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| ORIGINAL ARTICLES |
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| Year : 2019 | Volume
: 7
| Issue : 1 | Page : 29-37 |
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Prevalence of overweight and obesity in the Saudi population: A population-based cross-sectional study
Aayed R Alqahtani, Mohamed Elahmedi, Awadh Al Qahtani
New You Medical Center, Riyadh, Saudi Arabia
| Date of Submission | 03-Jul-2022 |
| Date of Decision | 08-Jul-2022 |
| Date of Acceptance | 09-Jul-2022 |
| Date of Web Publication | 02-Aug-2022 |
Correspondence Address:
Aayed R Alqahtani
New You Medical Center, Riyadh, Baabada, Riyadh 11671
Saudi Arabia
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/sjo.SJO_6_22
Background: There is a scarcity of comprehensive data on the epidemiology of overweight /obesity and its association with diet- and activity-related behaviors among the Saudi Arabian adult population. The present study aims to determine prevalence of overweight and obesity and estimates factors that may be associated with obesity in Saudi Arabia. Materials and Methods: A population-based cross-sectional study was conducted with a representative multistage random cluster sample of the Saudi Arabian adult population (n = 12,154; male= 5,523, female = 6631). Measurements included weight, height, body mass index (BMI), screen time, physical activity, and dietary habits (validated questionnaire). Data were analyzed by descriptive statistics; Student’s t-test, Chi-squared tests, ANOVA and logistic regression were employed to examine the associations between obesity and lifestyle factors. Results: Overall, 72.4% of the Saudis who participated in this study suffered from overweight or obesity; (31.9% overweight and 40.5% obese). The prevalence of obesity and overweight increased with age and reached a peak among those aged 50–59 years. Additionally, men were 1.5 times more likely to be overweight or obese than women (crude odds ratio [OR]: 1.54, 95% confidence interval [CI]: 1.42, 1.64). This association did not change after adjusting for other factors such as age, exercise habits, snack habits, educational attainment and co-morbidities. The odds of obesity/overweight was 42% greater for those who never exercised compared to those who exercised daily [adjusted (adj.) OR: 1.42 (1.21, 1.67)]. Conclusion: Age, gender, education attainment, exercise habits and co-morbidities were important factors found to be associated with high BMI among the adult population of Saudi Arabia. The present findings reinforce the importance of reforming public health strategies for effective prevention and management of overweight and obesity in Saudi Arabia. Keywords: Diet, healthy lifestyle, obesity prevalence, overweight, physical activity, Saudi population
How to cite this article:
Alqahtani AR, Elahmedi M, Qahtani AA. Prevalence of overweight and obesity in the Saudi population: A population-based cross-sectional study. Saudi J Obesity 2019;7:29-37 |
How to cite this URL:
Alqahtani AR, Elahmedi M, Qahtani AA. Prevalence of overweight and obesity in the Saudi population: A population-based cross-sectional study. Saudi J Obesity [serial online] 2019 [cited 2023 Jun 9];7:29-37. Available from: https://www.saudijobesity.com/text.asp?2019/7/1/29/353156 |
| Introduction | |  |
Overweight and obesity are the most significant health concerns of the 21stcentury among all age groups. According to World Health Organization (WHO), the prevalence of overweight and obesity, has risen dramatically worldwide in both developed and developing countries.[1] The health consequences of overweight and obesity are strongly associated with risk factors for cardiovascular diseases, diabetes, orthopedic problems.[2],[3] The etiology of obesity is very complex and generally affected by associated factors such as genetics and environment, in addition to social, physiological and psychological factors.[4],[5] Exponential increase in overweight and obesity rates over recent years cannot be attributed to genetic factors alone. This observation suggests that environmental and socioeconomic factors may be an important cause of rapid global rise in obesity.[4]
Saudi Arabia has experienced rapid transition and massive urbanization where fast food, high in sugar and salt, has been added to the diet.[5] Increased access to low-priced highly energy-dense fast foods combined with an increase in sedentary lifestyle has been detrimental to general health of the population. Previous national nutritional study on population revealed that eating non-nutritional and high calorie snacks is becoming common practice; fried foods and carbonated drinks have now become part of common diets in the country.[5] Decreased level of physical activity along with changes in food habits led to increase in obesity among the Saudi population. . As a result, apid growth in the prevalence of obesity and obesity-related non-communicable diseases (NCD) has been observed. However, suitable prevention programs are lacking to curb this rise. According to previous report a significant increase in obesity was recorded[5],[6],[7],[8] and is expected to impose a substantial burden in terms of disease outcomes and health-care costs. Several obesity-related diseases are of significant concerns among the health professionals in the country. The national prevalence data are the only major determinant of policy making to prevent disease prevalence.
Very few epidemiological studies were conducted in past for estimating the prevalence rate of obesity and overweight among Saudi Arabian population.[5],[6],[7],[8],[9] There is a scarcity of comprehensive data on the epidemiology of obesity and its associated risk factors. Therefore, a better understanding of the relationship between obesity and lifestyle factors is necessary for effective prevention and management of obesity diseases in Saudi population.
The goal of this study was twofold: (i) to determine the prevalence of overweight and obesity among the Saudi adult population using a representative sample; (ii) to analyze how dietary behaviors, physical activity and sedentary lifestyle influence weight in adult men and women.
| Materials and methods | | |
Sample and study design
The data for the present study were derived from a population based cross sectional representative sample and sampling frame with the Saudi population aged 18 or more years in the five geographical regions (East, West, North, South and Central) of Saudi Arabia. Selection from sampling frame and data collection followed a random cluster sampling procedure based on population gender, age and geographical distribution. The samples were stratified by geographical regions and sampling location. The samples were taken from 6 major cities (Riyadh, Khobar, Jeddah, Taif, Al Jouf and Dammam) covering the largest regions of Saudi Arabia. Data were collected in 2011–2012.
The samples of this population based cross sectional study conducted included 12,154 adults comprising 5,523 men and 6,631 women.
Ethics statement
All participants were informed about the purpose of the study, and written consent was taken for participation. The study was approved by the institutional review board at the College of Medicine, King Saud University, Riyadh, Saudi Arabia, and was conducted in accordance with the Declaration of Helsinki for Human Studies.[10]
Instrument
The study instrument was a structured questionnaire designed in English that included the following sections: a) demographic information; b) dietary behaviors; c) physical activity; d) screen time; e) physical activity and lifestyle; f) general awareness about cause of obesity; g) medical conditions and anthropometric measurement. The questionnaires were completed by interviewing the sampled individual by trained study team members.
Anthropometric measurement
The anthropometric measurement was taken by trained study team members. Participants were weighed to the nearest 0.1 kg wearing minimal clothing and without footwear, and height was measured to the nearest 0.5 cm, according to the standardized procedure as described elsewhere,[11] using calibrated instruments. Weight status was defined according to body mass index class.[12] Blood pressure (BP) was determined according to study protocol with a standardized sphygmomanometer that was regularly calibrated by manufacturer’s biomedical engineer. BP was classified according to the National Institute for Health and Care Excellence (NICE) guideline for clinical management of hypertension in adults. Participants taking BP -controlling drugs were classified as hypertensive.
Data and statistical analysis
The study data were collected from each center and entered into computer using standardized entry codes. For all tests statistical significance was set at P < 0.05. Descriptive statistics were used to present means, standard deviations and percentage. In addition, student’s t-test, ANOVA, Tukey’s range test and chi-squared tests were employed to compare anthropometric and lifestyle variables between sexes, age groups and other demographic variables. To examine the association between important co-morbidities that are known to be associated with obesity, we grouped diabetes mellitus, hypertension, heart disease and sleep apnea into a group of having co-morbid conditions whereas the rest of the samples were deemed not to have co-morbid conditions known to be associated with obesity.
The relationships between demographic and lifestyle factors and obesity were assessed using binary unconditional multiple logistic regression analysis. Adjusted odds ratios (adj. OR) and the corresponding 95% confidence intervals (CIs) were calculated for each independent variable. The goal of the regression analysis was to model the odds of obesity (obese + overweight) compared to being normal or under-weight using a set of independent variables. Modeling was performed with the goal of selecting the most parsimonious and reasonable explanatory model that explained the relationship between independent and dependent variables so that hypotheses could be generated for future research. The models were not developed to assess causality between independent variables and obesity. In choosing a final model, we used backward elimination employing likelihood ratio test starting with a “full” model of reasonable independent variables to drill down to a final model.
For bivariate analyses, we utilized all available data points. However, for multivariable analyses (logistic regression), we constructed a dataset that only had complete values for all relevant variables across the observations, thereby discarding the observations that had missing values for any of the variables involved in the regression analysis. This strategy was adopted to maintain comparability between models so that they could be developed from the same denominator. In total, there were 9272 observations that had complete values for all involved variables included in the logistic regression analysis. Factor sub-groups were re-combined for use in Logistic regression analysis to prevent quasi-separation of cells resulting from small cell sizes which allowed the models to converge and yet provided for meaningful analyses. All analyses were conducted in SPSS IBM SPSS, version 19, 2010 (SPSS, Inc., Chicago, IL).
| Results | | |
The study sample mean age and BMI were 32.4 ± 10.8 years and 29.1 ± 6.4 kg/m2, respectively. 2.8% of patients were underweight, 24.8% had normal weight; 31.9% were overweight; and 40.5% were obese [Table 1]. The characteristics of the study sample and prevalence of overweight and obesity in different groups are described in detail in [Table 1][Table 2][Table 3][Table 4][Table 5]. [Figure 1] describes the prevalence of obesity by age groups. It was noted that prevalence of obesity and overweight increased with age and reached a peak among those aged 50–59 years following which it declined, but remained 17 percentage points higher among the older age group compared to those who were 20–29 years of age. | Table 1: Distribution (mean ± standard deviation) of important anthropometric measurements of the study sample by descriptive characteristics
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 | Table 2: Demographic details [number and proportion (%)] of the study sample in men and women
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 | Table 3: Gender-specific trend in dietary behaviors with overweight and prevalence of overweight among Saudi Arabian adult population
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 | Table 4: Gender-specific trends in screen time, physical activity and prevalence of overweight among Saudi Arabian adult population
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 | Table 5: Gender-specific trends in co-morbidities, general awareness and prevalence of overweight among Saudi Arabian adult population
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 | Figure 1: Obesity distribution by age group (UN – underweight; N - normal weight; OW- overweight and obese)
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The overall percentage of obesity among men and women were 42.5% and 38.7%, respectively. BMI for men was significantly greater than women (P < 0.0001) [Table 1]. Among men, BMI was significantly higher among the middle-age group compared to others (P < 0.001) whereas BMI of the older and younger groups were similar to each other. However, this pattern was different for women. In women, BMI of younger group was significantly lower than middle and older-age groups (P < 0.001) whereas the BMI of the latter two groups were similar to each other. This difference in age-wise BMI distribution pattern is shown in [Figure 2]. As there is a difference in pattern of BMI with age between men and women, other characteristics are presented for men and women separately [Table 2][Table 3][Table 4][Table 5]. Men were 1.5 times as likely as women to be overweight or obese (crude OR: 1.54; 95% CI: 1.42, 1.64). This association did not change even after adjusting for other factors such as age, exercise habit, snack habit, educational attainment and co-morbidities [Table 6]. | Figure 2: Distribution of body mass index (BMI) according to age and gender
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 | Table 6: Logistic Regression - OR (95% CI) [n = 9272 full case data only) Modeling odds for overweight/ obese (vs. underweight/normal weight). All factors included in the models contributed to the model statistically significantly (P < 005)
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[Table 6] presents the logistic regression analysis or odds of over-weight and obesity. The overall model and individual models for men and women were all significantly better in explaining the relationship between obesity and independent variables compared to intercept-only model (P < 0.000). Age, gender, exercise habit, snack habit, educational attainment and co-morbidities were significant factors in the model. Although “eating while watching TV” by itself was not a significant factor, it was retained in the model because of its contribution to the overall model as demonstrated by the likelihood ratio test. Removing this factor from the model changed the smaller model significantly from the one that included this factor [Table 6]. Factors such as age, exercise habit, and snack habit contributed significantly to the obesity models for both men and women. However, educational attainment was significant for men and not for women, whereas co-morbidities were significant for women and not for men. The habit of eating while watching TV dropped out of both models for men and women [Table 6].
The odds of being obese/overweight in absence of obesity-related co-morbidities was significantly low compared to the presence of these co-morbidities even after adjusting for other factors in the model. This was certainly true for women although this was not seen among men. For women, without these co-morbidities, there was a 42% reduction in odds of obesity/overweight [adj. OR: 0.58 (0.49, 0.68)] [Table 5]. Exercising (daily or sometimes) demonstrated a positive association with obesity. The odds of obesity/overweight was 42% greater for those who never exercised compared to those who exercised daily [adj. OR: 1.42 (1.21, 1.67)]; even exercising sometimes like few hours a week had a reduced odds for obesity compared to not exercising at all (a 14 percentage point reduction in odds from never exercising to some exercising compared to exercising daily). These relationships were similar among men and women. However, contrast to common belief, odds of obesity/overweight was lower among those reporting snacking with sweets and sandwiches compared to fruits and vegetables [adj. OR: 0.77 (0.68, 0.91) for sweets and adj. OR: 0.78 (0.69, 0.91) for sandwiches while adj. OR: 1.00 for fruits and vegetable group]. This factor was significant for women compared to men [Table 6].
| Discussion | | |
The present investigation aimed to describe the current prevalence of overweight and obesity in the Saudi Arabian adult population (aged 18 and older). For the first time in Saudi Arabia, this study provides adult prevalence data with objectively measured weight and height, adjusting for educational level, dietary behaviors, physical activity and sedentary lifestyle of population, guaranteeing systemic representativeness. In the adult population (18 – and older), the overall prevalence of overweight in men was 42.5% while women presented a lower prevalence (38.7%), and the proportion of adults with obesity was near 40.5% for both genders. Earlier reports based on Saudi population had suggested that prevalence of obesity ranged from 11.7% to 33.9% in different areas.[5] Our study found prevalence of obesity was substantially greater at 40.5%. We also found that the prevalence of obesity in both men and women was also greater than the overall prevalence reported earlier by Al-Othaimeen et al. (2007).[5] Our prevalence rates of obesity in men and women were much higher than another study by El Hamzi and Warsy (2000)[7] which reported 13.1% obesity and 27.2% overweight for men while the percentages of obesity and overweight for women were 20.3% and 25.2% respectively. Our overall obesity rates especially rates among women were higher compared to the study by Al-Nozha et.al. (2005).[8] They reported the prevalence of obesity as 35.6%. Therefore, our results revealed that the overweight and obesity among Saudi population are increasing substantially.
Association of exercising with reduced odds for obesity/overweight is clearly visible in this study as expected. However, among women, the 95% confidence limits for the ORs were including or close to unity and the estimates were much lower compared to men. Therefore, it appears to be some dose-response association between exercising and reduced odds for obesity-overweight.
Men and women shared some common as well as some different associated factors for obesity /overweight. Whereas co-morbidities were associated with obesity-overweight among women, but not in men (for which one possible explanation was provided earlier). A recent study reported that low educational level was related to an increased risk for overweight (OR = 2.54; 95% CI: 2.08–3.09), obesity (OR = 2.76; 95% CI: 2.20–3.45), and abdominal obesity (OR = 5.48; 95% CI: 4.60–6.52),[13] and the study also suggested that public health strategies needed to be reformed to improve educational level. In general, higher educational attainment has many benefits for the person and the society. However, our study found that educational attainment was associated with obesity in men, although the same is not true for women. It is quite evident that obtaining education beyond high school produced lower odds of obesity-overweight among men while the same factor was not significant among women. This essentially indicates that whatever impact education may have on obesity-overweight, it may either already exist in women with high school or less than high school education or it has no impact among women despite attaining higher education.
In 2012, Chapman et al.[14] reported that “television watching, alcohol intake, and sleep deprivation are not merely correlated with obesity but likely contribute to it by encouraging excessive eating.” In our study, the habit of eating and TV watching was included in the overall model because it impacted the model significantly. However, as an independent explanatory factor, it was not significant as exemplified by OR estimates close to unity and the confidence interval including unity. Expectedly, the factor dropped out of the individual models for both men and women.
In both countries, the developed and the developing, obesity epidemic has been attributed to a growing obesogenic environment that essentially facilitates the intake of energy-dense foods while restricting or inhibiting all physical activities.[12] Eating fast food and snacks had a significant independent association with sedentary lifestyle, and obesity as reported earlier.[15] Additionally, high sugar (present in fast food) consumption and sedentary lifestyle are also associated with increased obesity prevalence.[16] It has been suggested by Mushtaq et al. (2011)[17] from a study in Pakistan that eating fast food and snacks and sedentary lifestyle had an independent positive association with BMI. They also reported that eating fast food and snacks similarly had independent positive association with sedentary lifestyle (adjusted OR 1.79, 95% CI 1.49–2.16). Our findings of association of carbohydrate rich snacks (such as sweets and sandwiches) showed counter-intuitive outcomes. This is also in line with results found by Tovar et al. (2012)[18] that after adjusting for covariates, obese children were twice as likely to eat 2 servings of vegetables per day (OR=2.0, CI 1.1–3.4). Measurement of lifestyle, behavior and factors may vary between studies and may not be able to measure the real exposure accurately (for example inaccurate exposure of overall sugar intake through recall-based estimates of consumption of different types of snack items). Measures of lifestyle as used in our study are generally not exact but cover several overlapping domains. For example, although snacking habit measurement was attempted to catch the impacts of healthy and potentially unhealthy food habits with obesity, it is clear that it does not faithfully address the complete nutritional status of an individual and may be subject to recall biased and complex measurement errors.
It may also assume that the some of the overweight or obese adults may have already started to improve their dietary or sedentary behaviors. These motivated overweight and obese participants are most likely being influenced by the increased awareness of obesity in their surroundings.[19] Conversely normal weight people may have changed their dietary behavior due to awareness about the rising rates of diabetes that created a fear about becoming obese. Most likely reporting the almost similar pattern by both groups did not produce any significant results to reach exact conclusion for some behavior. It is also possible that overweight and obese participants were over reported healthy behaviors and under reporting unhealthy behaviors. These factors could probably be considered as the limitations of the present study.
| Conclusions | | |
We conclude that overweight and obesity rates in adults are growing considerably, and approximately two third of Saudi populations are already overweight or obese. The obesity prevalence in Saudi Arabia is age dependent with highest prevalence in the middle age (30–59 years). Although the overall (and in men) prevalence starts to drop in older ages (60+ years) it continues to rise in women. As co-morbidity was not associated with obesity among men, education was also not associated with obesity among women. Present study suggests that particular attention should be given to adult population who are within a healthy weight range to prevent developing obesity, given the prevalence of unhealthy behaviors in population. Strategic interventions for the obesity related diseases and proper diet and physical activity management should be adopted countrywide, and most importantly prevention program should also be initiated to fight the obesity epidemic.
Acknowledgement
The authors extend their appreciation to the Deanship of Scientific Research at King Saud University for funding this work through research group no RGP-VPP-186. The authors also acknowledge the contribution from the Shaikh Ali Alshehri Obesity Chair and Chair team members Dr. Alaa Bashaikh, Ms. Nesma Mustafa and Ms. Layla Alfarra. We also thank the participants who took part in the study.
Financial support and sponsorship
Nil.
Conflict of interest
The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper.
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[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6]
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