The prevalence of undiagnosed type 2 diabetes and prediabetes in Eastern Mediterranean region (EMRO): A systematic review and meta-analysis

Journal Pre-proofs The Prevalence of undiagnosed type 2 diabetes and prediabetes in Eastern Mediterranean Region (EMRO): a systematic review and meta-analysis Alireza Mirahmadizadeh, Mohammad Fathalipour, Ali Mohammad Mokhtari, Shahryar Zeighami, Soheil Hassanipour, Alireza Heiran PII: DOI: Reference:

S0168-8227(19)31367-1 https://doi.org/10.1016/j.diabres.2019.107931 DIAB 107931

To appear in:

Diabetes Research and Clinical Practice

Received Date: Revised Date: Accepted Date:

22 September 2019 9 November 2019 14 November 2019

Please cite this article as: A. Mirahmadizadeh, M. Fathalipour, A. Mohammad Mokhtari, S. Zeighami, S. Hassanipour, A. Heiran, The Prevalence of undiagnosed type 2 diabetes and prediabetes in Eastern Mediterranean Region (EMRO): a systematic review and meta-analysis, Diabetes Research and Clinical Practice (2019), doi: https://doi.org/10.1016/j.diabres.2019.107931

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Review article The Prevalence of undiagnosed type 2 diabetes and prediabetes in Eastern Mediterranean Region (EMRO): a systematic review and meta-analysis

Alireza Mirahmadizadeh 1, Mohammad Fathalipour 2, Ali Mohammad Mokhtari 3, Shahryar Zeighami 4, Soheil Hassanipour 5, 6 * #, Alireza Heiran 3 * #

1. Non-communicable diseases research center, Shiraz University of Medical Sciences, Shiraz, Iran 2. Department of Pharmacology and Toxicology, Faculty of Pharmacy, Hormozgan University of Medical Sciences, Bandar Abbas, Iran 3. Student Research Committee, Shiraz University of Medical Sciences, Shiraz, Iran 4. Department of Urology, Shiraz University of Medical Sciences, Shiraz, Iran 5. Gastrointestinal and Liver Diseases Research Center, Guilan University of Medical Sciences, Rasht, Iran 6. GI Cancer Screening and Prevention Research Center, Guilan University of Medical Sciences, Rasht, Iran

*Corresponding Authors: Soheil Hassanipour, Gastrointestinal and Liver Diseases Research Center, Guilan University of Medical Sciences, Razi Hospital, Sardar-Jangle Ave., P.O. Box: 41448-95655, Rasht, Iran. Tel: +98(13)33535116 Fax: +98(13)33534951 Email: [email protected] Alireza Heiran, Department of Epidemiology, School of Health, Shiraz University of Medical Sciences, Shiraz, Iran Tel: +98 7137256007 Fax: +98 7137260225 E-mail: [email protected] # These

two authors have the equal contributions.

Abstract Background: Previous studies of diabetes in Eastern Mediterranean Region (EMRO) did not assess the prevalence of either unknown diabetes or prediabetes. We conducted a systematic review and meta-analysis to estimate the prevalence of undiagnosed type 2 diabetes and prediabetes as well as variations by region in EMRO, using the relevant publications since 2000. Methods: We carried out a comprehensive electronic search on electronic databases from January 1, 2000 to March 1, 2018. We selected cross-sectional and cohort studies reporting the prevalence of undiagnosed type 2 diabetes, prediabetes, or both. Two independent reviewers initially screened the eligible articles; then, synthesized the target data from full papers. Random or fixed effects model, subgroup analysis on Human Development Index (HDI), and publication year and sensitivity analysis to minimize the plausible effect of outliers were used. Results: Among 849 identified citations, 55 articles were entered into meta-analysis, involving 567025 individuals. The forest plots estimated 5.46% (confidence intervals [CI]: 4.77-6.14) undiagnosed diabetic and 12.19% (CI: 10.13-14.24) prediabetics in EMRO. Low HDI countries and high HDI countries had the highest (7.25%; CI: 4.59-9.92) and the lowest (3.98%; CI: 3.11-4.85) undiagnosed diabetes prevalence, respectively. Very high HDI countries and low HDI countries had the highest (13.50%; CI: 8.43-18.57) and the lowest (7.45%; 1.20-13.71) prediabetes prevalence, respectively. In addition, meta-regression analysis showed a statistically significant association between publication year and prevalence of prediabetes (Reg Coef = 0.059, P = 0.014). But such finding was not observed for undiagnosed diabetes and publication year (Reg Coef = 0.034, P = 0.124), prediabetes and HDI (Reg Coef = 0.128, P = 0.31) and undiagnosed diabetes and HDI (Reg Coef = - 0.04, P = 0.96). Conclusion: The prevalence of undiagnosed diabetes and prediabetes was high and increasing. The notion of universal health coverage is a priority; that is the integration of the primary, secondary and tertiary health levels, as well as employing the available action plans. Therefore, future studies, using identical screening tool and diagnostic criteria, are warranted to make an accurate picture of diabetes in EMRO. Keywords: Prevalence, Diabetes mellitus, Undiagnosed, Prediabetes, Eastern Mediterranean Region.

Introduction Non-communicable diseases (NCDs) is the major cause of global death, and diabetes is among the four most prevalent groups of NCDs [1]. Diabetes is a global health challenge, approximately affected 424.9 million people worldwide in 2017 and expected to rise to 628.6 million by 2045 [2]. Recent evidence estimates, diabetes causes worldwide more than 827 billion USD direct loss annually [3, 4]. These findings warrant for more comprehensive screening and monitoring strategies. This trend is accepted to be more dramatic in Middle East and North Africa as those countries account for amongst the most prevalent in top ten list [5], driven by urbanization, westernized lifestyle, improved socioeconomic status, fitness related risk factors, increased intake of refined carbohydrates, better screening programs, and aging [6]. World Health Organization (WHO) was reported 15,188,000 diabetic people in 2000 and estimated to rise to 42,600,000 diabetics in 2030 in the Eastern Mediterranean Region (EMRO) [7]. Similarly, in the latest diabetes atlas, the International Diabetes Federation (IDF) estimates 39.9 million diabetic adults in the Middle East and North Africa (MENA) in 2017, and will be more than double (85.9 million) by less than next three decades with the current 20.5 billion USD economic burden load that 81% will be increased [2]. Lowand middle- income countries share larger future expenditure burden than high-income countries [8]. Diabetes is like an iceberg; that is, diagnosed and undiagnosed diabetes are visible and invisible area and prediabetes lies in the transitional zone. The size of hidden part is linked to early detection by screening, and treatment and palliative care allocated to prediabetics. These fell on the scope of surveillance system that concerns with high risk people; that more living with undiagnosed diabetes, brings more health burden especially retinopathy, neuropathy and nephropathy. Undiagnosed diabetes is a state when a non-pregnant patient does not report the diagnosis of diabetes informed by a physician or healthcare provider, with fasting plasma glucose greater than or equal to 126 mg/dl or hemoglobin A1c greater than or equal to 6.5% [9]. WHO reported the wide variation on undiagnosed diabetes ranged between 6% and 70% amongst people who experienced blood glucose measurement [10]. Also, IDF has estimated that 84.5% of all undiagnosed diabetes cases are resided in low and middle income countries, linked to the limited resources and lack of extensive screening program [2]. However, most studies are performed in the U.S. where it is classically believed that a quarter to one third of patients are undiagnosed based upon abovementioned criteria [11, 12]. But applying the new confirmatory criteria (fasting plasma glucose ≥126 mg/dl and hemoglobin A1c ≥ 6.5%), which might lack the prevalence overstating, Selvin et al. [13] reported a decreased proportion of 10.9% in 2011 to 2014. In the other side, the estimated proportion of undiagnosed diabetes in Asia and Middle East ranges from 40.7% to 63%.2 of all type 2 diabetic patients [14]. Roughly speaking, assessing and tracing the burden of undiagnosed diabetes could evaluate programs and potentials related to at-risk patients

screening, diagnosis, management, preventing complications, and access to health care, as well as yielding evidences for making priorities and financial investments [15-17]. EMRO is a sub-community of WHO including a group of developing countries located in Southwest Asia, Western Asia and North Africa with heterogeneous economies [18]. Several reviews concerning with the prevalence of type 2 diabetes in Middle East and North Africa could be identified in literature. Similar meta-analysis done about epidemiology of diabetes and related complications in various region [19-23], nevertheless to the best of our knowledge, no study is elucidated the undiagnosed type 2 diabetes and prediabetes prevalence in Middle East and North Africa, in addition to the demand for more updated meta-analysis. Additionally, owing to the higher rate of several complications following undiagnosed type 2 diabetes and higher risk of developing diabetes in pre-diabetic subjects, a comprehensive and systematic epidemiologic data is warranted for early detection and prompt intervention [24, 25]. Therefore, we conducted a systematic review and metaanalysis of relevant studies published since 2000 to estimate the prevalence of prediabetes and undiagnosed type 2 diabetes and variations by region in EMRO.

Methods The present study is a systematic review and meta-analysis on estimating the prevalence of prediabetes and undiagnosed type 2 diabetes EMRO, designed and performed in 2018. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) is used to report the study [26]. Literature Search We searched Medline/PubMed, Scopus, Embase, and Web of knowledge, as well as Google Scholar- the gray literature- to identify the published relevant studies from Jan 1, 2000, until Mar 1, 2018. The keywords dashboard in title and abstract is booked in Appendix 1. The articles list collected in Endnote-x7 and the duplicates were automatically discarded. The articles without full-text or those were not written in English, removed. Additionally, the references of systematic reviews and meta-analysis manually searched, in order to including all relevant articles. Selection criteria The primary screening for eligibility, based upon on the title and the abstract, and quality assessment was performed by two independent researchers (AH and MF). Then, on the remaining articles, secondary screening was done through reading the whole manuscript. In the case of conflict in any of abovementioned stages, the first author (AM) made the final decision.

Articles were included if: (1) they studied the prevalence of undiagnosed diabetes and (or) prediabetes, or (2) they measured fasting plasma glucose, hemoglobin A1c, random blood sugar, or oral glucose tolerant test by blood sample, or (3) they used plasma for the tests, or (4) they studied the people with at least 30-to-45 years of age (lower limit of age). Studies were excluded if: (1) they were not conducted among the normal population, for example pregnant, those with tuberculosis and etc. or (2) their participants used medications that might affect the blood sugar control, like corticosteroids. Data extraction All targeted statistics were listed in a checklist prepared as a spreadsheet. This check list included first writer name, year of publishing, time period and country of study, total number of analyzed participants, and frequency (%) and upper and lower 95% confidence intervals for undiagnosed diabetes and prediabetes (Table 1). Quality assessment In order to assess the quality of the articles, a checklist for prevalence studies by the Joanna Briggs Institute (JBI) was used [27]. The purpose of this appraisal is to assess the methodological quality of a study and to determine the extent to which a study has addressed the possibility of bias in its design, conduct and analysis. All papers were evaluated on the basis of data relevance and methodological rigor. The results of quality assessment presented in Appendix 2. Assessing the chance of bias In order to investigate the heterogeneity plausible causes subgroups analysis and for measure probable publication bias, Egger test was used to in the studies. Statistical analysis The heterogeneity of the studies was assessed by Cochran test (with significance less than 0.1) and its composition using I2 statistics. In the case of heterogeneity, the random effects model was utilized with the inverse-variance method, and in the absence of heterogeneity, the fixed effects model was applied. In the case of a heterogeneity in the studies, subgroup analysis was used and factors like the geographical area and the Human Development Index (HDI). All analyzes were performed by the STATA (version 13) software. Additional analysis Due to the heterogeneity of the studies, the subgroups analysis was used to make results more robust. The HDI indicator was applied for this purpose. The HDI is a relative measure of life expectancy, education, quality and education level; in other words, it is the living standards in human societies. This Index is estimated by measure of welfare, especially amongst children and people of low age [28].

Sensitivity analysis Since outlier results obtained from some countries could notably affect the subgroup analysis results, we used sensitivity analysis; that is, data irrespective of these studies was also re-analyzed and contrasted with the results that included them.

Findings Results of the search We identified 849 citations initially. After discarding duplicates, 550 studies remained, in addition to the 32 studies that manually added; hence, 582 studies considered to investigate the titles and abstracts. 163 Articles were remained for the full-text review. Of which 87 studies fulfilled inclusion criteria. Finally, 55 articles were entered into meta-analysis. The exclusion reasons for 495 totally excluded papers were irrelevant title (n = 433), studies out of EMRO (n = 4), irrelevant population (n = 11), including inappropriate age groups (n = 6), not reporting prevalence of either undiagnosed diabetes or prediabetes (n = 15), reporting incidence of either undiagnosed diabetes or prediabetes (n = 3), review or meta-analysis study (n = 11), non-English papers (n = 6 [5: Persian, 1: French]), and editorial or letter papers (n = 2). The flowchart of included studies is shown in the Figure 1.

Identification Screening

Records identified through database searching (n = 849)

Additional records identified through other sources (n = 32)

Eligibility

Full-text articles assessed for eligibility (n = 163)

Included

Articles excluded (n = 419)

Records after duplicates removed (n = 582)

Full-text articles excluded, with reasons (n = 76)

Studies included in qualitative synthesis (n = 87)

Studies included in quantitative synthesis (meta-analysis) (n = 55)

Fig. 1. Flowchart of included studies (PRISMA-2009-Flow-Diagram) Description of studies Base on geographical location of 55 included studies [29-83], 13 studies conducted in Iran, 9 in Pakistan, 9 in Saudi Arabia, 4 in UAE, 4 in Iraq, 3 in Sudan, 2 in Afghanistan, 2 in Oman, 2 in Palestine, 1 in Tunisia, 1 in Qatar, 1 Yemen, 1 in Kuwait, 1 in Jordan, 1 in Libya, 1 in Syria and 0 in Morocco, Somalia, Lebanon, Egypt, Djibouti, and Bahrain. Characteristics of the included studies is shown in the table 1.

Table 1. Basic characteristics of the studies included in the review Prevalence Pre-DM UDDM 12.9 5.4

Author, year

Countries

Time period

Sample size

Age (years)

1

Eltom, 2018

Sudan

2015

5242

≥ 18

2

Niroomand, 2017

Iran

-

3976

20 - 69

19

5.8

Satisfactory

4941

20 - 69

20

5.1

Satisfactory

3

Islam Saeed, 2017

Afghanistan

2015

1129

25 - 70

-

6.6

Good

4

Zafar, 2016

Pakistan

2014

404

18 - 65

37.4

-

Satisfactory

5

Yazdanpanah, 2016

Iran

-

944

≥ 20

23.3

9.11

Satisfactory

6

Latifi, 2016

Iran

2009

593

≥ 20

22.6

-

Good

2014

593

≥ 20

18.3

-

Good

7

Elmadhoun, 2016

Sudan

2015

954

≥ 18

9.5

6

Good

8

Bahijri, 2016

Saudi Arabia

-

1419

≥ 18

10.22

1.34

Satisfactory

9

Saeed, 2016

Afghanistan

2015

1165

25 - 70

-

19.4

Good

10

Noor, 2015

Sudan

2013

1111

≥ 18

1.3

2.6

Good

11

Najafipour, 2015

Iran

2010 - 2011

5895

15 - 75

18.7

2.7

Good

12

Memish, 2015

Saudi Arabia

2009

1485

≥ 20

47.5

15.6

Good

13

Khalilzadeh, 2015

Iran

2013

403

≥ 30

34.7

7.5

Satisfactory

14

Katibeh, 2015

Iran

-

2090

20 - 40

1.9

2.7

Satisfactory

15

Al-rubeaan, 2015

Saudi Arabia

2007 - 2009

18034

≥ 30

25.5

10.2

Good

16

Afifi, 2015

Saudi Arabia

2010 - 2011

117

≥ 40

-

9.4

Good

17

Mansour, 2014

Iraq

2001 - 2012

5445

≥ 19

29.1

11

Satisfactory

10038 3342 51930

25 - 64 25 - 64 25 - 70

14.41 9.67 15.29

2.63 3.21 3.6

Satisfactory Good Satisfactory

Quality Satisfactory

18

Esteghamati, 2014

Iran

2011 2007 2005

19

El Bcheraoui, 2014

Saudi Arabia

2013

5590

≥ 15

15.8

6.96

Good

20

Ben Romdhane, 2014

Tunisia

2005

7700

35 - 70

5.9

7.72

Good

21

Al-Rubeaan, 2014

Saudi Arabia

2007 - 2009

53370

0 - 100

22.6

6.2

Satisfactory

22

Lotfi, 2013

Iran

2012

11027

≥ 30

11.9

1.5

Satisfactory

23

Al Riyami, 2012

Oman

2008

3370

≥ 18

4.4

6.4

Good

24

Bennet, 2011

Iraq

2010

96

46 - 65

24

5.2

Good

25

Zafar, 2011

Pakistan

2014

404

18 - 65

37.4

-

Good

26

Al-Windi, 2011

Iraq

2010

776

18 - 79

6.3

6.3

Good

27

Veghari, 2010

Iran

2006

1999

25 - 65

-

2.05

Satisfactory

28

Saadi, 2010

UAE

-

355

≥ 30

20.6

11.8

Good

29

Saadi, 2010

UAE

2009 - 2010

364

≥ 18

20.33

9.62

Good

30

Mahar, 2010

Pakistan

2006 - 2008

19211

≥ 30

-

2.18

Satisfactory

31

Al-Baghli, 2010

Saudi Arabia

2004 - 2005

197681

≥ 30

2.7

1.8

Good

32

Albache, 2010

Syria

2006

1168

≥ 25

6.16

4.62

Good

33

Al Khalaf, 2010

Kuwait

2007

562

-

10.2

4.1

Satisfactory

34

Shera, 2010

Pakistan

1998

1852

≥ 25

7.34

4.05

Good

35

Bener, 2009

Qatar

2007 - 2008

1117

≥ 20

13.8

5.9

Good

36

Shaikh, 2008

Pakistan

2003

16507

≥ 30

-

4

Satisfactory

37

Sajjadi, 2008

Iran

2000 - 2001

3940

≥ 19

6.2

1.1

Good

38

Mansour, 2008

Iraq

2007

3176

≥ 20

2.02

2.14

Good

39

Hadaegh, 2008

Iran

1999 - 2001

9489

≥ 20

4.6

5

Good

40

Azimi-Nezhad, 2008

Iran

-

3778

15 - 64

2.5

-

Satisfactory

41

Ajlouni, 2008

Jordan

2004

1121

≥ 25

8.1

4.37

Good

42

Shera, 2007

Pakistan

-

5433

≥ 25

13.8

5.37

Good

43

Sadeghi, 2007

Iran

-

12514

≥ 19

5.5

2.3

Good

44

Saadi, 2007

UAE

2005 - 2006

373

≥ 18

22.8

10.7

Good

45

Al Osaimi, 2007

Saudi Arabia

2002

380

≥ 18

7.3

2.37

Satisfactory

46

Afghani, 2007

Pakistan

1997 - 2001

79194

≥ 40

-

7.89

Satisfactory

47

Malika, 2005

UAE

1999 - 2000

5844

≥ 20

6.5

8.21

Good

48

Al-Nozha, 2004

Saudi Arabia

1995 - 2000

16917

30 - 70

14.1

-

Satisfactory

49

Al-Lawati, 2002

Oman

2000

5838

≥ 20

6.1

-

Good

Yemen

2000

1080

20 - 85

-

-

Good

Basit, 2002

Pakistan

-

2032

≥ 25

3

0.9

Good

52

Abdul-Rahim, 2001

Palestin

1998

492

30 - 65

5.9

2.6

Satisfactory

53

Riste, 2001

Pakistan (UK)

1991

132

25 - 79

-

15.16

Satisfactory

54

Kadiki, 2001

Lybia

-

738

-

8.5

-

Satisfactory

500

30 - 65

8.6

2.8

Good

50

Gunaid, 2002

51

55

Husseini, 2000

Palestin

1996

Abbreviations: Pre-DM; prediabetes, UDDM; undiagnosed diabetes, Pakistan (UK); Pakistani descent in United Kingdom.

Heterogeneity The result of chi-squared test and the I2 index indicated that there was a considerable interstudy heterogeneity. For undiagnosed diabetes (I2 = 99.5 %, P < 0.001) and prediabetes (I2 = 99%, P < 0.001).

Results of the meta-analysis Prevalence of undiagnosed diabetes Fifty studies were reported the undiagnosed diabetes prevalence and pooled analysis showed 5.45% (confidence intervals [CI]: 4.77-6.13) undiagnosed diabetic in EMRO. Figure 2 depicts the undiagnosed diabetes prevalence stratified by HDI. Low HDI countries and high HDI countries had the highest (7.25%; CI: 4.59-9.92) and the lowest (3.98%; CI: 3.11-4.85) undiagnosed diabetes prevalence. In sensitivity analysis, the change in total prevalence was minimal (5.46%; CI: 4.77-6.14) (appendix 3). Figure 3 demonstrated the undiagnosed diabetes prevalence compared to prediabetes and diagnosed diabetes prevalence in EMRO.

Fig. 2. Prevalence of undiagnosed diabetes stratified by Human Development Index (HDI)

Prevalence of prediabetes Forty-eight studies assessed the prediabetes prevalence. Our results showed a total of 12.78% for prediabetes prevalence (CI: 10.67-14.89) in EMRO. Figure 3 shows the prediabetes prevalence stratified by HDI. Accordingly, countries with medium HDI had the highest prediabetes prevalence (15.53%; CI: 9.84-21.23) and those with low HDI (7.45%; 1.20-13.71) had the lowest prevalence. In sensitivity analysis, total prevalence was 12.19 (CI: 10.13-14.24) and the highest and the lowest prediabetes prevalence observed in very high HDI countries (13.50%; CI: 8.43-18.57) and low HDI countries (7.45%; 1.20-13.71) (appendix 4).

Fig. 3. Prevalence of prediabetes stratified by Human Development Index (HDI)

Fig. 4. Prevalence of undiagnosed diabetes (top), prediabetes (bottom left), and diagnosed diabetes (bottom right) in EMRO.

Result of meta-analysis by each country Result of meta-analysis and heterogeneity about prevalence of unknown diabetes and prediabetes in EMRO base on each country indicated in table2.

Table 2– Result of meta-analysis and heterogeneity about prevalence of unknown diabetes and prediabetes in EMRO base on each country

Unknown Diabetes Country Afghanistan Iran Iraq Jordan Kuwait Libya Oman Pakistan Palestine Qatar Saudi Arabia Sudan Syria UAE Tunisia Overall NR: not reported

Prediabetes

# of study

P and 95 %CI

I2

P value

# of study

P and 95 %CI

I2

P value

2 14 4 1 1 NR 1 7 2 1 8 3 1 4 1 49

12.96 (0.4- 25.5) 3.6 (2.8- 4.5) 6.2 (0.5 – 11.8) 4.3 (3.1- 5.6) 4.1 (2.4- 5.8) NR 6.4 (5.5- 7.2) 4.9 (2.4-7.3) 2.7 (1.7-3.6) 5.9 (4.4- 7.3) 6.5 (3.9 – 9.1) 4.6 (2.6- 6.6) 4.6 (3.3- 5.9) 9.5 (7.7- 11.3) 7.7 (7.1- 8.3) 5.4 (4.7- 6.1)

98.9 99 99 NR 99.7 0 99.8 92.6 52 99.5

< 0.001 < 0.001 < 0.001 NR < 0.001 0.843 < 0.001 < 0.001 0.100 < 0.001

NR 15 4 1 1 1 2 5 2 1 7 3 1 4 1 47

NR 12.8 (9.6- 15.9) 15.1 (0.5- 30.9) 8.1 (6.4- 9.7) 10.2 (7.6- 12.8) 8.5 (5.7- 11.2) 5.2 (3.6- 6.9) 19.2 (11.9- 26.5) 7.2 (4.5- 9.8) 13.8 (11.7- 15.8) 14 (4.9- 23.1) 7.9 (0.5- 16.2) 6.1 (4.7- 7.5) 17.4 (7.2- 27.6) 5.9 (5.3- 6.4) 12.8 (10.6- 14.9)

NR 99.7 99.8 91.7 99.3 60.4 99.9 99.5 97.6 99.8

NR < 0.001 < 0.001 0.001 < 0.001 0.112 < 0.001 < 0.001 < 0.001 < 0.001

Results of the Meta-regression Results of meta-regression showed a statistically significant association between publication year and prevalence of prediabetes in EMRO. Thus, year of study is a cause of variability in results (Reg Coef = 0.059, P = 0.014). Such meaningful result was not found for undiagnosed diabetes (Reg Coef = 0.034, P = 0.124). According to the results, an increasing prevalence across the study period was observed (Figure 5).

Fig. 5. Trends in the annual prevalence (year of study) of undiagnosed diabetes and prediabetes

Also, we examined the HDI as another variability factor and results showed it was not correlated with prevalence of undiagnosed diabetes (Reg Coef = - 0.04, P = 0.96) and prediabetes (Reg Coef = 0.128, P = 0.31) (Figure 6).

Fig. 6. Trends in the prevalence of undiagnosed diabetes and prediabetes stratified by Human Development Index (HDI)

Discussion In the “A Prioritized Research Agenda for Prevention and Control of Non-communicable Diseases” published in 2011- with reference on “The Global Strategy for the Prevention and Control of NCDs and its Action Plan”, WHO clearly emphasized on conducting epidemiological and health-systems research to generate additional evidence to renew and to ascertain existing knowledge on preventive and controlling strategies, especially in the low- and middle-income countries [84]. Amongst the three main research priorities, the first one belongs to the identification of the NCDs magnitude. Additionally, WHO acknowledged that the prevalence of diagnosed and undiagnosed type 2 diabetes require further research [84]. To our knowledge, this systematic review and meta-analysis is the first in class study on the prevalence of either prediabetes or undiagnosed type 2 diabetes in EMRO, to date. Most of studies on both prediabetes and undiagnosed diabetes are conducted in Islamic Republic of Iran (prediabetes: 15 - undiagnosed diabetes: 14) and Saudi Arabia (prediabetes: 7 - undiagnosed diabetes: 8), followed by Pakistan (prediabetes: 5 - undiagnosed diabetes: 7), United Arab Emirates (prediabetes: 4 - undiagnosed diabetes: 4), Iraq (prediabetes: 4 undiagnosed diabetes: 4), and Sudan (prediabetes: 3 - undiagnosed diabetes: 3). Palestine, Kuwait, Qatar, Oman, Jordan, Syria, Tunisia, Libya and Afghanistan lack sufficient data on prediabetes or undiagnosed diabetes, and no study was found from Morocco, Somalia, Lebanon, Egypt, Djibouti, and Bahrain on both prediabetes and undiagnosed diabetes. Although region classifications of WHO and IDF are different, the two overlap in a large extent; that is, our results could be contrasted to those obtained from MENA, including the

latest IDF diabetes atlas [2] and Zabetian et al. systematic review and meta-analysis in 2013 [85]. The findings were: first, after sensitivity analysis, the forest plot showed a prevalence of 5.46% undiagnosed diabetics in EMRO. Low HDI and high HDI countries had the highest (7.25%) and the lowest (3.98%) undiagnosed diabetic prevalence. Notably, a high prevalence of undiagnosed diabetics was also found in very high HDI countries (7.19%) second, after sensitivity analysis, the pooled analysis showed a total of 12.19% for prediabetes in EMRO. Very high HDI and low HDI countries had the highest (13.50%) and the lowest prediabetes prevalence (7.45%); third, prediabetes and undiagnosed diabetes prevalence was increased by the publication year, but that was only significant for prediabetes (P = 0.014). Although publication year does not represent the exact prevalence trend, but this increase might be due to the better screening initiative programs from beginning of new millennium and the inadequate screening program targeting younger adults in developing countries, since the literature lacks the age specific data on undiagnosed diabetes [86, 87]; Finally, HDI was not associated with prevalence of undiagnosed diabetes and prediabetes. In the Zabetian and co-workers [85] study they searched the published studies on diabetes from MENA region, but its search strategy was not sensitive. They noted that the data on undiagnosed diabetes (7 study) is scarce; as a result, they did not yield any pooled analysis for it, as well as prediabetes. The latest IDF diabetes atlas reports that 4.7 and 8.2% of MENA population in 2017 have had undiagnosed diabetes and impaired glucose tolerance, no report on impaired fasting glucose, respectively [2]which are less than our estimates for EMRO. It is worth noting that EMRO has an exceptional situation that can modulate the current and the future prevalence estimates; that is, first, the vast majority of its countries have recently experienced a decrease in economic growth owing to political changes, refugees and migrants and warfare, second, EMRO has the greatest discrepancy amongst its countries regarding Gross National Income (GNI) per capita [88, 89]. We showed HDI was not associated with prevalence of undiagnosed diabetes and prediabetes. In addition, generally both highest undiagnosed diabetes and prediabetes prevalence belong to the very high HDI countries, as well as the highest diagnosed diabetes. This may appear counterintuitive [2]; but some explanations might be hypothesized: first, in countries with higher resources the better national screening program, encouraged in the past two decades by the responsible organizations, could identify more previously undiagnosed patients which are reflected in the publications; second, notwithstanding the proposed effect of urbanization in development and onset of diabetes [90, 91], some studies from developing countries have implied that rapid urbanization and development cannot fully justify the changes in lifestyle to be a risk factor causing diabetes [92, 93]; and third, Dwyer-Lindgren et al. [17] estimated

the trend in the prevalence of undiagnosed and total diabetes in United States in county-level from 1999 to 2012. They showed some insightful results: (1) Undiagnosed diabetes prevalence ranged from 3.2% to 6.8%, (2) Even in a developed country like United States, the rate of undiagnosed diabetes varies between regions due to the unequal distribution of public health strategies, (3) Between 1999 and 2012, the undiagnosed diabetes prevalence was increased in almost all counties, (4) A better screening plan and public health strategy might increase the total diabetes prevalence as time goes by, which diagnosed diabetes shares a higher proportion of this increase [94], and (5) Deep South counties had a higher prevalence of diagnosed and undiagnosed diabetes, simultaneously. Also, upper West, Midwest and parts of New England had a lower prevalence of diagnosed and undiagnosed diabetes, simultaneously. In conclusion, the authors affirmed that socioeconomic and demographic factors cannot solely explain all variations. And even the underlying factors causing disparity in socioeconomic and demographic variables are not fully understood. However, it can be said that managing diabetes is like a road and the epidemiologic statistics pattern is driven by efforts devoted to control and to prevent diabetes. For EMRO, where diabetes growth rate is higher compare to the other regions, this is still an untraveled road. Another finding that supports the abovementioned sophisticated background is the simultaneous high and low prevalence of undiagnosed diabetes and prediabetes, respectively. Screen-and-Treat strategies cannot reduce the diabetes prevalence in a large extent [95]; while, it is assumed that the cost-effective and user-friendly interventions of primary health care is an effective and a comprehensive approach in prevention, early detection and management of diabetes [96]. The optimum integrated primary health care and community settings with secondary care and tertiary referral centers might be the best strategy; that is, health policy makers must pay attention to the trade-off between the consequent health-care system workload due to screening program and local health-care resources [84]. The action plan to prevent and control diabetes, for example “WHO Package of Essential Noncommunicable Disease (PEN)” [97] and “EMRO regional plan of action” [98], is already established according to primary health care. It depends on the comprehensive commitment between the all health-related sectors. Recently, WHO reported that the level of prevention and control of diabetes in EMRO countries is approximately linked to class of income [99]; notwithstanding, most of such programs are not operational, regardless of that most counties are able to adopt these strategies [100]. Additionally, Diabetes primary prevention focusing on lifestyle modifications must be implemented population-wide, especially youth, which is required national efforts. Hence, it is difficult and positive results will achieve in long-term [101]. Again, in this regard, a little number of EMRO countries reported having an operational action plan. An example of domestic implemented program in preventing and controlling NCDs in EMRO, is established in Islamic Republic of Iran, the so-called IraPEN, in 2014. The national NCD committee coordinates the program and universities of medical

sciences lead the action plan across the country. Initially, it was piloted in four provinces and because of its promising results, IraPEN will be expanded to the nationwide scale [102, 103]. Estimating the prevalence of undiagnosed diabetes and prediabetes is sophisticated especially in the regions with limited resources. In addition to the number of limitations, several studies challenged the magnitude of undiagnosed diabetes which often obtained by a single none-repetitive test- mostly fasting plasma glucose and oral glucose tolerant testlikely our data, because of some issues on its definition can be misleading. These are: (1) intrapersonal variability in measurements that demands a second test as a confirmatory test [104-106], either a same test at two different time [105] or even two different tests at the same time; since asking for the second visit is not a reasonable decision in epidemiological surveys regardless of the fact that those tests are performed on one blood draw [13], (2) the type of screening test or not using an identical test over time [107], (3) choosing the screening test, especially in limited resource settings, is crucial and is linked to cost, reliability and convenience. Hemoglobin A1c is the best single none-repetitive test in the epidemiological surveys [105]; since, it has the least intrapersonal variability, does not require fasting and or re-attending after 2 hours for glycemic measurement, and better predicts microvascular and macrovascular complications [108, 109]. Also, American Diabetes Association has mentioned it as a high specific diagnostic test [110], (4) A person with self-report of diabetes conventionally classifies as diagnosed diabetes. But this rises the recall bias and a previously diagnosed patient may misclassify or mark as an undiagnosed diabetic [111]. The limitations and strengths of study Our study had several limitations: (1) for some articles, the full-text was not available. We tried to solve this issue by sending a direct request to the authors; however, some of them did not get positive answer or was not available, (2) due to poor representation of results in some studies, including not reporting confidence intervals, sample size or even not reporting the undiagnosed diabetes as obviously it could be presented in the paper, several studies were excluded from the meta-analysis, (3) some of the studies reported the proportion of undiagnosed diabetes out of total diabetes; hence, we had to recalculate their results to yield the undiagnosed diabetes in study population, (4) we only included English journal publications that may cause language publication bias and publication bias, (5) several methodological factors could rise the chance of under- or overestimation and the subsequent outlier, comprising small sample size, insufficient or lack of studies in some countries, lack of recent publications from some countries, varying age lower limit as an inclusion criteria, (6) screening tests (fasting plasma glucose, hemoglobin A1c, random blood sugar, and oral glucose tolerant test- alone or combinations) were different and diagnostic criteria were changed or different amongst studies. Notably, most of them applied a single test for each participant that may miss a considerable proportion of diabetics, especially older patients

by fasting plasma glucose, and prediabetics since it is suggested that different ethnicities may predominate as liver insulin resistant or skeletal muscle insulin resistant, making impaired fasting glucose or impaired glucose tolerance a better screening test, (7 [112]) most studies were not yielded age- and sex specific prevalence, so we could not do further analysis. These limitations withstanding, our study also has a number of strength: First, we used a sensitive search strategy to identify all the available English journal publications even in the grey literature and references; second, in addition to excluding duplicates, some studies overlapped in studied population. In this scenario, only one set of data was included into analysis; finally, we performed meta-regression analyses based upon HDI and publication year to describe whether variation in trend of undiagnosed diabetes and prediabetes prevalence is existed between studies.

Conclusion In summary, to our knowledge, this is the first meta-analysis which yields an up-to-date representation of both undiagnosed diabetes and prediabetes prevalence in EMRO. While, the prevalence was high for both conditions and increased with passing time, our estimates were higher compared to the in line studies. An effective strategy in prevention, early detection and management of diabetics would be integrating the primary health care strategies with secondary and tertiary health levels to yield universal health coverage. In addition, in light of the fact that only a quarter of the countries in EMRO were included in the national population based survey involving blood glucose measurement within the past 5 years, clearly, more high quality surveys in most EMRO countries are urgently demanded. Also, we recommend that future studies predict the prevalence of undiagnosed diabetes or prediabetes by an identical screening tool, especially hemoglobin A1c, as well as the unique diagnostic criteria.

Recommendation for future research Due to the high prevalence of unknown diabetes in this area and the various complications associated with diabetes, large-scale studies are recommended to screen for at-risk patients and early detection of disease.

Conflicts of interest The authors declare no conflicts of interest.

Author Contributions All authors conceived the study and were responsible for designing the protocol. AM, MF, SH, SZ and AH designed the study. SH did the literature search and, together with MF, and AH selected the studies, extracted the relevant information. All authors synthesized the data. AM and AMM wrote the first draft of the paper. SH, AM, and SZ provided critical guidance on the analysis and overall direction of the study. All authors critically revised successive drafts of the paper and approved the final version. Details of ethics approval This study approved by the Shiraz University of Medical Sciences ethical committee (Code: IR.SUMS.REC.1397.170).

Funding The present article was financially supported by the Shiraz University of Medical Sciences [grant No: 1396-01-106-16651].

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Appendix 1. Search strategy in PubMed from January 1 2000 to March 1 2018 # 1. (Iceberg [Title/Abstract]) OR early onset [Title/Abstract]) OR hidden [Title/Abstract]) OR newly diagnosed [Title/Abstract]) OR newly [Title/Abstract]) OR unknown [Title/Abstract]) OR undiagnosed [Title/Abstract]) OR undetected [Title/Abstract]) OR "Pre-diabetic State"[Mesh]) OR "pre-diabetic"[Title/Abstract]) #2. ("Diabetes Mellitus"[Mesh]) OR "Hyperglycemia"[Mesh]) OR "T2DM"[Title/Abstract]) OR "T2D"[Title/Abstract]) OR "diabetes"[Title/Abstract]) OR "impaired glucose tolerance"[Title/Abstract]) OR "impaired fasting glucose"[Title/Abstract]) #3. ("Epidemiology"[Title/Abstract]) OR "prevalence"[Title/Abstract]) OR "Incidence"[Title/Abstract]) OR "Occurrence"[Title/Abstract]) OR "Frequency"[Title/Abstract]) #4. ("EMRO"[Title/Abstract]) OR "Eastern Mediterranean Region"[Title/Abstract]) OR "Eastern Mediterranean Regional"[Title/Abstract]) OR "Yemen"[Title/Abstract]) OR "United Arab Emirates"[Title/Abstract]) OR "Tunisia"[Title/Abstract]) OR "Syria"[Title/Abstract]) OR "Syrian Arab Republic"[Title/Abstract]) OR "Sudan"[Title/Abstract]) OR "Somalia"[Title/Abstract]) OR "Saudi Arabia"[Title/Abstract]) OR "Qatar"[Title/Abstract]) OR "Palestine"[Title/Abstract]) OR "Pakistan"[Title/Abstract]) OR "Oman"[Title/Abstract]) OR "Morocco"[Title/Abstract]) OR "Libya"[Title/Abstract]) OR "Lebanon"[Title/Abstract]) OR "Kuwait"[Title/Abstract]) OR "Jordan"[Title/Abstract]) OR "Iraq"[Title/Abstract]) OR "Iran"[Title/Abstract]) OR "Egypt"[Title/Abstract]) OR "Djibouti"[Title/Abstract]) OR "Bahrain"[Title/Abstract]) OR "Afghanistan"[Title/Abstract]) #5. (#1 AND #2 AND #3 AND #4)

Appendix 2. JBI critical appraisal checklist applied for included studies in the systematic review 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48

Author, year Eltom, 2018 Niroomand, 2017 Islam Saeed, 2017 Zafar, 2016 Yazdanpanah, 2016 Latifi, 2016 Elmadhoun, 2016 Bahijri, 2016 Saeed, 2016 Noor, 2015 Najafipour, 2015 Memish, 2015 Khalilzadeh, 2015 Katibeh, 2015 Al-rubeaan, 2015 Afifi, 2015 Mansour, 2014 Esteghamati, 2014 El Bcheraoui, 2014 Ben Romdhane, 2014 Al-Rubeaan, 2014 Lotfi, 2013 Al Riyami, 2012 Bennet, 2011 Zafar, 2011 Al-Windi, 2011 Veghari, 2010 Saadi, 2010 Saadi, 2010 Mahar, 2010 Al-Baghli, 2010 Albache, 2010 Al Khalaf, 2010 Shera, 2010 Bener, 2009 Shaikh, 2008 Sajjadi, 2008 Mansour, 2008 Hadaegh, 2008 Azimi-Nezhad, 2008 Ajlouni, 2008 Shera, 2007 Sadeghi, 2007 Saadi, 2007 Al Osaimi, 2007 Afghani, 2007 Malika, 2005 Al-Nozha, 2004

Q1 Yes No No Yes Yes No No Yes Yes No Yes Yes Yes Yes Yes Yes Yes Yes Yes No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes No Yes Yes

Q2 Yes Yes No Yes Yes No Yes Yes Yes Yes Yes Yes Yes No No Yes Yes No No No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes

Q3 Yes Yes Yes No Yes Yes Yes Yes Yes Yes Yes Yes No Yes Yes No Yes Yes Yes Yes Yes Yes Yes No No Yes Yes No No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes No No Yes Yes Yes

Q4 No No Yes Yes No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Unclear Yes Yes Unclear Unclear Yes Yes Yes Yes Yes Yes Unclear Yes Yes Unclear Unclear Yes Yes Yes Yes Yes Yes Yes Yes Yes Unclear

Q5 Yes No No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Unclear Yes Yes Yes Yes Yes Yes Unclear Yes Yes Unclear Yes Yes Yes Yes Yes Yes Yes Unclear Yes Yes Unclear Yes Unclear Yes Unclear Yes Yes

Q6 Yes Yes No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes

Q7 Yes Yes Yes Yes No No Yes Yes No No Yes Yes Yes Yes No No Yes Yes Yes Yes No No Yes Yes No No Yes Yes Yes Yes No No Yes Yes Yes Yes Yes Yes No No Yes Yes No No Yes Yes Yes Yes

Q8 No Yes No Yes Yes No Yes Yes Yes No Yes Yes Yes Yes No No No Yes No Yes Yes No Yes Yes Yes No Yes Yes Yes Yes No No No Yes No Yes No Yes Yes No Yes Yes Yes No Yes Yes Yes Yes

Q9 No No Yes Yes No No Yes Yes No No Yes Yes Yes Yes No Yes Yes Yes Yes Unclear Yes Unclear Yes Yes Unclear Yes Yes Yes Yes Yes Yes Yes Unclear Yes Yes Unclear Yes Unclear Yes Unclear Yes Yes Yes Yes Yes Yes Unclear Yes

49 Al-Lawati, 2002 Yes No Yes Yes Yes Yes No No 50 Gunaid, 2002 Yes Yes Yes Yes Yes Yes No No 51 Basit, 2002 Yes Yes Yes Unclear Yes Yes Yes No 52 Abdul-Rahim, 2001 Yes Yes No Unclear Yes Yes No No 53 Riste, 2001 Yes Yes No Yes Unclear Yes Yes Yes 54 Kadiki, 2001 Yes Yes Yes Yes Yes Yes Yes Yes 55 Husseini, 2000 Yes Yes Yes Yes Yes Yes No Yes Q1. Was the sample frame appropriate to address the target population? Q2. Were study participants sampled in an appropriate way? Q3. Was the sample size adequate? Q4. Were the study subjects and the setting described in detail? Q5. Was the data analysis conducted with sufficient coverage of the identified sample? Q6. Were valid methods used for the identification of the condition? Q7. Was the condition measured in a standard, reliable way for all participants? Q8. Was there appropriate statistical analysis? Q9. Was the response rate adequate, and if not, was the low response rate managed appropriately?

Yes Unclear Yes Unclear Yes Unclear Yes