Abstract
Background:
This population-based study aimed at investigating the prevalence and associated factors of over-weight /obesity and abdominal obesity in Iran.
Methods:
The study population consists of 2818 inhabitant of the urban and regional area of East-Azerbaijan, Iran in 2015. The weight, height and waist circumferences were measured and the body mass index (BMI) and conicity index were calculated. The ANCOVA and logistic regression were used for statistical analysis.
Results:
Prevalence of overweight, obesity and abdominal obesity was 39.6%, 24%, and 76.4% respectively. Women showed the higher prevalence of obesity (32.2%) and abdominal obesity (81.4) than men (obesity: 15.1%; abdominal obesity: 68.6%). Age, marriage and family history of obesity were independent predictors of obesity in the population (P< 0.001). In men and women, nonsmokers (P<0.01) and subjects having more than two kids (P< 0.001) were also more expected to be overweight or obese and abdominally obese respectively.
Conclusion:
More actions mostly focusing on education and physical activity levels, and changing eating habits are required.
Keywords: Adults, Overweight, Obesity, Abdominal obesity
Introduction
Obesity is one of the major community health problems and its occurrence is notably growing in developed and developing countries (1, 2). Based on recent reports, the rate of obesity has tripled during the last two decades in developing countries (3). Iran has been no exception. According to the latest report of WHO, more than half of the Iranian adults are overweight or obese (4).
In adults, the most prevalent and practical indicator for evaluation of overweight and obesity is Body Mass Index (BMI) (5). Obesity and abdominal obesity are the main risk factors for developing cardiovascular diseases (CVD), diabetes, hypertension and dyslipidemia (6–9).
Increasing of obesity prevalence is related to the significant modification in the lifestyle in particular dietary habits and limited physical activity in both urban and rural regions (10, 11). Some of the ethnic dimensions underlying causes of obesity are low socioeconomic status, genetic factors, and the different eating patterns (12–15). In Iran, family history of obesity, aging, early marriage, low physical activity, parity, and education are responsible for both obesity and central obesity in the urban population (16).
There is no recent data available for prevalence and associated factors of overweight or obesity and abdominal obesity in Iran. This population-based investigation focused mainly on providing the estimates of obesity in Iran and also evaluating its association with various risk factors in the Iranian adult population in the urban and regional areas.
Materials and Methods
The data for this study were collected in 2015 as a part of the major Lifestyle Promotion Project (LPP) (17, 18) conducted in the districts of East Azerbaijan (urban and regional parts), one of the largest provinces of Iran. This study performed by probability proportional to size (PPS) multistage stratified cluster sampling through which 150 clusters selected. In each cluster, 20 participants (15–65 yr) were enrolled (3000 participants). All procedures performed in this study were in line with the ethical values of the Ethics Committee of Tabriz University of Medical Science and Informed consent was obtained from all participants included in the study.
Exclusion of incomplete questionnaire yielded 2818 final sample, subjected to statistical analysis. The final sample consists of 1370 and 1448 residents in the capital city (Tabriz) regional areas (including Marand, Mianeh, Varzegan, Khodafarin, Bonab, Osku, and Ilkhichi) respectively.
International Physical Activity Questionnaire (IPAQ) which the validity of the translated form was evaluated in the previous study on Iranian subjects (19). Dietary assessment is performed by means of quantitative food frequency questionnaires (20).
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 circumferences (cm) were measured in duplicate with an anthropometric tape at the minimum circumference between the iliac crest and the rib cage and conicity index was calculated as follow: Conicity index = waist circumference in meters/(0.109*square root of weight in kg/height in meters).
Statistical analysis
SPSS ver.18 (Chicago, IL, USA) Statistical computer software was used for all statistical analyses. Means and standard deviations (SD) were calculated for continuous variables, and proportions were calculated for categorical variables. Between-group comparisons were made by independent t-test, chi-square test, and ANCOVA. The multinomial logistic regression models were used to examine the relationships between over-weight/obesity/abdominal obesity and associated factors by adjusting for covariates. All analyses were performed for men and women separately since the literature usually reports gender differences for factors associated with obesity. A significance level of 0.05 was used.
Results
The prevalence of overweight, obesity and central obesity in the urban and regional areas is shown in Table 1. The rates of age, marital, occupational, educational and physical activity status, smoking habit, overweight, obesity and abdominal obesity were significantly different in the urban and regional areas (P<0.05).
Table 1:
The prevalence of overweight, obesity and abdominal obesity in urban and regional areas
| Urban (n= 1370) | Regional(n= 1448) | Total (n= 2818) | |
|---|---|---|---|
| Age, % (n)* | |||
| 15–25 | 5.1 (71) | 8.5 (123) | 6.8 (191) |
| 26–35 | 18.7 (257) | 22.2(322) | 20.5(578) |
| 36–45 | 32 (439) | 28.4(412) | 30.2(851) |
| 46–55 | 24 (330) | 23.2(335) | 23.8(671) |
| 56–65 | 19.8 (272) | 17.7(256) | 18.7 (527) |
| Marital status, % (n) | |||
| Married* | 89.1 (1220) | 85.5 (1239) | 87.1 (2454) |
| Occupational status, % (n)* | |||
| Employed or self employed | 39.2 (537) | 42.4 (614) | 40.9 (1153) |
| Student | 5.6 (77) | 6.7 (97) | 6.2 (175) |
| Unemployed | 55.2 (756) | 50.9 (737) | 52.9 (1490) |
| Educational status, % (n)* | |||
| Illiterate | 11.2 (153) | 14.8 (214) | 13.0 (366) |
| Under graduate | 67.1 (920) | 71.2 (1031) | 69.2 (1950) |
| College | 21.7 (279) | 14.1 (204) | 17.8 (501) |
| Smoking habit, % (n)* | |||
| yes | 9.5 (130) | 12.7 (184) | 11.1 (313) |
| Occasionally | 1.3 (18) | 2.0 (28) | 1.7 (48) |
| No | 89.1 (1221) | 85.4 (1236) | 87.2 (2457) |
| Physical activity, % (n)* | |||
| Inactive | 43.3 (593) | 18.1 (262) | 30.3 (854) |
| Minimally active | 34.8 (477) | 29.2 (423) | 31.9 (899) |
| Health enhancing activity | 21.9 (300) | 52.7 (763) | 37.7 (1062) |
| Prevalence of overweight, % (n)* | 41.6 (570) | 37.7 (546) | 39.6 (1116) |
| Prevalence of obesity, % (n)* | 25.7 (352) | 22.4 324) | 24.0 (676) |
| Prevalence of abdominal obesity, % (n)* | 76.3 (1045) | 74.1 (1074) | 75.2 (2119) |
(P<0.05), differences tested by chi-square test
The prevalence of overweight, obesity and central obesity was significantly higher in the urban areas (P<0.01); however, health-enhancing physical activity and smoking were significantly more prevalent in the regional areas (P<0.001).
Table 2 illustrates the prevalence of overweight, obesity, and abdominal obesity by age and sex. The prevalence of overweight, obesity and abdominal obesity were higher in middle-aged adults compared to young adults. Moreover, the prevalence of central obesity in normal weight subjects was 15.3% (men: 16.7%, women: 14.1%).
Table 2:
The prevalence of overweight, obesity, and abdominal obesity by age and sex
| Variables | Men (n=1368) | Women (n=1450) | P-value* |
|---|---|---|---|
| Weight, kg, (mean±SD)† | 76.4±13 | 69.7±13 | <0.001 |
| 15–25 | 64.9±12.7 | 59±12.1 | 0.005 |
| 26–35 | 74.7±13 | 64.3±12.4 | <0.001 |
| 36–45 | 80.1±12.4 | 70.6±12.5 | <0.001 |
| 46–55 | 78.8±11.9 | 72.8±12.6 | <0.001 |
| 56–65 | 77.1±11.8 | 73.1±12 | <0.001 |
| P-value | <0.001 | <0.001 | |
| Height, cm, (mean±SD)† | 171.9±8.4 | 157.2±13.7 | <0.001 |
| 15–25 | 171.9±9 | 160.2±7.5 | <0.001 |
| 26–35 | 174.8±7.4 | 159.4±14.6 | <0.001 |
| 36–45 | 173.6±8.4 | 157.5±14.8 | <0.001 |
| 46–55 | 171.4±9 | 157.3±16.2 | <0.001 |
| 56–65 | 169±7.5 | 153.6±18.7 | <0.001 |
| P-value | <0.001 | <0.001 | |
| BMI, kg/m2, (mean±SD)† | 25.9±4.7 | 28±5.6 | <0.001 |
| 15–25 | 22.2±4.2 | 22.9±4.5 | 0.127 |
| 26–35 | 24.5±4 | 25±4.4 | 0.09 |
| 36–45 | 26.7±5 | 28±5.3 | <0.001 |
| 46–55 | 27±4.6 | 29.4±4.9 | <0.001 |
| 56–65 | 27±4.1 | 30.4±6.2 | <0.001 |
| P-value | <0.001 | <0.001 | |
| Waist circumference, cm, (mean±SD)† | 91.6±12.3 | 91.2±12.7 | 0.44 |
| 15–25 | 79.1±10.2 | 77.7±12.9 | 0.42 |
| 26–35 | 86.3±11.4 | 84.4±11.8 | 0.06 |
| 36–45 | 92.7±12.4 | 90.7±11.1 | 0.01 |
| 46–55 | 94.9±10.5 | 94.2±12.1 | 0.49 |
| 56–65 | 96.9±10.8 | 98.5±10.4 | 0.027 |
| P-value | <0.001 | <0.001 | |
| Prevalence of overweight, %‡ | 42.2 | 37.1 | 0.01 |
| 15–25 | 16.1 | 16.4 | 0.56 |
| 26–35 | 30.8 | 28.6 | 0.62 |
| 36–45 | 44.6 | 42.3 | 0.55 |
| 46–55 | 49.4 | 40.7 | 0.046 |
| 56–65 | 52.3 | 37.5 | 0.001 |
| P-value | <0.001 | <0.001 | |
| Prevalence of obesity, %‡ | 15.1 | 32.2 | <0.001 |
| 15–25 | 2.7 | 7.2 | 0.16 |
| 26–35 | 8.6 | 15.1 | 0.039 |
| 36–45 | 18.9 | 29.5 | 0.001 |
| 46–55 | 18.2 | 42.6 | <0.001 |
| 56–65 | 19 | 47.5 | <0.001 |
| P-value | <0.001 | <0.001 | |
| Prevalence of abdominal obesity, %‡ | 68.6 | 81.4 | <0.001 |
| 15–25 | 20.0 | 36.2 | <0.04 |
| 26–35 | 43.9 | 63.9 | <0.001 |
| 36–45 | 75.3 | 84.0 | <0.001 |
| 46–55 | 81 | 90.7 | <0.001 |
| 56–65 | 86.6 | 96.6 | <0.001 |
| P-value | <0.001 | <0.001 |
Differences tested by unpaired Student’s t-test//
Differences tested by chi-square test
Odds ratios for overweight/obesity and abdominal obesity for demographic, socioeconomic and lifestyle factors were presented in Table 3. Results of logistic regression analysis, which controlled to confounders (age, marriage, residency area, employment, education, smoking and physical activity status, the number of kids and the family history of obesity) showed that in both sexes, higher age was the risk of over-weight/obesity and abdominal obesity. In married men, the risk of being overweight/obese and centrally obese was more than twice as high compared to single ones. Moreover, nonsmokers and subjects having the family history of obesity were also more expected to be overweight or obese and centrally obese than the others. In addition, 15% and 58% higher risk of obesity and abdominal obesity was seen in women with health-enhancing physical activity.
Table 3:
Logistic regression analysis for the association of overweight/obesity/abdominal obesity and demographic, socio-economic, lifestyle factors
| Men(n=1368) | Women(n=1450) | |||
|---|---|---|---|---|
| Overweight/ Obesity Adjusted OR (95% CI) | Abdominal obesity Adjusted OR (95% CI) | Overweight/ Obesity Adjusted OR (95% CI) | Abdominal obesity Adjusted OR (95% CI) | |
| Age groups | ||||
| 15–25 | 1.00 | 1.00 | 1.00 | 1.00 |
| 26–35 | 1.85 (0.83,4.14) | 1.93 (0.88, 4.20) | 2.09 (0.98, 4.45) | 2.15 (1.08, 4.27)* |
| 36–45 | 4.24 (1.77, 10.14) *** | 6.14 (2.59, 14.53) *** | 6.43 (3.02,13.70) *** | 6.18 (3.06, 12.49) *** |
| 46–55 | 4.6 (1.90,11.27) *** | 9.53 (3.88, 23.39) *** | 12.5 (5.71, 27.42) *** | 11.03 (5.14, 23.69) *** |
| 56–65 | 6.24 (2.49, 15.63) *** | 11.31 (4.37, 29.25) *** | 15.3 (6.61,35.41) *** | 44.95 (14.33, 141.04) *** |
| Residential place | ||||
| Urban | 1.00 | 1.00 | 1.00 | 1.00 |
| Rural | 0.98 (0.74, 1.29) | 1.24 (0.88, 1.74) | 0.82 (0.63, 1.07) | 0.95 (0.74, 1.22) |
| Marital status | ||||
| Single | 1.00 | 1.00 | 1.00 | 1.00 |
| Married | 2.24 (1.35, 3.73) *** | 2.09 (1.24, 3.15) *** | 1.76 (1.03, 3.01) * | 1.72 (1.10, 3.04) * |
| Occupational status | ||||
| Employed | 1.00 | 1.00 | 1.00 | 1.00 |
| Student | 1.10 (0.49, 2.44) | 1.15 (0.29, 4.63) | 0.61 (0.21, 1.78) | 2.07 (0.70, 6.08) |
| Unemployed | 1.93 (1.03, 2.99) ** | 0.81 (0.43, 1.52) | 1.13 (0.68, 1.87) | 0.87 (0.53, 1.41) |
| Educational status | ||||
| Illiterate | 1.00 | 1.00 | 1.00 | 1.00 |
| Under graduate | 1.40 (0.76, 258) | 1.50 (0.78, 2.89) | 1.55 (0.9, 1.99) | 0.94 (0.62, 1.43) |
| College | 1.42 (0.73, 2.77) | 1.35 (0.64, 2.82) | 0.99 (0.57, 1.74) | 1.41 (0.83,2.41) |
| Smoking habit | ||||
| yes | 1.00 | 1.00 | 1.00 | 1.00 |
| Occasionally | 1.64 (0.72, 3.76) | 0.59 (0.23, 1.54) | 2.30 (0.20,26.00) | 1.09 (0.06, 19.23) |
| No | 1.64 (1.19, 2.28) ** | 1.69 (1.17, 2.44) ** | 2.57 (0.54, 12.13) | 3.68 (0.61, 22.01) |
| Physical activity | ||||
| Inactive | 1.00 | 1.00 | 1.00 | 1.00 |
| Minimally active | 1.00 (0.68, 1.46) | 1.21 (0.80, 1.83) | 0.90 (0.65, 1.24) | 1.06 (0.73, 1.55) |
| Health enhancing activity | 1.06 (0.72, 1.55) | 1.32 (0.86, 2.01) | 0.88 (0.63, 1.23) | 1.58 (1.06, 2.30) * |
| Family history of obesity | ||||
| No | 1.00 | 1.00 | 1.00 | 1.00 |
| Yes | 1.93 (1.13, 3.31) * | 1.90 (1.34, 2.69) *** | 1.78 (1.30, 2.43) *** | 2.03 (1.22, 3.38) *** |
| Number of kids | ||||
| 0–1 | 1.00 | 1.00 | 1.00 | 1.00 |
| ≥2 | 0.65 (0.03, 11.6) | 1.07 (0.66, 1.72) | 1.59 (1.23, 2.05) *** | 2.08 (1.35, 3.19) *** |
P < 0.05
P < 0.01
P < 0.001
Multiple logistic regressions considering the simultaneous effect of all the explanatory variables
The energy and macronutrient intake of men and women in different subgroups of anthropometric measures are represented in Table 4. In both sexes, after adjusting for age, educational and professional profile, overweight/obese men and women presented a lower energy intake from fat than their leaner counterparts. Additionally, men with central obesity were existing higher and lower energy intake from carbohydrates and proteins respectively.
Table 4:
Energy and macronutrient intake of men and women in different subgroups of anthropometric measures
| BMI | Abdominal obesity | |||||
|---|---|---|---|---|---|---|
| BMI<25 | BMI≥25 | P-value* | CI<0.5 | CI≥0.5 | P-value* | |
| Men | ||||||
| Energy intake (Kcal/day) | 3695±956 | 3468±942 | 0.18 | 3719±966 | 3558±960 | 0.11 |
| Energy intake from carbohydrate (%) | 48.6±8.3 | 50.5±8.5 | 0.14 | 51.6±5.2 | 55.1±7.9 | 0.03 |
| Energy intake from protein (%) | 19.2±3.4 | 19.5±3.0 | 0.40 | 20.3±2.2 | 19.3±3.3 | 0.04 |
| Energy intake from fat (%) | 32.2±7.1 | 30±7.0 | 0.04 | 28.4±5.4 | 25.6±7.3 | 0.11 |
| Women | ||||||
| Energy intake (Kcal/day) | 2941±755 | 3115±825 | 0.28 | 3090±768 | 3020±723 | 0.60 |
| Energy intake from carbohydrate (%) | 49.4±8.0 | 51.8±9.4 | 0.12 | 49.3±8.4 | 48.4±7.9 | 0.41 |
| Energy intake from protein (%) | 18.9±3.0 | 19.1±3.2 | 0.60 | 19.1±3.0 | 18.7±3.4 | 0.45 |
| Energy intake from fat (%) | 31.7±7.3 | 29.1±8.3 | 0.048 | 31.6±8.5 | 32.9±6.7 | 0.15 |
BMI: Body Mass Index; CI: Conicity Index //
ANCOVA, adjusted for age, employment status, marital status, education, residential place, smoking habit, physical activity and number of kids
Discussion
We provided population-based estimates of obesity and associated factors in East Azerbaijan, Iran. Around 63.6% of the participants were either overweight or obese. This rate reflects a significant national obesity problem. In this study, higher rates of overweight and obesity were observed when compared with estimates for the Spanish (17%) (21) and Turkish (19%) (22) adult population. The results of current study are comparable to those reported by the National Health and Nutrition Examination Survey [NHANES] (more than one-third of adult were obese)(23), and in Pakistan (25.0%)(24).
According to the results of current study, 75.2% (81.4% in women and 68.6% in men) of the population had of central obesity. Abdominal obesity is a health problem in Iran (25–27). The prevalence of abdominal obesity reported being 39.2% in Rio de Janeiro(28), 24.1% in Egypt(29), 30.5% in Australia (30), and 64.4% in Oman (31).
Additionally, in agreement with other studies, overweight/obesity was significantly more prevalent in the urban than regional areas with rates of 67.3% versus 60.1%(32; 33). Compared to the previous report in Iran (34) and based on the results of this study, the prevalence of over-weight and obesity is also rapidly increasing among regional residents along with urban ones which have different resons (35–37).
The prevalence of overweight/obesity and central obesity was even more alarming (76.4%) especially among females (69.3% and 83.2%). These results were dissimilar to the studies in China (38) and Japan (39); however, it was in accordance with other provincial and national studies(1, 16, 40) and consistent with the findings from studies performed in some other countries (16, 40, 41). The number of pregnancies, the amount of weight gain in each pregnancy (42), physical activity pattern and more importantly dietary habits, the social norms and gender responsibilities in traditional communities, where females are perceived primarily as child bearers, may contribute to this gender difference.
The results of this study showed that obesity is increasing sharply with age in both sexes which is consistent with the data from other countries (43–46). In this study, the alarming point is that 45% of women in the 46–65 yr old age group were obese. Weight gain after menopause, age-related lower metabolic consumption (47), the decrease in the level of physical activity with age(48) and decrease in height as a person ages(33) were probably the relative causes of increasing obesity with increasing age. In addition, in consistence with other published studies, age has been considered as a predictor of abdominal obesity (49–52).
Our data indicated that being single was linked with the lower frequency of overweight/obesity and abdominal obesity in both sexes, confirming results of other studies (1, 53).
In this study, a high risk of overweight/obesity among unemployed men was also recognized. Unemployed subjects may have lower opportunities for physical activity and, on the other side, may have irregular eating patterns (54). Unlike other studies, there was no connection between education and obesity in this study (49, 55–58).
Among men, nonsmokers were also more likely to be overweight or obese and abdominally obese than the others. The smoking-BMI connection may be due to the effect of smoking on physiological processes that cause the changes in appetite, food choices, and basal metabolic rates (BMR) (59).
Despite our results, low physical activity and central obesity were associated in other studies reported from Iran and other countries (58; 60). This observation may be due to this fact that in recent years, many interventions to improve physical activity have been carried out in women between 18 and 65 yr of age in Iran and it seems that obese women tended to increase their physical activity in response to these intervention programs (61).
The connection between family size and the number of children and the prevalence of obesity have been reported in previous studies (32, 45, 62). This may be attributed to the age, pregnancy and breastfeeding, the situations most women suppose that it is healthier both for mother and baby to raise their energy intake (63).
Subjects with overweight/obesity and centrally obese subjects reported higher energy intake from fat and carbohydrate. Moreover, abdominally obese men reported lower protein intake than the others. The result of one study showed lower energy intake from proteins in abdominally obese men. High protein diet may increase the thermogenic response and decrease the calorie intake by satiety (64, 65). On the other hand, a high-carbohydrate diet causes hyperinsulinemia, high serum triglycerides and low HDL-C levels (66) which may cause central obesity. A low-fat, high-carbohydrate diet mainly consisting of highly refined grains and products with added sugar which may increase prevalence of obesity (67).
Conclusion
There is high prevalence of overweight/obesity (63.6%) and abdominal obesity (75.2%) among adults. More longitudinal study is desired to investigate the association between socio-demographic factors and obesity.
Ethical considerations
Ethical issues (Including plagiarism, informed consent, misconduct, data fabrication and/or falsification, double publication and/or submission, redundancy, etc.) have been completely observed by the authors.
Acknowledgements
The authors wish to thank the Tabriz Health services management research center at Tabriz University of Medical Sciences and Eastern Azerbaijan Governor General for financial support.
Footnotes
Conflict of interest
The authors declare that there is no conflict of interests.
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