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Type 2 diabetes prevalence in Pakistan: what is driving this? Clues from subgroup analysis of normal weight individuals in diabetes prevalence survey of Pakistan

Aamir, Azizul Hasana,,*; Ul-Haq, Ziab,,c,,*; Fazid, Sherazb; Shah, Basharat Hussainb; Raza, Abbasd; Jawa, Alie; Mahar, Saeed A.f; Ahmad, Ibrarg; Qureshi, Faisal Masoodh; Heald, Adrian H.i,,j

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Cardiovascular Endocrinology & Metabolism: December 2020 - Volume 9 - Issue 4 - p 159-164
doi: 10.1097/XCE.0000000000000212
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Abstract

Introduction

Type 2 diabetes mellitus (T2DM) is one of the main public health issues of concern worldwide and its incidence is increasing particularly in the developing world [1]. Due to complications linked with T2DM, it can have a profound impact on a person’s life and also on the society as a whole. Previously, diabetes was considered as a disease of the economically developed countries but as a result of urbanization, change in diet and adoption of a more inactive lifestyle for majority of the people; its prevalence has been increased in most developing nations, including Pakistan [2].

We recently reported a much higher burden of T2DM at 16.98 % and of prediabetes of 10.91% in a survey of 18 856 eligible participants in a representative sample covering all of Pakistan with even higher rates in an independent study by Basit et al. [3] who found a T2DM prevalence 26.3%, and prediabetes prevalence of 14.4%.

In this article, we report further analysis based on people with a normal range BMI; in other words, those who are phenotypically normal but metabolically abnormal, given the high prevalence of impaired glucose handling that we saw in nonoverweight individuals. The participants are from all regions of Pakistan, and we also report the way that specific factors were related to the probability of having prediabetes or T2DM. This is the first large-scale analysis of this kind to be undertaken in Pakistan.

Methodology

Together with partner organizations, we conducted a countrywide cross-sectional study for the prevalence of T2DM between April 2017 and November 2017. Sample selection was based on multistage stratified cluster design. Further details of the methodology are given in our recent article. Data of individuals having normal BMI were extracted from this study [4].

We categorized age into six groups, that is, 20–30, 31–40, 41–50, 51–60 and 61 years and above. Area of residence was classified as rural or urban based on the criteria provided by the local government which was based on the Pakistan national census 2017 [5]. Self-reported education status of the participants was categorized into: no formal education, primary, secondary and graduation/postgraduation. BMI was categorized into: <18.5 (underweight), 18.5–24.9 (normal weight), 25–29.9 (overweight), 30–34.9 (class I obese), 35–39.9 (class II obese) and >40 kg/m2 (class III obese) based on WHO criteria [6]. Waist circumference was categorized into ≤93.9 cm for males/≤79.9 cm for females (normal weight), 94–102 cm for males/80–88 cm for females (overweight) and >102 cm for males/>88 cm for females (obese) [6]. Past history of diabetes in family members was self-reported physician diagnosed and was categorized to negative or positive. Smoking status was by self-report according to standard criteria.

Participants were classified as known T2DM based on self-reporting and physician diagnosed who were on dietary or physical activity advice, oral antidiabetes medications or injectables, that is, insulin. This known T2DM group of individuals could both be on a single medication, on different drug combinations or diet and physical activity advice.

Diagnosis of T2DM was based on results of HbA1c in line with the WHO levels for nondiabetes, prediabetes (nondiabetic hyperglycaemia) and diabetes [7]. For multivariate logistic regression analysis, T2DM was dichotomized to no (0; HbA1c <6.5% or 48 mmol/mol level) and yes (1; HbA1c ≥6.5% or 48 mmol/mol).

Ethics approval was obtained as described in our previous related publication [4]. For analysing the differences in participants’ characteristics by glycaemic category, ANOVA and χ2 test were used for continuous and categorical data, respectively. The multivariate logistic regression model was used for the examination of association between glycaemic status and potential risk factors, that is, age, gender, area of residence, educational status, past history of diabetes in family and smoking status.

Stata version 14 (StataCorp, College Station, Texas, USA) was used for performing analysis. The level of statistical significance was defined as P <0.05.

Results

A total of 18 856 participants aged at least 20 years and above were recruited from 378 clusters among which 216 clusters were in rural areas. Mean age of the participants was 45.23 years (SD 13.97) and more than half, that is, 10 116 (53.55%) were men (Table 1).

Table 1 - Characteristics of the participants by diabetes categories (n = 6824) having normal BMI
Variable Nondiabetics (n = 5806), N (%) Diabetic (n = 1018), N (%) P value
Age (years)
 20–30 1174 (95.21) 59 (4.79) <0.001
 31–40 1118 (90.6) 116 (9.4)
 41–50 1577 (84.47) 290 (15.53)
 51–60 951 (78.34) 263 (21.66)
 60 and above 986 (77.27) 290 (22.73)
Gender
 Men 3038 (85.65) 509 (14.35) 0.170
 Women 2768 (84.47) 509 (15.53)
Education
 No formal education 4023 (83.8) 778 (16.2) <0.001
 Primary 1209 (86.36) 191 (13.64)
 Secondary 252 (90.65) 26 (9.35)
 Graduate 322 (93.33) 23 (6.67)
Area
 Urban 3161 (87.37) 457 (12.63) <0.001
 Rural 2645 (82.5) 561 (17.5)
Family history
 Negative 4467 (90.59) 464 (9.41) <0.001
 Positive 1339 (70.73) 554 (29.27)
Smoking
 Never 5393 (85.32) 928 (14.68) 0.109
 Ex-smoker 130 (80.25) 32 (19.75)
 Current smoker 283 (82.99) 58 (17.01)
 Systolic BP 124.72 (14.59) 129.46 (16.78) <0.001
 Diastolic BP 81.68 (10.01) 83.30 (11.49) <0.001
BP, blood pressure.

It was found that 13 834 (73.24%) study participants had no formal education, and 1209 (6.40%) had attained a graduate degree. A family history of T2DM was present in 6010 (31.81%) participants. There was a difference in the proportion of those with no formal education between the urban (80%)/rural (60.7%) studied (χ2 = 2.4, P < 0.001).

Overall on WHO cutoff for BMI, underweight were 345 (1.83%), normal weight were 6839 (36.20%), overweight were 8038 (42.55%), class I obese were 2864 (15.16%), class II obese were 633 (3.35%) and class III obese were 172 (0.91%). On the waist circumference cutoff, normal weight were (n = 12 865), 8574 (66.64%), overweight were 2318 (18.02%) and obese were 1974 (15.34%) [4]. Of the total group, 4148 (21.96%) were defined as hypertensive (BP 140/90 mmHg or more) according to British Heart Foundation Criteria. Other results for all participants are described in the recently published article [4].

Categorizing by WHO generic criteria for normal BMI (18.5–24.9), there remained a significantly elevated burden of T2DM even in participants of normal BMI at 14.92% and in underweight participants at 10.14% (Fig. 1). In line with this finding, there were higher rates for prediabetes 9.79% in the normal BMI category (18.5–24.9) and 8.99% in the underweight category. For normal waist circumference for men/women combined, the prevalence of T2DM was 13.32% and of prediabetes was 7.52% [6].

Fig. 1
Fig. 1:
Characteristics of the participants by diabetes categories (n = 6824) having normal BMI.

For normal BMI defined on the basis of the WHO Asian definition [8] as 18.5–22.9 (n = 3661), the rate of T2DM was 14.18% and prediabetes was 9.42%. The rates of T2DM (two-sample test of proportions P = 0.307) and prediabetes (P = 0.541) were not materially different by BMI cutoff for normal weight.

For those of normal BMI, the prevalence of T2DM increased with progressively higher age category (Fig. 1): 20–30 (4.79%); 31–40 (9.4%); 41–50 (15.53%); 51–60 (21.66%); and 61 years and above (22.73%). This was a similar trend to that seen in the whole sample [4].

For those of normal BMI, educational attainment influenced rates of T2DM with the prevalence in the categories decreasing by the category of educational attainment (Fig. 1): no formal education – 16.2%; primary school education – 13.64%; secondary school education – 9.35%; graduate level education – 6.67% (P < 0.001). There was a higher prevalence of T2DM in individuals living in rural areas 17.50% vs urban areas 12.63% (P < 0.001) (Fig. 1).

For those normal BMI individuals with a family history of T2DM, there was a high prevalence of T2DM at 29.27% vs 9.41% no family history of T2DM (P value < 0.001). There was no association of the smoking status in different glycaemic categories (Fig. 1). Both systolic and diastolic blood pressures were increased by the glycaemic category (P < 0.001). Diabetes was found in women more often than in men.

On applying multivariate logistic regression model (Table 2), there was a statistically significantly increased risk of T2DM and prediabetes (combined categories) with age groups [adjusted odds ratio (OR) 2.1, 3.3, 4.5 and 4.8], P < 0.001 for ages groups (years) 31–40, 41–50, 51–60 and 61 and above, respectively, compared to age 20–30 years]. Similarly, there was a significantly higher risk of T2DM with self-reported educational status (adjusted OR for no formal education vs graduate studies 2.4 [95% confidence interval (CI) 1.5–3.8]. There was also a significantly increased risk of T2DM in individuals having a positive family history of T2DM [adjusted OR 4.3 (95% CI 7.0–11.5)] than with no family history of T2DM.

Table 2 - Logistic regression analysis of the participant characteristics associated with having type 2 diabetes in BMI Normal participants (HbA1c ≥ 6.5% DCCT aligned/48 mmol/mol IFCC units) (n = 6824 for normal BMI)
Univariate Multivariate
Variable OR 95% CI P value OR 95% CI P value
Age (years)
 20–30 1 1 1 1 1 1
 31–40 2.06 1.49, 2.85 <0.001 2.08 1.49, 2.90 <0.001
 41–50 3.66 2.74, 4.89 <0.001 3.26 2.39, 4.44 <0.001
 51–60 5.50 4.10, 7.39 <0.001 4.52 3.29, 6.19 <0.001
 61 and above 5.85 4.37, 7.84 <0.001 4.77 3.47, 6.57 <0.001
Gender
 Men 1 1 1 1 1 1
 Women 1.10 0.96, 1.25 0.171 0.95 0.82, 1.11 0.535
Education
 No formal education 2.71 1.76, 4.16 <0.001 2.38 1.50, 3.78 <0.001
 Primary 2.21 1.41, 3.47 0.001 1.40 0.86, 2.28 0.171
 Secondary 1.44 0.80, 2.59 0.218 1.43 0.77, 2.63 0.254
 Graduation 1 1 1 1 1 1
Area
 Rural 1.47 1.28, 1.68 <0.001 1.10 0.93, 1.28 0.261
 Urban 1 1 1 1 1 1
Family history
 Positive 3.98 3.47, 4.57 <0.001 4.29 3.71, 4.96 <0.001
 Negative 1 1 1 1 1 1
Smoking status
 Nonsmoker 1 1 1 1 1 1
 Ex-smoker 1.43 0.97, 2.12 0.074 1.01 0.66, 1.54 0.978
 Current smoker 1.19 0.89, 1.59 0.239 1.09 0.79, 1.50 0.605
 Systolic BP 1.02 1.02, 1.02 <0.001 1.01 1.01, 1.02 <0.001
 Diastolic BP 1.02 1.01, 1.02 <0.001 1.00 0.99, 1.01 0.779
BP, blood pressure; CI, confidence interval; DCCT, Diabetes Control and Complications Trial; IFCC, International Federation of Clinical Chemistry and Laboratory Medicine; OR, odds ratio.

Multiple logistic regression for the sample as a whole indicated that categorizing by BMI, being overweight/obese increased the likelihood of having T2DM by 20% [OR 1.2 (95% CI) 1.1–1.4], independent of age category, gender, family history of T2DM, educational attainment and region.

Discussion

This article comes from the first national-level community-based study conducted in the region based on HbA1c on a total of 18 856 subjects from Pakistan. This is the largest study from Pakistan till date. The survey includes parts of Pakistan which until recently were accessible to all but a few Europeans and is comprehensive in its coverage.

The WHO Asian cutoff did not materially change the proportion of prediabetes and T2DM vs the WHO International cutoff. Therefore, the lower cutoff for BMI has limited utility in the Pakistan population.

The findings of high rates of T2DM/prediabetes even in normal BMI individuals and in individuals who were underweight raises the question of what dietary/environmental factors are driving the seemingly relentless increase in the prevalence of T2DM and of prediabetes across Pakistan with implications for many middle- and low-income countries. We excluded underweight participants from the detailed analysis of factors associated with impaired glucose handling (prediabetes or T2DM) because of the potential for undiagnosed conditions (including T2DM hyperglycaemia associated weight loss) to act as confounders.

The risk of T2DM was greatly increased by prior family history and by age decade but not by urban vs rural living environment. The factors associated with T2DM in normal BMI individuals must be seen in the context of the prevalence of T2DM across Pakistan being 16.98% (95% CI 16.44–17.51) and prediabetes 10.91% (95% CI 10.46–11.36).

In normal BMI individuals, there was a significant increase in T2DM prevalence with decreasing level of formal education. This has major implications for the way that messages about glycaemic risk need to be given to the Pakistan general population in ways that do not require written material as written messages are irrelevant to many.

The factors that underlie the very high prevalence of T2DM in Pakistan, even in rural areas are not clear. It is possible that specific strains of wheat or even the way that bread is made may influence glucose handling [9]. It has been proposed that arsenic and pesticides applied to crops and in the soil may contribute to the very high prevalence of diabetes in Pakistan [10]. Another possibility is environmental agents that directly damage pancreatic beta cells. This is an area that we plan to explore in the future.

The increase of 20% in the risk of T2DM with overweight/obese status, while significant is much less than that reported in studies from other parts of the world, for example [11], who described a 63% increase in the risk of T2DM for overweight vs normal BMI and 215% increase in the risk for class I obesity with even higher risk for classes II and III. Therefore, the BMI of 25 may be a less meaningful cutoff point for the risk of T2DM in Pakistan ethnicity individuals than in other ethnic groups.

While we did not carry out any measures of body fat per se, our results do accord with the hypothesis of Taylor and Holman [12] that each participant has their own personal fat threshold (PFT) which, if exceeded, can lead to the development of T2DM. Importantly, they hypothesized that PFT is independent of BMI. As stated by the authors, the concept allows both understandings of T2DM development in the nonobese and diabetes remission after significant decrease in weight in those people who remain obese.

In a 2016 study of lean vs obese T2DM [13] in the Chinese Han population, a genetic risk score (GRS) which included KCNQ1, TCF7L2, HHEX and TCF2 was associated with the risk for lean T2D vs obese T2DM. Notably, the T2DM GRS contributed to lower obesity-related measurements and greater pancreatic beta-cell dysfunction. Also in Yaghootkar’s 2014 Diabetes article [14], convincing genetic evidence was presented for a normal-weight ‘metabolically obese’ phenotype linking insulin resistance, hypertension, coronary artery disease (CAD) and type 2 diabetes. Importantly, this phenotype conferred a high risk of hypertension, T2DM and CAD irrespective of a lower BMI.

Further work need to be done on diet and nutritional status of pregnant women. The thrifty gene hypothesis may be relevant with the low threshold of glucose and body fat of new born in malnourished rural population as it may predispose them to diabetes at younger individuals and with normal BMI or relatively lesser increase in weight [15].

Strengths and limitations

Strengths

One of the strengths of our study is that we carried out the analysis on 18 856 participants with the characterization of their demographic and educational status. This study is the first national-level community-based study in Pakistan to use HbA1c as a diagnostic tool for T2DM. In our study, we did all the screening early in the day time so that working men who are the bread winners of the family had an equal chance to be part of the study.

Limitations

The absence of any genetic characterization of the individual participants relates to local concerns in some areas with regards to the perceived potential for misuse of the genetic material. Also, we excluded 16% of recruited participants due to anaemia. Finally, educational attainment was determined by self report and not externally validated.

Conclusion

This Pakistan national diabetes prevalence study has shown higher than expected rates of T2DM/prediabetes in normal BMI individuals. Within this group, educational attainment, age and family history of T2DM were powerful independent predictors of the likelihood of having prediabetes/T2DM.

The association of BMI 25 or more with T2DM is much less so than in other parts of the world. Genetic factors may be predisposing to a lower PFT in Pakistan ethnicity individuals with major consequences for glucose handling if the threshold is crossed. Specific nutritional factors may contribute to the high rates of T2DM that we describe and this area merits further detailed evaluation.

Targeted screening of older individuals with a family history of T2DM, particularly if they have not enjoyed educational opportunities, even of normal BMI may be of a significant benefit in the Pakistan population.

Acknowledgements

A.H.A. and Z.U.H. conceived the study. A.H.A., S.M., F.Q., A.J., A.R. and I.A. collected the data. A.H.A., B.H.S. and S.F. study design and data monitoring. Z.U.H., A.H.A., S.F., A.H. and B.H.S. conducted the analysis and wrote the manuscript. All authors critically reviewed the manuscript.

Conflicts of interest

There are no conflicts of interest.

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Keywords:

diabetes; HbA1c; normal BMI; Pakistan; prevalence; type 2 diabetes mellitus

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