Dietary Etiological Factors Contributing to the Prevalence of Hyperuricemia in Makkah Region

*Osama A Shaikhomar
Department Of Physiology, Faculty Of Medicine, Umm Al Qura University, Makkah, Saudi Arabia

*Corresponding Author:
Osama A Shaikhomar
Department Of Physiology, Faculty Of Medicine, Umm Al Qura University, Makkah, Saudi Arabia
Email:oashaikhomar@uqu.edu.sa

Published on: 2020-08-04

Abstract

Background: Recently there was an evolution in nutrition science, and scientific discoveries continued to highlight the importance of food in health maintenance and disease prevention.
Aim of the work: to investigate the association between purine-rich foods and body composition with the prevalence of hyperuricemia in Makkah city.
Methods: A convenes sample of one hundred subject’s male (n=77) and female (n=23) were chosen from inpatient and outpatient orthopaedic clinics and labs in hospitals in Makkah city, in the age range of 20-65 years. Data was collected through an interview with patients by using special questionnaire. A food frequency questionnaire was used to illustrate the consumption rate of purine foods. The weight and height were measured and body mass index (BMI) was estimated. Body composition was evaluated by Bodystat® Omron device. Blood uric acid, urea and creatinine were determined.
Results: About 23.4% of male subjects were Hyperuricemic patients. Mean value of uric acid was significantly higher for hyperuricemia subjects compared to Normouricemia (NU) (0.78 ±0.15 vs 0.33±0.06 µmol/l; p<0.001). There was a highly significant positive correlation (P<0.01) between hyperuricemia and each of age, waist, and visceral fat, as well as the consumption of camel meat, fish, salmon, liver, lentil and beans.
Conclusion: All hyperuricemic subjects were found to be male and the suspected cause was purine-rich diets and decreased activity. Hyperuricemia associated with an increase of age and visceral fat level. Therefore, nutrition education is recommended to improving nutrition and health status and protective of hyperuricemia.

Keywords

Hyperuricemic; Purine; Protein; Uric Acid; Body Composition; Makkah; KSA

Introduction

Gout is a rheumatic disease due to deposition of uric acid (UA) a waste in the body that the kidneys get rid of it through the urine. But when the body cannot remove UA enough or that the body produces large amount of it, this acid deposition in the form of crystals in many parts of the body including the joints causes the gout disease [1]. In humans, the upper end of the normal range is 360 µmol/L (6 mg/dL) for women and 400 µmol/L (6.8 mg/dL) for men [2]. In that respect, the significance of current study is to find the relationship between diet and the prevalence of hyperuricemia in Saudi Arabia and particularly in Makkah Area.

Lifestyle and Diet may play an important role in the development of hyperuricemia and gout. However, the association between dietary factors and hyperuricemia remains unclear, and few studies have though investigated direct links between food intake and hyperuricemia. Dietary causes account for about 12% of gout [3], and include a strong association with the consumption of alcohol, high saturated fats, fructose-sweetened drinks, meat, and seafood [4,5]. Recent studies have found dietary factors once believed associated with gout have in fact, the opposite effect including the intake of purine-rich vegetables (e.g., beans, peas, lentils, and spinach) and total protein [6]. The consumption of coffee, vitamin C and dairy products, as well as physical fitness, appear to decrease the risk of gout [7-9]. This is believed partly due to their effect in reducing insulin resistance.

The prevalence of hyperuricemia appears to be rising in many populations in the world. It is established that the prevalence of hyperuricemia is much higher in some communities than others [10-17]. In Saudi Arabia, the prevalence of hyperuricemia was only 8.42% [13]. The prevalence was higher in males above 30 years of age, as the male would have a stable family and career. The physiologic and economic reasons may explain this difference. In female, the influence of sexual hormones may explain as according to age of involvement of hyperuricemia. Another study demonstrated that the 45-64 age group had a higher prevalence compared to the 18-44 age group [18].

It was shown that the prevalence was 4.3% and 1.3% in men and women respectively who were younger than 18 years, but it increased to 17.4% and 15.4% in men and women from 30 to 39 years. A study about elderly people in Taiwan reported that men at age 65 to 69 had the highest proportion of hyperuricemia which was 69.8%, but women at age more than 80 had the higher prevalence which was 50% [19]. It was found that the prevalence of hyperuricemia increased in male than female. No case of gout was found in any of the Black African groups, while the prevalence among the urban Caucasians was 13/1000 men and 3/1000 women. This was generally higher in men than in women throughout the age range. Most textbooks describe hyperuricemia or gout as a disease of men [4]. Therefore, most studies have shown that hyperuricemia predominantly affects older men and shows an overall male: female ratio of approximately 3-4: 1 [20]. A study in a North European population has found that about 80% of the hyperuricemia cases were men. In Saudi Arabia, the mean age for the males was 46.89±17.01 years (range 14-83) and for the females as 45.08±13.67 years (range 21-80).

The presence of some of criteria (signs and symptoms, history of underlying disorders, the presence of risk factors and certain laboratory investigations) helps confirm gout. A complete examination of the blood, which includes estimation of the various normal parameters of the blood cells; uric acid (blood, urine and tissue); and the microscopy examination of the presence of refractile needle-shaped crystals of uric acid and intracellular monosodium urate (MSU) crystals in synovial fluid aspirated from an inflamed joint; and Radiographs using X-ray of the affected joints may display evidence of bone destruction with margins of tophi in chronic cases. Therefore, this work aims to investigate dietary etiological factors contributing to the prevalence of hyperuricemia in Makkah region.

Material and Methods

Subjects and Study Design

A cross-sectional study was conducted during the academic year (1432-1433h). A convenes sample of one hundred (100) subjects (77 male and 23 female) was chosen from orthopedic outpatient clinics and labs at public and central hospitals and labs from Makkah, Saudi Arabia. The age of the patients was 20-65 years. Hospitals were randomly selected to participate, as were patients from the selected hospitals. A quota of specific number of patients was assigned for each hospital. If the quota was not achieved, over sampling from other hospital was sought to be the solution. At the commencement, a letter was submitted to every hospital indicating our objectives for conducting the research. Patients were provided with the study questionnaire stating their health, nutritional and social conditions. From the same patients, the anthropometric data was recorded, and the food frequency and body composition of patients were measured.

Population

The study was conducted in the holy city of Makkah at different areas/ districts and from community with varied socio-economic and cultural backgrounds. Five hospitals were visited and contribution to the study was discussed with the administration and staff in hospitals. All hospitals followed the Ministry of health.

Data and Measurements

Data was collected through an interview with patients by using: Socioeconomic level questionnaire and food frequency questionnaire. A socioeconomic level questionnaire was used to collect data on age, sex, educational level, income. A food frequency questionnaire was used to illustrate the consumption rate of purine foods [21]. The weight and height were measured according to methods described by Jelliffe DB, et al. (1966) [22], as well as body mass index (BMI) was estimated. Garrow JS (1988) [23] reported that:

  • BMI= Body Weight (kg)/ Height2 (m).

Body Composition

Body composition measurement technique based on the principle that lean tissue has higher electrical conduction and lower impedance than fat. It uses resistance and reactance to estimate fat-free and fat mass. An unnoticeable, low electric current (900 A; frequency, 50 kHz) is passed through electrodes attached to the extremities of a patient to measure resistance and reactance [24]. Body composition using the device of Bodystat® Omron device by the technique of BIA for some children were found by entering weight and height in Bodystat® Omron device which was used to measure: BMI, total body fat, lean body %. This device has equations for adult body compositions and anthropometric measurements and BEE by estimation. The results appearing in the device were recorded into each sample questionnaire and on SPSS package. Interpretation of body fat percentage, skeletal muscle percentage and visceral fat level for adults [25].

Determination of Serum Uric Acid, Urea and Creatinine

Uric acid was determined according to the enzymatic colorimetric test of Fossatti E, et al. (1980), Urea was determined according to the enzymatic method of Patton CJ, et al. (1977), Creatinine was determined according to kinetic method of Henry RJ, et al. (1974) [26-28].

 Statistical Analysis

The statistical analysis was carried out using windows version of SPSS 16 and range values were computed. Quantitative data are presented as mean±standard deviation. Qualitative data were expressed as percentages. For the quantitative variables, compliance with the normal distribution was assessed using the Kolmogorov-Smirnoff test, as appropriate. For comparing the groups, the chi-square test or Fisher’s exact test were used for qualitative variables as well as the t-test or Mann-Whitney U test for quantitative variables. P value of less than 0.05 was considered to indicate statistical significance.

Results

Socio-Demographic Status

Table 1 shows the frequency distribution of samples according to gender. Our results revealed that the majority of studied subjects were male, and 23% (n=18 out of total 77 male subjects) of total male subjects were hyperuricemic. Female subjects did not suffer from hyperuricemia, which shows that only 18% (n=18 out of total 100 subjects) were hyperuricemics in whole data. The mean±SD of age for hyperuricemic patients (HP) was significantly higher (P=0.009) than without hyperuricemia or normouricemia (NU) (34.72±12.39 and 27.74±8.55 years respectively).

Table 1: The Mean±SD of age and distribution of subjects according to gender.

 

NU (n=82)

HP (n=18)

X2

P value

Frequency

Percent

Frequency

Percent

Male

59

72

18

100

6.557a

0.01

Female

23

28

0

 

Total

82

100

18

100

Age Mean

27.74

34.72

0.009*

   SD

8.55

12.39

HP= Hyperuricemic patients;  NU= Normouricemia;  X²: Chi-Square; P*: Mann-Whitney test

Table 2 illustrated the distribution of samples according to socio-demographic status. The greater part of investigated samples (73.2% and 38.9%) had graduate educational level for NU and HP respectively. As can be seen in the same table, the highest percentage (61.1% and 37.8) of HP and NU respectively from family had 5-10 persons. The highest ratio for total family subject’s income was <3500RS/month, 37.8% for NU, while about 27.8% of HP had 5000-<7000 RS/month.

Table 2: Distribution of subjects according to socio-demographic status.

 

NU (n=82)

HP (n=18)

X2

P value

No.

%

No.

%

Education level

12.67a

0.013

Primary

4

4.9

3

16.7

Intermediate

4

4.9

3

16.7

Secondary

11

13.4

2

11.1

Graduate

60

73.2

7

38.9

Postgraduate

3

3.7

3

16.7

Family size

3.408a

0.182

<5

25

30.5

4

22.2

05 Oct

31

37.8

11

61.1

>10

26

31.7

3

16.7

Total income

8.136a

0.087

<3500

31

37.8

3

16.7

3500≤5000

13

15.9

2

11.1

5000≤7000

6

7.3

5

27.8

7000≤10000

19

23.2

4

22.2

≥10000

13

15.9

4

22.2

HP= Hyperuricemic patients   NU= Normouricemia;  X²: Chi-Square 

Symptoms and Analyses of Hyperuricemia

Table 3 shows that most of HP subjects (44.4%) suffered from joint pain compared to 7.3% of NU. Also, about 38.9% of HP suffered from fingers/toe tenderness compared with 4.9% of NU. Significant differences were found for symptoms of both samples (p<0.001).

Table 3: Distribution of subjects according to hyperuricemia symptoms.

 

NU (n=82)

HP (n=18)

X2

P value

No.

%

No.

%

Joint Pain

Yes

6

7.3

8

44.4

24.4a

0

Sometimes

21

25.6

8

44.4

No

55

67.1

2

11.1

Fingers or toe tenderness

Yes

4

4.9

7

38.9

28.9a

0

Sometimes

18

22

9

50

No

60

73.2

2

11.1

Physical activity

Yes

29

35.4

7

38.9

   

Sometimes

34

41.5

4

22.2

2.89 a

0.236

No

19

23.2

7

38.9

 

 

HP= hyperuricemic patients   NU= normouricemia;  X²: Chi-Square

Uric Acid Level

Table 4 shows that shows the mean and standard deviation of lab tests. Mean value of uric acid was significantly higher (p<0.001) for HP compared with NU (780±150 vs. 330±60 resp.). The same trend was observed for Creatinine and Urea but not significant (p=0.069 and p= 0.085 resp.).

Table 4: Mean and standard deviation of laboratory tests for studied subjects.

 

 

NU (n=82)

HP (n=18)

P*

Mean±SD

Mean±SD

Uric acid (µmol/l)

330±60

780±150

0

Creatinine (µmol/l)

65.28±8.59

68.48±13.18

0.069

Urea (mmol/l)

3.94±1.02

4.39±1.07

0.085

HP= Hyperuricemic Patients;  NU= Normouricemia;   SD = Standard deviation;  P*: Mann-Whitney 

Anthropometric Measurements and Body Composition

Table 5 shows the mean±SD values of waist and weight for HP significantly higher (P=0.001) than NU, the values were (95.66±9.33 and 84.71±14.22cm vs. 81.62±7.71 and 71.25±19.84 kg respectively), the same trend was observed for BMI (28.34±2.44 vs. 25.06±5.85 kg/m2 respectively) and it is significant at (P<0.001). Height difference was insignificant.

Table 5: Mean±SD of anthropometric measurements for studied subject.

 

NU (n=82)

HP (n=18)

X2

P value

Frequency

Percent

Frequency

Percent

Male

59

72

18

100

6.557a

0.01

Female

23

28

0

 

Total

82

100

18

100

Age Mean

27.74

34.72

0.009*

   SD

8.55

12.39

HP= Hyperuricemic patients;  NU= Normouricemia;  X²: Chi-Square; P*: Mann-Whitney test

Table 6 show the frequency distribution of studied samples according to grades of BMI. The majority of HP (66.7%) had overweight at the level (25.0-29.9kg/m2), meanwhile the most of NU had normal level of BMI (18.5-24.9kg/m2). About 27.8% of HP were obese compared to13.4% of NU. As for BMI, the differences between two groups were significant p=0.005.

Table 6: Frequency distribution of investigated subjects according to BMI.

BMI

NU (n=82)

HP (n=18)

X2

P

No

%

No

%

Starvation (less than 16.5)

2

2.4

0

0

16.66a

0.005

Underweight (16.5 to 18.5)

1

1.2

0

0

Normal (18.5 - 24.9)

43

52.4

1

5.6

Overweight (25.0 - 29.9)

23

28

12

66.7

Obesity (30.0 - 34.9)

11

13.4

5

27.8

Morbidly Obese (40.0 +)

2

2.4

0

0

HP= Hyperuricemic Patients;  NU= Normouricemia;   a: X² Chi-Square; BMI = Body Mass

The mean and SD for body composition for studied samples are shown in table 7. The body visceral fat for HP was significantly higher (p<0.001) when compared with NU (11.28±3.72 vs 6.705±3.76kg respectively), the same trend was observed for body fat (kg) and muscle % but difference was insignificant (p>0.05) (29.61±4.74kg 34.72±4.23% vs 29.35±8.74kg and 32.17±7.86%) respectively.

Table 7: Mean and standard deviation of body composition for studied subjects.

 

NU (n=82) Mean±SD

HP (n=18) Mean±SD

P*

Body fat (kg)

29.35±8.74

29.61±4.74

0.788

Muscle (%)

32.17±7.86

34.72±4.23

0.360

Visceral fat (kg)

6.705±3.76

11.28±3.72

0.000

HP= Hyperuricemic Patients;  NU= Normouricemia; SD = Standard Deviation; P*: Mann-Whitney test

Consumption of Purine Diet

Frequency distribution of studied samples according to consumption of purine diets are shown in Table 8.1-8.2. Results revealed that the highest percentage of HP highly consumed Shoor fish, Hamoor fish, Najel fish, Mussel, Lentil, Beans, Goats/Sheep meat and Liver when compared with NU. The majority of NU (36.6%) did not prefer Lentil compared with (5.6%) of HP, the same trend was observed for Bean consumption (24.4% vs 5.6%). As for fish group, the greater part of NU did not prefer Shoor fish, Hamoor fish, Najel fish and Mussel compared with HP, the same trend was observed for meat group.

Table 8.1: Frequency distribution of subjects according to consumption of purine diets.

 

NU (n=82)

HP (n=18)

X2

p value

No.

%

No.

%

Lentil

 

 

 

 

 

 

Not prefer

30

36.6

1

5.6

17.635a

0.061

Once/day

7

8.5

0

0

Twice/day

2

2.4

0

0

>Three/day

2

2.4

0

0

Once/week

7

8.5

6

33.3

Twice/week

6

7.3

1

5.6

Three/week

28

8.9

10

10.6

>Three/week

23

28

9

50

Beans

 

 

 

 

15.350a

0.082

Not prefer

20

24.4

1

5.6

Once/ day

16

19.5

1

5.6

Twice/ day

4

4.9

0

0

Three times d

2

2.4

0

0

Once/ week

8

9.8

5

27.8

Twice/ week

5

6.1

2

11.1

Three/ week

27

32.9

9

50

Shoor fish

 

 

 

 

19.010a

0.004

Not prefer

52

63.4

6

33.3

Once/ day

1

1.2

0

0

Once/ week

8

9.8

2

11.1

Twice/ week

6

7.3

1

5.6

Once/monthly

10

12.2

7

38.9

Twice/monthly

5

6.1

2

11.1

Najel fish

 

 

 

 

28.394a

0

Not prefer

64

78

6

33.3

Once/ day

4

4.9

0

0

Once/ week

6

7.3

2

11.1

Twice/ week

1

1.2

0

0

Once/monthly

5

6.1

7

38.9

Twice/monthly

2

2.4

3

16.7

Hamoor fish

 

 

 

 

11.212a

0.19

Not prefer

46

56.1

5

27.8

Once/ day

2

2.4

0

0

Twice/ day

2

2.4

0

0

Once/ week

5

6.1

2

11.1

Twice/ week

1

1.2

1

5.6

Three/ week

1

1.2

0

0

Once/monthly

25

30.5

10

55.6

Table 8.2: Frequency distribution of subjects according to consumption of purine diets.

 

NU (n=82)

HP (n=18)

X2

p value

No.

%

No.

%

Mussel

       

11.738a

0.019

Not prefer

71

86.6

14

77.8

Once/day

5

6.1

0

0

Twice /day

3

3.7

0

0

Once/monthly

3

3.6

4

22.2

Goats - Sheep

       

18.932a

0.026

Not prefer

15

18.3

1

5.6

Once/day

16

19.5

0

0

Once/week

7

8.5

4

22.2

Twice/ week

10

12.2

4

22.2

Once/monthly

34

41.3

9

50.1

Camel meat

       

22.440a

0.001

Not prefer

61

74.4

5

27.8

Once per week

2

2.4

0

0

Twice per week

1

1.2

1

5.6

Once monthly

18

21.9

12

66.7

Liver

       

18.842a

0.027

Not prefer

38

46.3

2

11.1

Once/ day

7

8.5

0

0

Once /week

14

17.1

3

16.7

Twice/ week

8

9.7

3

16.7

Once /monthly

15

18.4

10

55.6

HP= Hyperuricemic Patients;  NU= Normouricemia;   a : X² Chi-Square

Correlation Coefficients between some Social Variables and Purine Diets

Table 9.1 showed the correlation coefficients between hyperuricemia, some social variables, and body composition for studied subjects. The results revealed that there was a highly significant positive correlation (P<0.01) between hyperuricemia and each of age, waist, and visceral fat, in the same time. There was a significant positive correlation (P<0.05) between it and both weight and BMI. On the other hand, correlation coefficients between hyperuricemia and purine diet are shown. In table 9.2 a positive highly significant correlation (p<0.01) was reported between hyperuricemia and consumption of camel meat, fish, salmon, liver, lentil and beans. Meanwhile a positive significant correlation (p<0.05) was reported between it and consumption of sardines and mussel.

Table 9.1: Correlation coefficients between hyperuricemia and other variables for studied subjects.

 

Hyper uricemia

Age

Education

family size

Total income

Ht

wc

wt

BMI

Body fat

Muscle percent

Age

.279**

                   

Education

-.174-

-.588**

                 

Family size

-.034-

-.026-

-.123-

               

Total Income

0.147

0.052

.319**

-.351**

             

Ht

0.084

0.144

-.172-

-.028-

0.067

           

Wc

.300**

.249*

-.155-

-.128-

.257**

.333**

         

Wt

.215*

.200*

-.206*

-.035-

0.141

.533**

.713**

       

BMI

.229*

0.191

-.165-

-.060-

0.171

.212*

.704**

.937**

     

Body fat

0.012

-.149-

0.156

-.106-

0.131

-.318**

.331**

.217*

.371**

   

Muscle %

0.133

0.051

-.057-

0.096

0.002

.416**

0.085

0.145

0.009

-.424**

 

Visceral fat

.428**

0.127

-.075-

-.156-

.220*

.251*

.660**

.700**

.708**

.478**

-.012-

**: Correlation is significant at the 0.01 level (2-tailed), *: Correlation is significant at the 0.05 level (2-tailed), Wt.= weight   wc = waist circumferences,   Ht.= height

Table 9.2: Correlation coefficients between hyperuricemia and purine diet.

 

Hyperuricemia

Camel meat

Liver

Sardines

Fish

Salmon

Tuna

Mussel

Lentil

Camel

.384**

               

Liver

.355**

.340**

             

Sardines

.205*

0.048

-.028-

           

Fish

.284**

.427**

0.163

-.047-

         

Salmon

.483**

.467**

.364**

-.011-

.676**

       

Tuna

.252*

.300**

.427**

.201*

.326**

.601**

     

Mussel

.250*

.252*

0.046

0.065

.401**

.513**

.312**

   

Lentil

.295**

.209*

-.078-

-.328**

.265**

.299**

0.18

0.13

 

Beans

.276**

0.167

0.124

-.342**

.231*

.289**

0.135

0.134

.619**

 

Discussion

The present study reveals that the female counterparts are protected from hyperuricemia and it is in accordance with the findings of many previous studies from different countries such as the prevalence of hyperuricemia in China [29]. The higher average age of hyperuricemic subjects compared to normal subjects in our study shows that aging is a key factor for higher risk and hyperuricemia, that is similar as that of Al-Arfaj AS (2001) study in Riyadh-KSA though the mean age for the hyperuricemic respondents in Al-Arfaj AS (2001) study was higher for men and women and the difference in gender age was negligible [13].

Elevated SUA due to absence of awareness in food habits and life style related to lower education attainment was an interesting investigation in our project, though further work is required for confirming the post-graduate degree holders suffering from elevated SUA than normal subjects. However, that might had been due to higher income associated with higher sea food and meat consumption. Furthermore, the consumption of high purine-diet in the daily food habit is not accessible to all because of higher price. Hence, an indirect indicator of food pattern and consumption type and level could be referred to family size and income. When the total family income is higher, purine-rich foods can be consumed conveniently. This is as described by Villegas R, et al. (2010) for middle aged men of urban China [30]. The symptoms of gout like joint pain and fingers or toe tenderness but without any cases of gout in our work most probably due to higher consumption of rich purine diet is evident in other studies [13,31].

Although, some but not all studies have reported inverse associations between uric acid and physical activity [32,33], yet, exercise may decrease uric acid excretion and accelerate purine degradation [34]. In contrast, in the current study lower physical activity level might also had played part in this problem. It is not surprising to find that the physical activity level of the HP was much lower than the normal counterparts. Even though in previous studies there was no difference observed between the two groups [30]. This study could be referred to that as most of them suffered from the disturbing symptoms that hindered their movements.

Comparing our study with the study of Al-Arfaj AS (2001) [13] conducted in Riyadh, our results varied much for SUA, and creatinine probably as the sample size in our study was too small in comparison with the samples used by Al-Arfaj AS (2001), though higher SUA levels similar to our results were also obtained in Indonesia and Japan [35,36].

In the study in Riyadh [13], it was indicated that the consumption of purine-rich seafood among the people of Riyadh was rare, which was not the case in our study in Makkah, where we found that purine-rich seafood consumption was higher to those with normal SUA, and this difference was more or less due to the proximity of Makkah to the Red Sea. This might explain the higher SUA found in the current study for the HP patients where they consumed some types of fish collectively 1-2 times per week in about 16% of them. On the other hand, we found that the consumption of sheep meat, camel meat, liver and chicken was similar between our study and Al-Arfaj AS (2001) study. However, the HP patients consumed collectively more frequently all these rich purine-food items. This also was emphasized by the result of correlations between the food frequency (FFQ) and HP where in addition to these items mentioned above. A positive correlation was found between consumption of lentil and beans with HP. This might be due to the dietary pattern of the locals in Makkah where the consumption of these food items in breakfast meals in daily basis was maintained for generations and changing these food intake habits proved to be difficult even if the patient suffered from food related disease such as hyperuricemia and keeping to consume larger amount of meat, fish and beans.

Some of the parameters of BMI, weight and waist circumference (WC) associated with serum uric acid elevation we studied provided similar information as previously by the reports of Nicholls A, et al. (1972) [37], Bonora E, et al. (1996) [33], Nakanishi N, et al. (1999) [32], Al-Arfaj AS (2001) [13] and Saleh SA, et al. (2009) [38].

The main limitation of the present report is that it is a cross-sectional design, which prevented us from making any causal inferences based on our results [39]. Another limitation of the study is that we did not have information on other factors that might be related to the prevalence of psoriasis, metabolic syndrome, or family history of gout or hyperuricemia, and the fact that we faced considerable difficulty in meeting patients with hyperuricemia because of the lack of cooperation from most of the hospitals we visited [40-44]. Another reason concerning less number of female subjects in our study was due to religious and socio-cultural traditions. Therefore, we recommended for a more comprehensive study in the future with large sample size of hyperuricemic and gout patients with the inclusion of female subjects of various age groups as more as possible in the Kingdom of Saudi Arabia. The future group of researchers might include the female researchers, female clinicians and female technicians who can help in collecting history, blood sampling, physiological studies and management measures for the female patients with hyperuricemia as well.

Conclusion and Recommendation

All hyperuricemic subjects (18% of total studied subjects) were found to be male and the suspected cause was purine-rich diets and decreased activity and educational level, hyperuricemia associated with increase of visceral fat level. Therefore, nutrition education is recommended to improving nutrition and health status to protect from hyperuricemia. In the future more research are needed to assess the association between obesity, body composition with the prevalence of hyperuricemia.

Limitations

The limitation in this study may be related to small sample size especially female subjects.

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