Link Between Less Education and Onesity Peer Reviewed Artcle
Objective: To examine the association of sociodemographic variables with the odds of being obese among adults in Kingdom of saudi arabia, and to examine whether or not the association betwixt the educational level and the odds of being obese among adults in Saudi arabia is modified by the income level. Methods: A total of 3,925 participants were recruited for this cross-sectional study. Sociodemographic and anthropometric data were collected using standardized procedures. Unadjusted and adjusted logistic regression models were examined, with a dichotomous obesity status variable as the outcome. Furthermore, an interaction term for income level with educational level was tested and appeared meaning. Thus, additional regression models were run in order to examine the association between educational level and obesity status separately among the depression- and higher-income groups. Results: Compared to participants with a college caste or college, illiterate participants and those with an elementary education had higher odds of obesity (OR: two.76, 95% CI: one.81–4.22, and OR: 2.68, 95% CI: 1.89–3.82, respectively). All the same, participants with a low income had lower odds than participants who had a higher income (OR: 0.84, 95% CI: 0.70–0.99). Examining the association betwixt educational level and obesity while stratifying past income revealed that a negative clan betwixt education and obesity exists among both income groups. However, the magnitude of the ORs was college among participants with higher income, suggesting a stronger association betwixt education and obesity among wealthier individuals. Conclusion: Individuals in the highest income bracket with lower levels of education may take greater odds of obesity. Targeting them in intervention programs is warranted.
© 2020 The Author(s) Published by Due south. Karger AG, Basel
Introduction
Overweight and obesity as defined by the World Health System (WHO) are a country of increased body fatty of varying degrees that could impair health [1]. It has long been known that increased adiposity exposes the individual to a college risk of developing a plethora of adverse health issues, such as hypertension, dyslipidemia, cerebrovascular stroke, and gallbladder and kidney stones, and diabetes [ii-7]. Cardiovascular disease chance is also known to be straight related to the caste of obesity [8, 9]. More recently, obesity has been linked to an increased hazard of various malignancies as well as survivorship from cancer in the form of recurrence, quality of life, as well equally long-term prognosis and cancer progression [10, 11]. Further information evidence that obesity is implicated in chronic respiratory disorders and sleep matted animate [12], musculoskeletal disease and osteoarthritis [xiii], and all-cause mortality [xiv].
In the first half of the 20th century, it was believed that overweight and obesity were weather unique to those of college socioeconomic status. However, starting from the 1990s, it became more recognized that obesity affects individuals of lower socioeconomic condition equally if non more than those of affluence in developing countries [15, sixteen]. The more recent trends of increased adiposity among lower-income groups are attributed to the lower costs and convenience of free energy-dumbo food options [17, xviii]. In both adult and developing countries effectually the world, fast and processed foods and snacks, refined grains, and sugary drinks price less than lower-energy, healthier nutrient options, such as fresh fruits and vegetables, fresh cuts of lean meats, and seafood [18, 19]. Moreover, a discrepancy in the educational level between higher- and lower-income groups may also exist an independent contributor to the higher obesity take a chance among less affluent individuals [xx]. Higher instruction was constitute to be associated with lower consumption of full fats and cholesterol [21] and greater intake of fruits and vegetables [22, 21]. This positive upshot of a better didactics may operate directly through greater nutritional knowledge, which affects dietary practices [22].
As seen in many developing countries around the world, obesity rates in the Saudi arabia (KSA) accept been on the rise during the by several years [23]. Although the association between sociodemographic factors and obesity gamble are well established in several other countries, such as the U.s.a. [24], findings from studies conducted on KSA samples are conflicting [25]. For case, while obesity was establish to be negatively associated with education among women [25-27], a positive clan between maternal educational activity and obesity was observed amidst Saudi adolescents [26]. Furthermore, while some institute that obesity rates were higher amidst lower-income groups [27], others plant that lower-income individuals were less likely to be obese [26].
A clearer agreement of how sociodemographic characteristics are associated with weight status is critical for more than constructive targeting and blueprint of obesity interventions and public wellness programs. Therefore, the primary objective of this study was to examine the association of sociodemographic variables, including educational level and income level, with odds of existence obese (BMI ≥xxx kg/yard2) amidst adults in KSA. The secondary objective was to examine whether or not the clan betwixt educational level and odds of being obese (BMI ≥30 kg/mii) amid KSA adults was modified by income level.
Methods
Participants and Procedure
The study included iii,925 participants who were recruited from shopping malls in Jeddah metropolis and surrounding areas, including Makkah and modest villages, during a series of public wellness campaigns conducted over a menstruation of 3 months. Study inclusion criteria were historic period ≥eighteen years; fluency in Standard arabic; and KSA residency. Women reporting that they were pregnant at the fourth dimension of data collection were also excluded from the study.
Following completion of an informed consent form to participate, research assistants collected sociodemographic and anthropometric data from participants. Due to a high prevalence of low literacy, to assess sociodemographic characteristics, research assistants read aloud questions and corresponding response options; then they entered participants' answers into electronic tablets. Research assistants measured participants' weight and height using standardized procedures [28].
Upstanding clearance to perform this written report was obtained from the Unit of measurement of Biomedical Ideals at the King Abdulaziz University Infirmary, and confidentiality was maintained as data remained anonymous for all participants.
Measures
Primary Predictors: Sociodemographic Characteristics
Data gathered included participant's sex (male vs. female); nationality (Saudi vs. not-Saudi); educational level (illiterate, elementary school, middle schoolhouse, high school, 2-year diploma, bachelor'southward degree, and graduate caste) (subsequently collapsed into but five categories); total monthly income (no income, <five,000, 5,000–x,000, 10,000–20,000, or ≥twenty,000 SAR per calendar month) (later collapsed into merely 2 categories: low income, i.eastward., defined as total monthly income <5,000 SAR per calendar month vs. higher income [29]) (1 USD = 3.75 SAR); fiscal sponsorship (financially supported by someone else, supports one's self, supports ane'southward self and spouse, and supports 1'due south self, spouse, and children) (subsequently collapsed into only ii categories); marital condition (single, married, widowed, and divorced) (afterwards complanate into only two categories); and current active smoker (yeah vs. no).
Master Outcome: Obesity Status (BMI ≥xxx kg/mtwo)
BMI was calculated by dividing weight in kilograms by height in centimeters squared. Based on the BMI score, torso weight was classified equally obese if BMI was ≥30 kg/mtwo [xxx].
Statistical Assay
Statistical analyses were conducted using the Statistical Package for Social Sciences (SPSS; version 24.0; Armonk, NY, USA). Descriptive statistics were conducted to assess characteristics of the full sample and bivariate analyses by obesity condition; differences in characteristics between the obese group and the nonobese grouping were examined using χ2 statistics.
To further examine the association betwixt each sociodemographic variable and obesity status, we conducted logistic regression analyses with the dichotomous obesity status variable (BMI ≥30 kg/m2 vs. not) equally the outcome. Offset, separate unadjusted models were examined for each of the main predictors (i.e., Saudi nationality, educational level, low-income level, financial sponsorship, and marital status). Then, a fully adjusted model including all primary predictors was tested. Since binary analyses showed that the association between sex and obesity status was not significant (p > 0.20), nosotros did not include sex activity in the adapted regression model.
In order to examine whether the association between educational level and obesity condition was modified by income level, we included an interaction term for income level with educational level in the fully adjusted model. Since the interaction term was statistically significant (p = 0.01), suggesting that the association between educational level and obesity condition may vary by income level, we ran separate adjusted regression models and examined the association between educational level and obesity status separately among the low- and higher-income groups.
Results
Sample Characteristics and Associations with Obesity Condition
Equally shown in Table 1, about i-quarter of the sample (25.8%) was classified as obese; 54.eight % of them were females. About one-half of the sample (52.2%) had only a loftier school instruction or less, and about ane-third (36.nine%) were considered low income (had a total monthly income of ≤5,000 SAR [29]) (Tabular array ane).
Table 1.
Characteristics of the total sample and associations with obesity status (n = 3,925)
The prevalence of obesity was significantly college amidst KSA participants (26.half-dozen%) than non-KSA participants (23.1%). The prevalence of obesity was significantly negatively associated with educational level. Obesity prevalence was 38.7% among illiterate participants, 41.4% amidst participants with an simple education, 28.3% among participants with a middle school educational activity, 25.4% among participants with a high school education, and 23.7% amidst participants with a college degree or college. Furthermore, obesity was significantly associated with total monthly income, such that the prevalence of obesity was lower amongst depression-income participants (22.4%) and participants making >20,000 SAR per month (24.iii%), compared to those making between 5,000 and 20,000 SAR per month (28.two%). Prevalence of obesity was too significantly associated with financial sponsorship and marital condition. However, no significant association betwixt sex and obesity status was observed (p > 0.10), and the association betwixt smoking and obesity merely reached marginal significance (p = 0.07) (Table 1).
Adjusted Associations between Sociodemographic Characteristics and Obesity
As shown in Tabular array 2, KSA participants had higher odds of obesity than non-KSA participants (OR: 1.21, 95% CI: ane.01–1.46). Compared to participants with a higher caste or higher, illiterate participants and those with an elementary didactics had college odds of obesity (OR: 2.76, 95% CI: 1.81–iv.22, and OR: 2.68, 95% CI: 1.89–3.82, respectively). Additionally, participants who were financially sponsored by someone else had higher odds of obesity than those who were not (OR: one.33, 95% CI: 1.14–ane.56). On the other hand, participants who had a depression income (v,000 SAR per month or less) had lower odds of obesity compared to participants who had a higher income (OR: 0.84, 95% CI: 0.70–0.99). Similarly, participants who were single (i.e., not married) had lower odds of obesity than those who were not single (OR: 0.45, 95% CI: 0.39–0.53) (Table 2).
Tabular array two.
Unadjusted and adapted associations between sociodemographic variables and obesity status
Associations between the Educational Level and Obesity by Income
Examining the association between educational level and obesity status while stratifying by income revealed that the negative association between education and obesity exists among both income groups (group with an income <5,000 SAR per calendar month vs. group of higher income). Withal, the magnitude of the ORs was higher amongst participants with higher income, suggesting a stronger association between education and obesity among wealthier individuals. Compared to participants with a college degree or higher, odds of obesity amidst participants who were illiterate was ii.29 (95% CI: i.33–three.94) in the low-income group compared to 4.46 (95% CI: 2.07–9.64) in the college income group. Odds of obesity amid participants who had an elementary school educational activity was 2.12 (95% CI: one.32–3.39) in the low-income group compared to iv.29 (95% CI: 2.35–7.84) in the higher income group (Table 3). In the low-income grouping, at that place were no significant differences in the odds of obesity between participants who completed middle or high school and participants with a college degree or higher (OR: ane.03, 95% CI: 0.66–1.61, and OR: 1.23, 95% CI: 0.92–ane.72, respectively). Withal, in the higher-income group, participants who only completed middle or loftier school had significantly college odds of obesity than participants with a college caste or higher (OR: 2.15, 95% CI: 1.48–3.11, and OR: one.24, CI: 1.01–1.fifty, respectively).
Tabular array 3.
Adjusted association between educational level and obesity status stratified by income1
Discussion
In the present written report, a quarter of the sample was classified equally obese, an estimate that is quite higher than the WHO 2016 estimation of worldwide adult obesity prevalence of xiii% [i]. We establish that obesity prevalence was higher among participants who were KSA residents compared to non-KSA residents (24% of the sample). In agreement with many studies effectually the globe [31], nosotros plant that a college educational level was associated with a lower obesity prevalence. Even so, contrary to findings from international studies [24, 27], our assay revealed that the clan between income and obesity might not be a negative, monotonic clan. Our data rather suggest that the association betwixt income and obesity might exist an inverted U-shaped curvilinear association. The prevalence of obesity was lower amongst low-income participants (22.4%) and participants making >20,000 SAR per month (24.3%) than those making between v,000 and 20,000 SAR per month (28.2%).
Adjusted analyses corroborated these associations, equally we plant illiterate participants and those with only an elementary educational activity to have higher odds of obesity than participants with a college degree or college. In addition, participants who made >5,000 SAR per month had college odds of obesity, and the odds of obesity was substantially college among college income individuals who were less educated. We can, therefore, infer from our results that the greatest group at take chances is those in the highest income subclass with lower levels of education. Equally such, these are the individuals that should be targeted with intensive education and health sensation programs. Moreover, we institute that participants who were single were less likely to be obese; a finding that is in line with results from other studies [32].
While KSA is considered an flush country, a prominent wealth gap exists between low- and high-income families. Equally in many Arab countries, the wealth of high-income families is often inherited transgenerationally and does not necessarily reflect superior education or employment status [33]. According to the Earth Bank website, while the population of Saudi Arabia ballooned since the 1960s from around iv million persons to over 32 million persons in 2015, the GDP suffered a noticeable dip in 2016–2017 but is on the style to recovery [34]. From the national statistics website [35], it appears that the private household income has overall increased, as did the average expenditure. However, reviewing the categories on which money was spent, it appears that health maintenance, such as gym memberships, counseling, and other wellness maintenance systems, were not a major source of expenditure [34]. This is concerning and may explicate adverse health outcomes presented in individuals at the college end of the income spectrum. A large percentage of loftier-income individuals may accept inadequate educational activity and may allocate less coin and resources to preserve a healthy lifestyle and seek preventative health care services.
Given our findings and the difficulty in reversing obesity once it is a reality, and the well-known association between obesity and the diseases mentioned earlier, early on prevention and intervention would make the about sense both economically and from a population health perspective. To this end, several options tin exist considered, such equally early on mass screening programs, national awareness campaigns with obesity and its comorbidities every bit the main focus, and possibly door-to-door campaigns for early detection and implementation of prevention and/or therapeutic programs. Efforts may specifically target and exist tailored to accost knowledge deficits and other psychosocial factors among high-income individuals who are less educated; awareness programs may be designed aiming to increase allotment of resources to promote a healthy lifestyle. Furthermore, programs may be directed towards other individuals who may have higher odds of obesity, such as those who are married and with a Saudi nationality.
This study has several limitations. First, since this is a cross-sectional study, we cannot infer a causal relationship betwixt low education among loftier income and higher likelihood of obesity. In addition, behaviors such as dietary intake and physical activity were non measured, and we, therefore, cannot infer that higher-income individuals who are less educated follow a poor lifestyle. Longitudinal studies that follow individuals with unlike income and educational levels over time while evaluating their lifestyle practices are needed. This study also has several strengths. The big sample size and the high response rate has likely resulted in adequate statistical power to find significant associations. Additionally, weight and height were objectively measured providing a precise estimate of BMI values. Finally, randomization of data collection and sampling from several areas around the city might accept strengthened our power to demonstrate the association between obesity and sociodemographic characteristics in a representative manner to the residents.
In summary, this written report examined the association of sociodemographic variables with odds of beingness obese. Our findings indicate that lower education and higher income are positively associated with obesity; and that obesity is significantly more than common among KSA participants and married individuals than not-KSA residents or singles. Intensive educational activity and wellness sensation programs should be performed nationwide and target KSA individuals of high income and low levels of teaching to promote health and well-being.
Acknowledgment
The authors would like to thank the VISION Medical Team, Dr. Manal Mohammed Shams, and Ms. Lamis Fahad Basaeed for their assistance.
Statement of Ethics
This written report was approved by the Unit of Biomedical Ethics at the King Abdulaziz Academy Infirmary, and confidentiality was maintained as data remained anonymous for all participants.
Disclosure Statement
The authors have no conflict of interest to disclose.
Funding Sources
This enquiry received no specific grant from whatsoever funding agency, or commercial or not-for-profit sectors.
Author Contributions
H.H.M., R.H.Grand., and H.A.K. designed the study and drafted the initial manuscript. R.H.M. and H.A.K. analyzed the data. H:H.M. and A.H.A. coordinated and supervised data collection, provided input on the analysis programme and critically reviewed the manuscript. All authors have approved the last manuscript as submitted.
Hala H. Mosli Division of Endocrinology and Metabolism, Department of Internal Medicine Faculty of Medicine, King Abdulaziz University PO Box 80215, Jeddah 21589 (Kingdom of saudi arabia) Eastward-Mail halamosli100@gmail.com First-Page Preview Received: April 25, 2019 Number of Print Pages: 9 ISSN: 1662-4025 (Print) For boosted data: https://www.karger.com/OFA This article is licensed nether the Creative Eatables Attribution-NonCommercial-NoDerivatives iv.0 International License (CC BY-NC-ND). Usage and distribution for commercial purposes besides every bit any distribution of modified material requires written permission. Drug Dosage: The authors and the publisher have exerted every effort to ensure that drug selection and dosage fix along in this text are in accord with current recommendations and practice at the time of publication. Withal, in view of ongoing enquiry, changes in government regulations, and the constant flow of information relating to drug therapy and drug reactions, the reader is urged to check the package insert for each drug for any changes in indications and dosage and for added warnings and precautions. This is peculiarly important when the recommended agent is a new and/or infrequently employed drug. Disclaimer: The statements, opinions and data contained in this publication are solely those of the individual authors and contributors and non of the publishers and the editor(s). The appearance of advertisements or/and product references in the publication is not a warranty, endorsement, or approving of the products or services advertised or of their effectiveness, quality or safety. The publisher and the editor(s) disclaim responsibleness for any injury to persons or property resulting from any ideas, methods, instructions or products referred to in the content or advertisements.
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Accepted: December 02, 2019
Published online: Jan 17, 2020
Effect release date: Feb 2020
Number of Figures: 0
Number of Tables: 3
eISSN: 1662-4033 (Online)
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Source: https://www.karger.com/Article/FullText/505246
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