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Obesity and Cardio-Metabolic Risk Factors in an Urban and Rural Population in the Ashanti Region-Ghana: A Comparative Cross-Sectional Study.

ABSTRACT: There is a surge in chronic diseases in the developing world, driven by a high prevalence of cardio-metabolic risk factors. This study described differences in prevalence of obesity and cardio-metabolic risk factors between urban and rural settlements in the Ashanti Region of Ghana. This comparative cross-sectional study included 672 participants (median age 50 years), of which 312 were from Kumasi (urban) and 360 from Jachie-Pramso (rural). Demographic, anthropometric and other cardio-metabolic risk factors were gathered and venous blood samples were drawn for biochemical assays. Results suggested significant differences in diastolic blood pressure (80.0 mmHg vs 79.5 mmHg; p = 0.0078), and fasting blood sugar (5.0 mmo/l vs 4.5 mmol/l; p < 0.0001) between the two groups. Further differences in anthropometric measures suggested greater adiposity amongst participants in the urban area. Participants in the urban area were more likely than rural participants, to have high total cholesterol and LDL-c (p < 0.0001 respectively). Risk factors including BMI ≥ 25 (p < 0.0001), BMI ≥ 30 (p < 0.0001), high waist circumference (p < 0.0001), high waist-to-height ratio (p < 0.0001) and alcohol consumption (p = 0.0186) were more prevalent amongst participants in the urban area. Markers of adiposity were higher amongst females than males in both areas (p < 0.05). In the urban area, hypertension, diabetes and lifestyle risk factors were more prevalent amongst males than females. Differences in risk factors by urban/rural residence remained significant after adjusting for gender and age. Obesity and cardio-metabolic risk factors are more prevalent amongst urban settlers, highlighting an urgent need to avert the rise of diet and lifestyle-related chronic diseases.

SUBMITTER: Obirikorang C

PROVIDER: S-EPMC4457529 | biostudies-other | 2015

REPOSITORIES: biostudies-other

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Project description:Background: We aimed at investigating the impact of malaria on the haematological parameters of residents from different demographic settlements in the Ashanti Region of Ghana. Malaria parasites trigger changes in certain haematological parameters, which may result in a number of clinical manifestations. Differences in demographic settlements, such as rural, peri-urban and urban settlements may also influence these changes, but this has not been extensively studied in Ghana. Methods: We conducted a hospital-based, cross-sectional study from January to December 2018 in three different settlements. A total of 598 participants were recruited. Blood smears were examined to detect and quantify malaria parasitaemia, while haematological parameters were measured using a haematology analyser. Results: Participants from the rural settlement had the highest malaria prevalence (21.3%) compared to urban (11.8%) and peri-urban areas (13.3%); however, the peri-urban area had the highest median parasite density (568; IQR=190.0-1312.0). Age was significantly associated with the odds of malaria positivity (OR: 0.97; CI:0.96 - 0.99; p=4.96*10 -4). When haematological parameters of the malaria-infected study participants were compared to the parameters of uninfected participants, red blood cell count (p=0.017), haemoglobin (p=0.0165), haematocrit (p=0.0015), mean corpuscular volume (p=0.0014), plateletcrit (p<0.0001) and platelet count (p<0.0001) were all significantly lower in the malaria infected group. In addition to age, haemoglobin and plateletcrit levels were also inversely correlated with the odds of testing positive for malaria, suggesting that children who were anaemic and/or thrombocytopaenic were likely to be infected. After fitting the data to a logistic regression model comprising the three variables, the model correctly categorised 78% of uninfected study participants, but only 50% of the malaria-positive participants. Conclusions: Study participants who were positive for malaria were younger and had low haemoglobin and plateletcrit levels compared to uninfected individuals. Further studies are needed to more precisely elucidate the relationship between malaria infection,demographic and haematological parameters.

Project description:BACKGROUND:Childhood obesity is a growing public health concern in many low-income urban settings; but its determinants are not clear. The purpose of this study is to assess the prevalence of childhood obesity and associated factors among in-school children aged 5-16 years in a Metropolitan district of Ghana. METHODS:A cross-sectional quantitative survey was conducted among a sample of 285 in-school children aged 5-16 years. Pre-tested questionnaires and anthropometric data collection methods were used to collect data. Descriptive, bivariate, binary and multivariate logistic regression statistical techniques were used to analyse data. RESULTS:Some 46.9% (42.2% for males and 51.7% for females) of the children were overweight. Of this, 21.2% were obese (BMI falls above 95th percentile). Childhood obesity was higher in private school (26.8%) than public school (21.4%), and among girls (27.2%) than boys (19%). Factors that increased obesity risks included being aged 11-16 as against 5-10 years (aOR = 6.07; 95%CI = 1.17-31.45; p = 0.025), having a father whose highest education is 'secondary' (aOR =2.97; 95% CI = 1.09-8.08; p = 0.032), or 'tertiary' (aOR = 3.46; 95% CI = 1.27-9.42; p = 0.015), and consumption of fizzy drinks most days of the week (aOR = 2.84; 95% CI = 1.24-6.52; p = 0.014). Factors that lowered obesity risks included engaging in sport at least 3times per week (aOR = 0.56; 95% CI = 0.33-0.96; p = 0.034), and sleeping for more than 8 h per day (aOR = 0.38; 95% CI = 0.19-0.79; p = 0.009). CONCLUSION:Higher parental (father) educational attainment and frequent consumption of fizzy drinks per week may increase obesity risks among in-school children aged 5-16 years in the Metropolitan district of Ghana. However, regular exercise (playing sport at least 3 times per week) and having 8 or more hours of sleep per day could lower obesity risks in the same population. Age and sex-appropriate community and school-based interventions are needed to promote healthy diet selection and consumption, physical activity and healthy life styles among in-school children.

Project description:BackgroundMigration from rural areas of India contributes to urbanisation and may increase the risk of obesity and diabetes. We tested the hypotheses that rural-to-urban migrants have a higher prevalence of obesity and diabetes than rural nonmigrants, that migrants would have an intermediate prevalence of obesity and diabetes compared with life-long urban and rural dwellers, and that longer time since migration would be associated with a higher prevalence of obesity and of diabetes.Methods and findingsThe place of origin of people working in factories in north, central, and south India was identified. Migrants of rural origin, their rural dwelling sibs, and those of urban origin together with their urban dwelling sibs were assessed by interview, examination, and fasting blood samples. Obesity, diabetes, and other cardiovascular risk factors were compared. A total of 6,510 participants (42% women) were recruited. Among urban, migrant, and rural men the age- and factory-adjusted percentages classified as obese (body mass index [BMI] >25 kg/m(2)) were 41.9% (95% confidence interval [CI] 39.1-44.7), 37.8% (95% CI 35.0-40.6), and 19.0% (95% CI 17.0-21.0), respectively, and as diabetic were 13.5% (95% CI 11.6-15.4), 14.3% (95% CI 12.2-16.4), and 6.2% (95% CI 5.0-7.4), respectively. Findings for women showed similar patterns. Rural men had lower blood pressure, lipids, and fasting blood glucose than urban and migrant men, whereas no differences were seen in women. Among migrant men, but not women, there was weak evidence for a lower prevalence of both diabetes and obesity among more recent (</=10 y) migrants.ConclusionsMigration into urban areas is associated with increases in obesity, which drive other risk factor changes. Migrants have adopted modes of life that put them at similar risk to the urban population. Gender differences in some risk factors by place of origin are unexpected and require further exploration. Please see later in the article for the Editors' Summary.

Project description:BackgroundBody fat distribution influences the risk of cardio-metabolic disease in people with overweight. This study was aimed at identifying the anthropometric parameters more strongly associated with the majority of cardio-metabolic risk factors.MethodsThis study included 1214 subjects (840 women), with a body-mass-index (BMI) ≥ 25 Kg/m2, aged 39.2 ± 13 years. Fasting blood glucose (FBG), triglycerides (TG), total, HDL- and LDL-cholesterol, uric acid, vitamin D, high-sensitive C-reactive protein (hs-CRP), white blood cells (WBC), platelets, insulin and insulin resistance (HOMA-IR), systolic (SBP) and diastolic blood pressure (DBP), smoking habit and snoring were evaluated as cardio-metabolic risk factors.We also included the Systematic COronary Risk Evaluation (SCORE) to estimate cardiovascular risk in our study population. BMI, waist circumference (WC), waist-to-height-ratio (WHtR) and neck circumference (NC) were evaluated as anthropometric parameters.ResultsAll four anthropometric parameters were positively associated to SBP, DBP, TG, FBG, insulin, HOMA-IR, WBC, and snoring (p<0.001), and negatively associated with HDL-cholesterol (p<0.001). NC showed a positive association with LDL-cholesterol (β = 0.76; p = 0.01; 95% C.I. 0.19 to 1.32), while vitamin D was negatively associated to WC (β = -0.16; p<0.001; 95% C.I. -0.24 to -0.09), BMI (β = 0.42); p<0.001; 95% C.I. -0.56 to -0.28) and WHtR (β = -24.46; p<0.001; 95% C.I. -37 to -11.9). Hs-CRP was positively correlated with WC (β = 0.003; p = 0.003; 95% C.I. 0.001 to 0.006), BMI (β = 0.01; p = 0.02; 95% C.I. 0.001 to 0.012) and WHtR (β = 0.55; p = 0.01; 95% C.I. 0.14 to 0.96). SCORE was associated to NC (β = 0.15; 95% CI 0.12 to 0.18; p<0.001), BMI (β = -0.18; 95% CI -0.22 to 0.14; p<0.001) and WHtR (β = 7.56; 95% CI 5.30 to 9.82; p<0.001).ConclusionsNC, combined with BMI and WC or WHtR could represent an essential tool for use in clinical practice to define the cardio-metabolic risk in individuals with excess body weight.

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Obesity and Cardio-Metabolic Risk Factors in an Urban and Rural Population in the Ashanti Region-Ghana: A Comparative Cross-Sectional Study.

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