Mon, Jun 17, 2024
[Archive]
Volume 8, Issue 4 (Nov 2023)
JNFS 2023, 8(4): 544-552 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Peigan P, Mirzaei M, Marques-Vidal P, Fallahzadeh H, Kraemer A, Sarebanhassanabadi M. Comparison of 5-year Incidence of Type 2 Diabetes in Obese and Non-Obese Adult Population: The YaHs Cohort. JNFS 2023; 8 (4) :544-552
URL: http://jnfs.ssu.ac.ir/article-1-667-en.html
URL: http://jnfs.ssu.ac.ir/article-1-667-en.html
Parisa Peigan 
, Masoud Mirzaei , Pedro Marques-Vidal , Hossein Fallahzadeh , Alexander Kraemer , Mohammadtaghi Sarebanhassanabadi *
, Masoud Mirzaei , Pedro Marques-Vidal , Hossein Fallahzadeh , Alexander Kraemer , Mohammadtaghi Sarebanhassanabadi *
Yazd Cardiovascular Research Center, Non-communicable diseases research institute, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
Full-Text [PDF 513 kb]
(120 Downloads)
| Abstract (HTML) (859 Views)
.PNG)
Full-Text: (71 Views)
Comparison of 5-year Incidence of Type 2 Diabetes in Obese and Non-Obese Adult Population: The YaHs Cohort
Parisa Peigan; MSc1, Masoud Mirzaei; MD, PhD2, Pedro Marques-Vidal; PhD3, Hossein Fallahzadeh; PhD1,
Parisa Peigan; MSc1, Masoud Mirzaei; MD, PhD2, Pedro Marques-Vidal; PhD3, Hossein Fallahzadeh; PhD1,
Alexander Kraemer; PhD4 & Mohammadtaghi Sarebanhassanabadi; PhD*2
1 Department of Biostatistics and Epidemiology, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran; 2 Yazd Cardiovascular Research Center, Non-communicable diseases research institute, Shahid Sadoughi University of Medical Sciences, Yazd, Iran; 3 Department of Internal Medicine, BH10-642, Rue du Bugnon 46, CH-1011 Lausanne, Switzerland; 4 Department of Health Sciences, Bielefeld University, Bielefeld, Germany.
| ARTICLE INFO | ABSTRACT | |
| ORIGINAL ARTICLE | Background: Obesity is an important predictor of diabetes. Defining the risk of diabetes among obese subjects is important for preventive health strategies. This study aims to compare the 5-year incidence of diabetes in obese and non-obese adult participants aged 20-70 years in a large population sample of central Iran. Methods: In this prospective study, 9964 people aged 20-70 years were selected between 2014 and 2015 using multi-stage cluster sampling from Yazd Greater Area, Iran. Participants with diabetes were excluded and non-diabetic individuals were evaluated for incident diabetes after a five-year follow-up. Logistic regression was used to find the association between obesity and 5-year incidence of diabetes in bivariate, and multivariate adjusted models for age, sex, physical activity, medical history, marital status, smoking, and education. Results: Out of the initial 9964 participants, 1383 (14%) were excluded due to prevalence of diabetes. The remaining 8413 (86.0%) participants were re-examined in 2019-2020. After five years of follow up, diabetes occurred in 6.6% (n=556) of the participants. The incidence of diabetes in obese men and women was 10.4% (n=109) and 9.9% (n=264), respectively; however, it was 4.5% (n=143) and 2.8% (n=40) in their non-obese counterparts (P<0.01). After multivariate analysis, obesity was associated with a higher likelihood of diabetes in men (OR=1.77, 95% CI: 1.33-2.35), women (OR=2.23, 95% CI: 1.55-3.21), and overall (OR=1.99, 95%CI: 1.60-2.48). Similar findings were obtained in participants aged under and over 60 years (P<0.05). Conclusion: There was a positive association between obesity and 5-year incidence of diabetes in an Iranian adult population. Interventions are required to change lifestyle in the adult population especially in younger participants to prevent obesity and diabetes. Keywords: Diabetes; Obesity; Incidence; Cohort study |
|
| Article history: Received: 3 Jul 2022 Revised: 28 Aug 2022 Accepted: 28 Sep 2022 |
||
| *Corresponding author: mtsareban@gmail.com Yazd Cardiovascular Research Center, Non-communicable diseases research institute, Shahid Sadoughi University of Medical Sciences, Yazd, Iran. Postal code: 8917945556 Tel: +98 35 35231421 |
Backgroun
The prevalence of obesity is increasing worldwide (De Onis and Blössner, 2000, Mokdad et al., 2000). It is predicted that by 2030, there will be over 2.16 billion overweight and 1.12 billion obese globally (World Health Organization, 2016). The World Health Organization has reported that obesity is a global epidemic (World Health Organization, 1997). In addition to causing insulin resistance and impaired glucose tolerance, obesity also leads to metabolic disorders associated with diabetes and consequently, increasing overall morbidity and mortality (Larijani et al., 1995).
The proportion of people with type 2 diabetes mellitus (T2DM) and obesity has increased throughout Asia, and the rate of increase and the prevalence of T2DM have now reached epidemic levels in Asia. The International Diabetes Federation (IDF) estimates that 194 million people were diagnosed with diabetes in 2003 and 333 million by 2025 (Roglic and King, 2000).
According to IDF, 463 million adults aged 20 to 79 years worldwide (9.3% of all adults in this age group) have diabetes, and 79.4% of them live in low- and middle-income countries (Williams et al., 2019). According to a study in India, the incidence of T2DM during 10 years of follow-up (2019) was estimated at 21.9% (Vijayakumar et al., 2019). In addition, in this study, the most important risk factors for T2DM were central obesity and overweight. The findings from other studies show conclusive evidence that the incidence of T2DM and pre-diabetes is rapidly increasing in developing countries (Mirzaei et al., 2020, Vijayakumar et al., 2019).
During the Tehran Lipid and Glucose Study in 2007, after the 3.6-year follow-up, the adjusted odds ratio (OR) for diabetes for overweight and obese people compared to normal-weight people was 1.76 and 3.54, respectively. In addition, the risk attributed to the population was 23.3% and 37.1%, respectively. Also, in this study, the independent role of abdominal obesity in the development of diabetes was proven (Hosseinpanah et al., 2007a). Also, according to a study in Yazd, the incidence of diabetes during a 10-year follow-up was 21.4 per 1,000 people of a population per year. In this study, the incidence of diabetes increased by increasing abdominal obesity and body mass index (BMI) (Namayandeh et al., 2019).
The risk of diabetes in Yazd province is twice the national average. Therefore, the high prevalence of diabetes in Yazd can be a serious problem for the health of the people of this province (Sarebanhassanabadi et al., 2020).
In addition, overweight and obesity affect more than half of the population (64%) in Yazd city, and abdominal obesity also has a high prevalence (Mirzaei et al., 2017). According to a study in 2022, the 10-year cumulative incidence of obesity was 14.8% of total population (20.8% for women and 10.5% for men) (Moghtaderi et al., 2022). Therefore, considering obesity as one of the critical concerns of public health in Yazd city, the present study compared the 5-year incidence of T2DM according to presence or absence of obesity in a representative sample of Yazd Greater Area inhabitants aged 20-70 years.
Materials and Methods
Study population: The Yazd Health Study (YaHs) is a prospective cohort study which was initially established in 2014-2015 and included 9964 adults aged 20-70 years living in Yazd Greater Area, Iran. The participants were selected using cluster random sampling. Initially, 200 clusters were randomly selected based on the participants' residential post codes. Then, each cluster of 50 samples was divided into two equal subgroups of men and women. Each group consists of 10 people (5 men, 5 women) in age groups of 20-29, 30-39, 40-49, 50-59, and 60-69 years, which followed up manually (for 5 years) from the beginning of the study. Participants with diabetes at the baseline, with missing covariates or without follow-up information were excluded from the analyses. Details of the study profile was published elsewhere (Mirzaei et al., 2018).
Measurements: In the first phase (baseline) of the cohort study in 2014-2015, biochemical tests, demographic data, smoking status, physical activity, and socioeconomic status were recorded for each participant, and re-evaluated in 2019-2020. Anthropometric measurements were measured by standard methods. Waist circumference (WC) was measured with a non-stretch tape measure at the point between the lower edge of the last rib and the upper edge of the iliac crest to the nearest 0.5 cm. Weight was measured using an Omron BF511 portable digital scale and body analyzer (Omron Inc. Nagoya, Japan) with minimal clothing and without shoes to the nearest 0.1 kg. Participants with a body mass index (BMI) ≥ 30 kg/m2 and WC ( ≥102 cm in men and ≥88 cm in women), were considered obese.
Blood glucose was measured using Pars Azmoon kits and a Ciba Corning (Ciba Corp., Basel, Switzerland) auto-analyzer. Diabetes was defined using at least one of the following conditions: 1) fasting blood plasma glucose (FPG) ≥126 mg/dl; 2) glycosylated hemoglobin (HbA1C) ≥6.5%; 3) two-hour postprandial plasma glucose (2hpp) ≥200 mg/dl, or 4) diagnosed by a physician and taking glucose-lowering drugs (Rossi, 2018).
Smoking history was classified as never, former, and current. Educational level was categorized as primary, diploma, and academic. Physical activity was defined by answering positively to never, exercising 2 or more times per week. Medical history and marital status was self-reported and categorized as (yes/no) and (single /married).
Ethical considerations: This study was approved by the ethics committee of School of Public Health in Shahid Sadoughi University of Medical Sciences with ethics code: IR.SSU.SPH.REC.1400.082. Informed consent was obtained from all participants in the first phase and in the follow-up phase of the study.
Data analysis: statistical analysis was performed using STATA version 14.0 software (Stata Corp LP, College Station, TX, USA) and SPSS v25.0 (IBM, New York). Descriptive results were expressed as a number of participants (percentage) for categorical variables and as average standard deviation for continuous variables. Between groups comparisons were performed using chi-square for categorical variables and student’s t-test or analysis of variance for continuous variables. Multivariate analysis regarding the determinants of 5-year incidence of diabetes was performed using
logistic regression and the results were expressed as OR and 95% confidence interval (95%CI). Multivariate analysis was adjusted for age continuous), sex, physical activity (categorical), medical history (yes/no), marital status (single/married), smoking history (never, former, current), and education (categorical). Statistical significance was considered P<0.05.
Results
Selection and characteristics of the participants:
Of the initial 9964 participants, 8362 (83.9%) were included in the analysis. The selection procedure is displayed in Figure 1. The 5-year incidence of diabetes in total population was 6.6% (n=556). Characteristics of 5-year incidence of diabetes in men and women are shown in Table 1. There were significant differences in BMI, medical history, marital status, education level, physical activity, and obesity between men and women (P<0.05). Characteristics of the 5-year incidence of diabetes in men and women are reported in Table 2. Participants with higher BMI and WC had higher risk of diabetes (P<0.05).
Five-year incidence of diabetes: The incidence of diabetes according to obesity status overall and stratified by sex is provided in Table 3. The 5-year incidence of diabetes in obese men, women, and overall participants was 10.4%, 9.9%, and 10%, respectively.
The association between obesity and the incidence of diabetes by sex is reported in Table 4. After adjusting for age, sex, physical activity, medical history, marital status, smoking history, and education level, there was a positive significant association between obesity and increased risk of diabetes in men (OR = 1.77, 95% CI: 1.33-2.35), women (OR = 2.23, 95%CI: 1.55-3.21), and total population (OR = 1.99, 95%CI: 1.60-2.48) compared to the non-obese group. On the other hand, participants with obesity had a higher incidence of diabetes, and this association was further confirmed after multivariate analysis; participants with obesity had a two-fold higher likelihood of developing diabetes compared to their non-obese peers. When stratifying on age, younger (<60 years) participants with obesity tended to present a higher likelihood of developing diabetes compared to older, obese participants (Table 5).
The proportion of people with type 2 diabetes mellitus (T2DM) and obesity has increased throughout Asia, and the rate of increase and the prevalence of T2DM have now reached epidemic levels in Asia. The International Diabetes Federation (IDF) estimates that 194 million people were diagnosed with diabetes in 2003 and 333 million by 2025 (Roglic and King, 2000).
According to IDF, 463 million adults aged 20 to 79 years worldwide (9.3% of all adults in this age group) have diabetes, and 79.4% of them live in low- and middle-income countries (Williams et al., 2019). According to a study in India, the incidence of T2DM during 10 years of follow-up (2019) was estimated at 21.9% (Vijayakumar et al., 2019). In addition, in this study, the most important risk factors for T2DM were central obesity and overweight. The findings from other studies show conclusive evidence that the incidence of T2DM and pre-diabetes is rapidly increasing in developing countries (Mirzaei et al., 2020, Vijayakumar et al., 2019).
During the Tehran Lipid and Glucose Study in 2007, after the 3.6-year follow-up, the adjusted odds ratio (OR) for diabetes for overweight and obese people compared to normal-weight people was 1.76 and 3.54, respectively. In addition, the risk attributed to the population was 23.3% and 37.1%, respectively. Also, in this study, the independent role of abdominal obesity in the development of diabetes was proven (Hosseinpanah et al., 2007a). Also, according to a study in Yazd, the incidence of diabetes during a 10-year follow-up was 21.4 per 1,000 people of a population per year. In this study, the incidence of diabetes increased by increasing abdominal obesity and body mass index (BMI) (Namayandeh et al., 2019).
The risk of diabetes in Yazd province is twice the national average. Therefore, the high prevalence of diabetes in Yazd can be a serious problem for the health of the people of this province (Sarebanhassanabadi et al., 2020).
In addition, overweight and obesity affect more than half of the population (64%) in Yazd city, and abdominal obesity also has a high prevalence (Mirzaei et al., 2017). According to a study in 2022, the 10-year cumulative incidence of obesity was 14.8% of total population (20.8% for women and 10.5% for men) (Moghtaderi et al., 2022). Therefore, considering obesity as one of the critical concerns of public health in Yazd city, the present study compared the 5-year incidence of T2DM according to presence or absence of obesity in a representative sample of Yazd Greater Area inhabitants aged 20-70 years.
Materials and Methods
Study population: The Yazd Health Study (YaHs) is a prospective cohort study which was initially established in 2014-2015 and included 9964 adults aged 20-70 years living in Yazd Greater Area, Iran. The participants were selected using cluster random sampling. Initially, 200 clusters were randomly selected based on the participants' residential post codes. Then, each cluster of 50 samples was divided into two equal subgroups of men and women. Each group consists of 10 people (5 men, 5 women) in age groups of 20-29, 30-39, 40-49, 50-59, and 60-69 years, which followed up manually (for 5 years) from the beginning of the study. Participants with diabetes at the baseline, with missing covariates or without follow-up information were excluded from the analyses. Details of the study profile was published elsewhere (Mirzaei et al., 2018).
Measurements: In the first phase (baseline) of the cohort study in 2014-2015, biochemical tests, demographic data, smoking status, physical activity, and socioeconomic status were recorded for each participant, and re-evaluated in 2019-2020. Anthropometric measurements were measured by standard methods. Waist circumference (WC) was measured with a non-stretch tape measure at the point between the lower edge of the last rib and the upper edge of the iliac crest to the nearest 0.5 cm. Weight was measured using an Omron BF511 portable digital scale and body analyzer (Omron Inc. Nagoya, Japan) with minimal clothing and without shoes to the nearest 0.1 kg. Participants with a body mass index (BMI) ≥ 30 kg/m2 and WC ( ≥102 cm in men and ≥88 cm in women), were considered obese.
Blood glucose was measured using Pars Azmoon kits and a Ciba Corning (Ciba Corp., Basel, Switzerland) auto-analyzer. Diabetes was defined using at least one of the following conditions: 1) fasting blood plasma glucose (FPG) ≥126 mg/dl; 2) glycosylated hemoglobin (HbA1C) ≥6.5%; 3) two-hour postprandial plasma glucose (2hpp) ≥200 mg/dl, or 4) diagnosed by a physician and taking glucose-lowering drugs (Rossi, 2018).
Smoking history was classified as never, former, and current. Educational level was categorized as primary, diploma, and academic. Physical activity was defined by answering positively to never, exercising 2 or more times per week. Medical history and marital status was self-reported and categorized as (yes/no) and (single /married).
Ethical considerations: This study was approved by the ethics committee of School of Public Health in Shahid Sadoughi University of Medical Sciences with ethics code: IR.SSU.SPH.REC.1400.082. Informed consent was obtained from all participants in the first phase and in the follow-up phase of the study.
Data analysis: statistical analysis was performed using STATA version 14.0 software (Stata Corp LP, College Station, TX, USA) and SPSS v25.0 (IBM, New York). Descriptive results were expressed as a number of participants (percentage) for categorical variables and as average standard deviation for continuous variables. Between groups comparisons were performed using chi-square for categorical variables and student’s t-test or analysis of variance for continuous variables. Multivariate analysis regarding the determinants of 5-year incidence of diabetes was performed using
logistic regression and the results were expressed as OR and 95% confidence interval (95%CI). Multivariate analysis was adjusted for age continuous), sex, physical activity (categorical), medical history (yes/no), marital status (single/married), smoking history (never, former, current), and education (categorical). Statistical significance was considered P<0.05.
Results
Selection and characteristics of the participants:
Of the initial 9964 participants, 8362 (83.9%) were included in the analysis. The selection procedure is displayed in Figure 1. The 5-year incidence of diabetes in total population was 6.6% (n=556). Characteristics of 5-year incidence of diabetes in men and women are shown in Table 1. There were significant differences in BMI, medical history, marital status, education level, physical activity, and obesity between men and women (P<0.05). Characteristics of the 5-year incidence of diabetes in men and women are reported in Table 2. Participants with higher BMI and WC had higher risk of diabetes (P<0.05).
Five-year incidence of diabetes: The incidence of diabetes according to obesity status overall and stratified by sex is provided in Table 3. The 5-year incidence of diabetes in obese men, women, and overall participants was 10.4%, 9.9%, and 10%, respectively.
The association between obesity and the incidence of diabetes by sex is reported in Table 4. After adjusting for age, sex, physical activity, medical history, marital status, smoking history, and education level, there was a positive significant association between obesity and increased risk of diabetes in men (OR = 1.77, 95% CI: 1.33-2.35), women (OR = 2.23, 95%CI: 1.55-3.21), and total population (OR = 1.99, 95%CI: 1.60-2.48) compared to the non-obese group. On the other hand, participants with obesity had a higher incidence of diabetes, and this association was further confirmed after multivariate analysis; participants with obesity had a two-fold higher likelihood of developing diabetes compared to their non-obese peers. When stratifying on age, younger (<60 years) participants with obesity tended to present a higher likelihood of developing diabetes compared to older, obese participants (Table 5).
| Figure 1. Flow diagram showing the incidence of diabetes in participants of the YaHS: 2015-2020. |
| Table 1. Characteristics of 5-year incidence of diabetes in men and women, YaHs study, Yazd, Iran | |||
| Variables | Incident diabetes | P-value | |
| Men | Women | ||
| Body mass index (kg/m2) | 28.2±4.5a | 30.7±5.0 | 0.01 |
| Waist circumference (cm) | 100.5±10.7 | 100.8±12.5 | 0.83 |
| Age (year) | 49.7±1.13 | 49.7±1.14 | 0.94 |
| Smoking history | |||
| Never | 183(5.8)b | 283(7.3) | 0.154 |
| Former | 14(10.8) | 2(12.5) | |
| Current | 51(6.1) | 8(9.9) | |
| Medical history | 105(8.1) | 126(8.6) | 0.01 |
| Education | 0.01 | ||
| Primary | 138(7.0) | 233(10.5) | |
| Diploma | 69(4.9) | 47(3.8) | |
| Academic | 37(4.6) | 22(3.4) | |
| Marital status | 0.001 | ||
| Single | 10(1.4) | 47(7.9) | |
| Married | 239(6.8) | 256(7.3) | |
| Physical activity | 0.008 | ||
| Never | 120(6.9) | 173(7.9) | |
| Once a week | 23(5.7) | 26(5.9) | |
| Twice a week | 45(6.5) | 44(7.0) | |
| Three to four times a week | 21(4.1) | 29(7.1) | |
| Five times a week | 38(4.6) | 27(6.1) | |
| Obese | 0.01 | ||
| Yes | 109(10.4) | 264(9.9) | |
| No | 143(4.5) | 40(2.8) | |
| a: Mean±SD; b: N (%); using Student t-test for qualitative and Chi-square test for qualitative variables. | |||
| Table 2. Univariate and multivariate regression analysis of the association between body mass index (BMI), waist circumference (WC) and the 5-year risk of diabetes based on age. | ||||
| Bivariate | P-value | Multivariate | P-value | |
| <60 years | ||||
| BMI<30 | 1.0 (ref.) | <0.01 | 1.0 (ref.) | <0.01 |
| BMI≥30 | 2.81 (2.28-3.45)a | 2.31 (1.84-2.92) | ||
| ≥60 years | ||||
| BMI<30 | 1.0 (ref.) | 0.001 | 1.0 (ref.) | 0.004 |
| BMI≥30 | 1.83 (1.30-2.58) | 1.76 (1.19-2.58) | ||
| Men | ||||
| <60 years | ||||
| WC<88 | 1.0 (ref.) | <0.01 | 1.0 (ref.) | <0.01 |
| WC ≥88 | 2.63 (1.93-3.59) | 2.05(1.45-2.88) | ||
| ≥60 years | ||||
| WC <102 | 1.0 (ref.) | 0.04 | 1.0 (ref.) | 0.11 |
| WC ≥102 | 1.64 (1.02-2.66) | 1.55 (0.91-2.63) | ||
| Women | ||||
| <60 years | ||||
| WC <102 | 1.0 (ref.) | <0.01 | 1.0 (ref.) | <0.01 |
| WC ≥102 | 3.98 (2.71-5.86) | 3.27 (2.14-5.01) | ||
| ≥60 years | ||||
| WC <102 | 1.0 (ref.) | 0.14 | 1.0 (ref.) | 0.20 |
| WC ≥102 | 1.73 (0.83-3.60) | 1.64 (0.77-3.50) | ||
| a: OR (95% confidence interval). Multivariate model was adjusted for sex, physical activity, medical history, marital status, smoking, and education. | ||||
| Table 3. Five-year incidence of diabetes according to obesity status in men, women, and overall population. | |||||
| Variables | No diabetes | Incident diabetes | P-valuea | ||
| N | % | N | % | ||
| Overall | <0.01 | ||||
| Non-obese | 4447 | 57.0 | 183 | 32.9 | |
| Obese | 3359 | 43.0 | 373 | 67.1 | |
| Men | <0.01 | ||||
| Non-obese | 3036 | 76.3 | 143 | 56.7 | |
| Obese | 944 | 23.7 | 109 | 43.3 | |
| Women (n) | <0.01 | ||||
| Non-obese | 1411 | 36.9 | 40 | 13.2 | |
| Obese | 2415 | 63.1 | 264 | 86.8 | |
| a: Chi-square test. | |||||
| Table 4. Bivariate and multivariate analysis of the 5-year incidence of diabetes according to obesity status and sex. | ||
| Bivariate | Multivariate | |
| Overall | ||
| Non-obese | 1.0 (ref.) | 1.0 (ref.) |
| Obese | 2.70 (2.25-3.24) | 1.99 (1.60-2.48) |
| Men | ||
| Non-obese | 1.0 (ref.) | 1.0 (ref.) |
| Obese | 2.45 (1.89-3.18) | 1.77 (1.33-2.35) |
| Women | ||
| Non-obese | 1.0 (ref.) | 1.0 (ref.) |
| Obese | 3.86 (2.75-5.41) | 2.23(1.55-3.21) |
| Multivariate model adjusted for age, physical activity, medical history, marital status, smoking history, and education. For the overall analysis, a further adjustment on sex was conducted. | ||
| Table 5. Bivariate and multivariate analysis of the 5-year incidence of diabetes according to obesity statusand age group. |
||
| Variables | Bivariate | Multivariate |
| <60 years | ||
| Non-obese | 1.0 (ref.) | 1.0 (ref.) |
| Obese | 2.87 (2.31-3.56) | 2.63 (2.04-3.38) |
| ≥60 years | ||
| Non-obese | 1.0 (ref.) | 1.0 (ref.) |
| Obese | 1.73 (1.22-2.46) | 1.57 (1.03-2.39) |
| Results are expressed as OR and (95% confidence interval). Analysis is conducted using logistic regression. Multivariate model adjusted for age, sex, physical activity, medical history, marital status, smoking history, and education. All results are statistically significant at P-value<0.01. | ||
Discussion
In this prospective study conducted in a representative sample of an Iranian population, the 5-year incidence of diabetes was 6.6%, and there was a strong positive significant association between obesity and 5-year incidence of diabetes.
According to a study in Australia, the incidence of diabetes during an average follow-up of 3.4 years was 1.6%, which was remarkably lower than in the current study (Ding et al., 2015). However, during a 10-year study in India, 21.9% developed diabetes during the follow-up period, which was much higher than in the current study, and which may be partly due to the longer follow-up period (Vijayakumar et al., 2019). Latifi et al., during a 5-year follow-up, reported an incidence of diabetes of 16.8% in Iran (Latifi et al., 2016). Azizi et al. during a 3-year follow-up in the Tehran Lipid and Glucose Study reported that 3.7% of people developed diabetes, which is lower than in the current study (HR and Azizi, 2008). Namayandeh et al. in 2019, during 10 years, estimated that 21.4 per 1000 of the population-years in Yazd had diabetes among people aged 20–74 years (Namayandeh et al., 2019).
In the current study, the risk of diabetes in obese women was higher than in obese men after a 5-year follow-up. In contrast, according to a prospective study in Tehran (2005) during a 6.3-year follow-up, the incidence of diabetes in both sexes was the same (Azadeh et al., 2005). According to the present study, the risk of developing diabetes in obese men, women, and the total population was 1.77, 2.23, and 1.99 times higher than that of non-obese population. In the study of Hosseinpanah et al. (Hosseinpanah et al., 2007b), the OR of T2DM for obese group was 3.61 times higher than the normal-weight group. Another study (Mokdad et al., 2003) reported that the risk of diabetes in adults with both high body fat and severe obesity was 7.37 times higher than in non-obese adults with low body fat. Also, Hart et al. stated that there was an association between obesity and increased risk of diabetes (Hart et al., 2007). Additionally, obese participants had the highest risk of developing diabetes compared to non-obese participants in similar studies (Ford et al., 1997, Rhee et al., 2011) and efforts to control weight can play an important role in the clinical management of diabetes (Knowler et al., 2002, Tuomilehto et al., 2001). It has been confirmed that there is a strong relationship between obesity and diabetes
(Gautier et al., 2010, Looker et al., 2001, Wannamethee and Shaper, 1999).
According to the findings, there was an association between obesity and increased risk of diabetes in participants aged under and over 60 years. Malone and Hansen (Malone and Hansen, 2019) reported similar results in younger people, i.e. severe obese children and adolescents. Also, according to the study by Farzad Hadayegh et al. (Azadeh et al., 2005), general obesity and central obesity, are two indicators predicting the incidence of type 2 diabetes in the Iranian population under 60 years of age.
There was a positive association between central and abdominal obesity and risk of diabetes. It seems that younger participants who are obese have a higher risk of developing diabetes than older obese people. It would be an important message for public health that the lifestyle of younger people might put them at higher risk of diabetes compared to older people.
The present study is the first study in a large population in the central part of Iran to estimate the incidence of diabetes overall and between obese and non-obese participants. There were some limitations in the present study. The repeated measurement was done after five years; therefore, the exact time of incidence of diabetes is unclear. Also, we could not check the population during the follow up, so lifestyle such as dietary habits, smoking, and physical activity may have changed.
Conclusion
The results of the present study showed the 5-year incidence of diabetes in men, women, and total population in an urban area of central Iran. There was a positive significant association between obesity and 5-year incidence of diabetes in obese participants compared to non-obese participants and younger compared to the elderly. Therefore, changing lifestyle is recommended in relation to obesity and diabetes in the adult population particularly in younger population aged less than 60 years.
Acknowledgment
The authors thank all YaHS research team and all participants who cooperated in this study.
Authors’ contributions
Peigan P, Mirzaei M, and Sarebanhassanabadi M designed and organized the study; Sarebanhassanabadi M, Fallahzadeh H, and Peigan P analyzed the data; Peigan P and Sarebanhassanabadi M wrote the manuscript; Sarebanhassanabadi M, Mirzaei M, Marques-Vidal P, and Kraemer A revised the manuscript, critically. All authors read and approved the final manuscript.
References
Azadeh Z, Farzad H, Hadi H & Fereidoun A 2005. Anthropometric parameters as helpful factors for prediction of type 2 diabetes onset, Tehran lipid and glucose study. Iranian journal of diabetes and lipid disorders. 5 (2): 143-151.
De Onis M & Blössner M 2000. Prevalence and trends of overweight among preschool children in developing countries. American journal of clinical nutrition. 72 (4): 1032-1039.
Ding D, Chong S, Jalaludin B, Comino E & Bauman AE 2015. Risk factors of incident type 2-diabetes mellitus over a 3-year follow-up: Results from a large Australian sample. Diabetes research and clinical practice. 108 (2): 306-315.
Ford ES, Williamson DF & Liu S 1997. Weight change and diabetes incidence: findings from a national cohort of US adults. American journal of epidemiology. 146 (3): 214-222.
Gautier A, et al. 2010. Increases in waist circumference and weight as predictors of type 2 diabetes in individuals with impaired fasting glucose: influence of baseline BMI: data from the DESIR study. Diabetes care. 33 (8): 1850-1852.
Hart C, Hole D, Lawlor D & Davey Smith G 2007. How many cases of Type 2 diabetes mellitus are due to being overweight in middle age? Evidence from the Midspan prospective cohort studies using mention of diabetes mellitus on hospital discharge or death records. Diabetic medicine. 24 (1): 73-80.
Hosseinpanah F, Rambod M & Azizi F 2007a. Population attributable risk for diabetes associated with excess weight in Tehranian adults: a population-based cohort study. BMC public health. 7 (1): 1-8.
Hosseinpanah F, et al. 2007b. Population attributable risk for diabetes associated to obesity in Iranian adults. Iranian journal of endocrinology and metabolism. 9 (1): 91-97.
HR AM & Azizi F 2008. The assessment of relation between lipid distribution and weight change with diabetes incidence in a group of Tehran, district 13 population. Research in medicine. 32 (2): 105-113.
Knowler WC, et al. 2002. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. New England journal of medicine. 346 (6): 393-403.
Larijani B, Bastanhagh M & Pajouhi M 1995. Prevalence of NIDDM in Tehran. In Proceedings of the Third International Congress on Endocrine Disorders, pp. 4-8.
Latifi SM, Karandish M, Shahbazian H & Hardani Pasand L 2016. Incidence of prediabetes and type 2 diabetes among people aged over 20 years in ahvaz: a 5-year perspective study (2009–2014). Journal of diabetes research. 2016.
Looker HC, Knowler WC & Hanson RL 2001. Changes in BMI and weight before and after the development of type 2 diabetes. Diabetes care. 24 (11): 1917-1922.
Malone JI & Hansen BC 2019. Does obesity cause type 2 diabetes mellitus (T2DM)? Or is it the opposite? Pediatric diabetes. 20 (1): 5-9.
Mirzaei M, Rahmaninan M, Mirzaei M, Nadjarzadeh A & Dehghani tafti AA 2020. Epidemiology of diabetes mellitus, pre-diabetes, undiagnosed and uncontrolled diabetes in Central Iran: results from Yazd health study. BMC public health. 20 (1): 166.
Mirzaei M, Salehi-Abargouei A, Mirzaei M & Mohsenpour MA 2018. Cohort Profile: The Yazd Health Study (YaHS): a population-based study of adults aged 20–70 years (study
design and baseline population data). International journal of epidemiology. 47 (3): 697-698h.
Mirzaei M, et al. 2017. Prevalence of general obesity and central adiposity and its related factors in adult population of Yazd. Journal of Shahid Sadoughi University of medical sciences. 25 (9): 736-747.
Moghtaderi F, et al. 2022. Incidence of Overweight and Its Predictors in Adults after 10 Years of Follow-up: Yazd Healthy Heart Project. Journal of nutrition and food security. 7 (3): 362-373.
Mokdad AH, et al. 2003. Prevalence of Obesity, Diabetes, and Obesity-Related Health Risk Factors, 2001. Journal of American Medical Association (JAMA). 289 (1): 76-79.
Mokdad AH, et al. 2000. The continuing epidemic of obesity in the United States. Journal of American Medical Association (JAMA). 284 (13): 1650-1651.
Namayandeh SM, et al. 2019. The incidence rate of diabetes mellitus (type II) and its related risk factors: A 10-year longitudinal study of Yazd Healthy Heart Cohort (YHHC), Iran. Diabetes & metabolic syndrome: Clinical research & reviews. 13 (2): 1437-1441.
Rhee E-J, et al. 2011. The association of unintentional changes in weight, body composition, and homeostasis model assessment index with glycemic progression in non-diabetic healthy subjects. Diabetes & metabolism journal. 35 (2): 138-148.
Roglic G & King H 2000. Diabetes mellitus in Asia. Hong Kong medical journal. 6 (1): 10-11.
Rossi G 2018. Association AD. Diagnosis and classification of diabetes mellitus. Diabetes care. 33 (Suppl 1): S62-S69.
Sarebanhassanabadi M, et al. 2020. Dietary habits and the 10-year risk of overweight and obesity in urban adult population: A cohort study predicated on Yazd Healthy Heart Project. Diabetes & metabolic syndrome: Clinical research & reviews. 14 (5): 1391-1397.
Tuomilehto J, et al. 2001. Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance. New England journal of medicine. 344 (18): 1343-1350.
Vijayakumar G, et al. 2019. Incidence of type 2 diabetes mellitus and prediabetes in Kerala, India: results from a 10-year prospective cohort. BMC public health. 19 (1): 1-10.
Wannamethee SG & Shaper AG 1999. Weight change and duration of overweight and obesity in the incidence of type 2 diabetes. Diabetes care. 22 (8): 1266-1272.
Williams R, et al. 2019. IDF diabetes atlas, International Diabetes Atlas. . United Kingdom.
World Health Organization 1997. Obesity epidemic puts millions at risk from related diseases. WHO Press Release.
World Health Organization 2016. Obesity and overweight Available from: https://www. who.int/newsroom/fact-sheets/detail/obesity-and-overweight.
In this prospective study conducted in a representative sample of an Iranian population, the 5-year incidence of diabetes was 6.6%, and there was a strong positive significant association between obesity and 5-year incidence of diabetes.
According to a study in Australia, the incidence of diabetes during an average follow-up of 3.4 years was 1.6%, which was remarkably lower than in the current study (Ding et al., 2015). However, during a 10-year study in India, 21.9% developed diabetes during the follow-up period, which was much higher than in the current study, and which may be partly due to the longer follow-up period (Vijayakumar et al., 2019). Latifi et al., during a 5-year follow-up, reported an incidence of diabetes of 16.8% in Iran (Latifi et al., 2016). Azizi et al. during a 3-year follow-up in the Tehran Lipid and Glucose Study reported that 3.7% of people developed diabetes, which is lower than in the current study (HR and Azizi, 2008). Namayandeh et al. in 2019, during 10 years, estimated that 21.4 per 1000 of the population-years in Yazd had diabetes among people aged 20–74 years (Namayandeh et al., 2019).
In the current study, the risk of diabetes in obese women was higher than in obese men after a 5-year follow-up. In contrast, according to a prospective study in Tehran (2005) during a 6.3-year follow-up, the incidence of diabetes in both sexes was the same (Azadeh et al., 2005). According to the present study, the risk of developing diabetes in obese men, women, and the total population was 1.77, 2.23, and 1.99 times higher than that of non-obese population. In the study of Hosseinpanah et al. (Hosseinpanah et al., 2007b), the OR of T2DM for obese group was 3.61 times higher than the normal-weight group. Another study (Mokdad et al., 2003) reported that the risk of diabetes in adults with both high body fat and severe obesity was 7.37 times higher than in non-obese adults with low body fat. Also, Hart et al. stated that there was an association between obesity and increased risk of diabetes (Hart et al., 2007). Additionally, obese participants had the highest risk of developing diabetes compared to non-obese participants in similar studies (Ford et al., 1997, Rhee et al., 2011) and efforts to control weight can play an important role in the clinical management of diabetes (Knowler et al., 2002, Tuomilehto et al., 2001). It has been confirmed that there is a strong relationship between obesity and diabetes
(Gautier et al., 2010, Looker et al., 2001, Wannamethee and Shaper, 1999).
According to the findings, there was an association between obesity and increased risk of diabetes in participants aged under and over 60 years. Malone and Hansen (Malone and Hansen, 2019) reported similar results in younger people, i.e. severe obese children and adolescents. Also, according to the study by Farzad Hadayegh et al. (Azadeh et al., 2005), general obesity and central obesity, are two indicators predicting the incidence of type 2 diabetes in the Iranian population under 60 years of age.
There was a positive association between central and abdominal obesity and risk of diabetes. It seems that younger participants who are obese have a higher risk of developing diabetes than older obese people. It would be an important message for public health that the lifestyle of younger people might put them at higher risk of diabetes compared to older people.
The present study is the first study in a large population in the central part of Iran to estimate the incidence of diabetes overall and between obese and non-obese participants. There were some limitations in the present study. The repeated measurement was done after five years; therefore, the exact time of incidence of diabetes is unclear. Also, we could not check the population during the follow up, so lifestyle such as dietary habits, smoking, and physical activity may have changed.
Conclusion
The results of the present study showed the 5-year incidence of diabetes in men, women, and total population in an urban area of central Iran. There was a positive significant association between obesity and 5-year incidence of diabetes in obese participants compared to non-obese participants and younger compared to the elderly. Therefore, changing lifestyle is recommended in relation to obesity and diabetes in the adult population particularly in younger population aged less than 60 years.
Acknowledgment
The authors thank all YaHS research team and all participants who cooperated in this study.
Authors’ contributions
Peigan P, Mirzaei M, and Sarebanhassanabadi M designed and organized the study; Sarebanhassanabadi M, Fallahzadeh H, and Peigan P analyzed the data; Peigan P and Sarebanhassanabadi M wrote the manuscript; Sarebanhassanabadi M, Mirzaei M, Marques-Vidal P, and Kraemer A revised the manuscript, critically. All authors read and approved the final manuscript.
References
Azadeh Z, Farzad H, Hadi H & Fereidoun A 2005. Anthropometric parameters as helpful factors for prediction of type 2 diabetes onset, Tehran lipid and glucose study. Iranian journal of diabetes and lipid disorders. 5 (2): 143-151.
De Onis M & Blössner M 2000. Prevalence and trends of overweight among preschool children in developing countries. American journal of clinical nutrition. 72 (4): 1032-1039.
Ding D, Chong S, Jalaludin B, Comino E & Bauman AE 2015. Risk factors of incident type 2-diabetes mellitus over a 3-year follow-up: Results from a large Australian sample. Diabetes research and clinical practice. 108 (2): 306-315.
Ford ES, Williamson DF & Liu S 1997. Weight change and diabetes incidence: findings from a national cohort of US adults. American journal of epidemiology. 146 (3): 214-222.
Gautier A, et al. 2010. Increases in waist circumference and weight as predictors of type 2 diabetes in individuals with impaired fasting glucose: influence of baseline BMI: data from the DESIR study. Diabetes care. 33 (8): 1850-1852.
Hart C, Hole D, Lawlor D & Davey Smith G 2007. How many cases of Type 2 diabetes mellitus are due to being overweight in middle age? Evidence from the Midspan prospective cohort studies using mention of diabetes mellitus on hospital discharge or death records. Diabetic medicine. 24 (1): 73-80.
Hosseinpanah F, Rambod M & Azizi F 2007a. Population attributable risk for diabetes associated with excess weight in Tehranian adults: a population-based cohort study. BMC public health. 7 (1): 1-8.
Hosseinpanah F, et al. 2007b. Population attributable risk for diabetes associated to obesity in Iranian adults. Iranian journal of endocrinology and metabolism. 9 (1): 91-97.
HR AM & Azizi F 2008. The assessment of relation between lipid distribution and weight change with diabetes incidence in a group of Tehran, district 13 population. Research in medicine. 32 (2): 105-113.
Knowler WC, et al. 2002. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. New England journal of medicine. 346 (6): 393-403.
Larijani B, Bastanhagh M & Pajouhi M 1995. Prevalence of NIDDM in Tehran. In Proceedings of the Third International Congress on Endocrine Disorders, pp. 4-8.
Latifi SM, Karandish M, Shahbazian H & Hardani Pasand L 2016. Incidence of prediabetes and type 2 diabetes among people aged over 20 years in ahvaz: a 5-year perspective study (2009–2014). Journal of diabetes research. 2016.
Looker HC, Knowler WC & Hanson RL 2001. Changes in BMI and weight before and after the development of type 2 diabetes. Diabetes care. 24 (11): 1917-1922.
Malone JI & Hansen BC 2019. Does obesity cause type 2 diabetes mellitus (T2DM)? Or is it the opposite? Pediatric diabetes. 20 (1): 5-9.
Mirzaei M, Rahmaninan M, Mirzaei M, Nadjarzadeh A & Dehghani tafti AA 2020. Epidemiology of diabetes mellitus, pre-diabetes, undiagnosed and uncontrolled diabetes in Central Iran: results from Yazd health study. BMC public health. 20 (1): 166.
Mirzaei M, Salehi-Abargouei A, Mirzaei M & Mohsenpour MA 2018. Cohort Profile: The Yazd Health Study (YaHS): a population-based study of adults aged 20–70 years (study
design and baseline population data). International journal of epidemiology. 47 (3): 697-698h.
Mirzaei M, et al. 2017. Prevalence of general obesity and central adiposity and its related factors in adult population of Yazd. Journal of Shahid Sadoughi University of medical sciences. 25 (9): 736-747.
Moghtaderi F, et al. 2022. Incidence of Overweight and Its Predictors in Adults after 10 Years of Follow-up: Yazd Healthy Heart Project. Journal of nutrition and food security. 7 (3): 362-373.
Mokdad AH, et al. 2003. Prevalence of Obesity, Diabetes, and Obesity-Related Health Risk Factors, 2001. Journal of American Medical Association (JAMA). 289 (1): 76-79.
Mokdad AH, et al. 2000. The continuing epidemic of obesity in the United States. Journal of American Medical Association (JAMA). 284 (13): 1650-1651.
Namayandeh SM, et al. 2019. The incidence rate of diabetes mellitus (type II) and its related risk factors: A 10-year longitudinal study of Yazd Healthy Heart Cohort (YHHC), Iran. Diabetes & metabolic syndrome: Clinical research & reviews. 13 (2): 1437-1441.
Rhee E-J, et al. 2011. The association of unintentional changes in weight, body composition, and homeostasis model assessment index with glycemic progression in non-diabetic healthy subjects. Diabetes & metabolism journal. 35 (2): 138-148.
Roglic G & King H 2000. Diabetes mellitus in Asia. Hong Kong medical journal. 6 (1): 10-11.
Rossi G 2018. Association AD. Diagnosis and classification of diabetes mellitus. Diabetes care. 33 (Suppl 1): S62-S69.
Sarebanhassanabadi M, et al. 2020. Dietary habits and the 10-year risk of overweight and obesity in urban adult population: A cohort study predicated on Yazd Healthy Heart Project. Diabetes & metabolic syndrome: Clinical research & reviews. 14 (5): 1391-1397.
Tuomilehto J, et al. 2001. Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance. New England journal of medicine. 344 (18): 1343-1350.
Vijayakumar G, et al. 2019. Incidence of type 2 diabetes mellitus and prediabetes in Kerala, India: results from a 10-year prospective cohort. BMC public health. 19 (1): 1-10.
Wannamethee SG & Shaper AG 1999. Weight change and duration of overweight and obesity in the incidence of type 2 diabetes. Diabetes care. 22 (8): 1266-1272.
Williams R, et al. 2019. IDF diabetes atlas, International Diabetes Atlas. . United Kingdom.
World Health Organization 1997. Obesity epidemic puts millions at risk from related diseases. WHO Press Release.
World Health Organization 2016. Obesity and overweight Available from: https://www. who.int/newsroom/fact-sheets/detail/obesity-and-overweight.
Type of article: orginal article |
Subject:
public specific
Received: 2022/07/3 | Published: 2023/11/20 | ePublished: 2023/11/20
Received: 2022/07/3 | Published: 2023/11/20 | ePublished: 2023/11/20
Send email to the article author
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
