Abstract
Background:
The prevalence of obesity has risen to over 650 million adults in 2016, and accounts for 41 million deaths globally. It is a major contributor to the burden of noncommunicable diseases. We determined the prevalence and associated factors of obesity to inform policy decisions toward developing robust prevention and management strategies.
Materials and Methods:
We conducted a population-based cross-sectional study in July 2017 among 1265 adults in urban and rural communities in Benue State. We used multistage sampling technique in selecting the participants. The WHO standardized and validated tool were used to collect information on sociodemographic and anthropometric measurements. We calculated age standardized prevalence of obesity and determined factors associated with obesity using logistic regression at 5% level of significance.
Results:
The age standardized prevalence of obesity was 11.1% (rural 4.2%, urban 14.3%). The odds for obesity was higher among females (adjusted odds ratio [aOR]: 3.4; 95% confidence interval [CI]: 2.27–4.99), those with tertiary education (aOR: 3.3; 95% CI: 1.61–6.95), married (aOR: 2.1; 95% CI: 1.37–3.36), and those residing in urban areas (aOR: 3.0; 95% CI: 1.73–5.05) compared to rural dwellers.
Conclusions:
The prevalence of obesity was high among adults in Benue State. It is more prevalent among females, married, educated, and urban dwellers. Interventions targeted at healthy lifestyle choices should be directed at these populations for effective control.
Keywords: Age standardization, Benue, obesity, population-based, prevalence, normalisation de l'âge, Bénoué, obésité, population, prévalence
Résumé
Contexte:
La prévalence de l'obésité est passée à plus de 650 millions d'adultes en 2016 et représente 41 millions de décès dans le monde. C'est un majeur contribuant au fardeau des maladies non transmissibles. Nous avons déterminé la prévalence et les facteurs associés de l'obésité pour éclairer les décisions politiques vers l'élaboration de stratégies solides de prévention et de gestion.
Matériels et méthodes:
Nous avons réalisé une analyse transversale basée sur la population étude réalisée en juillet 2017 auprès de 1265 adultes des communautés urbaines et rurales de l'État de Benue. Nous avons utilisé une technique d'échantillonnage à plusieurs degrés pour sélectionner les participants. L'outil normalisé et validé de l'OMS a été utilisé pour collecter des informations sur les mesures sociodémographiques et anthropométriques. Nous avons calculé la prévalence standardisée selon l'âge de l'obésité et déterminé les facteurs associés à l'obésité en utilisant une régression logistique à un niveau de 5% de importance.
Résultats:
La prévalence de l'obésité normalisée selon l'âge était de 11,1% (rurale 4,2%, urbainev 14,3%). Les probabilités d'obésité étaient plus élevées chez femmes (rapport de cotes ajusté [aOR]: 3,4; intervalle de confiance à 95% [IC]: 2,27–4,99), celles ayant fait des études supérieures (aOR: 3,3; IC à 95%: 1,61–6,95), mariés (aOR: 2,1; IC à 95%: 1,37–3,36) et ceux résidant dans les zones urbaines (aOR: 3,0; IC à 95%: 1,73–5,05) par rapport aux habitants des zones rurales.
Conclusion:
La prévalence de l'obésité était élevée chez les adultes de l'État de Benue. Il est plus répandu chez les femmes mariées, instruites et citadins. Les interventions ciblées sur les choix de modes de vie sains devraient être dirigées vers ces populations pour un contrôle efficace.
INTRODUCTION
Obesity is a major risk factor for cardiovascular disease, diabetes mellitus (DM), musculoskeletal disorders and cancers which all constitute a significant proportion of all noncommunicable diseases (NCDs).[1] It is also associated with poorer mental health outcomes and reduced quality of life.[2] NCDs account for an estimated 41 million (71%) of all deaths globally. Fifteen million people die from NCDs between the ages of 30 and 69 years annually and over 85% of these “premature” deaths occur in low- and middle-income countries including Nigeria.[3] The global burden of NCDs is rapidly increasing, and Africa is the most affected region in the world. Obesity and overweight are second only to elevated blood pressure as the leading metabolic risk factor globally in terms of attributable deaths. Globally, the prevalence of obesity has exponentially increased to an estimated over 650 million (13%) of adults 18 years and older, and more than 124 million children as well as adolescents in 2016.[4]
The epidemic of obesity is driven by economic growth, rapid urbanization, and sedentary lifestyle.[5] Nutritional transition is occurring globally and is characterized by changes from healthy nutritional diets to unhealthy energy-dense foods, high in fat. This transition, alongside epidemiological and demographic transition is contributing toward increased prevalence and incidence of obesity. Obesity occurs due to difference in the calories consumed and calories expended.[6]
In Nigeria, obesity, systemic hypertension, and DM and alongside their complications accounted for 27% of all deaths in 2008, and this is increasing rapidly annually.[7] Yet, NCDs in Nigeria, have been comparatively neglected, partly due to donor-driven funding priorities despite obesity being a principal cause of mortality in low- and middle-income countries.[8] Obesity is preventable.[7] The WHO “Global Action Plan” sets to achieve a 25% relative reduction in premature mortality from NCDs by 2025 and a halt in the rise of global obesity.[9] An important step for countries to contribute toward achieving these global targets is to generate evidence to accurately describe the burden of this emerging epidemic of obesity to inform policy change and actions.
In Nigeria, the prevalence of obesity is of epidemic proportion, with more obese people in the urban than in rural settings.[9] Although previous studies in the country have shown a rise in the incidence of obesity which has been attributed to the adoption of western diet and lifestyle patterns.[10,11] We conducted this study to determine the prevalence obesity and its determinants to provide evidence that will inform policy decisions toward developing robust prevention and management strategies.
MATERIALS AND METHODS
Study setting, population, and sampling technique
The study was conducted in Benue State Nigeria. The state is largely agrarian, and is tagged “food basket of the nation.” The study population included 1265 adults aged at least 18 years of age. We used multistage sampling method to recruit the participants. In stage one, a list of local government areas (LGA) in each senatorial district was made and stratified into rural and urban LGAs. One rural and one urban LGA were selected by balloting from each of the three senatorial districts. In stage two, a list of enumeration areas (EA) were made, and 33 EAs were selected by balloting using probability proportionate to size. In each EA, systematic sampling technique was used to select households for the study. In each household selected in stage three, a list of eligible adults was made and one eligible adult was selected by simple random sampling to participate in the study. The study was conducted from July to August 2017. Other details of the sampling and study setting have earlier been reported.[12]
Study tool and data collection
We used a standardized and validated WHO STEPwise tool to collect information on participant's sociodemographic characteristics and anthropometric measurements.[13] The anthropometric measurements were standing height, weight, and waist circumferences. We measured height without shoes and hat in an upright position with the aid of the stadiometer (ASCO height measuring scale floor model stadiometer). The height of the participants was measured to the nearest 0.1 cm. Validated electronic weighing scale (OMRON BF212), set to the nearest 0.1 kg was used to measure weight. Waist circumference was measured to the nearest 0.1 cm using measuring tape, placed directly over the skin or light clothing at the level of the midpoint in between the inferior margin of the last rib and iliac crest along the mid axillary line. Data were collected by trained research assistants.
Definition of terms
Body mass index (BMI, kg/m2) was calculated using the formula below, for each participant we used the weight in kilogram and height in meters.

We categorized the participants based on their BMI (underweight [BMI <18.5 kg/m2], normal weight [BMI 18.5–24.9 kg/m2], overweight [BMI 25–29.9 kg/m2], and obesity [BMI ≥30 kg/m2]). For the purpose of bivariate and multivariate analysis, we dichotomized BMI classification into two: BMI ≥30 kg/m2 as obese and BMI <30 kg/m2 as nonobese.
Statistical analysis
The analysis was done using Epi info version 7.2 (US CDC). We estimated the prevalence of obesity among the participants. We calculated age-specific standardization of the prevalence of obesity using the 2006 Benue State census population [Table 1]. We also calculated the standardized urban and rural prevalence of obesity in Benue [Table 2] and determined the relationship between sociodemographic characteristics and obesity using univariate logistic regression. The factors that were significant were modeled in a multivariable logistic regression at 5% level of significance. The adjusted odds ratio and the 95% confidence interval (CI) were reported.
Table 1.
Age-adjusted prevalence of obesity in Benue
| Age group | Standard population of Benue 2006 | Total respondents | Total obese | Age-specific prevalence of obesity in Benue (%) | Expected obese in Benue |
|---|---|---|---|---|---|
| 15-29 | 1,178,169 | 395 | 23 | 5.8 | 68,602 |
| 30-39 | 453,464 | 309 | 42 | 13.6 | 61,636 |
| 40-49 | 292,226 | 193 | 39 | 20.2 | 59,051 |
| 50-59 | 163,299 | 179 | 45 | 25.1 | 41,053 |
| ≥60 | 207,747 | 189 | 22 | 11.6 | 24,182 |
| Total | 2,294,905 | 1265 | 171 | 254,524 |
Age-specific standardization of the obese using the 2006 base population of Benue state
Table 2.
Age-adjusted prevalence of obesity stratified by place of residence in Benue State
| Age group | Standard population of Benue 2006 | Total urban | Urban obese | Age-specific prevalence of obesity in urban Benue (%) | Expected prevalence of obesity in urban Benue | Total rural | Rural obese | Age-specific prevalence of obesity in Rural Benue (%) | Expected prevalence of obesity in Rural Benue |
|---|---|---|---|---|---|---|---|---|---|
| 15-29 | 1,178,169 | 255 | 19 | 7.5 | 87,785 | 140 | 4 | 2.9 | 33,662 |
| 30-39 | 453,464 | 228 | 39 | 17.1 | 77,566 | 81 | 3 | 3.7 | 16,795 |
| 40-49 | 292,226 | 129 | 35 | 27.1 | 79,286 | 64 | 4 | 6.2 | 18,264 |
| 50-59 | 163,299 | 127 | 38 | 29.9 | 48,861 | 52 | 7 | 13.5 | 21,983 |
| ≥60 | 207,747 | 121 | 20 | 16.5 | 34,338 | 68 | 2 | 2.9 | 6110 |
| Total | 2,294,905 | 860 | 151 | 327,837 | 405 | 20 | 96,814 |
Ethical approval
We obtained ethical approval from the National Health Research Ethics Committee of Nigeria Federal Ministry of Health (NHREC/01/01/2007-22/12/2016). Written informed consent was obtained from each participant.
RESULTS
Among our respondents, 22.1% were overweight, 5.4% were underweight, and 59.1% were normal [Figure 1]. The prevalence of obesity was 13.5% among the respondents. However, after standardizing for age using Benue State population as the reference population, the age standardized prevalence of obesity was 11.1%. The urban and rural age standardized prevalence of obesity was 14.3% and 4.2%, respectively [Figure 2]. There is a statistically significant association between age, sex, tertiary education, marital status, occupation, and place of residence with obesity [P < 0.001, Table 3].
Figure 1.

Prevalence of obesity in the study respondents in Benue state
Figure 2.

Age standardized prevalence of obesity by location
Table 3.
Relationship between sociodemographic characteristics with obesity among respondents in Benue state
| Characteristics | Presence of obesity | COR (95% Confidence Interval) | P | |
|---|---|---|---|---|
| Yes (n=171) | No (n=1094) | |||
| Age | ||||
| <20 | 4 (6.5) | 58 (93.5) | Reference | |
| 20-29 | 19 (5.7) | 314 (94.3) | 0.9 (0.29-2.67) | 0.818 |
| 30-39 | 42 (13.6) | 267 (86.4) | 2.3 (0.79-6.61) | 0.129 |
| 40-49 | 39 (20.2) | 154 (79.8) | 3.7 (1.26-10.73) | 0.017 |
| 50-59 | 45 (25.1) | 134 (74.9) | 4.9 (1.67-14.17) | 0.004 |
| ≥60 | 22 (11.6) | 167 (88.4) | 1.9 (0.63-5.77) | 0.252 |
| Sex | ||||
| Female | 54 (8.8) | 559 (91.2) | 2.3 (1.6-3.2) | <0.001 |
| Male | 117 (18.0) | 534 (82.0) | Reference | |
| Level of education | ||||
| None | 13 (8.0) | 149 (92.0) | Reference | |
| Primary | 25 (10.8) | 207 (89.2) | 1.4 (0.69-2.80) | 0.363 |
| Secondary | 35 (7.6) | 425 (92.4) | 0.94 (0.49-1.83) | 0.864 |
| Tertiary | 98 (23.8) | 313 (76.2) | 3.6 (1.95-6.60) | <0.001 |
| Marital status | ||||
| Unmarried* | 18 (7.6) | 391 (92.4) | Reference | |
| Married | 139 (16.5) | 703 (83.5) | 2.0 (1.6-4.3.3) | <0.001 |
| Occupation | ||||
| Unemployed | 40 (11.8) | 299 (88.2) | Reference | |
| Employed | 131 (14.1) | 795 (85.9) | 1.2 (0.84-1.80) | 0.279 |
| Place of residence | ||||
| Rural | 20 (4.9) | 385 (95.1) | Reference | <0.001 |
| Urban | 151 (17.6) | 709 (82.4) | 4.1 (2.5-6.6) | |
*Unmarried=Never married, separated, divorced, and widowed. COR=Crude odds ratio, CI=Confidence interval
The odds for obesity was 3.4 times higher among females (adjusted odds ratio [aOR]: 3.4; 95% CI: 2.27–4.99) compared to males. Those with tertiary education (aOR: 3.3; 95% CI: 1.61–6.95) had 3.3 times odds of having obesity compared with those with no formal education. The odds of being obese was twice higher among married (aOR: 2.1; 95% CI: 1.37–3.36) compared with unmarried. The odds for obesity was about 3 times greater among those in the urban (aOR: 3.0; 95% CI: 1.73–5.05) compared to those in the rural settings [Table 4].
Table 4.
Logistic regression showing sociodemographic predictors of obesity among respondents in Benue state
| Characteristics | Presence of obesity | aOR (95% Confidence Interval) | P | |
|---|---|---|---|---|
| Yes (n=171) | No (n=1094) | |||
| Age | ||||
| <20 | 4 (6.5) | 58 (93.5) | Reference | |
| 20-29 | 19 (5.7) | 314 (94.3) | 0.4 (0.11-1.17) | 0.089 |
| 30-39 | 42 (13.6) | 267 (86.4) | 0.8 (0.24-2.50) | 0.674 |
| 40-49 | 39 (20.2) | 154 (79.8) | 1.4 (0.41-4.49) | 0.615 |
| 50-59 | 45 (25.1) | 134 (74.9) | 1.8 (0.54-5.85) | 0.344 |
| ≥60 | 22 (11.6) | 167 (88.4) | 1.2 (0.35-4.14) | 0.760 |
| Sex | ||||
| Female | 54 (8.8) | 559 (91.2) | 3.4 (2.27-4.99) | <0.001 |
| Male | 117 (18.0) | 534 (82.0) | Reference | |
| Level of education | ||||
| None | 13 (8.0) | 149 (92.0) | Reference | |
| Primary | 25 (10.8) | 207 (89.2) | 1.4 (0.63-2.91) | 0.432 |
| Secondary | 35 (7.6) | 425 (92.4) | 1.3 (0.58-2.81) | 0.546 |
| Tertiary | 98 (23.8) | 313 (76.2) | 3.3 (1.61-6.95) | 0.001 |
| Marital status | ||||
| Unmarried* | 18 (7.6) | 391 (92.4) | Reference | |
| Married | 139 (16.5) | 703 (83.5) | 2.1 (1.37-3.36) | <0.001 |
| Occupation | ||||
| Unemployed | 40 (11.8) | 299 (88.2) | Reference | |
| Employed | 131 (14.1) | 795 (85.9) | 1.2 (0.78-1.90) | 0.374 |
| Place of residence | ||||
| Rural | 20 (4.9) | 385 (95.1) | Reference | <0.001 |
| Urban | 151 (17.6) | 709 (82.4) | 3.0 (1.73-5.05) | |
*Unmarried=Never married, separated, divorced, and widowed. aOR=Adjusted odds ratio, CI=Confidence interval
DISCUSSION
The prevalence of obesity was generally high among the respondents. The prevalence was higher than earlier reported in Benue state[14] and elsewhere in Nigeria.[15] The high prevalence of obesity observed could probably be due to continued epidemiological transition ongoing in the population. The calculated age standardized prevalence of obesity was higher among urban than rural respondents. This could be attributed to the adoption of poorer nutritional habits and lifestyle choices. The higher prevalence of obesity observed in the urban compared to the rural dwellers has earlier been reported and attributed to sedentary lifestyle, and dietary options.[16,17]
Obesity was higher among females and among married respondents. It was also higher among the married females compared to the unmarried. These have been reported in earlier studies.[10,11,18,19,20,21,22] This could be due to pregnancy and hormonal changes in females. It could also be associated with more involvement of males in physical activities compared to females. In addition, obesity is associated with wealth, beauty, good health strength, and respect among African women. This perspective of “healthy obesity” may fuel the epidemic and may also account for the lack of attention given to obesity.
Obesity increases with age with a slight decline after 60 years. Other studies reported similar findings.[2,23,24] This may be due to changes occurring with advancing age. As people advance in age, they become less active physically. Physical inactivity has been associated with risk of obesity. However, the relationship between aging, physical inactivity, and obesity has not been fully understood. Obesity was higher among those with tertiary education compared to those with no formal education and has been reported.[25] Those that had attained tertiary education were more likely to lead a sedentary lifestyle, more likely to be employed, live in urban area and eat westernized foods hence are more at risk of developing obesity compared to the uneducated that are more likely to engage in manual and unskilled work requiring more physical activity, less access to westernized food and hence less prone to obesity.
CONCLUSIONS
The prevalence of obesity was high among adults in Benue State, and it is more prevalent among females, married, educated, and urban residents. Policy and intervention should target these populations for effective control. The interventions should be targeted at younger people to help model their lifestyle and nutritional choices.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
REFERENCES
- 1.Levesque RJ, Levesque RJ, editors. Encyclopedia of Adolescence. Cham: Springer; 2018. Obesity and overweight; pp. 2561–5. [Google Scholar]
- 2.Centers for Disease Control and Prevention. Adult Obesity Causes & Consequences. Overweight & Obesity. 2018. [Last accessed on 2019 May 27]. p. 7. Available from: https://www.cdc.gov/obesity/adult/causes.html .
- 3.World Health Organization. Geneva, Switzerland: World Health Organisation; 2018. [Last accessed on 2019 May 27]. Noncommunicable Diseases Key Facts. Available from: https://www.who.int/news-room/fact-sheets/detail/ noncommunicable-diseases . [Google Scholar]
- 4.Forouzanfar MH, Afshin A, Alexander LT, Biryukov S, Brauer M, Cercy K. Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: A systematic analysis for the Global Burden of Disease Study 2015. Lancet. 2016;388:1659–724. doi: 10.1016/S0140-6736(16)31679-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Popkin BM. Global nutrition dynamics: The world is shifting rapidly toward a diet linked with noncommunicable diseases. Am J Clin Nutr. 2006;84:289–98. doi: 10.1093/ajcn/84.1.289. [DOI] [PubMed] [Google Scholar]
- 6.Agyemang C, Boatemaa S, Frempong GA, de-Graft Aikins A. Metabolic Syndrome. Cham: Springer International Publishing; 2015. Obesity in Sub-Saharan Africa; pp. 1–13. [Google Scholar]
- 7.Oladimeji AM, Fawole O, Nguku P, Nsubuga P. Prevalence and factors associated with hypertension and obesity among civil servants in Kaduna, Kaduna State, June 2012. Pan Afr Med J. 2014;18(Suppl 1):13. doi: 10.11694/pamj.supp.2014.18.1.3260. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Powell RA, Ali Z, Luyirika E, Harding R, Radbruch L, Mwangi-Powell FN. Out of the shadows: Noncommunicable diseases and palliative care in Africa. BMJ Support Palliat Care. 2017;7:128–32. doi: 10.1136/bmjspcare-2014-000751. [DOI] [PubMed] [Google Scholar]
- 9.Chukwuonye II, Chuku A, John C, Ohagwu KA, Imoh ME, Isa SE, et al. Prevalence of overweight and obesity in adult Nigerians – A systematic review. Diabetes Metab Syndr Obes. 2013;6:43–7. doi: 10.2147/DMSO.S38626. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Chukwuonye II. Body mass index, prevalence and predictors of obesity in urban and rural communities in Abia State South Eastern Nigeria. J Diabetes Metab. 2015;6:1–4. [Google Scholar]
- 11.Iloh G, Amadi AN, Nwankwo BO, Ugwu VC. Obesity in adult Nigerians: A study of its pattern and common primary co-morbidities in a rural Mission General Hospital in Imo state, South-Eastern Nigeria. Niger J Clin Pract. 2011;14:212–8. doi: 10.4103/1119-3077.84019. [DOI] [PubMed] [Google Scholar]
- 12.Osunkwo D, Mohammed A, Kamateeka M, Nguku P, Umeokonkwo CD, Abolade OS, et al. Population-based prevalence and associated risk factors of hypertension among adults in Benue State, Nigeria. Niger J Clin Pract. 2020;23:944–9. doi: 10.4103/njcp.njcp_354_19. [DOI] [PubMed] [Google Scholar]
- 13.World Health Organization. Geneva: WHO; 2013. [Last accessed on 2017 Jun 12]. STEPwise Approach to Surveillance (STEPS) Version 3.2. Available from: https://www.who.int/ncds/surveillance/steps/en . [Google Scholar]
- 14.Sola AO, Steven AO, Kayode JA, Olayinka AO. Underweight, overweight and obesity in adults Nigerians living in rural and urban communities of Benue State. Ann Afr Med. 2011;10:139–43. doi: 10.4103/1596-3519.82081. [DOI] [PubMed] [Google Scholar]
- 15.Pollock NK, Bernard PJ, Gutin B, Davis CL, Zhu H, Dong Y. Adolescent obesity, bone mass, and cardiometabolic risk factors. J Pediatr. 2011;158:727–34. doi: 10.1016/j.jpeds.2010.11.052. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Nurwanti E, Hadi H, Chang JS, Chao JC, Paramashanti BA, Gittelsohn J, et al. Rural-urban differences in dietary behavior and obesity: Results of the riskesdas study in 10-18-year-old Indonesian children and adolescents. Nutrients. 2019;11:2813. doi: 10.3390/nu11112813. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Martins-Silva T, dos Santos Vaz J, de Mola CL, Assunção MC, Tovo-Rodrigues L. Prevalence of obesity in rural and urban areas in Brazil: National health survey, 2013. Rev Bras Epidemiol. 2019. [Last accessed on 2020 Jul 05]. pp. 22–E190049. doi: 10.1590/1980-549720190049. Available from: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-790 9000100445&lng=en&nrm=iso&tlng=en . [DOI] [PubMed]
- 18.Ofori-Asenso R, Agyeman AA, Laar A, Boateng D. Overweight and obesity epidemic in Ghana-a systematic review and meta-analysis. BMC Public Health. 2016;16:1239. doi: 10.1186/s12889-016-3901-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Agyemang C, Owusu-Dabo E, de Jonge A, Martins D, Ogedegbe G, Stronks K. Overweight and obesity among Ghanaian residents in The Netherlands: How do they weigh against their urban and rural counterparts in Ghana? Public Health Nutr. 2009;12:909–16. doi: 10.1017/S1368980008003510. [DOI] [PubMed] [Google Scholar]
- 20.Amoah AG. Sociodemographic variations in obesity among Ghanaian adults. Public Health Nutr. 2003;6:751–7. doi: 10.1079/phn2003506. [DOI] [PubMed] [Google Scholar]
- 21.Addo PN, Nyarko KM, Sackey SO, Akweongo P, Sarfo B. Prevalence of obesity and overweight and associated factors among financial institution workers in Accra Metropolis, Ghana: A cross sectional study. BMC Res Notes. 2015;8:599. doi: 10.1186/s13104-015-1590-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Biritwum R, Gyapong J, Mensah G. The epidemiology of obesity in Ghana. Ghana Med J. 2005;39:82–5. [PMC free article] [PubMed] [Google Scholar]
- 23.Gutiérrez-Fisac JL, León-Muñoz LM, Regidor E, Banegas J, Rodríguez-Artalejo F. Trends in obesity and abdominal obesity in the older adult population of Spain (2000-2010) Obes Facts. 2013;6:1–8. doi: 10.1159/000348493. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Rhee SY, Park SW, Kim DJ, Woo J. Gender disparity in the secular trends for obesity prevalence in Korea: Analyses based on the KNHANES 1998-2009. Korean J Intern Med. 2013;28:29–34. doi: 10.3904/kjim.2013.28.1.29. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Anyanwu GE, Ekezie J, Danborno B, Ugochukwu AI. Impact of education on obesity and blood pressure in developing countries: A study on the Ibos of Nigeria. N Am J Med Sci. 2010;2:320–4. doi: 10.4297/najms.2010.2320. [DOI] [PMC free article] [PubMed] [Google Scholar]
