Introduction

Obesity is one of the most prevalent public health problems in both high and middle-income countries [1]. Lifestyle changes toward an inactive life or eating more, are the major cause of obesity epidemic [2].

In adults, the most common criteria to evaluate the obesity is body mass index [BMI][3]. BMI ≥ 30 kg/m2 is defined as obesity and also, BMI 25–29.9 kg/m2 as overweight [4]. Obesity especially abdominal obesity, is associated with cardiovascular diseases and all-cause mortality [5,6,7]. According to the third National Health and Nutrition Examination Survey study, normal-weight central obesity (high waist-to-hip ratio) displayed higher association with cardiovascular mortality than obesity defined by BMI [7].

According to the World Health Organization, in 2016, more than 1.9 billion and 650 million adults were overweight and obese respectively, this is responsible for 2.8 million deaths annually [8]. In Iran, the prevalence of obesity in women and men were different in various regions, although all of them indicated a high prevalence of overweight and obesity [9, 10].

Obesity is a determinant risk factor for diabetes, cardiovascular disease, cancer, sleep problems and osteoarthritis. It can affect the quality of human life in various aspects including physical, social, economic and psychological conditions [8, 11,12,13]. In the United States, a positive association was observed between obesity and depression. The results showed that physical and social dysfunction as well as mental overeating are able to play mediating roles for this association [14]. The obesity epidemic is developing in low and middle-income countries, especially in urban areas [8, 11].

One of the most important strategies of the World Health Organization to control the obesity is to increase the physical activity and healthy diet [1]. Therefore, in designation of helpful strategies, a comprehensive understanding of the current situation and health determinants is important [15]. Studies which provide data available for evaluation of central and abdominal obesity and their risk factors in Rafsanjan city located in the southwest of Iran are scarce [4]. The aim of the present study was to investigate the current epidemic of overweight/obesity, abdominal obesity and their related factors in the adult population of the Rafsanjan cohort study (RCS)[16].

Methods

The data for this study were collected in Rafsanjan cohort study (RCS) [16] as a part of the Prospective Epidemiological Research Studies in Iran (PERSIAN) [17]. RCS was designed to enroll 10,000 participants of both genders aged 35–70 years, including both urban and suburban areas. In each cluster, 2500 participants (35–70 year) were enrolled (10,000 participants).

Variables assessment

Trained experts interviewed each participant and completed the related questionnaires about his/her socioeconomic status, demography, personal habits, physical activity, and medical history. The anthropometric characteristics were measured by trained health professionals at RCS Center.

All questionnaires were previously validated in the PERSIAN cohort study [17]. Marital status was categorized into married and single including never married, divorced, widowed or other. The daily physical activity of the participants was weighted based on its relative metabolic cost, known as a metabolic equivalent (MET), and MET-h/day for 24 h is derived in this way. Then MET was classified into three categories including low ( < = 35.299), moderate (35.3-40.325) and heavy ( > = 40.326) groups respectively based on the 25th and 75th percentiles. Data on the lifestyle habits including cigarette smoking was coded as never, current and former smokers, Alcohol drinking and opium consumption were coded as yes (currently or formerly) and no (never).

Socio-economic status was measured according to the Wealth score index (WSI). The wealth score index (WSI) was classified into four categories based on 25th, 50th and 90th percentiles: low income (1st group: ≤ − 0.6069), low-middle income (2nd group: − 0.607 to 0.0349), middle-high income (3rd group: 0.035 to 1.169) and high income (4th group: ≥ 1.170).

BMI was calculated from height and weight data as kg/m2. Overweight was defined as BMI 25–29.9 kg/m2 and obesity as BMI ≥ 30 kg/m2. Waist circumference ≥ 102 cm for men and ≥ 88 cm for women was defined as abdominal obesity based on NCEP-ATP III criteria [18]. The frequency difference between total number and some of the covariates was related to missing data.

Statistical analysis

Stata software V.12 was used for all the statistical analyses. Means and standard deviations (SD) were calculated for continuous variables, and proportions were calculated for the categorical variables. Between-group comparisons were made by independent t-test and chi-square test. Multinomial logistic regression models were used to examine the relationships between overweight/obesity/abdominal obesity and associated factors by adjusting for covariates. Potential confounding variables were sequentially entered into model according to their hypothesized strengths of association with overweight/obesity/abdominal obesity. Variables with a p-value < 0.25 were selected as confounders. A cut off value of 0.25 is supported by some literature [19, 20]. The adjusted model is adjusted for confounding variables age (continuous variable), gender (male, female), education years (categorical variable), wealth status index (categorical variable), and the lifestyle variables cigarette smoking (categorical variable), alcohol drinking (yes, no) and opium consumption (yes, no), physical activity level (categorical variable) and marital status (categorical variable). All p-values were two-sided, and a significance level of 0.05 was used for p-value.

Results

According to the results, from 9980 participants, 4089 (40.97%) were overweight, 3007 (30.13%) were obese and 2884 (28.90%) had normal weight. The prevalence of normal BMI, overweight and obesity were shown based on demographic characteristics of individuals in both genders in Table 1. From 4653 male participants, in categorize of BMI, 1974 (42.42%) were overweight, and 784 (16.85%) were obese and from 5327 female participants, 2115 (39.70%) were overweight and 2223 (41.73%) were obese.

Table 1 Prevalence of demographic, selected medical and laboratory characteristics of study participants by BMI categorize
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There were significant differences for variables age (male: P = 0.003 and female: P < 0.001), marital status (male: P = 0.019 and female: P = 0.022), educational level (both gender P < 0.001), physical activity (both gender P < 0.001), wealth status index (male: P < 0.001 and female: P = 0.001), smoking habit (both gender P < 0.001) and opium consumption (male: P < 0.001 and female: P = 0.046) between adults with overweight/obese compared to those with normal weight.

The prevalence of overweight and obesity was significantly lower in the male group aged ≥ 56 years old compared to younger adults (P = 0.003); Moreover, the prevalence of obesity was higher in female subjects aged > 45 (P < 0.001) (Table 1).

Table 2 represents the prevalence of abdominal obesity according to demographic, socio-economic and lifestyle factors. The prevalence of abdominal obesity in females was significantly higher in age group ≥ 56 years and education level ≤ 5 years (P < 0.001). Moreover, there were significant difference between the prevalence of abdominal obesity in the categorical levels of physical activity and WSI in both genders (P < 0.001). The highest prevalence of abdominal obesity in females was in age group ≥ 56 years and education level ≤ 5 years (P < 0.001). In male subjects, the highest prevalence of abdominal obesity was in high WSI group and former smokers (P = 0.001 and P < 0.001 respectively), while it was lower in opium users (P = 0.001). (Table 2).

Table 2 Prevalence of demographic, selected medical and laboratory characteristics of study participants by Abdominal obesity
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Table 3 represents the association between related risk factors and overweight/obesity and abdominal obesity, using the univariate and multivariate analyses. The related risk factors associated with obesity in univariate analysis were also assessed and the subjects with overweight/obesity and abdominal obesity were compared with the normal subjects (Table 3). The odds of having overweight/obesity and abdominal obesity were estimated for nine factors: age, gender, marital status, education level, physical activity, WSI, alcohol consumption, cigarette smoking, and opium consumption (Table 3). In the univariate analysis, it was found that all of these factors were significantly associated with overweight/obesity except for age group ≥ 56 years and married and in the abdominal obesity except for low-middle group of WSI.

Table 3 Logistic regression analysis for the association of overweight/obesity and abdominal obesity with demographic, socio-economic and lifestyle factors
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After adjustment, the variables including age, gender, education ≥ 13 years, heavy physical activity, WSI, alcohol consumption, current smoking and opium consumption were shown to be significantly associated with overweight/obesity. On the other hand, all assessed risk factors except married and former smoking had significant relationship with abdominal obesity (Table 3).

In the crude regression model, the odds ratio (OR) of overweight/ obesity (OR: 3.02, 95% CI 2.75 to 3.30) and abdominal obesity (OR: 26.84, 95% CI 24.12 to 29.86) were higher among women compared with men, and after adjustment for confounders this association remained significant, although it slightly diminished. In the regression model, the odds of abdominal obesity for all categories of age (46–55 years old OR: 1.31, 95% CI 1.19 to 1.44 and age ≥ 56 OR: 1.32, 95% CI 1.20 to 1.45) and the odds of overweight/ obesity for all categories of age (46–55 years old OR: 1.24, 95% CI 1.11 to 1.38 and age ≥ 56 years old OR: 1.32, 95% CI 1.20 to 1.42) were higher compared to reference age group (35–45 years) and this association remained significant after adjustment for the confounders. In terms of age, people with age 46–55 had highest prevalence of overweight/ obesity than 35–45 years old individuals (OR: 1.32, 95% CI 1.18 to 1.49) and people with age ≥ 56 had highest prevalence of central obesity than 35–45 years old individuals (OR: 1.68, 95% CI 1.45 to 1.95).

In the regression model, the odds of overweight and obesity was lowest in education ≥ 13 years (OR: 0.80, 95% CI 0.71 to 0.91), in comparison to people with education ≤ 5 years and this association persisted after adjustment for confounders (OR: 0.73, 95% CI 0.62 to 0.86). Also, in adjusted model the odds of abdominal obesity in categories of education for education ≥ 13 was lowest in comparison with people with education ≤ 5 years (OR: 0.57, 95% CI 0.47 to 0.69). Results of multivariate logistic regression analysis showed that moderate and heavy physical activity decreased the ORs of overweight/obesity and abdominal obesity.

Regarding Socio-economic status (WSI), in adjusted model the odds of overweight/obesity and abdominal obesity increased significantly with the improvement of socio-economic status.

The ORs of overweight/obesity in the un-adjusted model were significantly lower for current cigarette smoking (OR: 0.29, 95% CI 0.26–0.32), and opium consumption (OR: 0.36, 95% CI 0.33–0.40), and remained significant in the adjusted models (OR: 0.54, 95% CI 0.47–0.63 and OR: 0.67: 0.67, 95% CI 0.59–0.76 respectively). Similarly, lower ORs of abdominal obesity were seen with current cigarette smoking and opium consumption in both the un-adjusted and adjusted models.

Alcohol consumption decreased the odds of overweight/obesity and central obesity in the univariate models (OR: 0.54, 95% CI 0.47–0.62 and OR: 0.17, 95% CI 0.14–0.20), while after adjusting for confounders, these odds were significantly increased (OR: 1.30, 95% CI 1.11–1.52 and OR: 1.36, 95% CI 1.12–1.65 respectively). In order to find which confounding factor influences this result, we did the stepwise adjustment. The result showed that after adding opium to the model, effect of alcohol became significant.

Discussion

According to the results, the overall prevalence of overweight and obesity were 40.97% (39.70% in women and 42.42% in men) and 30.13% (41.73% in women and 16.85% in men), respectively. In the study by Tabrizi et al., that conducted in the northwestern of Iran [21] similar with this study, around 63.6% of the participants were either overweight or obese. In another study from southwest of Iran, the total prevalence of overweight and obesity were almost similar to the results of this study (38.7% and 26.5%)[22]. These rates may reflect a significant national obesity problem. In the current study higher rates of overweight and obesity were observed when compared with estimates for the Spanish (17%) [23], Turkish (19%) [24] and Pakistan (25.0%) [25] adult population.

The total prevalence rate of abdominal obesity was 53.92% (85.39% in women and 17.88% in men). This rate was lower than the results of the study by Tabrizi et al., [21] who reported 75.2% central obesity (81.4%in women and 68.6% in men). In the Persian Giulan cohort study [26], central obesity had the highest prevalence (75.8%), and this index was more than 98% in females. But, the prevalence of abdominal obesity was 32.1% (57.2% in women and 15.8% in men) in Golestan (north of Iran) [27] and 21.2% in Ahvaz (south of Iran) [28]. These differences can be related to the lifestyle of people in large cities compared to small cities, and environmental conditions such as humidity that causes more sweating. The prevalence of abdominal obesity was 24.1% in Egypt [29], 30.5% in Australia[30], and 64.4% in Oman[31].

In the regression model, the ORs of overweight/obesity and abdominal obesity were higher among women compared with men. This results are in agreement with other studies in Iran [21, 22, 32,33,34] and other countries [35]. However, these results were dissimilar to the studies in China [36] and Japan[37]. This difference can be due to the cultural and occupational differences of women in Iranian society, especially in the south of the country compared to other countries. Moreover, the prevalence of abdominal obesity in females was significantly higher in age group ≥ 56 years and this association remained significant for both of them after adjustment for the confounders. In the study by Tabrizi et al.,[21], 45% of women in the 46–65 year old age group were obese. In agreement with the results of this study, age was considered as a predictor of abdominal obesity in other studies [27, 38,39,40].

After adjustment, the variable education ≥ 13 years, was shown to be significantly associated with overweight/obesity. These results are in according with some studies [41, 42], but there are other studies in Iran which found no relation between education and obesity [27, 43].

The multivariate analysis showed that moderate and heavy physical activity decreased the risk of overweight/obesity and abdominal obesity. Low physical activity and central obesity were associated in other studies reported from Iran and other countries [27, 32, 44, 45].

Lower ORs of overweight/obesity and abdominal obesity were seen in current cigarette smoking. Consistent with our results, another study in the northwest of Iran found that nonsmokers were more likely to be overweight or obese and abdominally obese [21]. The present study showed that opium consumption decreased and alcohol consumption increased the odds of overweight/obesity and abdominal obesity. These results were in line with other studies [46,47,48,49].

According to the results of the present study around 71.1% of adult population in this region have overweight/ obesity and half of them have central obesity, which emphasizes the need for comprehensive preventive strategies to reduce energy consumption. There is an urgent need for public health prevention strategies to help modify health behaviors to decrease obesity and its subsequent complications such as diabetes, hypertension, and coronary artery disease. An increase in physical activity by walking, bicycle riding, and sports, lifestyle changes by replacing high fiber and low-fat diets for routine diets are recommended.

The strengths of this study are the population-based design and the sample size. None of the previous studies had a sample size as much as our samples. Moreover, another noteworthy point of this study is that it was conducted by the experts and trained interviewers and all data carefully recorded. The limitations of this study are as follows: first, in this study, data on habits was based on the self-reporting and the individual’s memory, raising the possibility of errors. Second, in the present study, other parameters such as dietary pattern, stress and environmental factors were not assessed. Therefore, this issue should be taken into account in the future studies.

Conclusions

The results of this study added more evidence related to the overweight/obesity and abdominal obesity in this region. These findings may help public health professionals, to develop the strategies that prevent of obesity in the community.