Obesity, overweight, and underweight among urban Nigerians

Okafor, CI; Gezawa, Ibrahim; Sabir, Anas Ahmad; Raimi, Taiwo Hussean; Enang, Ofem

doi:10.4103/1119-3077.144389

Cited by 34 publications

(53 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…[9] It was, however, lower than the 28.2% and 38.4% reported in two Nigerian studies. [16,25] The first study was community-based, the second HIV clinicbased, while ours was hospital-based: this might be the reason for the difference in the prevalence of overweight compared to that noted in our study.…”

Section: Discussioncontrasting

confidence: 48%

“…[9,10,16,20] Unlike our study which was carried out in an outpatient clinic, these studies were community-based with much larger population sizes.…”

Section: Discussionmentioning

confidence: 99%

“…[7,8,9] Under-nutrition is high among rural dwellers in developing countries. [10] The prevalence of overweight was 62% and obesity 26% for both sexes in the World Health Organization (WHO) region of the Americas, compared to overweight of 14% and obesity 3% in South East Asia.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Body Mass Index and Associated Factors of Obesity and Underweight in a General Out-patient Population in a Tertiary Hospital in Nigeria

Anyabolu¹

2016

AJIM

View full text Add to dashboard Cite

Abstract:There is increasing incidence of abnormal weight changes in Sub-Saharan Africa, including Nigeria. Factors which influence body mass index (BMI) in developing countries have not been completely identified. Weight changes may be observed even in general out patients, unrelated to the major complaints for which the patients are presenting in clinics. This study was set out to evaluate BMI and potential risk factors of underweight and obesity in subjects attending the general outpatient clinic in Federal Medical Centre, Owerri, Nigeria. This was a cross-sectional study conducted on general out patients. Body mass index was determined. Relevant investigations were performed. Association of weight changes with their potential risk factors and the strength of variables to predict BMI, underweight and obesity were determined. The mean BMI of the subjects was 25.5± 6.5kg/m 2 . Underweight was present in 14(10.3%), normal weight in 57(41.9%), overweight in 24(17.6%) and obesity in 41(30.1%) of the subjects. There was significant association between BMI and hemoglobin (Hb), 24-hour urine osmolality (24HUOsm), serum cholesterol, serum low density lipoprotein cholesterol (LDL), serum high density lipoprotein cholesterol (HDL), as well as serum triglyceride. There was significant but poor correlation between BMI and spot urine protein (SUP), spot urine creatinine (SUCr), spot urine osmolality (SUOsm), serum cholesterol, serum triglyceride, serum HDL, serum LDL, as well as Hb. Spot urine protein, SUOsm, and Hb predicted BMI. Furthermore, SUOsm, serum cholesterol, serum HDL and serum LDL predicted obesity. The prevalence of underweight (10.3%) and obesity (30.1%) were high in the general out patients. Abnormalities of serum lipids, proteinuric renal disease with dilute urine were common in these subjects. There is a need for clinicians to routinely assess BMI and further search for anemia, dyslipidemia and renal damage in subjects with underweight and obesity attending the general out-patient clinics.

show abstract

Section: Discussioncontrasting

confidence: 48%

“…[9,10,16,20] Unlike our study which was carried out in an outpatient clinic, these studies were community-based with much larger population sizes.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Body Mass Index and Associated Factors of Obesity and Underweight in a General Out-patient Population in a Tertiary Hospital in Nigeria

Anyabolu¹

2016

AJIM

View full text Add to dashboard Cite

show abstract

“…In Tanzania, prevalence of obesity and overweight was 40 % and 35 %, respectively and this was higher than 32.54 % and 23.44 % reported in 2012, respectively [25]. In Nigeria, the prevalence of overweight and obese in a study in 2011 was 22 % and 4 %, while in 2014 another reported prevalence of 31 % and 17 %, respectively [33] Okafor et al, 2014; these values are much lower than 37 % and 31 % found in our study.…”

Section: Discussionmentioning

confidence: 98%

Urban–rural and geographic differences in overweight and obesity in four sub-Saharan African adult populations: a multi-country cross-sectional study

et al. 2016

View full text Add to dashboard Cite

BackgroundOverweight and obesity are on the rise in developing countries including sub-Saharan Africa. We undertook a four-country survey to show the collective burden of these health conditions as they occur currently in sub-Saharan Africa and to determine the differences between urban and rural populations and other socio-economic factors.MethodsParticipants were nurses in two hospitals in Nigeria (200), school teachers in South Africa (489) and Tanzania (229), and village residents in one peri-urban (297) and one rural location in Uganda (200) who completed a standardised questionnaire. Their height and weight were measured and body mass index calculated. Factor analysis procedure (Principal component) was used to generate a wealth index. Univariate and multivariate analyses with binary logistic regression models were conducted to examine the associations between potential correlates and the prevalence of overweight and obesity with 95 % confidence intervals.ResultsThe prevalence of overweight and obese (combined) was 46 %, 48 %, 68 %, 75 % and 85 % in rural Uganda, peri-urban Uganda, Nigeria, Tanzania and South Africa (SA), respectively. Rural Uganda, Peri- urban Uganda, Nigeria, Tanzania and SA had obesity prevalence of 10 %, 14 %, 31 %, 40 % and 54 %, respectively (p < 0.001). Overall, prevalence of overweight was 374 (31 %) and obesity, 414 (34 %). Female sex was a predictor of overweight and obesity (combined) in peri-urban Uganda [AOR = 8.01; 95 % CI: 4.02, 15.96) and obesity in rural Uganda [AOR = 11.22; 95%CI: 2.27, 55.40), peri-urban Uganda [AOR = 27.80; 95 % CI: 7.13, 108.41) and SA [AOR = 2.17; 95 % CI: 1.19, 4.00). Increasing age was a predictor of BMI > =25 kg/m2 in Nigeria [Age > =45 - AOR = 9.11; 95 % CI: 1.72, 48.16] and SA [AOR = 6.22; 95 % CI: 2.75, 14.07], while marital status was predictor of BMI > =25 kg/m2 only in peri-urban Uganda. [Married - AOR = 4.49; 95 % CI: 1.74, 11.57]. Those in Nigeria [AOR = 2.56; 95 % CI: 1.45, 4.53], SA [AOR = 4.97; 95 % CI: 3.18, 7.78], and Tanzania [AOR = 2.68; 95 % CI: 1.60, 4.49] were more likely to have BMI > =25 kg/m2 compared with the rural and peri-urban sites.ConclusionThe high prevalence of overweight and obesity in these sub-Saharan African countries and the differentials in prevalence and risk factors further highlights the need for urgent focused intervention to stem this trend, especially among women, professionals and urban dwellers.

show abstract

“…That's indicated the physical fitness level and economic and social development is not coordinated in the similar level of economic development regions. Studies such as Fan et al (Fan et al 2012;Okafor et al 2014;) have shown that the higher the standard of living, the more likely to suffer from chronic diseases which caused by over nutrition and exercise too little. Jiang (Jiang et al 1998) have suggested to institute a regional evaluation standards, integrating the national physical fitness into the social development evaluation index that the purpose is arouse people's attention to exercise.…”

Section: Introductionmentioning

confidence: 99%

Quantitative evaluation of economic level effects on physical fitness condition among elderly population in Hebei province of China

Li¹,

Chai²,

Liu³

et al. 2017

Physical Activity and Health

View full text Add to dashboard Cite

The purpose of this study is to investigate the influence of economic level on physical fitness condition among elderly population. Cities with regard to The National Physical Fitness Surveillance in Hebei province were divided into three regions based on variant economic levels. According to the properties of testing indexes and the functional coverage, this study classified test indexes as the body level, the organic tissues level, the cellular/molecular level, and quantitatively compared the differences between these levels. The results showed that the index value differences failed to reach significant level except for the balance ability which was significantly higher for cities with better economy condition than cities at general economic level and the capital city. Findings of this study indicates that the economic difference does not cause the effective stress of physical fitness improvement among elderly population. The complete biological function stress caused by the increased economic level is during plateau stage. In addition, the average BMI value of the elderly in Hebei province presented overweight feature despite of economic level, which should draw more focuses. The quantitative difference evaluation of the threshold point is applicable for health engineering research, but the application in other disciplines needs to be further studied.

show abstract

Obesity, overweight, and underweight among urban Nigerians

Cited by 34 publications

References 2 publications

Body Mass Index and Associated Factors of Obesity and Underweight in a General Out-patient Population in a Tertiary Hospital in Nigeria

Body Mass Index and Associated Factors of Obesity and Underweight in a General Out-patient Population in a Tertiary Hospital in Nigeria

Urban–rural and geographic differences in overweight and obesity in four sub-Saharan African adult populations: a multi-country cross-sectional study

Quantitative evaluation of economic level effects on physical fitness condition among elderly population in Hebei province of China

Contact Info

Product

Resources

About