bmj open · for peer review only 2 abstract background: to assess the prevalence and risk factors...

For peer review only

A community based survey for different abnormal glucose

metabolism among pregnant women in a random household study (SAUDI-DM).

Journal: BMJ Open

Manuscript ID: bmjopen-2014-005906

Article Type: Research

Date Submitted by the Author: 12-Jun-2014

Complete List of Authors: Al-Rubeaan, Khalid; King Saud University, University Diabetes Center, Collage of medicine, Youssef, Amira; King Saud University, University Diabetes Center, Collage of medicine, Al-Sharqawi, Ahmad; King Saud University, Biostatistics department, Strategic center for diabetes research Siddiqui, Khalid; King Saud University, Biochemistry department, Strategic center for diabetes research Ahmad, Najlaa; King Saud University, Biostatistics department, Strategic

center for diabetes research

<b>Primary Subject Heading</b>:

Diabetes and endocrinology

Secondary Subject Heading: Epidemiology

Keywords: DIABETES & ENDOCRINOLOGY, Diabetes in pregnancy < DIABETES & ENDOCRINOLOGY, General diabetes < DIABETES & ENDOCRINOLOGY

For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml

BMJ Open on M

ay 18, 2021 by guest. Protected by copyright.

http://bmjopen.bm

j.com/

BM

J Open: first published as 10.1136/bm

jopen-2014-005906 on 19 August 2014. D

ownloaded from

http://bmjopen.bmj.com/


1

A community based survey for different abnormal glucose metabolism among pregnant

women in a random household study (SAUDI-DM).

Khalid Al-Rubeaan1*, Amira M Youssef

1, Ahmad H Al-Sharqawi

2, Khalid Siddiqui

3 Najlaa A

Ahmad2

1University Diabetes Center, Collage of medicine, King Saud University, Saudi Arabia.

2Biostatistics department, Strategic center for diabetes research, King Saud University, Saudi

Arabia.

3Biochemistry department, Strategic center for diabetes research, King Saud University, Saudi

Arabia.

*Corresponding Author:

Dr. Khalid Al-Rubeaan, MD, FRCP(C)

University Diabetes Center, King Saud University

P.O. Box 18397, Riyadh 11415

Saudi Arabia.

Phone:+966112825402

Fax: +966114775696

E-mail: [email protected]

Word count: 2711 words

Keywords: Community based, abnormal glucose metabolism, gestational diabetes mellitus,

SAUDI-DM

Page 1 of 26


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on May 18, 2021 by guest. P

rotected by copyright.http://bm

jopen.bmj.com

/B

MJ O

pen: first published as 10.1136/bmjopen-2014-005906 on 19 A

ugust 2014. Dow

nloaded from



2

Abstract

Background: To assess the prevalence and risk factors of gestational diabetes mellitus (GDM)

in a society known to have a high prevalence of abnormal glucose metabolism.

Methods: Among 13,627 women in the childbearing age, 549 women were found to be

pregnant, out of which 43 (7.8%) were women with known diabetes. Women without diabetes

were subjected for fasting plasma glucose (FPG) to identify GDM cases using the International

Association of Diabetes and Pregnancy Study Group (IAPSG) criteria.

Results: The overall GDM prevalence was 36.6%, categorized into 32.4% new cases and 4.2%

known cases. Another 3.6% had preconception type 1 or type 2 diabetes. GDM cases were older

and had significantly higher body mass index (BMI), in addition to higher rate of macrocosmic

baby and history of GDM. Monthly income, educational level, living in urban areas and smoking

were not found to be significantly different between normal and GDM cases. The most important

and significant risk factors for GDM were past history of GDM, macrosomic baby, obesity and

age >30 years. However, hypertension, low HDL, family history of diabetes and increased

triglycerides did not show any significant effect on GDM prevalence in this cohort.

Conclusions: This society is facing a real burden of abnormal glucose metabolism during

pregnancy, where almost half of the pregnant women are subjected for its maternal and neonatal

complications. Early screening of pregnant women, especially those at a high risk for GDM is

mandatory to identify and manage those cases.

Page 2 of 26


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



3

Strengths and limitations of this study

� Our study is a community household based study seeking for cases with

abnormal glucose metabolism among pregnant women in a country ranked the

seventh worldwide in term of diabetes prevalence.

� The new IAPSG criteria was used to screen for GDM cases at a community

setup rather than hospital based, especially when there is a limited number of

studies that have used this criteria.

� The studied cohort is unique because of its quick and severe socioeconomic

transition that gives a good setup to assess for different modifiable and non-

modifiable risk factors for GDM and to compare this with other ethnicities.

� One of the limitations of this study was the use of FPG which was found to

have lower sensitivity when compared with the oral glucose tolerance test

(OGTT), although it has been recently recommended by the ADA for GDM

screening.

Page 3 of 26


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



4

INTRODUCTION

Ever since gestational diabetes mellitus (GDM) was first recognized in 1967,1 it has been the

primary focus of interest for both clinicians and scientists, due to its increased risk of fetal

macrosomia, neonatal hypoglycemia, jaundice, polycythemia, hypocalcemia, and also in its

increased frequency of maternal hypertensive disorders with the need for cesarean deliveries.2

GDM, an asymptomatic disorder, is defined as glucose intolerance with the onset or its first

recognition during pregnancy. It is the most common metabolic disorder accounting for almost

90% of all diabetes cases during pregnancy, and has been found to be present in approximately

7% of all pregnant women.3 Moreover, mothers with the history of GDM are at a greater risk of

developing type 1 diabetes (5-10%)4or type 2 diabetes (over 70%),

5 while their offspring are

more likely to be obese or suffer from diabetes in their latter life.6 The global prevalence of

GDM ranges between 1%-14% depending on the population studied and used diagnostic tests.3

The prevalence estimates for GDM in 2007 were the following; 11.6% for Asian Indians, 10%

for Vietnamese, 9.8% for Pacific Islanders and 7.9% for East Asians and while it ranged from

4.0%-6.0% for Hispanics, it was found to be 4.0% in non-Hispanic African Americans and 4.7%

in non-Hispanic whites.7

Even though a hospital based study among Saudi women using the National Diabetes Data

Group (NDDG) criteria8 showed the GDM prevalence to be at 12.5%, no community based study

have been undertaken to look into the extent of this medical problem in the Kingdom of Saudi

Arabia, even after knowing that the risk factors of GDM are highly prevalent in this society.

Page 4 of 26


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



5

During the childbearing period, Women are subjected to increased risk of abnormal glucose

metabolism with the progression of age and other general risk factors including obesity and

physical inactivity. Several reproductive risk factors namely parity, the presence of polycystic

ovary, the history of GDM, macrosomic baby >4.5 kg, and the use of contraceptive drugs have

been found to significantly increase the risk of abnormal glucose metabolism in this group of

women.9 10

Based on the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study results, the

International Association of Diabetes and Pregnancy Study Group (IADPSG) recommended

lowering the fasting plasma glucose threshold for the GDM diagnosis to be ≥92 mg/dl (5.1

mmol/l)11

which was also adopted by the American Diabetes Association (ADA) in 2011.12

This

new diagnostic criteria, as expected, resulted in a significant increase in GDM prevalence in

many countriea,13-15

wherein it had increased from 10.3% to 30.1% in Mexicans15

whilst

reaching up to 30.5% and 37.7% in Norway and United Arab of Emirates.16 17

This present study, being community based, provided a great opportunity for the assessment of

abnormal glucose metabolism prevalence among pregnant Saudi women. The prevalence of

GDM and its different risk factors were also investigated using the new IADPSG diagnostic

criteria.

Page 5 of 26


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



6

METHODS

The Saudi Abnormal Glucose Metabolism and Diabetes Impact Study (SAUDI-DM study) is a

household random population based cross-sectional study conducted at a national level in the

Kingdom of Saudi Arabia during the period from 2007 to 2009. After adjusting for age, gender,

and geographical distribution according to the 2007 census, a total of 53,370 participants were

used for the assessment of different states of abnormal glucose metabolism. Out of those

participants, 13,627 participants were found to be women in their childbearing age (18-49 years)

as shown in figure (1) and within this childbearing women participants, 549 participants were

found to be pregnant in different trimesters confirmed by their pregnancy tests, who represented

4.0% of the total women participants' cohort. All the SAUDI-DM participants were consented

and subjected for interview. Clinical assessment of the participants, which also included

pregnant women, wherein their clinical data including age, family history of diabetes, history of

GDM and macrosomic baby, educational level, monthly income, smoking status, residency area

were all collected by specially trained primary care physicians from the thirteen official regions.

The anthropometric parameters including weight, height, body mass index (BMI), waist to hip

ratio and blood pressure were all measured by trained nurses.

Pregnant women who were not known to be suffering from diabetes were tested for FPG after

overnight fasting of at least 10 hours and three days of usual activity and diet. Using the

IADPSG criteria, pregnant women were diagnosed with GDM if FPG is ≥92 mg/dl (5.1 mmol/l).

All the blood samples collected using vacuum tubes containing sodium fluoride were transported

to the strategic center for diabetes research laboratory in Riyadh. Blood glucose assessment was

performed using the glucose oxidase-paraoxidase methodology, serum cholesterol assessment

Page 6 of 26


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



7

was performed using the cholesterol oxidase-paraoxidase methodology, and HDL, LDL and

triglyceride assessments were performed using the direct glycerokinase oxidase-paraoxidase

methodology as provided by Mindray (B5-200) chemistry analyzer reagent.

This study has been approved by the Institutional Review Board (IRB) at the College of

medicine, King Saud University.

Statistical analysis

All data were analyzed using software package for social science (SPSS) version 17. Descriptive

analyses and frequency tables were performed using this program for all variables. Chi square

test (χ2) was used for categorical variables, while t-test was used for continuous variables. Odds

ratio (OR) with 95% confidence interval (CI) were used for assessing the risk factor using

univariate analysis. P-value of <0.05 was used as a level of significance.

RESULTS

Out of the selected cohort containing Saudi pregnant women, 43 participants were women with

known diabetes (7.8%), in which, 4 participants (9.3%) were found to be patients with type

1diabetes, 16 participants (37.2%) were found to be patients with type 2 diabetes, and 23

participants (53.5%) were found to be with GDM. And among the remaining 506 women not

known to be suffering from diabetes, 178 (32.4%) were found to be new GDM cases.

When comparing the clinical characteristic of GDM cases with the clinical characteristic of

pregnant women without diabetes, the GDM cases were found to be significantly older (33.26 ±

7.63 years) and more obese presented by their body weight (73.94 ± 14.83 kg) and BMI

(30.27±5.57 kg/m2). There was no significant difference between the two groups in their mean

Page 7 of 26


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



8

height and waist to hip ratio. The GDM cases had a significantly higher mean systolic blood

pressure (SBP) at 114.02 ± 11.61 mmHg and a low diastolic blood pressure (DBP) at 72.71 ±

8.81 mmHg. And as expected, the mean FPG was found to be significantly higher in GDM cases

at 6.55 (±2.21) mmol/l when compared with the mean FPG of the normal women at 4.21 ± 0.65

mmol/l. Lipids showed no significant difference between the two groups with the exception of

mean HDL which was found to be lower in the GDM cases at 1.07 ± 0.32 mmol/l when

compared with the mean HDL for normal women at1.15 ± 0.32 mmol/l. Percentage of women

with positive family history of diabetes was not found to be significantly different between the

GDM cases and normal women, whilst it was found to be significantly higher for the history of

GDM and macrocosmic baby >4.5kg among GDM cases at 12.49% versus 3.66% and 11.44%

versus 3.66% respectively when compared with the normal women. Educational level showed no

significant difference in percentage between the two groups, whilst the percentage of women

with monthly income <4000 SR was found to be significantly higher among normal women.

Smoking or living in urban areas also showed no significant difference between the two groups.

Figure (2) demonstrates the prevalence of different types of abnormal glucose metabolism in the

selected cohort of the Saudi pregnant women aged 18 to 49 years. Type 1 diabetes was found in

0.7% of the total sample, while type 2 was reported in 2.9% of the total sample. 4.2% of the

total sample were known cases of GDM and 32.4% of the total sample were newly discovered

GDM cases. The overall prevalence of abnormal glucose metabolism showed an age specific

increased with a significant difference from 31.8% to 43.9% and 60.3% in the age groups 18-29,

30-39, and 40-49 years respectively. The prevalence of newly discovered GDM cases showed an

increase from 28.0% to 35.4% and 39.7% in the three groups respectively. This was also

observed in the prevalence of known GDM cases from 1.9% in the age group 18-29 years to

Page 8 of 26


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



9

4.7% in the age group 30-39 years and peaking at 11.0% in the age group 40-49 years. The

prevalence of known patients with type 1 and type 2 diabetes was 0.8% and 1.1% for the age

group 18-29 years, 0.5% and 3.3% for the age group 30-39 years and 1.4% and 8.2% for the age

group 40-49 years. The ratio of known to unknown GDM cases was calculated at 1:15, 1:8, and

1:4 for the age groups 18-29, 30-39, and 40-49 years respectively.

Figure (3) shows the odds ratio (OR) with the 95% CI for GDM using univariate analysis, where

the past history of GDM was found to be the highly significant risk factor with OR 3.91 (1.93-

7.95), p value <0.0001. It was followed by the history of macrosomic baby weighing >4.5kg that

had OR (95% CI) of 3.40 (1.65-7.00) p value<0.0001. Obesity was the third significant risk

factor with OR (95% CI) 2.50 (1.35-4.60) followed by age >30 years, wherein the OR (95% CI)

was 2.00 (1.26-3.18), both with a significant p value =0.003. Other risk factors which include

hypertension, low HDL, and family history of diabetes, showed a non-significant increased risk

for GDM presented by OR (95% CI) [1.50 (0.47-4.75), 1.34 (0.76-2.36), and 1.15 (0.81-1.63)]

respectively. Lastly, the high triglycerides showed no significant risk for GDM.

DISCUSSION

This study investigates the occurrence of abnormal glucose metabolism during pregnancy using a

community-based rather than a traditional hospital based set up. A study with this set up provides

a better image of the extent of this medical problem, especially when using the new diagnostic

criteria to identify GDM cases at a community level. This study shows the importance of

subjecting women for GDM screening, particularly when known that only 4.2% of pregnant

women were picked up by the health system (known GDM cases). The current survey picked up

another 32.4% of GDM cases, this would mean that, only one out of each nine GDM cases were

Page 9 of 26


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



10

detected by the antenatal screening which also clearly demonstrates that there are many

undiagnosed GDM cases at the community level. Another crucial finding of this study was that,

the overall GDM prevalence to be at 36.6%, three folds higher than what was reported earlier,8

but similar to the findings of the studies from other ethnicities using this criteria,15

which is most

likely due to the lower cut off value of the new criteria used and the high prevalence of

overweight and obesity reflected by high mean BMI in the studied cohort. This may be coupled

with the fact that, such a community based study, would identify more GDM cases, especially in

a society where diabetes prevalence is found to be increasing over the past three decades.18

The

patients with preexisting type 1 and type 2 diabetes in this study represent 3.6% of all

pregnancies, which was three times more than what had been reported in north America19

and is

most likely a reflection of the high prevalence of abnormal glucose metabolism in our society.

This studied cohort showed that the mean age for GDM Saudi pregnant women was higher than

what had been earlier reported in other studies involving the Chinese and Indian populations20 21

,

which could be the result of cultural factors that encourage women to get pregnant even at an

older age, in addition to high parity.22

This may also have contributed to the higher prevalence of

GDM in this cohort with the mean age of GDM cases found to be significantly higher than the

normal cases. Another explanation for the higher prevalence of GDM in our cohort is provided

by the presence of high mean BMI when compared with the studies involving Caucasian and

Asian populations.23 24

More than 50% of GDM cases had family history of diabetes which was

not significantly different from the normal cases and this could be explained by the high

prevalence of diabetes and high consanguinity rates in our society.25

As expected and seen from

other studies,21 26

the history of GDM and macrosomic baby was found to be higher in GDM

cases than normal pregnant women, wherein it was almost four times higher in our GDM cohort.

Page 10 of 26


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



11

Neither education nor monthly income showed any significant increase in GDM cases, with the

exception of monthly income less than 4000 SR which was found to be associated with a

decreased percentage of GDM cases. Surprisingly, both smoking and living in urban areas

showed no significant difference between the two groups, which could be evidently explained on

the basis of cultural effect, wherein smoking is not culturally acceptable for women in Saudi

Arabia and on the basis of high socioeconomic status that has eliminated the difference between

urban and rural areas in the kingdom.

In consistent with many studies27

and as expected, the prevalence of preconception diabetes,

known GDM and newly discovered GDM cases showed significant increase with age, peaking at

age more than 40 years. This could be explained by the effect of both age progression and

muliparity in our society.23

The ratio of the known to newly discovered GDM cases decreased

with the progression of age which could be explained by the fact that, older women were

subjected for screening more than the younger women as also observed by other researchers.27

This study also shows that, past history of GDM increased the risk for GDM significantly, which

was found to be much lower than what had been observed in the studies involving Persian,

Indian, and Caucasian populations,21 26

which could be the effect of the nature of the study

sample with our sample being a community based and the rest being hospital based. Past

history of macrosomia was the second risk factor found to increase GDM cases in the Saudi

pregnant women closer to what had been reported in other ethnicities.21 28

Both obesity and being

more than 30 years of age, known to be important risk factors for diabetes in general,

significantly increased the risk for GDM as reported earlier in many ethnicities.20 23

Hypertension, low HDL, family history of diabetes and high triglycerides, were all found to be

Page 11 of 26


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



12

non-significant risk factors for GDM in this study. Hypertension and low HDL increased the risk

for developing GDM in this society to a significant level similar to the Caucasians,23

whilst

positive family history of diabetes had a minimal non-significant increase, which could have

resulted from high consanguinity rates and family history of diabetes in general population.25

Although high triglycerides was known to be a risk factor for GDM,23

this study showed no

effect of this risk factor, which could be due to the high mean triglycerides in both normal and

GDM cases.

This study derives strength from being a community based household survey representing a

normal distribution cohort that was randomly selected. One of the limitations of this study was

the use of FPG which was found to have lower sensitivity when compared with the oral glucose

tolerance test (OGTT),29

although it has been recently recommended by the ADA for GDM

screening.12

Another limitation of this study was the exclusion of pregnancy by history alone,

which may have excluded some pregnant women in their early pregnancy in addition to the lack

of obstetrical and diet history. Although this study involved special ethnicity, the results could be

generalized at an international level, especially when looking at risk factors.

CONCLUSIONS

Around 40% of Saudi pregnant women suffer from either preexisting diabetes or GDM

secondary to the increased prevalence of its risk factors in this society. A limited number of

GDM cases are picked up by the health system indicating the weak antenatal screening and

thereby, warranting an extensive public and medical staff education. The GDM risk factors that

are significant in this society including; past history of GDM and macrosomic baby, obesity and

Page 12 of 26


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



13

age more than 30 years that should be considered for early screening of pregnant women. Public

awareness programs for reducing modifiable risk factors like obesity would contribute in

decreasing the prevalence of GDM and prenatal mortality.

Page 13 of 26


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



14

List of abbreviations

ADA American Diabetes Association

DBP Diastolic Blood Pressure

FPG Fasting Plasma Glucose

GDM Gestational Diabetes Mellitus

IADPSG International Association of Diabetes and Pregnancy Study Group

IFG Impaired fasting glucose

SAUDI-DM study Saudi Abnormal Glucose Metabolism and Diabetes Impact study

SR Saudi Riyals

SBP Systolic Blood Pressure

Collaborators

The authors would like to acknowledge the staff at the University Diabetes Center for and the

staff of the primary care centers from Ministry of Health their collaboration in conducting to the

study.

Contributors

All the authors have contributed towards the conduct of the study, preparation of the manuscript.

"A.K. designed the study, wrote the manuscript, designed figures and interpreted data, and

approved the final version to be published. Y.A. researched data, wrote the manuscript, and

critically revised the article. A.A. analyzed data, developed figures, interpreted data, and

approved the final version to be published. S.K. handled and analyzed blood samples, revised

Page 14 of 26


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



15

the article critically, and approved the final version to be published. A.N. researched data,

analyzed data, and approved the final version to be published.

Funding: This study was funded by the University Diabetes Center at King Saud University,

Ministry of Health and the Tawuniya Company for health insurance.

Competing interests

The authors declare that they have no competing interests.

Data sharing statement:

No additional data available

Page 15 of 26


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



16

References

1. O’Sullivan JB, Mahan CM. Criteria for the oral glucose tolerance test in pregnancy.

Diabetes 1964; 13: 278-285.

2. American Diabetes Association. Gestationl Diabetes Mellitus. Diabetes Care 2004;

27(suppl 1): s88-s90.

3. Tracy L. Setji, Ann J. Brown, Mark N. Feinglos. Gestational Diabetes Mellitus. Clinical

Diabetes 2005; 23:17-24.

4. Damm P, Kuhl C, Buschard K, Jakobsen BK, Svejgaard A, Sodoyez-Goffaux F, et al.

Prevalence and predictive value of islet cell antibodies and insulin autoantibodies in

women with gestational diabetes. Diabet Med 1994; 11: 558-563.

5. Kim C, Newton KM, Knopp RH. Gestational diabetes and the incidence of type 2

diabetes: a systematic review. Diabetes Care 2002; 25: 1862-8.

6. Buchanan TA, Xiang AH, Page KA. Gestational diabetes mellitus: risks and

management during and after pregnancy. Nat Rev Endocrinol 2012; 8: 639-49.

7. Kim SY, England L, Sappenfield W, et al. Racial/ethnic differences in the percentage of

gestational diabetes mellitus cases attributable to overweight and obesity, Florida, 2004–

2007. Prev Chronic Dis 2012; 9: E88.

8. Ardawi MS, Nasrat HA, Jamal HS, et al. Screening for gestational diabetes mellitus in

pregnant females. Saudi Med J 2000; 21: 155-160.

9. Ben-Haroush A, Yogev Y, Hod H. Epidemiology of gestational diabetes mellitus and its

association with Type 2 diabetes. Diabet Med 2004; 21: 103-113.

10. Hedderson MM, Ferrara A, Williams MA, et al. Androgenicity of Progestins in

Hormonal Contraceptives and the Risk of Gestational Diabetes Mellitus. Diabetes Care

2007; 30: 1062-1068.

11. The HAPO Study cooperative research group, Metzger BE, Lowe LP, Dyer AR, et al.

Hyperglycemia and adverse pregnancy outcomes. N Engl J Med 2008; 358: 1991-2002.

12. American Diabetes Association: Diagnosis and Classification of Diabetes Mellitus.

Diabetes Care 2011; 34: S62-S69.

Page 16 of 26


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



17

13. Wei YM, Yang HX. Comparison of the diagnostic criteria for gestational diabetes

mellitus in china. Zonghua Fu chan Ke Za Zi 2011; 46: 578-591.

14. Moses RG, Morris GJ, Petocz, et al. The impact of potential new diagnostic criteria on

the prevalence of gestational diabetes mellitus in Australia. Med J Aust 2011; 194: 338-

340.

15. Reyes-Muñoz E, Parra A, Castillo-Mora A, et al. Effect of the new diagnostic criteria of

the International Associatio of Diabetes and Pregnanacy Study groups on the prevelance

of gestational diabetes mellitus in urban mexican women: A cross sectional Study.

Endocr Pract 2012; 18: 146-151.

16. Jenum AK1, Mørkrid K, Sletner L, et al. Impact of ethnicity on gestational diabetes

identified with the WHO and the modified International Association of Diabetes and

Pregnancy Study Groups criteria: a population-based cohort study. Eur J Endocrinol

2012; 166: 317-324.

17. Agarwal MM, Dhatt G S, Shah SM. Gestational Diabetes Mellitus Simplifying the

International Association of Diabetes and Pregnancy diagnostic algorithm using fasting

plasma glucose. Diabetes Care 2010; 33: 2018-2020.

18. Al-Nozha MM, Al-Maatouq MA, Al-Mazrou YY, et al. Diabetes mellitus in Saudi

Arabia. Saudi Med J 2004; 25: 1603-1610.

19. Lawrence JM, Contreras R, Chen W, et al. Trends in the Prevalence of Preexisting

Diabetes and Gestational Diabetes Mellitus Among a Racially/Ethnically Diverse

Population of Pregnant Women, 1999-2005. Diabetes Care 2008; 31: 899-904.

20. Yang H, Y. Wei Y, Gao X, et al. Risk factors for gestational diabetes mellitus in Chinese

women: a prospective study of 16286 pregnant women in China. Diabet Med 2009; 26:

1099-1104.

21. Soheilykhah S, Mogibian M, Rahimi-Saghand S, et al. Incidence of gestational diabetes

in pregnant women. Iranian Journal of Reproductive Medicine 2010; 8: 24-28.

22. Al Rowaily MA, Alsalem FA, Abolfotouh MA. Cesarean section in a high-parity

community in Saudi Arabia: clinical indications and obstetric outcomes. BMC Pregnancy

Childbirth 2014; 14: 92.

23. Gunderson EP1, Quesenberry CP Jr, Jacobs DR Jr, et al. Longitudinal Study of

Prepregnancy Cardiometabolic Risk Factors and Subsequent Risk of Gestational Diabetes

Mellitus. Am J Epidemiol 2010; 172: 1131-1143.

Page 17 of 26


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



18

24. Cheung NW, Wasmer G, Al-Ali J. Risk Factors for Gestational Diabetes Among Asian

Women. Diabetes Care 2001; 24: 955-956.

25. Al-Gazali L, Hamamy H, Al-Arrayad S. Genetic disorders in the Arab world. BMJ 2006;

333: 831-834.

26. Bhat M, Ramesha K N,

Sarma SP,

et al. Determinants of gestational diabetes mellitus: A

case control study in a district tertiary care hospital in south India. Int J Diabetes Dev

Ctries 2010; 30: 91-96.

27. Makgoba M, Savvidou MD, Steer PJ. An analysis of the interrelationship between

maternal age, body mass index and racial origin in the development of gestational

diabetes mellitus. BJOG 2012; 119: 276-82.

28. Cypryk K, Szymczak W, Czupryniak L, et al. Gestational diabetes mellitus-an analysis

of risk factors. Endokrynol Pol 2008; 59: 393-7.

29. Taylor R, Zimmet P: Limitation of fasting plasma glucose for the diagnosis of diabetes

mellitus. Diabetes Care 1981; 4: 556-558.

Page 18 of 26


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



19

Table (1): Baseline clinical and biochemical characteristics of the selected cohort, newly diagnosed GDM and normoglycemic

pregnant participants:

Normal (N=328) GDM (N=201) P value¥

Mean subject age in years (±SD) 29.63(±7.53) 33.26(±7.72) <0.0001

Mean weight in kgm (±SD) 67.11(±13.55) 73.94(±14.83) <0.0001

Mean height in cm (±SD) 154.98(±5.42) 156.37(±6.97) 0.057

Mean BMI=kgm/m2 (±SD) 27.97(±5.37) 30.27(±5.57) <0.0001

Mean waist /Hip Ratio (±SD) 0.89(±0.14) 0.87(±0.14) 0.176

Mean systolic blood pressure (±SD) 110.03(±10.84) 114.02(±11.61) 0.002

Mean diastolic blood pressure (±SD) 71.34(±8.32) 72.71(±8.81) 0.160

Mean fasting plasma glucose (±SD) 4.21(±0.65) 6.55(±2.21) <0.0001

Mean total cholesterol (±SD) 5.58(±1.29) 5.41(±1.32) 0.278

Mean HDL cholesterol (±SD) 1.15(±0.32) 1.07(±0.32) 0.025

Mean LDL cholesterol (±SD) 3.57(±1.05) 3.52(±1.16) 0.704

Mean triglycerides (±SD) 1.81(±0.94) 1.84(±0.95) 0.778

Number with family history of diabetes (%) 157(47.87) 103(51.24) 0.451

Number with history of gestational diabetes (%) 12(3.66) 26(12.94) <0.0001

Number with history of Macrosomia (%) 12(3.66) 23(11.44) <0.0001

Number of illiterate subjects (%) 74(22.56) 35(17.41) 0.155

Number with less than high school education (%) 113(34.45) 78(38.81) 0.311

Number with more than high school education (%) 141(42.99) 88(43.78) 0.858

Number with monthly income <4000 SR* (%) 153(46.65) 73(36.32) 0.020

Number with monthly income 4000-8000 SR* (%) 97(29.67) 69(34.33) 0.253

Number with monthly income >8000 SR* (%) 78(23.78) 59(29.35) 0.156

Number of smoking subjects (%) 4(1.22) 2(1.00) 0.811

Number of subjects living in urban areas† (%) 213(64.94) 135(67.16) 0.601

* Saudi Riyal (SR) is equivalent to 0.267 USD.

† According to the definition given by the Ministry of Municipal and Rural

Affairs. ¥ P value was calculated as difference between normal and GDM cases.

Page 19 of 26


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on May 18, 2021 by guest. Protected by copyright. http://bmjopen.bmj.com/ BMJ Open: first published as 10.1136/bmjopen-2014-005906 on 19 August 2014. Downloaded from



20

Figures Legends:

Figure (1): Sample selection of childbearing age pregnant women from of the SAUDI-

DM study cohort classified according to abnormal glucose metabolism status.

Figure (2): The prevalence of abnormal glucose metabolism in pregnant Saudi women

aged 18 to 49 years.

Figure (3): Odds Ratio (OR) for GDM risk factors among Saudi pregnant participants.

Page 20 of 26


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



Figure (1): Sample selection of childbearing age pregnant women from of the SAUDI-DM study cohort classified according to abnormal glucose metabolism status.

74x42mm (300 x 300 DPI)

Page 21 of 26


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



Figure (2): The prevalence of abnormal glucose metabolism in pregnant Saudi women aged 18 to 49 years. 67x56mm (300 x 300 DPI)

Page 22 of 26


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



Figure (3): Odds Ratio (OR) for GDM risk factors among Saudi pregnant participants. 53x45mm (300 x 300 DPI)

Page 23 of 26


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



1

STROBE Statement Checklist of items that should be included in reports of observational studies

Section/Topic Item

No Recommendation

Reported

on Page No

Title and abstract 1 (a) Indicate the study’s design with a commonly used term in the title or the abstract 2

(b) Provide in the abstract an informative and balanced summary of what was done and what was found 2

Introduction

Background/rationale 2 Explain the scientific background and rationale for the investigation being reported 3

Objectives 3 State specific objectives, including any prespecified hypotheses 4

Methods

Study design 4 Present key elements of study design early in the paper 5

Setting 5 Describe the setting, locations, and relevant dates, including periods of recruitment, exposure, follow-up, and data collection

5

Participants 6

(a) Cohort study—Give the eligibility criteria, and the sources and methods of selection of participants. Describe methods of

follow-up

Case-control study—Give the eligibility criteria, and the sources and methods of case ascertainment and control selection. Give the

rationale for the choice of cases and controls

Cross-sectional study—Give the eligibility criteria, and the sources and methods of selection of participants

5

(b) Cohort study—For matched studies, give matching criteria and number of exposed and unexposed

Case-control study—For matched studies, give matching criteria and the number of controls per case

Variables 7 Clearly define all outcomes, exposures, predictors, potential confounders, and effect modifiers. Give diagnostic criteria, if

applicable 5

Data sources/measurement 8* For each variable of interest, give sources of data and details of methods of assessment (measurement). Describe comparability of

assessment methods if there is more than one group 5

Bias 9 Describe any efforts to address potential sources of bias No bias

Study size 10 Explain how the study size was arrived at 5

Quantitative variables 11 Explain how quantitative variables were handled in the analyses. If applicable, describe which groupings were chosen and why 6

Statistical methods 12

(a) Describe all statistical methods, including those used to control for confounding 6

(b) Describe any methods used to examine subgroups and interactions 6

(c) Explain how missing data were addressed No missing

data

(d) Cohort study—If applicable, explain how loss to follow-up was addressed

Case-control study—If applicable, explain how matching of cases and controls was addressed

Cross-sectional study—If applicable, describe analytical methods taking account of sampling strategy

5

Page 24 of 26


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960




2

(e) Describe any sensitivity analyses None

Section/Topic Item

No Recommendation

Reported

on Page No

Results

Participants 13*

(a) Report numbers of individuals at each stage of study—eg numbers potentially eligible, examined for eligibility, confirmed

eligible, included in the study, completing follow-up, and analysed 5

(b) Give reasons for non-participation at each stage Figure 1

(c) Consider use of a flow diagram Figure 1

Descriptive data 14*

(a) Give characteristics of study participants (eg demographic, clinical, social) and information on exposures and potential

confounders Table 1

(b) Indicate number of participants with missing data for each variable of interest No missing

data

(c) Cohort study—Summarise follow-up time (eg, average and total amount)

Outcome data 15*

Cohort study—Report numbers of outcome events or summary measures over time

Case-control study—Report numbers in each exposure category, or summary measures of exposure

Cross-sectional study—Report numbers of outcome events or summary measures Figure 2

Main results 16

(a) Give unadjusted estimates and, if applicable, confounder-adjusted estimates and their precision (eg, 95% confidence interval).

Make clear which confounders were adjusted for and why they were included Table 1

(b) Report category boundaries when continuous variables were categorized Table1

(c) If relevant, consider translating estimates of relative risk into absolute risk for a meaningful time period Not

applicable

Other analyses 17 Report other analyses done—eg analyses of subgroups and interactions, and sensitivity analyses None

Discussion

Key results 18 Summarise key results with reference to study objectives 8-9

Limitations 19 Discuss limitations of the study, taking into account sources of potential bias or imprecision. Discuss both direction and magnitude

of any potential bias 11

Interpretation 20 Give a cautious overall interpretation of results considering objectives, limitations, multiplicity of analyses, results from similar

studies, and other relevant evidence 8-13

Generalisability 21 Discuss the generalisability (external validity) of the study results 11

Other Information

Funding 22 Give the source of funding and the role of the funders for the present study and, if applicable, for the original study on which the

present article is based 14

*Give information separately for cases and controls in case-control studies and, if applicable, for exposed and unexposed groups in cohort and cross-sectional studies.

Page 25 of 26


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960




3

Note: An Explanation and Elaboration article discusses each checklist item and gives methodological background and published examples of transparent reporting. The STROBE checklist is

best used in conjunction with this article (freely available on the Web sites of PLoS Medicine at http://www.plosmedicine.org/, Annals of Internal Medicine at http://www.annals.org/, and

Epidemiology at http://www.epidem.com/). Information on the STROBE Initiative is available at www.strobe-statement.org.

Page 26 of 26


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960




A community based survey for different abnormal glucose metabolism among pregnant women in a random household

study (SAUDI-DM).

Journal: BMJ Open

Manuscript ID: bmjopen-2014-005906.R1

Article Type: Research

Date Submitted by the Author: 16-Jul-2014

Complete List of Authors: Al-Rubeaan, Khalid; King Saud University, University Diabetes Center, Collage of medicine, Mana, Hamad; Ministry of Health,

Khoja, Tawfik; Gulf Corporation Council, Youssef, Amira; King Saud University, University Diabetes Center, Collage of medicine, Al-Sharqawi, Ahmad; King Saud University, Biostatistics department, Strategic center for diabetes research Siddiqui, Khalid; King Saud University, Biochemistry department, Strategic center for diabetes research Ahmad, Najlaa; King Saud University, Biostatistics department, Strategic center for diabetes research

<b>Primary Subject Heading</b>:

Diabetes and endocrinology

Secondary Subject Heading: Epidemiology, Diabetes and endocrinology

Keywords: DIABETES & ENDOCRINOLOGY, Diabetes in pregnancy < DIABETES & ENDOCRINOLOGY, General diabetes < DIABETES & ENDOCRINOLOGY


BMJ Open on M

ay 18, 2021 by guest. Protected by copyright.

http://bmjopen.bm

j.com/

BM

J Open: first published as 10.1136/bm

jopen-2014-005906 on 19 August 2014. D

ownloaded from



1



Khalid Al-Rubeaan1*, Hamad A Mana

2, Tawfik A Khoja

3, Amira M Youssef

1, Ahmad H Al-

Sharqawi4, Khalid Siddiqui

5 Najlaa A Ahmad4

1University Diabetes Center, College of Medicine, King Saud University, Saudi Arabia.

2Ministry of Health, Riyadh, Kingdom of Saudi Arabia

3Gulf Corporation Council, Riyadh, Kingdom of Saudi Arabia


Arabia.


Arabia.




P.O. Box 18397, Riyadh 11415

Saudi Arabia.

Phone:+966112825402

Fax: +966114775696




SAUDI-DM

Page 1 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



2

Abstract

Objective: To assess the prevalence and risk factors of gestational diabetes mellitus (GDM) in a

population known to have a high prevalence of abnormal glucose metabolism.

Methods: A household random population based cross-sectional study of 13,627 women in the

childbearing age, were subjected for fasting plasma glucose (FPG) if they were not known to be

diagnosed with any type of diabetes before. GDM cases were diagnosed using the International














Page 2 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



3








� The studied cohort is unique because of its swift socioeconomic transition

observed in the Saudi society that gives a good setup to assess for different

modifiable and non-modifiable risk factors for GDM and to compare this with

other ethnicities.




screening.

Page 3 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



4

INTRODUCTION









developing type 1 diabetes (5-10%)4

or type 2 diabetes (over 70%),5 while their offspring are











Page 4 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



5






women.9,10




mmol/l)11


This




whilst

reaching up to 30.5% and 37.7% in Norway and United Arab of Emirates.16,17

The aim of the present study was to investigate the prevalence of different abnormal glucose

conditions among pregnant women in the Kingdome of Saudi Arabia. The prevalence of GDM

and its different risk factors were also investigated using the new IADPSG diagnostic criteria.

Page 5 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



6

METHODS









4.0% of the total women participants' cohort. All the SAUDI-DM participants gave their consent

to participate and were subjected for interview. Clinical assessment of the participants, which

also included pregnant women, wherein their clinical data including age, family history of

diabetes, history of GDM and macrosomic baby, educational level, monthly income, smoking

status, residency area were all collected by specially trained primary care physicians from the

thirteen official regions. The anthropometric parameters including weight, height, body mass

index (BMI), waist to hip ratio and blood pressure were all measured by trained nurses.

Pregnant women who were not known to be suffering from diabetes were tested for FPG and

Lipids profile after overnight fasting of at least 10 hours and three days of usual activity and diet.

Using the IADPSG criteria, pregnant women were diagnosed with GDM if FPG is ≥92 mg/dl

(5.1 mmol/l).



Page 6 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



7




methodology as provided by Mindray (B5BS-200) chemistry analyzer reagent (China).


Medicine, King Saud University.







RESULTS

Table (1) describes the characteristics of the study population. Out of the selected cohort

containing Saudi pregnant women, 43 participants were women with known diabetes (7.8%), in

which, 4 participants (9.3%) were found to be patients with type 1diabetes, 16 participants

(37.2%) were found to be patients with type 2 diabetes, and 23 participants (53.5%) were found

to be with GDM. And among the remaining 506 women not known to be suffering from

diabetes, 178 (32.4%) were found to be new GDM cases. The studied cohort was divided into

three age groups, the first group is between 18 to 29 years of age with a total number of 264

(48.1%). The second age group is between 30 to 39 years totaling to 212 (38.6%), while the third

group is between 40 to 49 years with a total number of 73 (13.3%).

Page 7 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



8



7.63 years), ( p<0.0001) and more obese presented by their body weight (73.94 ± 14.83 kg) and

BMI (30.27±5.57 kg/m2) (p<0.0001). There was no significant difference between the two

groups in their mean height and waist to hip ratio (p=0.176). The GDM cases had a significantly

higher mean systolic blood pressure (SBP) at 114.02 ± 11.61 mmHg (p=0.002) and a low

diastolic blood pressure (DBP) at 72.71 ± 8.81 mmHg (p=0.160). And as expected, the mean

FPG was found to be significantly higher in GDM cases at 6.55 (±2.21) mmol/l when compared

with the mean FPG of the normal women at 4.21 ± 0.65 mmol/l (p<0.0001). Lipids showed no

significant difference between the two groups with the exception of mean HDL which was found

to be lower in the GDM cases at 1.07 ± 0.32 mmol/l when compared with the mean HDL for

normal women at1.15 ± 0.32 mmol/l (p=0.025). Percentage of women with positive family

history of diabetes was not found to be significantly different between the GDM cases and

normal women (p=0.451), whilst it was found to be significantly higher for the history of GDM

and macrocosmic baby >4.5kg among GDM cases at 12.49% versus 3.66% (p<0.0001) and

11.44% versus 3.66% (p<0.0001) respectively when compared with the normal women.

Educational level showed no significant difference in percentage between the two groups, whilst

the percentage of women with monthly income <4000 SR was found to be significantly higher

among normal women (p=0.02). Smoking or living in urban areas also showed no significant

difference between the two groups (p=0.811 and p=0.601).




Page 8 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



9












Figure (3) shows the odds ratio (OR), where the past history of GDM was found to be the highly

significant risk factor with OR 3.91 (1.93-7.95), (p <0.0001). It was followed by the history of

macrosomic baby weighing >4.5kg that had OR (95% CI) of 3.40 (1.65-7.00), (p <0.0001).

Obesity was the third significant risk factor with OR (95% CI) 2.50 (1.35-4.60) followed by age

>30 years, wherein the OR (95% CI) was 2.00 (1.26-3.18), both with a significant p value

(p=0.003). Other risk factors which include hypertension, low HDL, and family history of

diabetes, showed a non-significant increased risk for GDM presented by OR (95% CI) [1.50

(0.47-4.75), 1.34 (0.76-2.36), and 1.15 (0.81-1.63)] respectively. Lastly, the high triglycerides

showed no significant risk for GDM.

Page 9 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



10

DISCUSSION












which is most





The



and is

most likely a reflection of the high prevalence of abnormal glucose metabolism in our

population.


what had been earlier reported in other studies involving the Chinese and Indian populations,20,21


Page 10 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



11






Asian populations.23,24





other studies,21,26















The ratio of the previously known to newly discovered GDM cases

decreased with the progression of age which could be explained by the fact that, older women

were subjected for screening more than the younger women as also observed by other

researchers.27

Page 11 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



12



Indian, and Caucasian populations,21,26




pregnant women closer to what had been reported in other ethnicities.21,28



significantly increased the risk for GDM as reported earlier in many ethnicities.20,23



for developing GDM in this population but not to a significant level similar to the Caucasians,23

whilst positive family history of diabetes had a minimal non-significant increase, which could

have resulted from high consanguinity rates and family history of diabetes in general

population.25


this study

showed no effect of this risk factor, which could be due to the high mean triglycerides in both

normal and GDM cases.






screening.12



Page 12 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



13



CONCLUSIONS









Page 13 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



14



BMI Body Mass Index

C.I Confidence Interval




HDL High-density lipoprotein



LDL Low-density lipoprotein

OGTT Oral Glucose Tolerance Test

OR Odds Ratio


SR Saudi Riyals


Collaborators

The authors would like to acknowledge the staff at the University Diabetes Center and the staff

of the primary care centers from Ministry of Health for their collaboration in conducting to the

study.

Page 14 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



15

Contributors


A.K. designed the study, wrote the manuscript, designed figures and interpreted data, and

approved the final version to be published. M.H. supervised the field work in different health

sectors in relation to this project. K.T. provided training to the research physicians and did the

statistical analysis. Y.A. researched data, wrote the manuscript, and critically revised the article.

A.A. analyzed data, developed figures, interpreted data, and approved the final version to be

published. S.K. handled and analyzed blood samples, revised the article critically, and approved

the final version to be published. A.N. researched data, analyzed data, and approved the final

version to be published.



Competing interests




Page 15 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



16

References


Diabetes 1964; 13: 278-285.


27(suppl 1): s88-s90.


Diabetes 2005; 23:17-24.

4. Damm P, Kuhl C, Buschard K, et al. Prevalence and predictive value of islet cell

antibodies and insulin autoantibodies in women with gestational diabetes. Diabet Med

1994; 11: 558-563.














2007; 30: 1062-1068.







Page 16 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



17



340.




Endocr Pract 2012; 18: 146-151.




2012; 166: 317-324.











1099-1104.











Page 17 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



18


333: 831-834.


Sarma SP,



Ctries 2010; 30: 91-96.








Page 18 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



19



Normal (n=328) GDM (n=201) P value¥


Mean weight in kg (±SD) 67.11(±13.55) 73.94(±14.83) <0.0001


Mean BMI=kg/m2 (±SD) 27.97(±5.37) 30.27(±5.57) <0.0001


Mean systolic blood pressure, mmHg (±SD) 110.03(±10.84) 114.02(±11.61) 0.002

Mean diastolic blood pressure, mmHg (±SD) 71.34(±8.32) 72.71(±8.81) 0.160

Mean fasting plasma glucose, mmol/l (±SD) 4.21(±0.65) 6.55(±2.21) <0.0001

Mean total cholesterol, mmol/l (±SD) 5.58(±1.29) 5.41(±1.32) 0.278

Mean HDL cholesterol, mmol/l (±SD) 1.15(±0.32) 1.07(±0.32) 0.025

Mean LDL cholesterol, mmol/l (±SD) 3.57(±1.05) 3.52(±1.16) 0.704

Mean triglycerides, mmol/l (±SD) 1.81(±0.94) 1.84(±0.95) 0.778















Page 19 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960




20

Figures Legends:

Figure (1): Sample selection of childbearing age pregnant women from of the SAUDI-DM study cohort classified according

to abnormal glucose metabolism status.

Figure (2): The prevalence of abnormal glucose metabolism in pregnant Saudi women aged 18 to 49 years.


Page 20 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960




1



Khalid Al-Rubeaan1*, Hamad A Mana

2, Tawfik A Khoja

3, Amira M Youssef

1, Ahmad H Al-

Sharqawi4, Khalid Siddiqui

5 Najlaa A Ahmad4

1University Diabetes Center, College of Medicine, King Saud University, Saudi Arabia.

2Ministry of Health, Riyadh, Kingdom of Saudi Arabia

3Gulf Corporation Council, Riyadh, Kingdom of Saudi Arabia


Arabia.


Arabia.




P.O. Box 18397, Riyadh 11415

Saudi Arabia.

Phone:+966112825402

Fax: +966114775696




SAUDI-DM

Page 21 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



2

Abstract

Objective: To assess the prevalence and risk factors of gestational diabetes mellitus (GDM) in a

population known to have a high prevalence of abnormal glucose metabolism.

Methods: A household random population based cross-sectional study of 13,627 women in the

childbearing age, were subjected for fasting plasma glucose (FPG) if they were not known to be

diagnosed with any type of diabetes before. GDM cases were diagnosed using the International














Page 22 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



3








� The studied cohort is unique because of its swift socioeconomic transition

observed in the Saudi society that gives a good setup to assess for different

modifiable and non-modifiable risk factors for GDM and to compare this with

other ethnicities.




screening.

Page 23 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



4

INTRODUCTION









developing type 1 diabetes (5-10%)4

or type 2 diabetes (over 70%),5 while their offspring are











Page 24 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



5






women.9,10




mmol/l)11


This




whilst

reaching up to 30.5% and 37.7% in Norway and United Arab of Emirates.16,17

The aim of the present study was to investigate the prevalence of different abnormal glucose

conditions among pregnant women in the Kingdome of Saudi Arabia. The prevalence of GDM

and its different risk factors were also investigated using the new IADPSG diagnostic criteria.

Page 25 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



6

METHODS









4.0% of the total women participants' cohort. All the SAUDI-DM participants gave their consent

to participate and were subjected for interview. Clinical assessment of the participants, which

also included pregnant women, wherein their clinical data including age, family history of

diabetes, history of GDM and macrosomic baby, educational level, monthly income, smoking

status, residency area were all collected by specially trained primary care physicians from the

thirteen official regions. The anthropometric parameters including weight, height, body mass

index (BMI), waist to hip ratio and blood pressure were all measured by trained nurses.

Pregnant women who were not known to be suffering from diabetes were tested for FPG and

Lipids profile after overnight fasting of at least 10 hours and three days of usual activity and diet.

Using the IADPSG criteria, pregnant women were diagnosed with GDM if FPG is ≥92 mg/dl

(5.1 mmol/l).



Page 26 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



7




methodology as provided by Mindray (B5BS-200) chemistry analyzer reagent (China).


Medicine, King Saud University.







RESULTS

Table (1) describes the characteristics of the study population. Out of the selected cohort

containing Saudi pregnant women, 43 participants were women with known diabetes (7.8%), in

which, 4 participants (9.3%) were found to be patients with type 1diabetes, 16 participants

(37.2%) were found to be patients with type 2 diabetes, and 23 participants (53.5%) were found

to be with GDM. And among the remaining 506 women not known to be suffering from

diabetes, 178 (32.4%) were found to be new GDM cases. The studied cohort was divided into

three age groups, the first group is between 18 to 29 years of age with a total number of 264

(48.1%). The second age group is between 30 to 39 years totaling to 212 (38.6%), while the third

group is between 40 to 49 years with a total number of 73 (13.3%).

Page 27 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



8



7.63 years), ( p<0.0001) and more obese presented by their body weight (73.94 ± 14.83 kg) and

BMI (30.27±5.57 kg/m2) (p<0.0001). There was no significant difference between the two

groups in their mean height and waist to hip ratio (p=0.176). The GDM cases had a significantly

higher mean systolic blood pressure (SBP) at 114.02 ± 11.61 mmHg (p=0.002) and a low

diastolic blood pressure (DBP) at 72.71 ± 8.81 mmHg (p=0.160). And as expected, the mean

FPG was found to be significantly higher in GDM cases at 6.55 (±2.21) mmol/l when compared

with the mean FPG of the normal women at 4.21 ± 0.65 mmol/l (p<0.0001). Lipids showed no

significant difference between the two groups with the exception of mean HDL which was found

to be lower in the GDM cases at 1.07 ± 0.32 mmol/l when compared with the mean HDL for

normal women at1.15 ± 0.32 mmol/l (p=0.025). Percentage of women with positive family

history of diabetes was not found to be significantly different between the GDM cases and

normal women (p=0.451), whilst it was found to be significantly higher for the history of GDM

and macrocosmic baby >4.5kg among GDM cases at 12.49% versus 3.66% (p<0.0001) and

11.44% versus 3.66% (p<0.0001) respectively when compared with the normal women.

Educational level showed no significant difference in percentage between the two groups, whilst

the percentage of women with monthly income <4000 SR was found to be significantly higher

among normal women (p=0.02). Smoking or living in urban areas also showed no significant

difference between the two groups (p=0.811 and p=0.601).




Page 28 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



9












Figure (3) shows the odds ratio (OR), where the past history of GDM was found to be the highly

significant risk factor with OR 3.91 (1.93-7.95), (p <0.0001). It was followed by the history of

macrosomic baby weighing >4.5kg that had OR (95% CI) of 3.40 (1.65-7.00), (p <0.0001).

Obesity was the third significant risk factor with OR (95% CI) 2.50 (1.35-4.60) followed by age

>30 years, wherein the OR (95% CI) was 2.00 (1.26-3.18), both with a significant p value

(p=0.003). Other risk factors which include hypertension, low HDL, and family history of

diabetes, showed a non-significant increased risk for GDM presented by OR (95% CI) [1.50

(0.47-4.75), 1.34 (0.76-2.36), and 1.15 (0.81-1.63)] respectively. Lastly, the high triglycerides

showed no significant risk for GDM.

Page 29 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



10

DISCUSSION












which is most





The



and is

most likely a reflection of the high prevalence of abnormal glucose metabolism in our

population.


what had been earlier reported in other studies involving the Chinese and Indian populations,20,21


Page 30 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



11






Asian populations.23,24





other studies,21,26















The ratio of the previously known to newly discovered GDM cases

decreased with the progression of age which could be explained by the fact that, older women

were subjected for screening more than the younger women as also observed by other

researchers.27

Page 31 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



12



Indian, and Caucasian populations,21,26




pregnant women closer to what had been reported in other ethnicities.21,28



significantly increased the risk for GDM as reported earlier in many ethnicities.20,23



for developing GDM in this population but not to a significant level similar to the Caucasians,23

whilst positive family history of diabetes had a minimal non-significant increase, which could

have resulted from high consanguinity rates and family history of diabetes in general

population.25


this study

showed no effect of this risk factor, which could be due to the high mean triglycerides in both

normal and GDM cases.






screening.12



Page 32 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



13



CONCLUSIONS









Page 33 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



14



BMI Body Mass Index

C.I Confidence Interval




HDL High-density lipoprotein



LDL Low-density lipoprotein

OGTT Oral Glucose Tolerance Test

OR Odds Ratio


SR Saudi Riyals


Collaborators

The authors would like to acknowledge the staff at the University Diabetes Center and the staff

of the primary care centers from Ministry of Health for their collaboration in conducting to the

study.

Page 34 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



15

Contributors


A.K. designed the study, wrote the manuscript, designed figures and interpreted data, and

approved the final version to be published. M.H. supervised the field work in different health

sectors in relation to this project. K.T. provided training to the research physicians and did the

statistical analysis. Y.A. researched data, wrote the manuscript, and critically revised the article.

A.A. analyzed data, developed figures, interpreted data, and approved the final version to be

published. S.K. handled and analyzed blood samples, revised the article critically, and approved

the final version to be published. A.N. researched data, analyzed data, and approved the final

version to be published.



Competing interests




Page 35 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



16

References


Diabetes 1964; 13: 278-285.


27(suppl 1): s88-s90.


Diabetes 2005; 23:17-24.

4. Damm P, Kuhl C, Buschard K, Jakobsen BK, Svejgaard A, Sodoyez-Goffaux F, et al.

Prevalence and predictive value of islet cell antibodies and insulin autoantibodies in

women with gestational diabetes. Diabet Med 1994; 11: 558-563.














2007; 30: 1062-1068.



Page 36 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



17







340.




Endocr Pract 2012; 18: 146-151.




2012; 166: 317-324.











1099-1104.






Page 37 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



18







333: 831-834.


Sarma SP,



Ctries 2010; 30: 91-96.








Page 38 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



19



Normal (n=328) GDM (n=201) P value¥


Mean weight in kg (±SD) 67.11(±13.55) 73.94(±14.83) <0.0001


Mean BMI=kg/m2 (±SD) 27.97(±5.37) 30.27(±5.57) <0.0001


Mean systolic blood pressure, mmHg (±SD) 110.03(±10.84) 114.02(±11.61) 0.002

Mean diastolic blood pressure, mmHg (±SD) 71.34(±8.32) 72.71(±8.81) 0.160

Mean fasting plasma glucose, mmol/l (±SD) 4.21(±0.65) 6.55(±2.21) <0.0001

Mean total cholesterol, mmol/l (±SD) 5.58(±1.29) 5.41(±1.32) 0.278

Mean HDL cholesterol, mmol/l (±SD) 1.15(±0.32) 1.07(±0.32) 0.025

Mean LDL cholesterol, mmol/l (±SD) 3.57(±1.05) 3.52(±1.16) 0.704

Mean triglycerides, mmol/l (±SD) 1.81(±0.94) 1.84(±0.95) 0.778















Page 39 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960




20

Figure (1): Sample selection of childbearing age pregnant women from of the SAUDI-DM study cohort classified according to abnormal glucose

metabolism status.

43 (7.8%) Known diabetics:

4 patients (9.3%) with type 1 diabetes.

16 patients (37.2%) with type 2 diabetes.

23 patients (53.5%) with known GDM.

221 (40.2%) Total diabetic cases

506 (92.2%) Not known to be diabetics: Screened with FPG using 2011 ADA

criteria of ≥92 mg/dL (>5.1 mmol/L).

13,627 participant women

All women aged 18 to 49 years from the

community adjusted cohort of SAUDI DM

study.

549 (4.0%) Pregnant women

Pregnant confirmed by pregnancy test.

13,078 (96%) Non-pregnant women

Pregnancy excluded by history.

178 (32.4%) Participants

New GDM cases

328 (77.6%) Participants

with normal fasting

plasma glucose level

Page 40 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960




21

Figures Legends:

Figure (1): Sample selection of childbearing age pregnant women from of the SAUDI-DM study cohort classified according

to abnormal glucose metabolism status.

Figure (2): The prevalence of abnormal glucose metabolism in pregnant Saudi women aged 18 to 49 years.


Page 41 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960




Figure (1): Sample selection of childbearing age pregnant women from of the SAUDI-DM study cohort classified according to abnormal glucose metabolism status.

234x156mm (300 x 300 DPI)

Page 42 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



Figure (2): The prevalence of abnormal glucose metabolism in pregnant Saudi women aged 18 to 49 years. 67x56mm (300 x 300 DPI)

Page 43 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



107x52mm (300 x 300 DPI)

Page 44 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



jopen.bmj.com

/B

MJ O


ugust 2014. Dow

nloaded from



1

STROBE Statement Checklist of items that should be included in reports of observational studies

Section/Topic Item

No Recommendation

Reported

on Page No

Title and abstract 1 (a) Indicate the study’s design with a commonly used term in the title or the abstract 2

(b) Provide in the abstract an informative and balanced summary of what was done and what was found 2

Introduction

Background/rationale 2 Explain the scientific background and rationale for the investigation being reported 3

Objectives 3 State specific objectives, including any prespecified hypotheses 4

Methods

Study design 4 Present key elements of study design early in the paper 5

Setting 5 Describe the setting, locations, and relevant dates, including periods of recruitment, exposure, follow-up, and data collection

5

Participants 6

(a) Cohort study—Give the eligibility criteria, and the sources and methods of selection of participants. Describe methods of

follow-up

Case-control study—Give the eligibility criteria, and the sources and methods of case ascertainment and control selection. Give the

rationale for the choice of cases and controls

Cross-sectional study—Give the eligibility criteria, and the sources and methods of selection of participants

5

(b) Cohort study—For matched studies, give matching criteria and number of exposed and unexposed

Case-control study—For matched studies, give matching criteria and the number of controls per case

Variables 7 Clearly define all outcomes, exposures, predictors, potential confounders, and effect modifiers. Give diagnostic criteria, if

applicable 5

Data sources/measurement 8* For each variable of interest, give sources of data and details of methods of assessment (measurement). Describe comparability of

assessment methods if there is more than one group 5

Bias 9 Describe any efforts to address potential sources of bias No bias

Study size 10 Explain how the study size was arrived at 5

Quantitative variables 11 Explain how quantitative variables were handled in the analyses. If applicable, describe which groupings were chosen and why 6

Statistical methods 12

(a) Describe all statistical methods, including those used to control for confounding 6

(b) Describe any methods used to examine subgroups and interactions 6

(c) Explain how missing data were addressed No missing

data

(d) Cohort study—If applicable, explain how loss to follow-up was addressed

Case-control study—If applicable, explain how matching of cases and controls was addressed

Cross-sectional study—If applicable, describe analytical methods taking account of sampling strategy

5

Page 45 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960




2

(e) Describe any sensitivity analyses None

Section/Topic Item

No Recommendation

Reported

on Page No

Results

Participants 13*

(a) Report numbers of individuals at each stage of study—eg numbers potentially eligible, examined for eligibility, confirmed

eligible, included in the study, completing follow-up, and analysed 5

(b) Give reasons for non-participation at each stage Figure 1

(c) Consider use of a flow diagram Figure 1

Descriptive data 14*

(a) Give characteristics of study participants (eg demographic, clinical, social) and information on exposures and potential

confounders Table 1

(b) Indicate number of participants with missing data for each variable of interest No missing

data

(c) Cohort study—Summarise follow-up time (eg, average and total amount)

Outcome data 15*

Cohort study—Report numbers of outcome events or summary measures over time

Case-control study—Report numbers in each exposure category, or summary measures of exposure

Cross-sectional study—Report numbers of outcome events or summary measures Figure 2

Main results 16

(a) Give unadjusted estimates and, if applicable, confounder-adjusted estimates and their precision (eg, 95% confidence interval).

Make clear which confounders were adjusted for and why they were included Table 1

(b) Report category boundaries when continuous variables were categorized Table1

(c) If relevant, consider translating estimates of relative risk into absolute risk for a meaningful time period Not

applicable

Other analyses 17 Report other analyses done—eg analyses of subgroups and interactions, and sensitivity analyses None

Discussion

Key results 18 Summarise key results with reference to study objectives 8-9

Limitations 19 Discuss limitations of the study, taking into account sources of potential bias or imprecision. Discuss both direction and magnitude

of any potential bias 11

Interpretation 20 Give a cautious overall interpretation of results considering objectives, limitations, multiplicity of analyses, results from similar

studies, and other relevant evidence 8-13

Generalisability 21 Discuss the generalisability (external validity) of the study results 11

Other Information

Funding 22 Give the source of funding and the role of the funders for the present study and, if applicable, for the original study on which the

present article is based 14

*Give information separately for cases and controls in case-control studies and, if applicable, for exposed and unexposed groups in cohort and cross-sectional studies.

Page 46 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960




3

Note: An Explanation and Elaboration article discusses each checklist item and gives methodological background and published examples of transparent reporting. The STROBE checklist is

best used in conjunction with this article (freely available on the Web sites of PLoS Medicine at http://www.plosmedicine.org/, Annals of Internal Medicine at http://www.annals.org/, and

Epidemiology at http://www.epidem.com/). Information on the STROBE Initiative is available at www.strobe-statement.org.

Page 47 of 47


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



bmj open · for peer review only 2 abstract background: to assess the prevalence and risk factors...

Documents