Body Mass Index, Prevalence and Predictors of Obesity in Urban and Rural Communities in Abia State South Eastern Nigeria

Chukwuonye, Innocent Ijezie

doi:10.4172/2155-6156.1000570

Cited by 11 publications

(22 citation statements)

References 10 publications

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“…On the contrary, the prevalence of overweight 38.4% and obesity 21.5% noted in this study are similar to those reported in two studies, one in Brazil [10], the other in USA [22]. These, including our findings, are similar to the BMI reported in a general population in Eastern Nigeria [23]. The high prevalence of obesity observed in our study in subjects who were not on HAART, might be explained by a background high prevalence of obesity in the general population [23].…”

Section: Discussionsupporting

confidence: 91%

BMI and Risk Factors of Underweight and Obesity in HIV Subjects in Eastern Nigeria

Anyabolu¹

2016

WJA

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Background and Objectives: Human immunodeficiency virus infection (HIV) is a global healthcare problem. Progression of HIV infection is commonly associated with decreasing weight. In the early phases of HIV infection, factors associated with weight changes are not completely known. This study evaluated the body mass index (BMI) and its potential risk factors in drug-naïve HIV subjects in Owerri, Eastern Nigeria. Methodology: This was a cross-sectional study of HIV subjects. BMI was determined. Relevant investigations were performed. Potential risk factors of BMI were analyzed at different BMI categories. Association of variables with BMI and the strength of variables to predict BMI, underweight and obesity were determined. Results: The mean BMI of the HIV subjects was 26.2 ± 5.4 kg/m 2. Underweight was present in 24 (6.1%), overweight in 150 (38.4%) and obesity in 84 (21.5%) of the HIV subjects. High spot urine creatinine (SUCr), high 24-hour urine osmolality (24HUOsm), high serum cholesterol and high hemoglobin predicted BMI in HIV subjects. Low 24HUOsm predicted under weight, whereas low 24-hour urine protein (24 HUP) and high 24HUOsm predicted obesity in HIV subjects. Conclusion: The prevalence of underweight was low (6.1%), overweight high (38.4%) and obesity high (21.5%) in HIV subjects. High SUCr, high 24HUOsm, high serum cholesterol and high hemoglobin were predictors of BMI in HIV subjects. Low 24HUOsm was a predictor of underweight, while low 24HUP and high 24HUOsm were predictors of obesity in HIV subjects. Abnormalities of serum lipids, renal function, and anemia were common in HIV subjects who were underweight and in those obese. Underweight HIV subjects should be evaluated at the early stages for dyslipidemia, renal damage and anemia.

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Section: Discussionsupporting

confidence: 91%

BMI and Risk Factors of Underweight and Obesity in HIV Subjects in Eastern Nigeria

Anyabolu¹

2016

WJA

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“…In contrast, this is higher than the 2.5% documented by Chukwuonye et al [16] in Abia State, Nigeria. Both studies were done in the same Southeast geopolitical zone of Nigeria.…”

Section: Discussioncontrasting

confidence: 53%

“…[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: 42%

“…[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%

“…[12,13,14,15] Two Nigerian studies reported underweight prevalence of 2.5% and 5.0%. [13,16] Factors associated with obesity included: sex, leisure-time, physical exercise, (and educational level appear to influence obesity) low physical activity, high wealth index, no livestock, low animal fat consumption, high n-6 polyunsaturated fat consumption, television ownership, time spent watching television, low rurality index, high caste, older age, rural living, current smoking, lower systolic pressure, urbanization, higher systolic pressure, and diabetes. [10,13,17,18] On the other hand, studies have shown that underweight was associated with low wealth index, high rurality index, low intake of n-6 PUFAs and less urbanization.…”

Section: Introductionmentioning

confidence: 99%

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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

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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.

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Exploring the relationship between dietary patterns and obesity among Nigerian adults: a cross-sectional study

Segun,

Zhang,

Mary

et al. 2024

BMC Public Health

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Background/Objective No previous study has investigated the association between dietary pattern and both general and abdominal obesity risk among adults in Nigeria. This study aimed to evaluate the associations between dietary patterns and the risk of obesity among adult age 18 and above in Ekiti State, Southwestern Nigeria. Methods and study designs A total of 1003 adults were included in this cross-sectional study (males = 558; females = 445). Body mass index (BMI) and waist-to-hip (WHR) were used to assess general and abdominal obesity respectively and they were categorized using WHO recommendation. Partial correlation analyses were performed to assess the associations of dietary patterns with BMI and WHR. Prevalence ratio between dietary pattern and both general and abdominal obesity were calculated using Robust Poisson Regression. Results The prevalence of general obesity among adults was 15.9%, (11.6% among men and 20.2% among women); abdominal obesity was 32.3% (28.9% among males and 44.5% among females). Four dietary patterns were identified; diversified traditional pattern; typical traditional pattern; milk and bread pattern and egg and fish pattern. Diversified traditional pattern was negatively associated with BMI (PR = 0.571, 95%CI: 0.360 ~ 0.905, p = 0.017), and typical traditional pattern was positively associated with BMI (PR = 1.561, 95% CI: 1.043 ~ 2.339, p = 0.031) and WHR in females (PR = 1.849, 95% CI: 1.256 ~ 2.721, p = 0.005). In comparison to those in the lowest quartile, adults with the highest quartile of the typical traditional pattern had a higher risk for abdominal obesity (PR = 1.849, 95%CI = 1.256 ~ 2.721, p = 0.020). Conclusion This study reports an alarming increase in Obesity prevalence among Nigeria adults which is greatly influence by their lifestyle and eating pattern. We found out that a typical traditional food pattern was associated with a higher risk of both general and abdominal obesity, but a diverse traditional food pattern was associated to a reduced risk of general obesity.

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Body Mass Index, Prevalence and Predictors of Obesity in Urban and Rural Communities in Abia State South Eastern Nigeria

Cited by 11 publications

References 10 publications

BMI and Risk Factors of Underweight and Obesity in HIV Subjects in Eastern Nigeria

BMI and Risk Factors of Underweight and Obesity in HIV Subjects in Eastern Nigeria

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

Exploring the relationship between dietary patterns and obesity among Nigerian adults: a cross-sectional study

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