

106

132

347

 

% within renal failures

31.4%

30.5%

38.0%

100.0%

 

Anemia

Anemic

Count

34

33

42

109

0.996

 

% within anemia

31.2%

30.3%

38.5%

100.0%

 

Normal

Count

76

75

93

244

 

% within anemia

31.1%

30.7%

38.1%

100.0%

 

Asthma

Disease

Count

2

2

5

9

0.556

 

% within asthma

22.2%

22.2%

55.6%

100.0%

 

Normal

Count

108

106

130

344

 

% within asthma

31.4%

30.8%

37.8%

100.0%

Medications

Osteoporosis

Disease

Count

3

3

9

15

0.208

% within osteoporosis

20.0%

20.0%

60.0%

100.0%

Normal

Count

107

105

126

338

% within osteoporosis

31.7%

31.1%

37.3%

100.0%

Rheumatism

Disease

Count

5

8

9

22

0.659

% within rheumatism

22.7%

36.4%

40.9%

100.0%

Normal

Count

105

100

126

331

% within rheumatism

31.7%

30.2%

38.1%

100.0%

Osteoarthritis

Disease

Count

4

11

8

23

0.138

% within osteoarthritis

17.4%

47.8%

34.8%

100.0%

Normal

Count

106

97

127

330

% within osteoarthritis

32.1%

29.4%

38.5%

100.0%

 

Allergy

Disease

Count

0

2

4

6

0.201

 

% within osteoarthritis

0.0%

33.3%

66.7%

100.0%

 

Normal

Count

110

106

131

347

 

% within osteoarthritis

31.7%

30.5%

37.8%

100.0%

 

Corticosteroids

Use

Count

4

8

7

19

0.463

 

% within Corticosteroids

21.1%

42.1%

36.8%

100.0%

 

Not use

Count

106

100

128

334

 

% within Corticosteroids

31.7%

29.9%

38.3%

100.0%

 

Atorvastatin

Use

Count

23

22

30

75

0.935

 

% within atorvastatin

30.7%

29.3%

40.0%

100.0%

 

Not use

Count

110

108

135

353

 

% within atorvastatin

31.2%

30.6%

38.2%

100.0%

 

Conclusion 
ARC is a multifactorial ocular dysfunction that results from aging. There are various risk factors associated with the progression of ARC. In this study, the purpose was to investigate the possible associations between underlying diseases and ARC. In brief, it was found that obesity, diabetes mellitus, hypertension, and asthma are potential risk factors of the prevalence of ARC. Also, the use of atorvastatin as a routine medication for hyperlipidemia has a negative association with the prevalence of ARC. Furthermore, asthma, anemia, and rheumatism are involved in prevalence of certain types of ARC. 
 
Acknowledgements 
We thank the staff at Babol University of Medical Sciences, Babol, Iran. This study was approved by the ethics committee of Babol University of Medica Sciences (approval ID: IR.MUBABOL.HRI.REC.1398.091).
Conflict of Interest 
All authors declare that there is no conflict of interest.  

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